Dolly Indra

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Indra, Dolly; Purnawansyah; Universitas Muslim Indonesia, Indonesia; Madenda, Sarifuddin; Wibowo, Eri Prasetyo; Universitas Gunadarma, Indonesia

Abstract

In this research the proposes a method of recognition of BISINDO letters based on hand-shape features that hint every shape of BISINDO Letters. In outline, this method is divided into two parts: the first is part of formation database shape features of BISINDO letters A-Z and the second is part of BISINDO letters recognition. In the first section consist of hand-shape image acquisition that hint every BISINDO letters, segmentation process, edge detection process, feature extraction process that is probability value of hand-shape chain code occurrence and process of database feature formation. In the second section is consist of hand-shape image acquisition process as BISINDO letters query followed by segmentation process, edge detection process, hand-shape feature extraction and recognition process by using calculation difference in distance between query shape feature to each shape feature in database feature. The image acquisition process in two parts above conducted directly (real time) via Webcam connected to the computer device. The method above has been implemented into prototype of Bisindo letters recognition software interface. The experiment results show the accuracy level of BISINDO letter recognition (26 BISINDO letters A to Z) which is reaching above 95%.

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Sugiarti; Julius, Santony; Yuhandri; Na’am, Jufriadif; Indra, Dolly; Universitas Muslim Indonesia, Indonesia

Abstract

This study aims to present diagnose of melanoma skin cancer at an early stage. It applies feature extraction method of the first order for feature extraction based on texture in order to get high degree of accuracy with method of classification using artificial neural network (ANN). The method used is training and testing phases with classification of Multilayer Perceptron (MLP) neural network. The results showed that the accuracy of test image with 4 sets of training for image not suspected of melanoma and melanoma with the lowest accuracy of 80% and the highest accuracy of 88.88%, respectively. The 4 sets of training used consisted of 23 images. Of the 23 images used as a training consisted of 6 as not suspected of melanoma images and 17 as suspected melanoma images.

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Indra, Dolly; Alwi, Erick Irawadi; Mubaraq, Muhammad Al; Universitas Muslim Indonesia, Indonesia

Abstract

The fire was one of the incidents that disturbed the comfort of the homeowner. When a fire occurs there is no early warning to the homeowner concerned. In its handling also often we find the fire department itself difficult to extinguish the fire. The research method used is experimental research by conducting trials on tools to extinguish house fires with output given in the form of flames and smoke using fire sensor modules and MQ7 sensors. Test results on the fire sensor obtained a maximum distance of detecting the flame of 120 cm. The MQ7 sensor detects smoke when smoke levels exceed 100 PPM. The DHT22 sensor can read room temperature with an accuracy value of 97.1%. System success rate when working on living room is 100%, room 1 is 100%, room 2 is 100% and bathroom is 100%. The average percentage rate of overall success of the system in work is 100%.

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Indra, Dolly; Hayati, Lilis Nur; Universitas Muslim Indonesia, Indonesia

Abstract

Segmentation is a process to extract the objects in an image. In this study, segmentation process is used to perform skin detection which aims to detect skin pixels and areas in an image. Pixel-based measures is used in the similarity measurement model in image area segmentation to detect skin and non-skin areas in 3 color spaces i.e. RGB with Euclidean distance, HSV with Dcyl distance, HCL with DHCL distance and the thresholding value as the limit of the similarity between two colors. The results of this study indicate that color space segmentation process using thresholding value (Th ≦ 80

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Indra, Dolly; Tasmil, Tasmil; Herman, Herman; Mansyur, St Hajrah; Alwi, Erick Irawadi; Universitas Muslim Indonesia, Indonesia

Abstract

Abstract-- The use of current website technology can be applied as a control and monitoring system, which is used to control electrical devices, so that the user can only control the PC or smartphone that has been connected to Wi-Fi or the Internet. In this case the control uses the Raspberry Pi Mini PC which has several advantages such as low power and is relatively easy when connected with a web server compared to a microcontroller. By utilizing the Raspberry Pi Mini PC as a web server, it can replace PC functions in general. The results in this study are the Electric Control System that has been made capable of controlling 4 AC voltage electronics as well as 4 relays with each relay capable of bearing a maximum load of 2200 watts using a power supply on the Raspberry Pi which has a minimum of 0.7 amperes and Control of electrical load can be done within a distance of 0 meters - 15 meters from the wireless route

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Budiman, Edy; Puspitasari, Novianti, Dept. of Informatics Engineering, Universitas mulawarman Samarinda, Indonesia; Alam, Sitti Nur, Dept. of informatisc engineering, Stimik sepuluh nopember jayapura, Jayapura, Indonesia; Akbar, Mohammad Aldrin, Dept. of Economics Faculty, University of yapis papua, Jayapura, Indonesia; Haeruddin, Dept. of mathematics education, Universitas mulawarman, Samarinda, Indonesia; Indra, Dolly, Universitas muslim indonesia, Makassar, Indonesia

Abstract

The problem of speed of page load time in the Borneo Biodiversity information system which is decreasing has an impact on the level of user satisfaction. The amount of resources used and the amount of data stored causes the system to be slow. The paper analyzes the load time of web pages based on key indicators performance for page loading timings. The variable analysis of webpage for calculates value; loading time (Time to First Byte, First paint time, First contentful paint time, DOM interactive time, DOM loaded time content, Onload time), total page size, and the number of requests. The results of the analysis have given a grade to the web performance and evaluated the results by providing a solution to optimize the low parameter values.

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Indra, Dolly; Mansyur, Umar; Satra, Ramdan; Universitas Muslim Indonesia

Abstract

Mitra pengabdian ini adalah Sekolah Luar Biasa Negeri 2 Makassar. Permasalahan mitra adalah belum adanya informasi berbasis online untuk penyebaran informasi sekolah dan metode pengajaaran masih bersifat konfensional. Pengabdian ini bertujuan melakukan pengabdian dengan menerapkan ICT pada proses belajar mengajar guru dan pembuatan website informasi sekolah. Metode yang digunakan dalam pengabdian ini adalah penerapan ICT dalam proses belajar mengajar dengan membuatkan aplikasi berbasis Mobile Android dan pembuatan webiste informasi sekolah. Pada pengabdian ini dilakukan juga pendampingan bagi guru dan admin webiste desa untuk melatih mengoperasikan aplikasi pembelajarn berbasis mobile dan penginputan informasi pada webiste sekolah . Hasil pengabdian ini adalah telah menerapkan ICT pada sekolah SLB N 2 Makassar. Penerapan ICT pada SLB N 2 Makassar yaitu berupa website http://slbn2makassar.sch.id/ dan aplikasi berbasis Mobile Android dengan nama aplikasi UMIBISA. Hasil pengambilan data pengguna website dan aplikasi menunjukan bahwa penguna merasa tertarik dengan website dan aplikasi dan mereka mudah dalam menggunakan aplikasi dan website tersebut

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Hayati, Lilis Nur; Indra, Dolly; Fahmi, Universitas Muslim Indonesia; Handayani, Anik Nur; Irianto, Wahyu Sakti Gunawan, Universitas Negeri Malang; Asmara, Rosa Andrie, Politeknik Negeri Malang

Abstract

Indonesian Sign Language (BISINDO) is one of the sign languages used in Indonesia. The process of classifying BISINDO can be done by utilizing advances in computer technology such as deep learning. The use of the BISINDO letter classification system with the application of the MobileNet V2 FPNLite SSD model using the TensorFlow object detection API. The purpose of this study is to classify BISINDO letters A-Z and measure the accuracy, precision, recall, and cross-validation performance of the model. The dataset used was 4054 images with a size of consisting of 26 letter classes, which were taken by researchers by applying several research scenarios and limitations. The steps carried out are: dividing the ratio of the simulation dataset 80:20, and applying cross-validation (k-fold = 5). In this study, a real time testing using 2 scenarios was conducted, namely testing with bright light conditions of 500 lux and dim light of 50 lux with an average processing time of 30 frames per second (fps). With a simulation data set ratio of 80:20, 5 iterations were performed, the first iteration yielded a precision result of 0.758 and a recall result of 0.790, and the second iteration yielded a precision result of 0.635 and a recall result of 0.77, then obtained an accuracy score of 0.712, the third iteration provides a recall score of 0.746, the fourth iteration obtains a precision score of 0.713 and a recall score of 0.751, the fifth iteration gives a precision score of 0.742 for a fit score case and the recall score is 0.773. So, the overall average precision score is 0.712 and the overall average recall score is 0.747, indicating that the model built performs very well

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Indra, Dolly; Herman; Budi, Firman Shantya, Universitas Muslim Indonesia

Abstract

The development of computer technology today is very helpful for humans in completing their work in various fields. One application of computer technology i.e., in the field of computer vision which has a very important role for object recognition. In this study, we designed a computer vision-based automatic vehicle counting system. The system that we created uses the MobileNetV2 Single Shot Multibox Detector (SSD) which is placed on the Raspberry Pi 4 to carry out the process of classifying cars and motorcycles and the raspberry pi 4 also functions as a system controller. This automatic vehicle counter system has been integrated between Raspberry Pi 4 and a mobile application on a smartphone where the smartphone functions to display information such as day, date, month, year and together with the number of cars and motorcycles. We tested this automatic vehicle counting system on steam services (car and motorcycle washing) for 3 days where 10 vehicles were collected every day. The test results show that the system is capable of detecting cars and motorcyles with an average accuracy rate of 46.6%

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Indra, Dolly; Ilmawan, Lutfi Budi; Lahuddin, Harlinda; Universitas Muslim Indonesia, Indonesia; Fadlillah, Hadyan Mardhi; Kasman, Kasman;

Abstract

Rice production is massive in Indonesia, therefore maintaining the quality of the product is necessary. Detection and classification of objects have become a very important part in image processing. We performed object detection namely rice. After the object is found, it can be classified into two categories, namely good and damaged rice. We conducted a new study on rice which was carried out per group not per grain to obtain or classify good and damaged rice where we had carried out several steps, namely segmentation process using HSV (hue, saturation, value) color space. HSV is used because of its excellence in representing brightness of the image. We considered evaluating brightness because the tendency of damaged rice is darker or paler compared to good rice. To accomodate environment lighting ambiguity we perform the image acquisition in a controlled environment, so that all the images have the same light intensity. Here we use only channel V of HSV to be used in feature extraction using the gray-level co-occurrence matrix (GLCM) and finally convolutional neural network (CNN) is used for classification. From the test experiments that we have done, we have produced 83% prediction accuracy. Considering how similar the good rice is to the spoiled rice, the results are quite impressive.

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Rahim, Muh.Ridwan; Indra, Dolly; Alwi, Erick Irawadi, Program Studi Teknik Informatika, Universitas Muslim Indonesia, Jalan Urip Sumoharjo KM.05, Makassar, 90231, Indonesia

Abstract

Umumnya masyarakat Indonesia memanfaatkan panas matahari untuk mengeringkan pakaian yang dicuci, namun pada kondisi cuaca yang tidak menentu seperti saat masa pancaroba, aktivitas menjemur menjadi kurang efisien karena harus dilakukan berulang kali saat hujan dan cerah. Kondisi ini menyebabkan pemborosan waktu dan tenaga. Oleh karena itu, diperlukan solusi berupa alat penggerak jemuran dengan kontrol otomatis yang mampu mengoptimalkan pemanfaatan sinar matahari sekaligus menghemat waktu dan tenaga. Alat ini dirancang untuk secara otomatis mengeluarkan jemuran saat cuaca cerah dan menariknya kembali ke tempat yang terlindungi ketika hujan. Dengan demikian, proses pengeringan pakaian menjadi lebih optimal, pakaian dapat kering dengan baik, serta mengurangi kebutuhan intervensi manual dalam mengangkat dan menjemur kembali pakaian.

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Indra, Dolly; Satra, Ramdan; Azis, Huzain; Manga, Abdul Rachman; Universitas Muslim Indonesia, Indonesia

Abstract

Strawberry is one type of fruit that is favored by the people of Indonesia. The detection process to identify strawberries can be done by utilizing advances in computer technology, One of them is in the field of digital image processing. In this study, we made a strawberry ripeness detection system using the values of Red, Green and Blue as the reference values, while for identification in determining the type of classification using the K-Means algorithm that uses the Euclidean distance difference as the reference. Based on the results of testing using the K-Means algorithm on 51 strawberry images consisting of ripe, semi ripe and raw fruit yielding an accuracy rate of 82.14%, we also conducted tests other than strawberry images as many as 8 images yielded an accuracy rate of 100%.

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Indra, Dolly; Universitas Muslim Indonesia, Indonesia

Abstract

SMEs are a type of business that is carried out on a small to medium scale. Bilqis UKM is located in Sanrobone Village, Takalar Regency that focuses on sales, namely school clothes, and uniforms where sales are still conventional. With the rapid development of information technology today, we implement a website-based information system for UKM Bilqis as an online sales medium. In this service, we provide assistance in the use of sales information systems both from shop owners in this case Bilqis UKM, and from buyers taken from random samples. The results in this service are a questionnaire used for application assessment that we made with the result was good.

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Tuasikal, Abdul Rauf; Indra, Dolly; Fattah, Farniwati, Universitas Muslim Indonesia, Jalan Urip Sumoharjo, Makassar, 90231, Makassar

Abstract

Hill Cipher merupakan salah satu algoritma kriptografi kunci simetris yang termasuk dalam kategori polyalphabetic cipher dan dapat diklasifikasikan sebagai block cipher karena teks yang diproses dibagi ke dalam blok-blok dengan ukuran tertentu. Setiap karakter dalam satu blok saling memengaruhi dalam proses enkripsi dan dekripsi sehingga karakter yang sama tidak selalu dipetakan menjadi karakter yang sama. Algoritma ini menggunakan matriks berukuran m × m sebagai kunci, dengan dasar teori yang meliputi operasi perkalian matriks dan invers matriks. Tujuan penelitian ini adalah melakukan kriptanalisis untuk membongkar cipherteks tanpa mengetahui kunci pada metode Hill Cipher. Hasil pengujian menunjukkan bahwa teknik known plaintext dan chosen plaintext dapat digunakan untuk menemukan kunci, dan kedua metode tersebut cukup efektif, dengan tingkat akurasi yang dipengaruhi oleh ordo matriks yang digunakan.

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Umar, Andi Achmad Zufadly; Satma, Satma; Mukarramah, Rifqatul; Agung, Riski Dewa; Amir, Nur Hikmah; Indra, Dolly; Hayati, Lilis Nur; Universitas Muslim Indonesia, Indonesia

Abstract

Many inhabitants of Indonesia, including individuals who have physical characteristics, the characters are different traits supplied by heredity and the formation of characteristics related to the physical environment and social environment. Based on these factors, humans are classified as normal people and those with special needs such as deaf. At Sekolah Luar Biasa Negeri 02 Makassar the sign language learning process still considered less effective because of the limited teaching team. In the PKM-M activities, it aims to introduce the features that provide in Android based PEMBASIINDO consisting of video tutorials. The benefit of this activity is the teaching team can carry out an effective learning process and the program can be useful as a learning media that can be used by the deaf and the general society. The Implementation method of these activities carried out at SLBN starts from observation, design activities, coordination with partner related to the activities, socialization, and training PEMBASIINDO application. The results of these activities are related to increasing knowledge about Indonesian sign language by PEMBASIINDO application media, helping teachers to the learning process and students with hearing impairment to communicating with their friends and the environment related to support the learning process.

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Indra, Dolly, Departmentof Information System, Universitas Muslim Indonesia, Makassar, Indonesia; Ramdaniah, Departmentof Informatics Engineering, Universitas Muslim Indonesia, Makassar, Indonesia; Sukur, Widianti, Department of Information System, Universitas Muslim Indonesia, Makassar, Indonesia

Abstract

Hybrid learning, which combines online and face-to-face instruction, has gained significant attention. Particu-larly in the Faculty of Computer Science, student engagement in hybrid learning is a central concern that arises during implementation. Hybrid, or blended learning, integrates various teaching methods, such as face-to-face, computer-based, and mobile learning, and offers advantages by reducing the time required for meetings and in-formation delivery. Sentiment analysis, a branch of text mining, aims to determine public opinion or sentiment on topics, events, or issues. This study surveyed 112 Information Systems students using an online questionnaire to assess their responses to hybrid learning, classified as positive, negative, or neutral using the Naïve Bayes classi-fier. The research stages included data collection, preprocessing, Naïve Bayes model training, model evaluation, and sentiment analysis. The study aimed to analyze hybrid learning’s impact on students' learning experiences and assess the accuracy of the Naïve Bayes method in classifying sentiments regarding this impact. The results indicated that the initial test had an accuracy of 60.87% withoutusing the SMOTE up-sampling operator, while the second test achieved 80.65% accuracy with the operator.

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Maila, Hayudin Hasnanda; Indra, Dolly; Satra, Ramdan, Universitas Muslim Indonesia, Jalan Urip Sumoharjo, Makassar, 90231, Indonesia

Abstract

Dalam penerapannya, data dan informasi disimpan pada suatu layanan yang disebut server, dan salah satu sarana untuk memperoleh data serta informasi tersebut adalah melalui web, di mana aktivitas pelayanan akan ditanggapi dan diproses oleh web server. Terdapat dua web server berbasis open source yang umum digunakan, yaitu Apache dan Nginx, yang kinerjanya bersama database sebagai media penyedia konten diharapkan mampu memenuhi kebutuhan pengguna. Penelitian ini bertujuan untuk membandingkan ketersediaan layanan data server menggunakan teknik failover cluster pada web server Apache dan Nginx berdasarkan waktu saat proses load atau migrasi server. Hasil penelitian menunjukkan bahwa berdasarkan perbandingan waktu saat load sistem atau perpindahan layanan server, web server Nginx memiliki kualitas layanan yang lebih baik dibandingkan web server Apache, di mana melalui skenario pengujian yang dilakukan, mesin Apache menghasilkan total rata-rata waktu perpindahan layanan sebesar 25,82 detik, sedangkan mesin Nginx menghasilkan total rata-rata waktu perpindahan layanan sebesar 22,98 detik.

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Hayati, Lilis Nur; Indra, Dolly; Magfirah, Fakultas Ilmu Komputer Universitas Muslim Indonesia; Arman, Muh., Fakultas Teknologi Industri Universitas Muslim Indonesia

Abstract

n Indonesia, UKM has an important role in the pace of economy of the community. Many UKM create new jobs that using new staff who can support household income. In UKM of banana chips of ilologading has a problem that is faced, they are not active and understanding about marketing their product extensively. There is still a lack of facilities or media for online information systemsfor information services to market their products. The solution for this service activity are counseling, and marketing of information system-based product in supporting the information service needs of product marketing, training on the implementation of online-based information system applications for product marketing and attractive product packaging design. Beginner PkMD results by facilitating with counseling, simulation and training for UKM by creating a prosperous and clever community in marketing products with online-based information system services at UKM of Ilologading Banana Chips in Borisallo village, Parangloe District, Gowa Regency. The output is 1) The Partner gets online based training modules in product marketing and partner is able to be independent in implementing and skilled in product marketing, 2) Information System application for web-based product marketing, 3) Articles in the media, journal of Balireso LPMD

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Harlinda; Rendi, Ahmad; Azis, Huzain; Indra, Dolly; Hayati, Lilis Nur; Kurniati, Nia, Faculty of Computer Science, Universitas Muslim Indonesia, Makassar, Indonesia

Abstract

The Cia-cia script, one of Indonesia's threatened cultural heritages, was chosen as the object of study due to the lack of research and documentation on the script. This study aims to create an automated system for classifying Cia-cia letters by utilizing the MobileNetV2 architecture and Convolutional Neural Networks (CNN). By applying deep learning techniques, the developed system achieves high accuracy, reaching 98.35% after 100 epochs. The research involved collecting 1823 handwriting samples covering 23 Ciacia alphabets, processed through a series of augmentation and normalization techniques to improve model performance. The results show that artificial intelligence-based technology is effective in documenting and preserving traditional scripts, while providing a foundation for the development of educational applications that can reintroduce Cia-cia alphabets to the younger generation. This research contributes to cultural preservation by integrating modern technology to ensure the continued use of the Cia-cia script in the digital era.

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Indra, Dolly; Syahnur, Muh Haerdiansyah; Hayati, Lilis Nur, Universitas Muslim Indonesia, Makassar, Indonesia

Abstract

This study explores the implementation of a web-based information system for Karang Taruna Parangloe, a youth organization in Kelurahan Lanna, Parangloe District. The initiative was driven by the need to improve information dissemination, which previously relied on traditional methods like WhatsApp groups. While convenient, this approach had limitations in reaching a broader audience and effectively promoting organizational activities. To address these challenges, a Community Partnership Program (PKM) was carried out in four key stages: observation, socialization and training, technology implementation, and evaluation. During the observation phase, it became clear that the organization lacked an official platform for sharing updates and announcements. This was followed by socialization and training sessions, aimed at improving digital literacy among members, equipping them with the skills needed to manage and utilize a web-based system.The technology implementation phase focused on developing and launching the organization's official website, https://karangtarunaparangloe.com. Designed as a comprehensive information hub, the website includes a user guide to help administrators manage content effectively. The evaluation phase showed significant improvements in members' understanding and technical skills, with average post-test scores rising from 62 to 85. More than just a tool for sharing information, the website has helped enhance the organization's image and boost community engagement. This initiative demonstrates the power of digital transformation in empowering youth organizations and strengthening communication within communities. It also serves as an inspiring example for other organizations looking to adopt digital solutions to streamline operations and enhance their outreach efforts.

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Indra, Dolly; Umar, Fitriyani; Jafar, Putri, Universitas Muslim Indonesia, Makassar, Indonesia

Abstract

The problem addressed in this research is the lack of an efficient and accurate method for automaticallyidentifying grape varieties. Accurate identification is crucial for quality control in the agricultural andfood industries, impacting product labeling, pricing, and consumer trust.The aim of this researchisto develop an automated system to classify green, black, and red grapes using digital image processingtechnology.This research methodemploys Napve Bayes classification combined with color featureextraction. Testing was conducted under two scenarios: a database scenario with predefined grapeimage datasets and an out-of-database scenario with images resembling grape colors. Image process-ing includes resizing images to 200200 pixels, Gamma Correction, Gaussian filtering, conversionto Lab* color space, K-Means Clustering for segmentation, followed by feature extraction and NapveBayes classification.The results of thisresearch are that in the database scenario, the system achievedaccuracies of 98.33% with an 80:20 data split and 98.89% with a 70:30 split. In the out-of-databasescenario, accuracies were 96.67% with an 80:20 split and 97.78% with a 70:30 split. The conclusionof this research is the proposed method provides a reliable and efficient solution for automatic grapevariety identification, benefiting quality control in agriculture and food industries.

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Purnawansyah; Indra, Dolly; Hayati, Lilis Nur, Universitas Muslim Indonesia

Abstract

Tujuan program pengabdian yang kami lakukan yaitu memberikan penyuluhan, dan simulasi tentang pemasaran produk, memberikan pelatihan bagi mitra desa Lonjoboko tentang kewirausahaan dalam memasarkan produk berbasis online dan mendesain kemasan yang menarik dan praktis. Metode dalam pelaksanaaan kegiatan ini adalah memfasilitasi dengan penyuluhan, simulasi dan pelatihan bagi para UKM dengan mewujudkan masyarakat sejahtera dan pandai dalam memasarkan produk dengan layanan sistem informasi berbasis online di desa Lonjoboko Kabupaten Gowa dalam bentuk pelatihan. Luarannya Mitra mendapatkan modul pelatihan manajemen kewirausahaan berbasis online untuk memasarkan produknya, mitra mampu mandiri dalam mengimplementasikan dan terampil dalam pemasaran produk, Software Aplikasi Web Sistem Informasi pemasaran produk

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Zainuddin, Arfan; Indra, Dolly; Abdullah, Syahrul Mubarak, Universitas Muslim Indonesia, Jl. Urip Sumoharjo KM. 5, Makassar 90231, Indonesia

Abstract

Proses antrian merupakan suatu aktivitas yang berkaitan dengan kedatangan pelanggan pada suatu fasilitas pelayanan dan menunggu dalam barisan untuk mendapatkan layanan, namun dalam praktiknya sering terjadi masyarakat membatalkan antrian atau meninggalkan sistem akibat panjangnya antrian dan lamanya waktu tunggu yang tidak sesuai dengan harapan. Kondisi ini juga terjadi pada Kantor Dinas Kependudukan dan Pencatatan Sipil Kabupaten Enrekang. Oleh karena itu, penelitian ini bertujuan untuk membantu masyarakat dalam proses antrian dengan menyediakan informasi terkait jadwal dan estimasi waktu tunggu. Sistem yang dikembangkan berupa aplikasi berbasis Android yang memanfaatkan metode push notification dan metode First In First Out (FIFO) untuk menghitung waktu tunggu antrian. Hasil implementasi menunjukkan bahwa sistem antrian yang dibangun mampu mempermudah proses pelayanan antrian di Kantor Dinas Kependudukan dan Pencatatan Sipil Kabupaten Enrekang sehingga menjadi lebih efektif dan efisien.

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Indra , Dolly;Harlinda; Hayati, Lilis Nur; Rismayanti, Nurul Fakultas Ilmu Komputer.Universitas Muslim Indonesia

Abstract

Marketing is one of the most important functions in UKM (Small and Medium Business), where appropriate marketing can determine the sales volume and product position in the market. UKM of shaking flower, Lonjoboko village, Parangloe sub-district has a problem that is they are not active and understanding about marketing their product extensively and still a lack of media facilities for online information systems. On this PkMD for solving the problem of partner such as providing counseling, and simulations about product marketing, provide training for the partner and provide information system service facilities based online. PkMD target is facilitate counseling, simulation and training for UKM by creating realize a prosperous and smart society in marketing products based online. PkMD output is partners get an online entrepreneurship management training module and application based web and partner is able to be independent in implementing it and articles in the media.

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Herman, Faculty of Computer Science, Universitas Muslim Indonesia, Makassar, Indonesia; Nasir, Haidawati; Noor, Megat Norulazmi Megat Mohamed, Computer Engineering Technology, MIIT Universiti Kuala Lumpur, Kuala Lumpur, Malaysia; Hasanuddin, Tasrif; Indra, Dolly, Faculty of Computer Science, Universitas Muslim Indonesia, Makassar, Indonesia; Lumentut, Hence Beedwel, Computer Engineering, STMIK Agamua Wamena, Wamena, Indonesia

Abstract

Toraja is a part of Indonesia located on the island of Sulawesi. One form of Toraja culture is carving art made from wood, bamboo or stone. There are around 70 types of Toraja carving motifs. With so many motifs and some motifs being almost similar to each other, it can make it difficult for the public and tourists to know the name of the motif. This research focuses on classifying Toraja carving images using Convolutional Neural Network (CNN) and measuring the performance of the LeN et-5 architecture. The number of Toraja carving motifs used in this research is 7 and the data is 700, where each motif is represented by 100 data. In testing, 3 explorations were carried out, namely dividing training and validation data, Batch Size values, and Target Size values. Based on test results, the 70:30 data division provides the highest level of accuracy compared to other data divisions. Increasing the Batch Size value has a negative impact on the level of accuracy. On the other hand, increasing the Target Size value has a positive impact on the accuracy value. The best Batch Size and Target Size values in this study were 32 and 256x256 with respective accuracies of 50.67% and 69.33%.

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Indra, Dolly; Umar, Fitriyani; Fattah, Farniwati; Azis, Huzain; Manga, Abdul Rachman, Faculty Of Computer Science, Universitas Muslim Indonesia, Makassar, Indonesia

Abstract

The global spread of COVID-19 had altered human behavior. One example was the shift from direct touch to less contact in interpersonal interactions. At that time, during the COVID-19 pandemic, digital technology was vital for reducing and eliminating social, physical, and psychological risk factors and managing the long-term consequences of social isolation and lockdown loneliness. Throughout the previous decade, various nations, notably developing nations, have embraced technology and adapted it to local conditions in response to the pandemic. The technologies are advantageous and might be expanded for further applications. This chapter will discuss deploying various technologies, including an automatic barrier gate, a smart stick for the blind, and automatic handwashing. These instruments utilized microcontroller technology. These tools are helpful, but they require further improvement.

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Indra, Dolly; Alwi, Erick Irawadi, Fakultas Ilmu Komputer, Universitas Muslim Indonesia

Abstract

Mizanul Ulum Islamic Boarding School has problems in educational activities, namely the learning model provided by teachers to students is conventional and has not utilized computer technology. The service we carry out aims to make partners gain knowledge about the benefits of information and communication technology by conducting outreach and training to teachers. Socialization and training for Learning module consists of learning Word, Excel, Power Point and using Google Forms. To find out the results of this socialization, we conducted an evaluation of the teachers through a pretest and posttest with a total of 30 questions with a maximum score of 30. Participants involved in the socialization were 16 teachers. Based on the evaluation results, it was found that the pretest score was 334 and the posttest score was 414. The average pretest score was 20.875 and posttest was 25.875 while the maximum pretest score was 26 and posttest was 28, the minimum score for pretest was 15 and posttest was 23. The socialization activity that we carried out at the Mizanul Ulum Sanrobone Islamic Boarding School in Takalar Regency was able to increase the knowledge of teachers.

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Indra, Dolly, Departemen Sistem Informasi, Fakultas Ilmu Komputer, Universitas Muslim Indonesia; Ilmawan, Lutfi Budi, Departemen Teknik Infomatika, Fakultas Ilmu Komputer, Universitas Muslim Indonesia

Abstract

This community service partner is Autis Bunda Special School (SLB). Our partner’s issue is the lack of an official school information platform in the form of a website. The school has been using traditional methods for information dissemination. This community project aims to implement a web-based information system for the Autis Bunda Special School (SLB). The methods employed in this service include observation, interviews, data collection, design, socialization, implementation of the school website, and training. We also evaluated 11 Autis Bunda Special School teachers, assessing their knowledge about website information systems through pretests and posttests. This community service initiative resulted in creating the SLB Autis Bunda school website, accessible at the link https://slbautisbunda.sch.id/. The school website administrators we trained have been able to update information independently. The measurement results from the pretests and posttests show increased knowledge among the teachers, with average pretest and post-test scores of 61.36 and 89.09, respectively.

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Munawar, Zen; Hasnawi, Mardiyyah; Beno, Ishak Semuel; Darma, I. Wayan Agus Surya; Sastradipraja, Cecep Kurnia; Sutramiani, Ni Putu; Amir, Ashadi; Manurung, Halomoan Edy; Mandowen, Samuel Aleksander; Pomalinggo, Suwito; Indra, Dolly; Irmawati; Setywan, Adhita Arif; Mansyur, St. Hajrah; Koibur, Mayko Edison

Abstract

Buku Visi Komputer: Konsep, Metode, dan Aplikasi memberikan pengantar yang komprehensif dan terperinci tentang konsep dasar dan perkembangan terbaru dalam bidang komputer visi. Buku ini mencakup topik-topik mulai dari classical computer vision hingga deep learning, convolutional neural networks, object detection, face recognition, image segmentation, image stitching, dan augmented reality. Penulis juga membahas algoritma, teknik, dan library yang dapat digunakan untuk memproses citra dan video, serta memberikan studi kasus yang menarik untuk mengilustrasikan konsep yang dijelaskan. Buku ini sangat cocok untuk pembaca pemula yang ingin mempelajari dasar-dasar komputer visi, serta bagi mereka yang ingin memperluas pengetahuan mereka tentang topik terkait.

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Indra, Dolly; Ilmawan, Lutfi Budi, Mansyur, Budi, Universitas Muslim Indonesia

Abstract

Dalam pengabdian masyarakat ini kami sebagai pengabdi berkolaborasi dengan Sekolah Luar Biasa (SLB) Autis Bunda yang menghadapi tantangan terkait ketersediaan media pembelajaran berbasis digital. Selama ini, sekolah ini telah mengandalkan metode konvensional seperti ceramah, papan tulis, dan pengajaran melalui kertas dan pensil. Tujuan utama dari pengabdian ini adalah menerapkan sistem pembelajaran digital berbasis android yang inovatif di SLB Autis Bunda. Metode pelaksanaan pengabdian ini meliputi observasi, wawancara, perancangan aplikasi, sosialisasi, pelatihan, dan penerapan aplikasi bernama "GEMA" (Game dan Edukasi Mobile untuk Anak). Selain itu, pengabdian ini juga melibatkan evaluasi terhadap 11 guru SLB Autis Bunda untuk mengukur peningkatan pengetahuan mereka tentang aplikasi mobile. Hasil evaluasi ini disusun berdasarkan uji pretest dan posttest, di mana rata-rata nilai pretest awalnya mencapai 59.55 dan mengalami peningkatan menjadi 88.64 pada posttest

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Indra, Dolly; Hayati, Lilis Nur; Asis, Muhammad Arfah, Universitas Muslim Indonesia

Abstract

Al-Fadhilah Store is one of the fruit stores located in Makassar. The increasing demand for fruits among the community has led to customers becoming more discerning in product selection and having diverse needs. It is important for Al-Fadhilah Store to enhance sales by considering customer satisfaction levels. This research adopts a quantitative method involving 70 customer respondents. The hypothesis test results indicate that the Sales Strategy variable (X) has a positive and significant influence on Customer Satisfaction (Y) at Al-Fadhilah Store in Makassar. In this study we used several tests, namely the Validity test, Reliability test, Normality Test, Multicollinearity Test, Heteroscedasticity Test, Simple Linear Regression Test, Coefficient of Determination Test, T-test and F-test. Based on several tests conducted, it has been found that the Sales Strategy (X) variable has a positive and significant impact on Customer Satisfaction (Y) at Al-Fadhilah Store in Makassar. This relationship indicates that variable X has a good relationship with Y, from the results of the coefficient of determination or R square which indicates that 81.1% of Customer Satisfaction (Y) is influenced by the variable Sales Strategy (X) The rest is equal to 18.9 % influenced by other factors

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Indra; Dolly, Alwi; Erick Irawadi,

Abstract

Program Pengabdian Kepada Masyarakat (PKM) ini dilaksanakan dengan tujuan utama untuk meningkatkan literasi digital bagi para pengelola dan anggota Rumah Baca Pangngadakkang. Intervensi ini dinilai penting karena peran rumah baca sebagai pusat literasi semakin krusial di tengah tantangan literasi digital yang ada di Indonesia. Revolusi digital yang kian pesat menuntut kompetensi literasi dan digital untuk menghadapi tumbuhnya masyarakat informasi dan jaringan. Oleh karena itu, PKM ini berfokus pada pelatihan penggunaan aplikasi Canva untuk mendorong kemampuan kreatif dalam membuat konten visual yang menarik dan edukatif, serta Microsoft Excel untuk memperkuat keterampilan dalam pencatatan dan pengelolaan data rumah baca secara digital. Pelaksanaan kegiatan melalui tahapan observasi, sosialisasi, pelatihan, dan evaluasi. Hasil evaluasi terhadap 22 peserta menunjukkan perbaikan nilai rata-rata posttest yang cukup mencolok untuk Canva yaitu 80.00 dari pretest 65.00, dan untuk Microsoft Excel naik drastis menjadi 80.45 dari pretest 45.00. Keberhasilan program ini didukung oleh fasilitas yang memadai dan antusiasme tinggi dari para peserta, serta dampak langsungnya terlihat pada peningkatan kapasitas literasi digital dan manajemen administrasi rumah baca.

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Ariani, Lisna; Indra, Dolly; Umar, Fitriyani, Universitas Muslim Indonesia, Makassar, Indonesia

Abstract

Cengkeh merupakan salah satu komoditas unggulan di sektor pertanian Indonesia yang memiliki nilai ekonomi tinggi, namun rentan mengalami penurunan kualitas akibat kontaminasi jamur selama proses panen dan pascapanen. Selama ini, proses klasifikasi cengkeh berjamur dan tidak berjamur masih dilakukan secara manual, yang cenderung tidak efisien, subjektif, dan berpotensi menimbulkan inkonsistensi, terutama ketika harus menangani volume data dalam jumlah besar. Oleh karena itu, penelitian ini dirancang untuk mengembangkan sistem klasifikasi otomatis berbasis kecerdasan buatan menggunakan metode Convolutional Neural Network (CNN) dengan arsitektur InceptionV3. Penelitian akan dilakukan di Kecamatan Lasusua, Kabupaten Kolaka Utara, dengan menggunakan dataset sebanyak 1.000 citra digital cengkeh yang diambil dari dua pose berbeda. Seluruh citra akan melalui tahapan preprocessing dan augmentasi guna memperkuat kualitas dan keragaman data, sebelum digunakan dalam proses pelatihan model CNN. Evaluasi terhadap performa model akan dilakukan dengan mengukur nilai akurasi, presisi, recall, dan F1-score untuk menentukan sejauh mana efektivitas sistem dalam mengklasifikasikan cengkeh ke dalam dua kelas, yaitu berjamur dan tidak berjamur. Diharapkan hasil dari penelitian ini dapat memberikan kontribusi nyata terhadap peningkatan efisiensi, akurasi, dan objektivitas dalam proses sortasi cengkeh serta menjadi langkah awal dalam penerapan teknologi deep learning untuk mendukung digitalisasi mutu hasil pertanian, khususnya pada komoditas strategis seperti cengkeh

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Dolly, Indra, Departement of information Systems, Computer Science, Universitas Muslim Indonesia, Indonesia; Ramdaniah; Ode, Nada Kayatri, Department of Informatic Engineering, Computer Science, Universitas Muslim Indonesia, Indonesia

Abstract

Deforestation in Papua has emerged as a significant environmental concern, attracting considerable attention due to its effects on biodiversity and the livelihoods of indigenous communities. This study seeks to examine public sentiment toward the issue by analyzing comments posted on the YouTube platform, employing the Long Short-Term Memory (LSTM) method. A dataset of 3,000 comments was gathered and processed through several stages, including text cleaning, tokenization, normalization, and Term Frequency–Inverse Document Frequency (TF-IDF) weighting. Subsequently, an LSTM model was developed and assessed using accuracy, precision, recall, and F1-score as evaluation metrics. The results reveal that the LSTM model achieved an accuracy of 88.43%, a precision of 90.01%, a recall of 97.49%, and an F1-score of 93.60%. Nevertheless, signs of overfitting were observed, indicated by lower validation performance compared to training results. These findings demonstrate that the LSTM approach is effective for identifying public opinion regarding deforestation and can serve as a valuable reference in decision-making and the formulation of environmental policies.

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Fathrurahman, Fauzy; Indra, Dolly; Hasanuddin, Tasrif; Darwis, Herdianti, Universitas Muslim Indonesia, Makassar, Indonesia; Kazuaki, Tanaka, Kyushu Institute of Technology, Iizuka, Japan

Abstract

Background: Waste mismanagement remains a critical issue in Indonesian campuses, where ineffective segregation and collection practices contribute to environmental pollution. Smart technologies offer opportunities to improve waste handling efficiency and monitoring in university environments. Methods: This study developed a smart waste bin prototype that integrates Internet of Things (IoT) sensors, machine learning–based image classification (MobileNetV2 with TensorFlow Lite), GPS tracking, and LoRa communication. The system was designed to classify three types of waste—plastic bottles, snack packaging, and cans—while enabling fill-level monitoring, automated sorting, and real-time location reporting. Results: Experimental results showed strong classification accuracy for plastic bottles (100%), but lower performance for snack packaging (53–80%) and cans (40–67%), especially in low-light conditions or with darker materials. The overall real-time testing accuracy reached 45.1%. LoRa communication provided long-range connectivity but was affected by electromagnetic interference, while GPS tracking was reliable in open areas but inconsistent indoors. Conclusions: The prototype demonstrates the feasibility of integrating AI and IoT for scalable campus waste management. Despite environmental and hardware limitations, it offers a modular framework that can be refined with improved lighting, EMI shielding, and enhanced datasets. This research contributes a practical model for smart campus initiatives and supports the adoption of sustainable waste management practices in higher education environments.

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Hayati, Lilis Nur; Indra, Dolly; Djamereng, Asdar; Suat, Wahyu Kadri Rahmat; Scania, Muhammad Rifky Saputra; Scania, Dewi Ernita, Universitas Muslim Indonesia

Abstract

This community engagement program aims to empower the "Kana Tojeng" craftswomen group in Bontokassi Village, Galesong Selatan District, Takalar Regency, through training in e-commerce-based marketing of woven products made from lontara fiber. The primary issues faced by the partners include limited understanding of digital marketing, lack of an established online business identity, and underutilization of e-commerce platforms. The method applied was an educational-participatory approach, consisting of observation, awareness sessions, hands-on training, and evaluation. The results show a significant improvement in participants' knowledge and skills, with pre-test scores at 50.30% and post-test scores reaching 86.19%. The program also resulted in the activation of e-commerce accounts and enhanced digital marketing capabilities among local artisans. Supporting factors included high participant enthusiasm and contextual learning materials, while limitations in digital infrastructure emerged as the main challenge. This initiative demonstrates that integrating information technology into local business management is an effective strategy for enhancing the competitiveness of culturally rooted products.

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Mandasari, Juita; Indra, Dolly; Gafar, Andi Widya Mufila, Universitas Muslim Indonesia, Makassar, Indonesia

Abstract

Tanaman seledri merupakan komoditas hortikultura bernilai tinggi yang membutuhkan kelembapan tanah ideal antara 65%–75% untuk pertumbuhan optimal. Namun, proses penyiraman secara manual sering kali tidak konsisten dan bergantung pada kehadiran petani. Pemantauan kondisi tanah merupakan hal yang penting dalam melakukan penyiraman tanaman dengan kadar air yang sesuai. Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem penyiraman otomatis berbasis Arduino Uno dan komunikasi LoRa untuk budidaya seledri skala kecil. Sistem ini memanfaatkan sensor soil moisture untuk mendeteksi tingkat kelembapan tanah, kemudian mengaktifkan pompa air secara otomatis melalui relay jika kelembapan berada di bawah ambang batas. Modul LoRa digunakan sebagai media komunikasi jarak jauh antara unit transmitter dan receiver, sementara LCD 16x2 menampilkan data kelembapan dan status pompa secara real-time. Sistem ini dirancang untuk melakukan penyiraman otomatis dan komunikasi LoRa yang dapat memantau kondisi tanah dan melakukan penyiraman secara mandiri sesuai dengan kebutuhan tanaman. Hasil pengujian simulator menunjukkan bahwa seluruh komponen bekerja dengan baik

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Hayati; Lilis Nur, Department of Electrical Engineering and Informatics, Universitas Negeri Malang, Malang, Indonesia; Department of Computer Science, Universitas Muslim Indonesia, Makassar, Indonesia; Handayani, Anik Nur; Irianto, Wahyu Sakti Gunawan, Department of Electrical Engineering and Informatics, Universitas Negeri Malang, Malang, Indonesia; Asmara, Rosa Andrie, Information Technology Department, Politeknik Negeri Malang, Malang, Indonesia; Indra, Dolly, Department of Computer Science, Universitas Muslim Indonesia, Makassar, Indonesia; Damanhuri, Nor Salwa, Electrical Engineering Studies, Universiti Teknologi MARA (UiTM),Cawangan Pulau Pinang, Malaysia

Abstract

Sign language recognition plays a critical role in promoting inclusive education, particularly for deaf children in Indonesia. However, many existing systems struggle with real-time performance and sensitivity to lighting variations, limiting their applicability in real-world settings. This study addresses these issues by optimizing a BISINDO (Bahasa Isyarat Indonesia) alphabet recognition system using the SSD MobileNetV2 architecture, enhanced with gamma correction as a luminance normalization technique. The research contribution is the integration of gamma correction preprocessing with SSD MobileNetV2, tailored for BISINDO and implemented on a low-cost assistive robot platform. This approach aims to improve robustness under diverse lighting conditions while maintaining real-time capability without the use of specialized sensors or wearables. The proposed method involves data collection, image augmentation, gamma correction (γ = 1.2, 1.5, and 2.0), and training using the SSD MobileNetV2 FPNLite 320x320 model. The dataset consists of 1,820 original images expanded to 5,096 via augmentation, with 26 BISINDO alphabet classes. The system was evaluated under indoor and outdoor conditions. Experimental results showed significant improvements with gamma correction. Indoor accuracy increased from 94.47% to 97.33%, precision from 91.30% to 95.23%, and recall from 97.87% to 99.57%. Outdoor accuracy improved from 93.80% to 97.30%, with precision rising from 90.33% to 94.73%, and recall reaching 100%. In conclusion, the proposed system offers a reliable, real-time solution for BISINDO recognition in low-resource educational environments. Future work includes the recognition of two-handed gestures and integration with natural language processing for enhanced contextual understanding.

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Hayati, Lilis Nur; Indra, Dolly; Suat, Wahyu Kadri Rahmat; Scania, Muhammad Rifky Saputra; Rahma, Dewi Ernita, Fakultas Ilmu Komputer , Universitas Muslim Indonesia, Makassar, Indonesia

Abstract

Kegiatan pengabdian ini berhasil Meningkatkan Daya Saing Pengrajin Anyaman Lontara Kana Tojeng Melalui Edukasi Penggunaan Media Sosial di Desa Bontokassi di Desa Bontokassi. Berdasarkan hasil evaluasi menggunakan instrumen pre-test dan post-test yang terdiri dari 10 butir pertanyaan, dengan koresponden 20 anggota pengerajin Kana Tojeng terjadi peningkatan pemahaman yang signifikan. Skor rata-rata pre-test peserta berada pada angka 45,8%, sedangkan nilai post-test meningkat menjadi 75,5%, yang menunjukkan efektivitas pendekatan edukatif-partisipatif dalam mentransfer pengetahuan Penggunaan Media Sosial mitra. Memperlihatkan perbandingan yang jelas antara sebelum dan sesudah sosialisasi, yang turut memperkuat bukti pencapaian program. Di samping peningkatan kognitif, mitra juga menunjukkan perubahan Penggunaan Media Sosia untuk produk kerajinan. Secara umum, hasil kegiatan ini tidak hanya memperkuat daya saing produk lokal berbasis budaya, tetapi juga membuka peluang baru untuk ekspansi digital melalui e-commerce dan kolaborasi lebih luas di masa mendatang.

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Indra, Dolly; Manga, Abdul Rachman; Harlinda; Herman; Alwi, Erick Irawadi; Mansyur, St. Hajrah; Nurhayati, Lilis; Purnawansyah; Fajrin, Ade Moehammad; Universitas Muslim Indonesia, Indonesia

Abstract

Penyandang tuna netra saat ini masih memiliki kesulitan dalam melakukan aktifitasnya terutama dalam masalah mobilitas di dalam masyarakat. Hal ini tentunya diakibatkan karna masih minimnya sarana dan prasarana yang dapat menunjang para penyandang tuna netra dalam melakukan kegiatan sehari-hari. Salah satu alat bantu yang biasa digunakan oleh penyandang tuna netra untuk melakukan kegiatan sehari-hari adalah tongkat tuna netra, dengan tongkat ini para penyandang tuna netra cukup terbantu terutama ketika berjalan, namun tongkat tuna netra tersebut masih memiliki keterbatasan, salah satunya adalah tidak dapat mendeteksi keberadaan objek yang berada diluar dari jangkauan tongkat tersebut, dengan kata lain penyandang tuna netra dapat merasakan objek yang ada disekitarnya ketika tongkat tuna netra menyentuh objek tersebut. Maka dari itu pada penelitian ini dikembangkan sebuah konsep alat bantu jalan bagi penyandang tuna netra dengan menambahkan sebuah perangkat baru yang dapat menutupi keterbatasan yang ada pada tongkat tuna netra. Alat yang dirancang memanfaatkan teknologi mikrokontoler berupa arduino, sensor ultrasonik, modul Mp3 dan micro DC.

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Taliba,Juraiz Hi.; Mansyur, St. Hajrah; Indra, Dolly, Universitas Muslim Indonesia, Makassar, Indonesia

Abstract

Penerimaan siswa baru adalah suatu hal yang perlu ditentukan secara cepat dan tepat. Dalam hal penentuan calon siswa baru di perlukan beberapa pertimbangan yang cukup banyak dan rumit yaitu standarisasi nilai, persyaratan masuk serta kebijakan-kebijakan dari pemerintah dan lembaga pendidikan yang sering berubah setiap tahunnya. Selama ini pemilihan sekolah yang dilakukan oleh siswa SMP Negeri 42 Halmahera Selatan tetap di lakukan secara subjektif tanpa ada penyeleksian artinya penilaian tentang kemampuan siswa hanya dari pengamatan saja tanpa adanya parameter dan siswa yang memilih sekolah untuk melanjutkan pendidikan tingakat menengah atas tidak mendapatkan hasil yang maksimal karena tidak sesuai dengan kemampuan yang di miliki. Penelitian ini bertujuan untuk menentukan jenjang pendidikan tingkat menengah atas yang akan menjadi rekomendasi pada siswa kelas IX SMP Negeri 42 Halmahera Selatan berbasis website. Metode yang digunakan adalah Profile Matching yang merupakan metode dalam keputusan pendukung sistem (SPK) karena perhitungan yang dilakukan dengan pembobotan dan perhitungan gap. Berdasarkan hasil penelitian yang telah dilakukan pada SMP Negeri 42 Halmahera selatan dengan menerapkan metode profile matching maka dari 15 data jenjeng pendidikan tingkat menengah atas diperoleh, pertama madrasah Aliyah ulul albab dengan nilai 4,7 lalu SMA Negeri 5 kota ternate dengan Nilai 4,64 dan SMK Bina infomartika Kota Ternate dengan nilai 4,58 yang menjadi rekomendasi untuk siswa kelas IX SMP Negeri 42 Halmahera Selatan. Adapun hasil dari pengujian dari aplikasi menggunakan Blackbox Testing berdasarkan rencana pengujian maka diperoleh kesimpulan diterima.

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Indra, Dolly; Hayati, Lilis Nur; Irja, Mulianty Cipta, Universitas Muslim Indonesia,

Abstract

Digital image processing, also known as digital image manipulation, is a method used to process or manipulate digital images. Digital image processing can address various problem domains, one of which is the recognition of Indonesian Sign Language (BISINDO) letters used by the deaf and speech-impaired individuals for communication. The aim of our research is to develop a digital image-based application that can recognize BISINDO letters from A to Z with a high level of letter similarity accuracy. The BISINDO letter dataset consists of 260 images, divided into an 80% (208 images) training data set and a 20% (52 images) testing data set. The letter recognition process begins with pre-processing, including converting RGB images to grayscale, segmentation using thresholding, morphological opening, and Sobel edge detection. The shape feature extraction is then performed using Chain Code Contour. The values obtained from this feature extraction are used in the final stage, which is the recognition of BISINDO letter images using the Naive Bayes classification method. The research involves two testing scenarios: a database scenario and an out-of-database scenario, each with three dataset divisions: 80:20, 70:30, and 60:40. The results of the database scenario testing with an 80:20 dataset division achieved 100% accuracy, while the 70:30 division achieved 92.3% accuracy, and the 60:40 division achieved 88.4% accuracy. In the out-of-database scenario, the 80:20 dataset division achieved 80.7% accuracy, the 70:30 division achieved 73.07% accuracy, and the 60:40 division achieved 75.9% accuracy. Based on the conducted testing, the best accuracy was obtained with the 80:20 dataset division, achieving 100% accuracy in the database scenario and 80.7% accuracy in the out-of-database scenario. This indicates that the Chain Code Contour shape feature extraction method and Naive Bayes classification method are capable of recognizing BISINDO letters effectively.

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Indra, Dolly; Hayati, Lilis Nur; Syahnur, Muhammad Haerdiansyah; Suat, Wahyu Kadri Rahmat; Scania, Muhammad Rifky Saputra, Universitas Muslim Indonesia

Abstract

This initiative's service partner is a Parangloe Youth Organization member. The challenge faced by this group is a lack of digital literacy, particularly in utilizing digital technology for personal development. This service aims to empower Parangloe Youth Organization members by equipping them with graphic design skills using Canva. The methods employed in this service include observation, socialization, training, and evaluation. We assessed the graphic design knowledge of 30 youth organization members through pretests and posttests. The results indicated that members who received training can now create graphic designs using Canva. The evaluation revealed a significant improvement in knowledge, with average pretest and posttest scores of 66.303 and 82.709, respectively.

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Ramadan, Syahril; Indra, Dolly; Azis, Huzain, Universitas Muslim Indonesia

Abstract

Sistem informasi kependudukan merupakan salah satu faktor utama dalam pemerintahan dan pembangunan kependudukan yang diarahakan pada pemenuhan hak dari setiap warga negara dibidang pelayanan data kependudukan. Desa Kaduaja salah satu bagian dari Desa di Kecamatan Gandangbatu Sillanan Kabupaten Tana Toraja, pengelolaan data pada Kantor Desa Kaduaja dilakukan secara manual mengakibatkan dokumen-dokumen tersebut disusun dengan tidak teratur dan tersimpan pada arsip yang terpisah sehingga pihak pemerintah Desa Kaduaja, untuk menyelesaikan permasalahan tersebut dibangunlah sebuah sistem informasi data kependudukan. penelitian ini menghasikan sistem informasi data kependudukan Desa Kaduaja Kecamatan Gandangbatu sillanan berbasis web yang dapat mempermudah pemerintah desa mengolah data kependudukan. metode yang digunakan dalam perancangan aplikasi yaitu metode waterfall yaitu model dimana tiap tahapannya dikerjakan secara berurutan dari atas ke bawah. Pengujian yang dilakukan berdasarkan blackbox testing mendapatkan nilai penggunaan secara keseluruhan dalam tampilan interface maupun fungsionalitas aplikasi yaitu 85% dari 24 responden.

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Suherman, Muh Yeyen Dwi; Indra, Dolly; Manga, Abdul Rachman, Universitas Muslim Indonesia, Makassar, Indonesia

Abstract

Kebiasaan merokok sering kita jumpai di kafe dan tempat umum lainnya. Kebiasaan ini dapat membuat pengunjung lain merasa canggung dengan asap rokok. Udara bersih tentu dibutuhkan oleh semua orang, baik orang dewasa, tua, maupun muda, Namun, banyak orang yang mengotori udara bersih, salah satu contohnya adalah dengan merokok di tempat umum. Kurangnya kesadaran dan pandangan negatif masyarakat setempat tentang risiko rokok bagi mereka dan orang di sekitar mereka, membuat kurangnya kapasitas masyarakat setempat mengubah cara berperilaku dan menciptakan lingkungan yang sehat. Oleh karena itu, upaya pencegahan harus dilakukan di rumah, di kelas, dan di masyarakat. Dengan hal tersebut peneliti membuat rancangan bangun prototype smoke detector berbasis arduino uno R3. Dengan menggunakan beberapa komponen alat yang dapat membantu mendeteksi asap rokok seperti arduino uno R3 berfungsi untuk mengolah hasil input-an yang dibaca oleh sensor MQ 135 kemudian mengeluarkan output sesuai dengan apa yang telah diprogramkan. MQ 135 berfungsi mendeteksi asap rokok, L298n sebagai pengatur kecepatan pada fan, LCD 12c menampilkan data yang tersedia, fan untuk mengeluarkan asap

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Utami, Amalia Putri; Indra, Dolly; Umar Fitriyani,. Universitas Muslim Indoensia;

Abstract

Identifikasi daun herbal secara manual sering mengalami kendala akibat kemiripan visual antarspesies yang berpotensi menimbulkan kesalahan pemanfaatan. Penelitian ini bertujuan mengklasifikasikan sepuluh jenis daun herbal menggunakan kombinasi fitur tekstur Local Binary Pattern (LBP) dan fitur bentuk, yaitu aspect ratio, eccentricity, circularity, dan convexity. Dataset terdiri dari 500 citra yang dibagi menjadi 400 data latih dan 100 data uji dengan rasio 80: 20. Tahap pre-processing meliputi resize, konversi ke grayscale, dan Gaussian Blur untuk mengurangi noise. Segmentasi dilakukan menggunakan Otsu thresholding untuk memperoleh objek daun dan Canny Edge Detection untuk menonjolkan struktur tekstur. Proses klasifikasi menerapkan algoritma Random Forest dengan pengujian beberapa kombinasi parameter guna memperoleh model optimal. Hasil terbaik diperoleh pada model dengan n_estimators= 200, max_features= 2, max_depth= none, dan min_samples_leaf= 2, yang menghasilkan akurasi 92%, precision 92%, recall 92%, dan F1-score 92%.

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Hayati, Lilis Nur; Indra Dolly, Universitas Muslim Indonesia; Handayani, Anik Nur; Irianti, Wahyu Sakti Gunawan, Universitas Negeri Malang; Damanhuri Nor Salwa, Universiti Teknologi MARA (UiTM);

Abstract

Indonesian Sign Language (Bahasa Isyarat Indonesia/BISINDO) enables communication for deaf individuals through hand gestures, yet limited public awareness creates significant barriers between deaf and hearing communities. Existing recognition systems often fail to generalize across diverse skin tones, reducing their effectiveness in inclusive real-world deployment. The contribution of this research is a BISINDO alphabet recognition system that integrates skin color features - extracted via HSV-based skin segmentation - as an additional preprocessing layer within the Faster R-CNN framework, explicitly improving detection robustness across varied skin tones. The dataset consists of 8,000 images from ten adult actors representing light, medium-brown, and dark skin tones, augmented through flipping and brightness variation, with a 90:10 training-to-testing ratio. The model was trained over 15,000 steps with a batch size of 24, selected through empirical validation to balance convergence stability and dataset size. Experimental results show that indoor conditions outperform outdoor settings due to controlled lighting. Light-skinned and dark-skinned participants achieved the highest accuracy of 87.5% and F1-score of 85.71%, while medium-brown-skinned participants showed slightly lower performance, likely attributed to greater variability in reflectance under mixed lighting. The system achieves 24 frames per second, demonstrating potential for real-time communication support. These findings confirm that Faster R-CNN with skin color feature integration is effective for BISINDO alphabet recognition, with skin tone diversity being a critical performance factor. Future work will explore larger participant pools and dynamic gesture recognition under varied real-world lighting scenarios.

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Husain, Alfiansyah Anugrah; Indra Dolly; Jabir Sitti Rahmah, Universitas Muslim Indonesia;

Abstract

Platform X menjadi ruang utama bagi masyarakat dalam mengekspresikan opini terhadap tokoh publik, termasuk Kang Dedi Mulyadi. Penelitian ini bertujuan menganalisis sentimen publik sekaligus menjawab keterbatasan studi sebelumnya yang umumnya berfokus pada isu politik nasional atau hanya menggunakan satu algoritma klasifikasi, sehingga perbandingan kinerja model pada konteks figur politik daerah masih terbatas. Data penelitian terdiri dari 7.190 tweet yang dikumpulkan melalui crawling selama Februari–September 2025. Data diproses melalui tahapan pre-processing, kemudian dilabeli otomatis menggunakan InSet Lexicon ke dalam sentimen positif dan negatif. Ekstraksi fitur dilakukan dengan TF-IDF menggunakan konfigurasi n-gram (1,2), dengan pembagian data 80:20 untuk pelatihan dan pengujian. Hasil pengujian menunjukkan bahwa SVM Linear memberikan performa terbaik dengan akurasi 0,8982, presisi 0,8991, recall 0,8970, dan F1-score 0,8977. Sementara itu, Naïve Bayes menghasilkan akurasi 0,8287, presisi 0,8297, recall 0,8268, dan F1-score 0,8276. Temuan ini menunjukkan bahwa SVM lebih efektif dibandingkan Naïve Bayes dalam mengklasifikasikan sentimen publik pada data media sosial X, serta memberikan kontribusi empiris pada kajian analisis sentimen tokoh politik berbasis media sosial

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Hayati, Lilis Nur; Indra Dolly, Universitas Muslim Indonesia; Djamereng Asdar;

Abstract

Buku “Rahasia Social Media Marketing untuk Bisnis Online” membahas bagaimana media sosial dapat dimanfaatkan secara optimal untuk mengembangkan bisnis di era digital. Pembahasan dimulai dari pemahaman dasar mengenai media sosial, jenis-jenis platform yang populer, serta peluang yang dapat dimanfaatkan oleh pelaku usaha untuk memperluas jangkauan pasar dan membangun hubungan dengan pelanggan. Buku ini juga menjelaskan berbagai keunggulan media sosial sebagai sarana promosi yang mudah diakses, interaktif, dan mampu menjangkau audiens secara luas. Selain peluang, dijelaskan pula tantangan yang sering dihadapi dalam mengelola media sosial sehingga pembaca dapat memahami pentingnya strategi yang tepat dalam menjalankan pemasaran digital. Buku ini memberikan panduan praktis mengenai cara membuat dan mengelola akun bisnis di berbagai platform media sosial, teknik membuat konten yang menarik, serta langkah membangun identitas brand yang kuat. Berbagai strategi promosi seperti kolaborasi, penggunaan influencer, hingga pemanfaatan fitur iklan juga dibahas secara sistematis agar bisnis dapat berkembang secara lebih efektif. Melalui penjelasan yang mudah dipahami dan disertai contoh penerapan, buku ini diharapkan dapat menjadi panduan bagi pelaku usaha, pelajar, maupun siapa saja yang ingin memanfaatkan media sosial sebagai sarana membangun dan mengembangkan bisnis online secara berkelanjutan.

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Astuti, Wistiani; Mude, Muh Aliyazid; Abdullah Syahrul Mubarak; Kurniati, Nia; Indra, Dolly; Manga, Abul Rachman; Ilmawan, Lutfi Budi, Universitas Muslim Infdonesia;

Abstract

Buku ini disusun secara sistematis agar mudah dipahami, mulai dari konsep dasar penilaian Openness dan Webometrics, hingga panduan teknis penggunaan Google Scholar dan SINTA. Pembaca akan dipandu langkah demi langkah dalam mengelola akun profil, meningkatkan jumlah sitasi, hingga strategi menulis artikel agar lebih mudah ditemukan secara global.

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Rezky, Putri Nur; Indra Dolly; Darwis, Herdianti, Universitas MUslim Indonesia;

Abstract

The Program Makan Bergizi Gratis (MBG) is a flagship program of the Prabowo Subianto administration launched in 2024, triggering diverse public responses on social media. Sentiment analysis using deep learning models offers an effective approach to understanding public opinion at scale. However, selecting the appropriate model for Indonesian social media text remains challenging. This study aims to compare the performance of two pretrained transformer models, RoBERTa Base and IndoBERTweet Base, in conducting automatic sentiment labeling on Indonesian tweets related to the MBG program using a zero-shot labeling approach without human-annotated ground truth. A total of 1,831 tweets were collected from platform X and preprocessed using case folding, normalization, and stopword removal. Both models were applied in parallel to label each tweet with sentiment categories (positive, neutral, negative) along with confidence scores. The comparison was evaluated using agreement rate, Cohen's Kappa, and confidence score analysis. RoBERTa Base exhibits a conservative tendency with 75.20% neutral labels, while IndoBERTweet Base produces a more balanced distribution (68.16% neutral). The comparison shows 77.28% agreement with Cohen's Kappa of 0.490 (Moderate Agreement). RoBERTa Base achieves higher confidence (mean: 0.9559, 83.01% above 0.95) compared to IndoBERTweet Base (mean: 0.9236, 68.65% above 0.95). IndoBERTweet Base is more effective in detecting negative sentiment, identifying nearly twice as many negative tweets (13.54% vs. 7.48%). This study recommends IndoBERTweet Base for exploratory research requiring sensitive sentiment detection and RoBERTa Base for precision-critical applications. An ensemble approach combining both models is recommended for production-critical applications

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Zahra, Andi Fathimatuz; Indra Dolly; Hayati, Lilis Nur, Universitas Muslim Indonesia

Abstract

Pemanfaatan aplikasi perbankan digital menjadi bagian penting dalam mendukung produktivitas masyarakat melalui layanan perbankan yang efisien dan praktis. Byond by BSI sebagai salah satu mobile banking turut berperan dalam memenuhi kebutuhan layanan keuangan nasabahnya. Seiring meningkatnya jumlah pengguna aplikasi Byond by BSI, muncul beragam opini yang belum terpetakan secara sistematis. Hal ini menciptakan kebutuhan akan analisis sistematis agar ulasan tersebut dapat dimanfaatkan sebagai basis evaluasi fungsionalitas aplikasi dan optimalisasi pengalaman pengguna. Penelitian ini bertujuan mengidentifikasi distribusi sentimen positif dan negatif pada ulasan pengguna aplikasi Byond by BSI serta menentukan algoritma terbaik berdasarkan nilai akurasi, presisi, recall, dan F1-score dalam mengklasifikasikan sentimen ulasan pengguna. Metode yang diterapkan untuk menentukan kategori sentimen ulasan adalah algoritma Naïve Bayes dan SVM. Hasil evaluasi penelitian menunjukkan bahwa algoritma SVM mampu menunjukkan kinerja lebih baik daripada Naïve Bayes dalam mengklasifikasikan ulasan. SVM menunjukkan kinerja terbaik pada pembagian data 90: 10 dengan akurasi 95.33%, presisi 97.12%, recall 94.94%, dan f1-score 96%. sedangkan Naïve Bayes mencapai kinerja terbaiknya pada pembagian data 70: 30 dengan akurasi 94%, presisi 95.10%, recall 94.45%, dan f1-score 94.81%.

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Indra, Dolly; Alwi, Erick Irawadi; Kasim, Fadil, Universitas Muslim Indonesia

Abstract

Indonesian Sign Language (BISINDO) is an essential means of communication for deaf people in Indonesia. However, communication challenges persist for the general public, who lack sign language proficiency. To bridge this gap, a real-time BISINDO recognition system is essential. This research compares the performance of several distance models in recognizing BISINDO letters using a camera-based recognition system. The study evaluated three distance methods City Block, Canberra, and Chebyshev applied to shape feature extraction through chain code analysis. Testing was conducted under both indoor and outdoor conditions to assess system robustness. The results revealed that the Chebyshev distance method achieved the highest accuracy in indoor scenarios, particularly when participants wore white clothing, reaching an accuracy of 100%. Meanwhile, in outdoor conditions, the Canberra distance method outperformed the others, achieving the highest accuracy of 96.15% with white clothing. However, outdoor accuracy was generally lower due to uncontrollable lighting, which affected recognition. Despite these challenges, the system demonstrated its capability to recognize BISINDO letters effectively in both environments.

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Musdalifah, Musdalifah; Indra, Dolly; Jabir, Sitti Rahmah, Faculty Of Computer Science, Universitas Muslim Indonesia, Makassar, Indonesia

Abstract

Pemanfaatan sistem informasi di tingkat pemerintahan desa menjadi krusial untuk memenuhi ekspektasi publik terhadap pelayanan yang responsif dan transparan. Penelitian ini bertujuan untuk mengevaluasi efektivitas website resmi Desa Lamundre (https://lamundre.kolakadesa.id/) dalam menunjang efisiensi operasional aparatur desa serta kualitas layanan bagi masyarakat. Metode evaluasi yang digunakan adalah kerangka kerja PIECES yang meninjau enam dimensi utama: performance, information, economy, control, efficiency, dan service. Data dikumpulkan melalui observasi, wawancara, dan penyebaran kuesioner kepada 10 aparatur desa serta 30 responden masyarakat dengan teknik analisis statistik deskriptif menggunakan skala Likert. Hasil penelitian menunjukkan bahwa secara keseluruhan sistem informasi Desa Lamundre berada pada kategori "Puas". Dimensi control mendapatkan penilaian tertinggi (skor 3,66), sedangkan dimensi efficiency memerlukan perhatian lebih untuk peningkatan performa sistem di masa mendatang. Evaluasi ini diharapkan menjadi acuan bagi Pemerintah Desa Lamundre dalam mengoptimalkan sistem informasi desa.

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Hasnawi, Mardiyyah; Astuti, Wistiani; Puspitasari, Andi; Kurniati, Nia; Indra, Dolly

Abstract

Data processing in waste bank management systems faces substantial challenges when extracting structured information from unstructured textual data containing transaction records, customer information, and waste categorization details. This study develops and validates an automated Named Entity Recognition (NER) system based on the IndoBERT transformer architecture to process textual records from Makassar waste bank operations. The approach fine-tunes the indolem/indobert-base-uncased model through domain-specific adaptation targeting waste management vocabulary and operational terminology. The dataset comprises 975 textual records collected from 8 Waste Bank Units in Makassar City. These records were systematically annotated using the BIO tagging scheme for eight entity types: B-LOCATION, B-PERSON, B-WASTE_CATEGORY, B-WASTE_TYPE, I-PERSON, I-WASTE_CATEGORY, I-WASTE_TYPE, and O. The dataset was partitioned into training (682 samples, 69.9%), validation (146 samples, 15.0%), and test sets (147 samples, 15.1%) using stratified sampling methodology with high inter-annotator agreement (κ=0.91). Experimental results show outstanding performance with 94.37% test accuracy, 90.65% precision, 94.37% recall, and 92.21% F1-score, outperforming general-purpose Indonesian NER approaches. Perfect performance was achieved for waste type recognition (B-WASTE_TYPE: 100% F1-score) and location identification (B-LOCATION: 100% F1-score), while waste category classification reached 96% F1-score. This implementation successfully automates entity extraction from Makassar waste bank textual data, reducing manual processing time by 95% while maintaining high accuracy levels. This research makes important contributions to Indonesian environmental natural language processing. These contributions include transformer adaptation methodologies for resource-constrained domains, validated IndoBERT performance on Indonesian waste bank data, the first Indonesian waste management NER dataset, and demonstrated feasibility of NLP-based environmental policy systems.

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