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All Journal EDUMATIC: Jurnal Pendidikan Informatika Building of Informatics, Technology and Science Jurnal Algoritma
Nasucha, Mohammad
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Computer Science & IT Education

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Aplikasi Deteksi Otomatis Hukum Tajwid Utama pada Ayat Al-Qur’an menggunakan YOLOv8 Arfiansah, Arfiansah; Nasucha, Mohammad
Jurnal Pendidikan Informatika (EDUMATIC) Vol 9 No 2 (2025): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v9i2.30978

Abstract

Tajwid learning faces challenges in visually recognizing recitation rules from Arabic script, thus requiring an interactive and accurate digital medium. This study aims to develop a web-based application to automatically detect seven core tajwid rules using YOLOv8. This research follows a Research and Development approach adopting the ADDIE model, which consists of five systematic stages: analysis, design, development, implementation, and evaluation. The YOLOv8 model was trained using 200 annotated images of Qur’anic verses, with a data split of 70% for training, 20% for validation, and 10% for testing. Data augmentation was applied through rotation, flipping, and brightness adjustment, with training facilitated using Roboflow. Our main finding is an interactive web application capable of automatically detecting seven tajwid rules from Qur’anic verse images. The application allows users to upload images, which are then analyzed and displayed with colored bounding boxes and interactive captions. Testing results showed accurate and responsive detection performance, achieving a mAP@50 of 89.88% with high accuracy across several tajwid classes. These findings highlight the potential of Artificial Intelligence (AI) to support more interactive, independent, and adaptive tajwid learning, while also promoting the digitization of Islamic manuscripts.
Implementation of an Artificial Neural Network in the Classification of Handwritten Javanese Script Images Rohim, Zainuri; Nasucha, Mohammad
Building of Informatics, Technology and Science (BITS) Vol 7 No 2 (2025): September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i2.7625

Abstract

Javanese script is an Indonesian cultural heritage rich in historical, aesthetic, and spiritual values, but it is now becoming marginalized. To reintroduce its use, this research develops a Javanese script recognition application based on an Artificial Neural Network (ANN). In this study, the Javanese script was divided into 120 classes (ha, hi, hu, he, hee, ho, up to nga, ngi, ngu, nge, ngee, ngo). Each class was represented by 40 sample images of the script handwritten by 40 different respondents, resulting in 4800 samples. The research began with preprocessing, which included adding padding to the top, bottom, left, and right sides of the script; downsizing the image to a 33x33 resolution by applying average pooling; image segmentation to separate the script characters from the background; converting the color image to grayscale; and converting the grayscale image to a binary image with the help of thresholding. A number of images that had undergone preprocessing were then structured into a ready-to-use dataset of 4800 samples. This dataset was then divided with an 80:20 ratio, where 80% of the data was used to train the model and 20% was used to validate the model. An evaluation was conducted to measure the model's accuracy. Subsequently, the application was developed using PySide6 as the desktop interface. After the application development, the researchers provided an additional 600 images, where each class was represented by 5 samples, for real-world application testing. The evaluation results showed that the model achieved a validation accuracy of 70.21%. Meanwhile, testing with the application using the additional test images showed an accuracy of 73.83%.
Pengembangan Model Avatar untuk Memvisualisasikan Kasus Non-interoperabilitas antar Metaverse Rakasiwi, Muhammad Raihan; Nasucha, Mohammad
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2425

Abstract

Permasalahan non-interoperabilitas antar metaverse menjadi tantangan utama dalam pengembangan dunia virtual yang terintegrasi. Ketidaksesuaian standar pengembangan antar platform menghambat mobilitas dan pertukaran data pengguna, khususnya dalam representasi avatar. Penelitian ini bertujuan untuk memvisualisasikan permasalahan tersebut melalui pengembangan model avatar tiga dimensi (3D) berbentuk humanoid menggunakan pendekatan komputasi grafis. Metodologi yang digunakan melibatkan serangkaian tahapan teknis mulai dari pembuatan objek 3D (bola dan silinder) sebagai representasi bagian tubuh, implementasi fungsi translasi dan rotasi berdasarkan tiga urutan koordinat (XYZ, YXZ, ZXY), hingga simulasi rotasi searah dan berlawanan arah jarum jam menggunakan pustaka numpy dan matplotlib dalam lingkungan Python. Penelitian ini berhasil membuktikan bahwa perbedaan urutan sistem koordinat (XYZ, YXZ, ZXY) dan arah rotasi menghasilkan visual avatar yang tidak konsisten meskipun diuji menggunakan parameter yang sama.
Co-Authors Arfiansah, Arfiansah Rakasiwi, Muhammad Raihan Rohim, Zainuri