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All Journal Sisfo: Jurnal Ilmiah Sistem Informasi Jurnal Ilmu Komputer Aceh
Dasril Azmi
Universitas Almuslim
Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering Library & Information Science Mechanical Engineering

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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.
Analisis Sistem Pakar dalam Deteksi Kerusakan dan Penerapan Decision Support System pada Kualitas Mesin Mobil Iskandar Zulkarnaini; Edi Yusuf; Dasril Azmi; Munar Munar
Sisfo: Jurnal Ilmiah Sistem Informasi Vol. 9 No. 2 (2025): Sisfo: Jurnal Ilmiah Sistem Informasi, Oktober 2025
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/.v9i2.26031

Abstract

Penerapan Sistem Pakar dalam deteksi kerusakan mobil dan penerapan Decision Support System (DSS) untuk menilai kualitas mesin mobil. Sistem pakar digunakan untuk mendiagnosis kerusakan berdasarkan gejala yang dilaporkan oleh pengguna, sedangkan DSS diintegrasikan untuk mendukung pengambilan keputusan yang lebih efisien dalam menentukan langkah-langkah perbaikan yang tepat. Metode penelitian ini berbasis pengetahuan berbasis aturan untuk mengidentifikasi masalah potensial, dan model inferensi probabilistik digunakan untuk menghitung tingkat keparahan kerusakan berdasarkan data yang masuk. Metode forward chaining digunakan untuk menghubungkan gejala dengan diagnosis kerusakan, sedangkan logika fuzzy diterapkan untuk menangani ketidakpastian dalam penilaian gejala. Hasil dari penelitian menunjukkan bahwa DSS mampu memberikan rekomendasi perbaikan yang efisien dan akurat, dengan tingkat probabilitas yang tinggi untuk mengidentifikasi kerusakan utama, seperti masalah pada sistem kelistrikan dan timing belt. Probabilitas Kerusakan Sistem Kelistrikan: 90%, Probabilitas Kerusakan Timing Belt: 64%, Probabilitas Kerusakan Level Oli: 49%, Waktu Rata-Rata Diagnosis dengan DSS: 2 menit, Akurasi Rekomendasi DSS: 95%, Penghematan Waktu Diagnosis: 20% lebih cepat, Penghematan Biaya Perbaikan: 15% lebih rendah, Akurasi Diagnosa DSS dan Sistem Pakar: 92%, Kepuasan Pengguna: 85%. Hasil Penelitian ini dapat digunakan dalam diagnostik otomatis yang dapat meningkatkan efisiensi perawatan kendaraan, mengurangi kesalahan manusia, dan mempercepat proses deteksi kerusakan pada mobil. Implementasi sistem ini juga berpotensi untuk digunakan dalam sektor otomotif sebagai alat bantu bagi teknisi dan pemilik kendaraan untuk melakukan diagnosa dan perbaikan secara lebih tepat dan cepat.
Expert System for Diagnosing Hernia Disease (Herniae) Using the Forward Chaining Method Iqbal Iqbal; Dasril Azmi; Fitriani Fitriani
Sisfo: Jurnal Ilmiah Sistem Informasi Vol. 10 No. 1 (2026): Sisfo: Jurnal Ilmiah Sistem Informasi, Mei 2026
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/sisfo.v10i1.26943

Abstract

This study aims to analyze and design an expert system for diagnosing hernia using the Forward Chaining and Certainty Factor methods. This system was developed to assist in the process of determining a diagnosis based on the main symptoms experienced by the patient, while also providing appropriate treatment recommendations. To address the problem of knowledge uncertainty that often arises in expert systems, this study integrates the Certainty Factor method to measure the level of confidence in the diagnosis results. Meanwhile, the Forward Chaining method is used as a reasoning mechanism that starts from facts or symptoms provided by the patient to a conclusion in the form of a disease diagnosis. The diagnosis process in this system begins with a consultation session, where the system will ask a series of relevant questions according to the symptoms experienced by the patient. Based on the answers given, the system will make inferences to produce a diagnostic decision. Based on the test results, the expert system built is able to provide a diagnosis that is close to the assessment of medical experts. The Certainty Factor testing model provides advantages in measuring the level of confidence in the diagnosis, so that the results given are not absolute, but have a more realistic probabilistic value. Thus, an expert system for diagnosing hernia is able to overcome uncertainty and produce a confidence level value for the diagnosis. Based on test results, the system demonstrated a fairly good accuracy rate, around 90%–97%, depending on the combination of symptoms selected. Thus, the CF method is effective as an aid in initial diagnosis, although it still requires further examination by medical personnel.
Co-Authors Armita Jaya Cut Haura Hayatun Jannah Edi Yusuf Fitriani Fitriani Iqbal Iqbal Iskandar Zulkarnaini Mifzal Munar Munar Muslem R, Imam