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All Journal Jurnal Ilmu Komputer Aceh
Dasril Azmi
Universitas Almuslim

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Sistem Pendukung Keputusan Penentuan Siswa Terbaik Sma Negeri 19 Takengon Menggunakan Metode Saw Armita Jaya; Iqbal Iqbal; Dasril Azmi
Jurnal Ilmu Komputer Aceh Vol 2 No 3 (2025): Jurnal Ilmu Komputer Aceh
Publisher : Fakultas Ilmu Komputer Universitas Almuslim

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Abstract

Decision Support Systems (DSS) can be in the form of a computer-based system that produces various decision alternatives to assist management in dealing with various structured and unstructured problems using data and models. SPK can also be applied to determine the best student assessment, one of which is at Takengon 19 State High School (SMA)
Klasifikasi Plat Nomor Kenderaan Bedasarkan Wilayah Tertentu Menggunakan Algoritma Optical Character Recognition (OCR) Cut Haura Hayatun Jannah; Imam Muslem; Dasril Azmi
Jurnal Ilmu Komputer Aceh Vol 2 No 3 (2025): Jurnal Ilmu Komputer Aceh
Publisher : Fakultas Ilmu Komputer Universitas Almuslim

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Abstract

The advancement of artificial intelligence (AI) and digital image processing technologies has enabled the development of automated vehicle identification systems. This study aims to design a license plate classification system based on specific regional codes using the Optical Character Recognition (OCR) approach. The process involves several key stages, including image preprocessing (grayscale conversion, sharpening, noise reduction, and thresholding), character extraction via EasyOCR, and regional classification using Support Vector Machine (SVM) and Random Forest algorithms. The dataset consists of 1,920 vehicle plate images collected from two regions: BK (Medan) and BL (Aceh). Experimental results indicate that the SVM model achieved 86% accuracy, while the Random Forest model reached 84% accuracy. The system is deployed as a web-based application to facilitate automatic and efficient regional identification of vehicle plates. This research is expected to contribute to traffic monitoring systems and transportation security improvements
Perancangan Sistem Pengolahan Citra Digital Klasifikasi Jenis Ikan Laut Menggunakan Model Logisitic Regression Mifzal; Iqbal Iqbal; Dasril Azmi
Jurnal Ilmu Komputer Aceh Vol 3 No 1 (2026): Jurnal Ilmu Komputer Aceh
Publisher : Fakultas Ilmu Komputer Universitas Almuslim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51179/ilka.v3i1.37

Abstract

This research develops a web-based marine fish classification system by applying digital image processingtechniques and the Logistic Regression algorithm. The system is intended to recognize four marine fish species, namely milkfish, mackerel tuna, yellowstripe scad, and threadfin bream, through the combination of color and texture feature representations. Color characteristics are extracted using HSV color histograms, while texture information is obtained using the Local Binary Pattern (LBP) method. The experimental dataset consists of 4,000 fish images, with 3,200 images allocated for model training and 800 images used for testing. The evaluation results indicate that the proposed approach achieves an overall accuracy of 89%, with precision, recall, and f1-score values exceeding 0.85 for most fish categories. The system enables automatic image uploading, feature extraction, and classification via a Flask-based web interface, including the capability to detect images that do not belong to the trained classes. Despite achieving promising results, the system is still affected by limitations related to dataset size and visual similarities among fish species. Future work may focus on increasing data diversity and performing evaluations in real-world environments to enhance system reliability and generalization.
Co-Authors Armita Jaya Cut Haura Hayatun Jannah Iqbal Iqbal Mifzal Muslem R, Imam