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Evaluating The Quality of K-Medoids Clustering on Crime Data in Indonesia Sujacka Retno; Rozzi Kesuma Dinata; Novia Hasdyna
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 8 No. 2 (2024): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol8No2.pp274-280

Abstract

This study evaluates the quality of K-Medoids clustering applied to criminal incident data in Indonesia from 2000 to 2023. The analysis compares the clustering performance on both original and normalized datasets using various evaluation metrics, including the Davies-Bouldin Index (DBI), Silhouette Score (SS), Normalized Mutual Information (NMI), Adjusted Rand Index (ARI), and Calinski-Harabasz Index (CH). The findings reveal that the original dataset consistently outperforms the normalized dataset across all metrics. The optimal clustering was achieved in the seventh iteration of the original data, with the lowest DBI (0.438), the highest SS (0.683), NMI (0.916), ARI (0.984), and CHI (57.418). In contrast, the normalized data exhibited higher DBI values and, in some cases, negative Silhouette Scores, indicating less distinct clusters. These results suggest that for this dataset, K-Medoids clustering performs more effectively on the original data without normalization, providing more accurate and well-defined clusters of criminal incidents. This insight is crucial for future research and practical applications in crime data analysis, emphasizing the importance of dataset preprocessing in clustering methodologies.
Enhancing K-Means Clustering Model to Improve Rice Harvest Productivity Areas in Aceh Utara Using Purity Sujacka Retno; Bustami; Rozzi Kesuma Dinata
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 13 No. 2 (2024)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v13i2.78254

Abstract

To optimize the performance of the clustering process using K-Means, an optimalization approach employing the Purity algorithm is needed. This research was tested on a dataset of rice harvest productivity areas in Aceh Utara Regency by comprehensively analyzing the number of iterations and the DBI values produced by K-Means and Purity K-Means in clustering priority and non-priority rice production areas. This is in line with the efforts of the Regional Government to implement rice production intensification programs in Aceh Utara Regency. From the testing of Purity K-Means, an average of 5, 2, 2, 5, and 3 iterations were obtained from all tested datasets sequentially from 2019 to 2023. Meanwhile, from the testing of conventional K-Means, the average number of iterations obtained was 5.4, 4.8, 4.2, 5.6, and 3.8 iterations, sequentially. This indicates that the clustering performance conducted by Purity K-Means is better than conventional K-Means. The DBI values obtained from Purity K-Means for the entire dataset sequentially are 0.6781, 0.4175, 0.4419, 0.6182, and 0.4973. This value is lower compared to the DBI values obtained from conventional K-Means, which are 0.7178, 0.6025, 0.4971, 0.7222, and 0.5519, respectively. This also indicates that the validity level of the clustering results performed by Purity K-Means is higher than conventional K-Means.
Comparison of K-Medoids and K-Means Result for Regional Clustering of Capture Fisheries in Aceh Province Salsabila, Thifal; Nurdin, Nurdin; Retno, Sujacka
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.
Pemanfaatan Internet of Thing dalam Sistem Monitoring Hama Burung di Gampong Reuleut Timu Retno, Sujacka; Ula, Mutammimul; Fahrizal, Effan; Zulkarnaen, Teuku; Faliza, Nur; Muhammad, Muhammad
Jurnal Malikussaleh Mengabdi Vol. 3 No. 2 (2024): Jurnal Malikussaleh Mengabdi, Oktober 2024
Publisher : LPPM Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jmm.v3i2.20833

Abstract

Pengabdian kepada masyarakat ini bertujuan untuk memberikan solusi terhadap permasalahan petani dalam pengendalian hama burung di area pertanian melalui penerapan sistem monitoring otomatis berbasis teknologi. Sistem ini dilakukan untuk monitoring kehadiran hama burung secara real-time dan mengusirnya menggunakan perangkat pengusir otomatis. Metode pelaksanaan meliputi sosialisasi, pelatihan, dan implementasi langsung sistem monitoring di area pertanian. Hasil kegiatan menunjukkan bahwa sistem ini efektif dalam mengurangi kehadiran hama burung di area pertanian hingga 80%, meningkatkan produktivitas hasil panen. Peserta pelatihan juga menunjukkan pemahaman yang baik tentang cara instalasi dan pengoperasian sistem, yang diukur melalui evaluasi praktik lapangan. Kegiatan ini memberikan manfaat langsung kepada petani dalam meningkatkan hasil panen dan menciptakan kesadaran akan pentingnya adopsi teknologi modern dalam pengelolaan pertanian. Diharapkan hasil dari pengabdian ini dapat dikembangkan lebih lanjut dengan dukungan pihak terkait untuk meningkatkan keberlanjutan dan skala penerapan sistem ini di masa depan.
Penerapan Mental dan Karakter Anggota Silat di Kelatnas Perisai Diri Asrianda, Asrianda; Wibowo, Patmono; Zulfadl, Zulfadl; ZA, Nasrul; Retno, Sujacka
Jurnal Malikussaleh Mengabdi Vol. 3 No. 2 (2024): Jurnal Malikussaleh Mengabdi, Oktober 2024
Publisher : LPPM Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jmm.v3i2.20944

Abstract

Penerapan mental dan karakter dalam latihan silat di Kelatnas Perisai Diri dilakukan melalui berbagai metode. Termasuk disiplin latihan, pembinaan etika, dan pembiasaan nilai luhur dalam kehidupan sehari-hari. Anggota diwajibkan mengikuti latihan secara rutin mencakup pemanasan, teknik dasar, sparing untuk menguji ketahanan fisik dan mental. Nilai moral seperti kesabaran, kejujuran, dan saling menghormati menjadi fokus utama dalam sesi latihan. Anggota telah lama berlatih memiliki karakter yang disiplin, percaya diri, dan mampu mengendalikan emosi dengan baik dibandingkan anggota baru. Latihan terstruktur dan berkelanjutan terbukti memberikan dampak positif terhadap pembentukan karakter pesilat. Beberapa tantangan dihadapi, kurangnya konsistensi dalam latihan serta pengaruh lingkungan luar kurang mendukung perkembangan mental dan karakter anggota.  Anggota Perisai Diri menyatakan latihan silat membantu meningkatkan kedisiplinan dalam kehidupan sehari-hari. Merasakan peningkatan dalam kemampuan mengendalikan emosi. Menegaskan latihan silat Perisai Diri tidak hanya berdampak pada aspek fisik, tetapi memberikan pengaruh signifikan terhadap aspek psikologis dan emosional anggota. Metode latihan diterapkan di Kelatnas Perisai Diri mengandung unsur pendidikan karakter yang kuat. Pelatih tidak hanya mengajarkan teknik bela diri, tetapi menanamkan nilai moral melalui contoh nyata kehidupan sehari-hari. Anggota aktif dalam latihan menunjukkan kemampuan berpikir lebih statis dan strategis dalam pengambilan keputusan saat bertanding. Kelatnas Perisai Diri tidak hanya membentuk fisik kuat, tetapi melatih pola piker yang analitis dan adaptif terhadap berbagai situasi.
Implementation of Game Design Document (GDD) in the Development of the 2D Android-Based Game Komodo Isle Retno, Sujacka
Gameology and Multimedia Expert Vol 2, No 2 (2025): Gameology and Multimedia Expert - April 2025
Publisher : Department of Informatics Faculty of Engineering Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/game.v2i2.21228

Abstract

Game development techniques have evolved in this technological era in line with the rapid advancement of technology. Considering the significant influence of technology today, where young children are already familiar with and proficient in operating technological devices such as mobile phones, this phenomenon can be leveraged for more positive purposes. One such approach is introducing Indonesian culture to children through game-based applications. This study presents an Android-based game application that features one of Indonesia's protected animals as the main character—the Komodo, which originates from the province of East Nusa Tenggara. The game development technique used in this study follows the Game Design Document (GDD) framework, which includes Core Loop, Core Mechanics, and Asset Design. This research aims to serve as a positive initiative to increase children's interest in Indonesian culture, ensuring that Indonesia's noble cultural heritage can be effectively conveyed to the younger generation in the digital era. Additionally, this study can serve as a reference for future research, particularly in game development techniques.
Classification of Family Hope Program Assistance Recipients Using the C4.5 Algorithm with Z-Score Normalization (Case Study in Atu Lintang District) Wahyuni, Siti; Asrianda, Asrianda; Retno, Sujacka
ITEJ (Information Technology Engineering Journals) Vol 10 No 1 (2025): 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/itej.v10i1.207

Abstract

One of the challenges in distributing social assistance is determining recipients who are truly eligible objectively and efficiently. This study develops a classification system for Family Hope Program (PKH) recipients by utilizing the C4.5 algorithm combined with Z-Score normalization to group citizen data into Eligible or Ineligible categories. The data used came from 551 residents of Atu Lintang District and included attributes such as house status, wall type, toilet facilities, occupation, and income. The research stages started from data preprocessing, attribute normalization, training the model, to evaluating its performance through metric such as accuracy, precision, recall, and F1-score. The evaluation results showed that the model achieved an accuracy of 94%, precision 0.96, recall 0.90, and F1-score 0.93 for the Eligible category. Based on the confusion matrix, the model was able to correctly classify 47 Eligible residents and 57 Ineligible residents. Analysis of the attributes showed that occupation was the most influential feature in the classification process. These results prove that the application of the C4.5 algorithm can be applied effectively to build a decision support system in the distribution of social assistance, and provide accurate and easy-to-understand results. This study also opens up opportunities for improving model performance by adding more data and testing with alternative algorithms going forward.
Geographic Information System for Mapping Accommodation Locations in Lhokseumawe City Using the AHP Method and Dijkstra's Algorithm Wahdana, Aldi; Nurdin; Sujacka Retno
Journal of Applied Informatics and Computing Vol. 9 No. 3 (2025): June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i3.9597

Abstract

This study aims to develop a web-based Geographic Information System (GIS) to provide recommendations for the best accommodation and the fastest route to the accommodation location in Lhokseumawe City. The Analytical Hierarchy Process (AHP) method is used to determine the priority of accommodation based on five main criteria, namely price, public facilities, cleanliness, security, and year founded. The Dijkstra algorithm is applied to calculate the shortest path from the user's position to the selected accommodation. This study involved 21 accommodations as study objects. The results of the analysis showed that Hotel Diana obtained the highest value of 0.08873, so it was recommended as the main accommodation. The shortest distance from the Faculty of Engineering, Malikussaleh University to Hotel Diana is 11.53857 km. These results indicate that the combination of the AHP method and the Dijkstra algorithm is effective in supporting location-based decision making, as well as making it easier for users to determine appropriate accommodation and the fastest route efficiently.
Analysis of Clustering Results for Crime Incident Data in Indonesia Using Fuzzy C-Means Retno, Sujacka; Hakimi, Musawer
Journal of Advanced Computer Knowledge and Algorithms Vol. 2 No. 3 (2025): Journal of Advanced Computer Knowledge and Algorithms - July 2025
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v2i3.22565

Abstract

This study examines the clustering of crime incident data across Indonesia from 2000 to 2024 using the Fuzzy C-Means (FCM) algorithm, with a focus on the impact of data normalization. Comprehensive annual provincial crime statistics from Badan Pusat Statistik (BPS) were preprocessed to handle missing values and then standardized via the Standard Scaler. FCM clustering was performed separately on both the original and normalized datasets, with the number of clusters set to three. Cluster quality was evaluated over ten independent runs using five metrics: Davies-Bouldin Index (DBI), Silhouette Score (SS), Calinski-Harabasz Index (CH), Adjusted Rand Index (ARI), and Normalized Mutual Information (NMI). Results indicate that normalization consistently yields lower DBI values (average 0.824 vs. 0.830) and higher SS (average 0.367 vs. 0.363) and CH scores (average 55.35 vs. 54.09), while ARI and NMI remain stable across treatments. These findings demonstrate that normalization enhances cluster compactness and separation without altering underlying data structures, leading to more interpretable and reliable groupings. By uncovering regional crime patterns and highlighting the methodological importance of preprocessing, this research provides actionable insights for policymakers and law enforcement agencies to allocate resources more effectively and develop targeted crime prevention strategies.
Mathematics Adventure: Game Edukasi Interaktif untuk Meningkatkan Pemahaman Matematika Siswa Sekolah Dasar Retno, Sujacka; Agusniar, Cut; Meiyanti, Rini; Fitria, Rahma
Jurnal Malikussaleh Mengabdi Vol. 4 No. 1 (2025): Jurnal Malikussaleh Mengabdi, April 2025
Publisher : LPPM Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jmm.v4i1.22233

Abstract

Program pengabdian masyarakat ini bertujuan untuk meningkatkan kualitas pembelajaran matematika di SD Negeri 28 Sawang, Aceh Utara, melalui pengembangan dan implementasi game edukasi berbasis teknologi, Mathematics Adventure. Game ini dirancang untuk siswa kelas III dengan tujuan membantu mereka memahami konsep operasi bilangan bulat, seperti penjumlahan, pengurangan, perkalian, dan pembagian, melalui pendekatan yang interaktif dan menyenangkan. Kegiatan ini melibatkan analisis kebutuhan pengguna, pengembangan game menggunakan platform Unity, pelatihan bagi guru, serta implementasi dan evaluasi langsung kepada siswa. Hasil evaluasi menunjukkan bahwa penggunaan Mathematics Adventure berhasil meningkatkan minat dan motivasi siswa dalam belajar matematika, dengan 90% siswa menunjukkan antusiasme yang lebih besar dan peningkatan pemahaman konsep sebesar 20%. Guru juga merasakan manfaat signifikan dari media pembelajaran ini, yang dinilai efektif dalam menyampaikan materi matematika dengan cara yang lebih menarik. Melalui program ini, siswa tidak hanya memperoleh pengalaman belajar yang lebih menyenangkan tetapi juga mengembangkan keterampilan digital dasar. Diharapkan kegiatan ini dapat menjadi inspirasi untuk pengembangan lebih lanjut media pembelajaran berbasis teknologi, serta mendorong kolaborasi yang berkelanjutan antara pendidik dan pengembang.