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All Journal Jurnal Ilmu Komputer Jurnal Transformatika Jurnal Edukasi dan Penelitian Informatika (JEPIN) INFORMAL: Informatics Journal Sistemasi: Jurnal Sistem Informasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JOURNAL OF APPLIED INFORMATICS AND COMPUTING METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi ILKOM Jurnal Ilmiah Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JOISIE (Journal Of Information Systems And Informatics Engineering) INFOKUM Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Computer Science and Information Technology (CoSciTech) International Journal of Engineering, Science and Information Technology Jurnal Informatika dan Teknologi Komputer ( J-ICOM) Multica Science and Technology jeti Jurnal Minfo Polgan (JMP) Jurnal Pengabdian Masyarakat : Pemberdayaan, Inovasi dan Perubahan TECHSI - Jurnal Teknik Informatika Sisfo: Jurnal Ilmiah Sistem Informasi Journal of Information Technology (JINTECH) International Journal of Information System & Innovative Technology Jurnal Pengabdian Masyarakat Bangsa Jurnal Malikussaleh Mengabdi Journal of Advanced Computer Knowledge and Algorithms Gameology and Multimedia Expert International Journal of Information System and Innovative Technology Smatika Jurnal : STIKI Informatika Jurnal Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MICoMS) ITEJ (Information Technology Engineering Journals)
Sujacka Retno
Universitas Malikussaleh
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Clustering Analysis of Cocoa-Producing Areas Using the Gaussian Mixture Model Algorithm (A Case Study in Southeast Aceh Regency) Pathia Pathia; Taufiq Taufiq; Sujacka Retno
ITEJ (Information Technology Engineering Journals) Vol. 11 No. 1 (2026): June
Publisher : Pusat Teknologi Informasi dan Pangkalan Data IAIN Syekh Nurjati Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24235/93m0r329

Abstract

This study aims to identify and cluster agricultural areas in Southeast Aceh Regency using the Gaussian Mixture Model (GMM) algorithm. The dataset consists of village-level agricultural data, including land area, production volume, productivity, and the number of farmers. To ensure comparability across variables, Z-Score normalization was applied. The optimal number of clusters was determined using the Bayesian Information Criterion (BIC), resulting in three distinct groups: high, medium, and low production areas. Clustering performance was evaluated using the Silhouette Score (0.3893) and the Davies-Bouldin Index (0.8548), indicating moderate clustering quality with reasonable separation between clusters. To improve accessibility and practical use, a web-based information system was developed to visualize agricultural data, clustering outcomes, and evaluation metrics interactively. These findings highlight the value of GMM-based machine learning in supporting data-driven decision-making and prioritizing agricultural development efforts by local governments.
Phishing Email Detection Using SVM with RBF Kernel Based on Manhattan Distance Asrianda Asrianda; Sujacka Retno; Beno Jange; Mansur Mansur
ILKOM Jurnal Ilmiah Vol 18, No 2 (2026)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v18i2.2806.268-280

Abstract

This study examines the performance of a Support Vector Machine (SVM) model with a Radial Basis Function (RBF) kernel for phishing email detection using Euclidean and Manhattan distance measures. The dataset consists of 3,600 email samples, including 2,400 legitimate emails and 1,200 phishing instances. The features are designed to capture both linguistic and structural characteristics of emails, including word count, vocabulary diversity, stop word usage, number of links and domains, presence of email addresses, spelling errors, and urgency-related terms. The experiments were conducted using two train-test split ratios, 80:20 and 70:30, combined with hyperparameter tuning of C and gamma across 15 iterations. The findings indicate that the Manhattan distance consistently outperforms the Euclidean distance, particularly in terms of recall and F1-score, which are critical for detecting the minority class. The model achieved a best accuracy of 78.33%, accompanied by noticeable improvements in recall and F1-score. These results suggest that the choice of distance function within the RBF kernel plays a crucial role in enhancing model sensitivity and generalization when dealing with imbalanced data. Furthermore, the iterative hyperparameter tuning process contributes significantly to improving both performance and model stability. Overall, the SVM-RBF approach with Manhattan distance provides an effective and reliable framework for phishing email detection in machine learning applications.
Hiace Transportation Departure Scheduling Information System in Lhokseumawe With Genetic Algorithm Narita Taskia; Rozzi Kesuma Dinata; Sujacka Retno
International Journal of Engineering, Science and Information Technology Vol 5, No 3 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i3.878

Abstract

This study aims to address challenges in transportation scheduling by employing a suitable algorithm to ensure the scheduling process operates efficiently and effectively. One algorithm identified as appropriate for this task is the Genetic Algorithm, which is widely recognized for its robust capabilities in optimization tasks. Known for its adaptability and robustness, the Genetic Algorithm is well-suited for scheduling applications, including academic timetabling, as it can handle complex problems involving multiple criteria and objectives. Inspired by principles of biological evolution and natural selection, this algorithm iteratively explores solutions to approach optimal outcomes, refining the schedule in each iteration until an effective solution is achieved. Based on the analysis of experimental results using real-world data and evaluation of the system's design, the study concludes that the Hiace transportation departure scheduling system was successfully developed using a web-based approach. This web-based system offers significant advantages, as it facilitates more efficient management of departure schedules and eliminates the need for manual checks. As a result, it reduces the risk of human error and allows for better resource allocation. The integration of Genetic Algorithms into the development of the Hiace transportation scheduling system demonstrates the potential of evolutionary computation in solving practical, real-life scheduling problems. The resulting system is supported by internet-based technologies, providing easy access to passengers and system administrators. Despite the positive outcomes achieved, the current implementation is not without limitations. Further refinement and continued development are essential to enhance system performance, increase reliability, and ensure it can adapt to evolving needs and operational complexities, ensuring its long-term effectiveness.
Comparison of K-Medoids and K-Means Result for Regional Clustering of Capture Fisheries in Aceh Province Thifal Salsabila; Nurdin Nurdin; Sujacka Retno
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.829

Abstract

This research aims to develop a web-based application that can categorize areas of capture fisheries in Aceh Province. The methods used in this research are K-Means and K-Medoids. The methods used in this research are K-Means and K-Medoids, a clustering technique used to group districts/cities based on high and low catch areas. This application will use data from the Marine and Fisheries Service (KKP) of Aceh Province, covering the period 2017 to 2023. This research will analyze variables such as production (tons), number of vessels, sub-districts, villages, and fish species. The system is developed using the PHP programming language to facilitate implementation and data access by stakeholders. Stakeholders. As an evaluation tool for clustering results, the Davies-Bouldin Index (DBI) is used to measure the quality of clustering results. The results of this study are expected to provide an overview of areas with high catches and assist policymakers in designing a more strategic approach to fishing—policymakers in developing more effective strategies to increase fishing, especially in districts with low fish catch. In addition, this application also provides an interactive platform for users to analyze fisheries data quickly and efficiently.
Application of Fuzzy C-Means and Borda in Clustering Crime–Prone Areas and Predicting Crime Rates Using Long Short Term Memory in Northern Aceh Regency Syahrul Andika Lubis; Munirul Ula; Sujacka Retno
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.747

Abstract

North Aceh is a district with diverse geographical conditions, ranging from vast lowland areas in the north stretching from west to east, to mountainous areas in the south. The average altitude in North Aceh is 125 meters. The district covers an area of 2,694.66 km² with a population of 614,640 people in 2022. The issue of crime in North Aceh District has caused significant discomfort among the community. According to data from the Central Bureau of Statistics (BPS) of Aceh Province, the number of criminal cases increased from 6,651 cases in 2022 to 10,137 cases in 2023. Using the Fuzzy C-Means clustering method, the data was grouped into three clusters: cluster 1 represents safe areas, cluster 2 represents moderately vulnerable areas, and cluster 3 represents vulnerable areas. For ranking using the Borda method, the Dewantara Police Sector ranked first for the physical aspect, while the Muara Batu Police Sector ranked first for the item aspect. As for predictions using the LSTM model, almost all subdistricts achieved MAPE values below 20%, indicating that the LSTM model is quite effective in predicting crime-prone areas. For example, Baktiya District recorded a MAPE value of 15.85% for the physical aspect, while the best result was achieved by Simpang Keramat District for the item aspect with a MAPE value of 0.00%. However, in Syamtalira Bayu District, the item aspect reached a MAPE value of 20.07%. Although the MAPE value for the item aspect in Syamtalira Bayu is relatively high, it is still considered acceptable as it remains below 50%.
Co-Authors Abdul Azis Andra Munandar Angga Pratama Ardi Wirya Indarto Asrianda Asrianda Asrillah Asrillah Aulia, Faizul Azrai Putra Barumun Daulay Beno Jange Bustami Bustami Bustami Cut Agusniar Devi, Salma EDI YUSUF, EDI Ekamaida, Ekamaida Fadlisyah Fadlisyah Fahrizal, Effan Fajri, T Irfan Fiasari, Fiasari Fikran, Rifzan Fortilla, Zeny Arsya Gadis Ayu Sofiana Gilang Wahyu Ramadhan Gilang Hakimi, Musawer Haried Novriando Hayatun Nisa Hidayatsyah Hidayatsyah ilham - sahputra Ilham Sahputra Ilmi Suciani Sinambela Ima Pratiwi Irvan Na’syakban Lidya Rosnita Maghfirah, Riezka Mahsa, Masithah Mansur Mansur Maryana Maryana Maryana Maryana Maryana, Maryana Muhammad Al Imran Muhammad Daud Muhammad Fikry Muhammad Ikhwanus Muhammad Nurfahmi Muhammad, Muhammad Munirul Ula Mutammimul Ula Mutasar Nadia Saphira Narita Taskia Nasrul ZA, Nasrul Nisa Ul Fadila Novia Hasdyna Nur Faliza Nurdin Nurdin Panjaitan, Cherlina Helena Purnamasari Pathia Pathia Rahma Fitria, Rahma Reza Pahlevi Ginting Richki Hardi Rijal, Himmatur Rini Meiyanti Rizky Putra Fhonna Rizkya, Dini Dara Rozzi Kesuma Dinata Safriandi, Safriandi Safwandi Safwandi Safwandi, Safwandi Sahputra, Ilham Said Fadlan Anshari Sayed Fachrurrazi Selly Alfika Sinambela, Ilmi Suciani Siti Fatimatun Zahro Siti Wahyuni Sudirman Sudirman Syahrul Andika Lubis T Irfan Fajri Taufiq Taufiq Teuku Zulkarnaen Thifal Salsabila Tsania Asha Fadilah Daulay Utari, Sylva Putri Uzia Ulfa Veri Ilhadi Wahdana, Aldi Wahyu Isnanda Nasution Wibowo, Patmono Yafis, Balqis Yanti, Riski Yesy Afrillia Yopy Anfelia Zara Yunizar Zulfadl, Zulfadl Zulfia , Anni