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All Journal Building of Informatics, Technology and Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH)
Hilyatul Mustafidah
Universitas Muhammadiyah Bima, Bima
Computer Science & IT Decision Sciences, Operations Research & Management

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Perbandingan Metode Elbow dan Silhouette Coefficient pada K-Means untuk Pengelompokan Wilayah Berdasarkan Indeks Pembangunan Manusia Shinta Zahira Hayathun Nufus; Fathir Fathir; Hilyatul Mustafidah
Building of Informatics, Technology and Science (BITS) Vol 8 No 1 (2026): June 2026
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v8i1.10114

Abstract

One of the primary metrics for evaluating the effectiveness of efforts to improve people’s well-being through human development is the Human Development Index (HDI). Although Indonesia’s HDI has continued to improve, disparities in human development remain evident across regions, particularly in Bali, West Nusa Tenggara (NTB), and East Nusa Tenggara (NTT). Identifying regions with similar HDI characteristics is important for supporting more targeted development policies. However, the performance of K-Means clustering is highly influenced by the number of clusters used, making the selection of an appropriate cluster number essential. This study compares the Elbow Method and Silhouette Coefficient in determining the optimal number of clusters for 2024 HDI data covering 41 regencies and municipalities based on Life Expectancy, Expected Years of Schooling, Mean Years of Schooling, and Per Capita Expenditure. The results show that the Elbow Method produces three clusters, while the Silhouette Coefficient produces two clusters with a silhouette value of 0.5312. Evaluation using the Davies–Bouldin Index (DBI) indicates that the two-cluster solution achieves a lower DBI value (0.7350) than the three-cluster solution (1.0382). These findings suggest that the HDI structure in Bali, NTB, and NTT tends to form two major groups: regions with high human development and regions with medium-to-low human development. The results also indicate that the Silhouette Coefficient is more representative for determining the optimal number of clusters in HDI data with relatively similar regional characteristics. The clustering results may support policymakers in prioritizing development programs in education, health, and community welfare
Klasifikasi Penyakit Daun Bawang Merah Menggunakan MobileNetV2 Convolutional Neural Network (CNN) Widia Ainun Arabiah; Fathir Fathir; Hilyatul Mustafidah
Journal of Information System Research (JOSH) Vol 7 No 4 (2026): July 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i4.10575

Abstract

Diseases affecting shallot plants are a primary cause of reduced crop quality and yield. Manual disease identification relies on visual observation, making it prone to error and time-consuming. This study aims to develop a classification model for shallot leaf diseases by combining Gray Level Co-occurrence Matrix (GLCM) feature extraction with MobileNetV2, classified using a Convolutional Neural Network (CNN). The dataset comprises 1,188 shallot leaf images categorized into five classes: downy mildew, healthy, leaf blight, *moler* (basal rot), and purple blotch. The research process involved dataset collection; pre-processing (image resizing to 224×224 pixels, grayscale conversion, normalization, and data augmentation); texture feature extraction using GLCM; and deep feature extraction using MobileNetV2. These features were then combined and used as input for the CNN classification model. Model evaluation was conducted using a confusion matrix, assessing accuracy, precision, recall, and F1-score. The results demonstrate that the proposed model achieved 93% accuracy, with balanced precision, recall, and F1-score values ​​across most classes. The contribution of this research is the integration of gray level co-occurrence matrix (GLCM) texture feature extraction with mobilenetv2 visual features within a convolutional neural network (CNN) model to improve the classification performance of shallot leaf diseases.
Rancang Bangun Sistem Informasi Pengaduan Fasilitas Publik pada Dinas PUPR Kabupaten Bima Menggunakan Prototyping dan Black Box Testing Nur Anisa; Syarifuddin Syarifuddin; Hilyatul Mustafidah
Journal of Information System Research (JOSH) Vol 7 No 4 (2026): July 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i4.10714

Abstract

The management of complaints regarding public facility damage at the Public Works and Spatial Planning Agency (Dinas PUPR) of Bima Regency currently faces challenges, specifically regarding the lack of optimal integration across the processes of report submission, verification, disposition, follow-up, and monitoring. This situation results in an unstructured complaint management process and hinders the monitoring of report handling progress. This research aims to design and develop a web-based Public Facility Complaint Information System capable of supporting structured complaint management aligned with the workflow of the Bima Regency PUPR Agency. The system development method employed is Prototyping, which allows for the evaluation and refinement of the prototype based on user feedback. System design utilizes the Unified Modeling Language (UML), encompassing Use Case Diagrams, Activity Diagrams, Entity Relationship Diagrams (ERD), and user interface design. The system is implemented using the Laravel framework and a MySQL database. System testing was conducted using the Black Box Testing method across 12 test scenarios covering core system functions—ranging from user management, complaint submission, verification, disposition, follow-up, and monitoring to report generation. Test results indicate that all 12 scenarios were executed successfully, yielding the expected outcomes with a 100% success rate. The contribution of this research is the creation of a complaint information system that integrates report submission via Village Operators, verification and disposition by the General Admin, follow-up by Division Admins, and monitoring by the Head of the PUPR Agency. Consequently, the designed and developed system facilitates a more structured, well-documented, effective, and easily monitored process for managing public facility complaints.
Co-Authors Fathir Fathir Nur Anisa Shinta Zahira Hayathun Nufus Syarifuddin Syarifuddin Widia Ainun Arabiah