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All Journal Teorema: Teori dan Riset Matematika Kappa Journal Jurnal Statistika dan Aplikasinya
Chandrawati
Universitas Hamzanwadi
Agriculture, Biological Sciences & Forestry Astronomy Computer Science & IT Economics, Econometrics & Finance Education Mathematics Physics Social Sciences Other

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A Study of Grouping of Earthquake Damage from Magnitude Scale in Lombok Using K-Means Modeling Kertanah; Alissa Chintyana; Chandrawati; Basirun; Mutia Rosiana Nita Putri; Nasibatul Mahmudah
Kappa Journal Vol 8 No 3 (2024): Kappa Journal
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/kpj.v8i3.27563

Abstract

This study aims to group earthquake damage from its magnitude scale and visualize it on a geographical map. The magnitude of the earthquake was grouped using the K-means model. It is one of the most popular and effective clustering models in grouping data, such as earthquake data. The dataset used in this study is earthquake data for the last ten years on Lombok Island. The optimal number of clusters was used which is 2 in this case, based on the highest Silhouette score of 0.930. The highest Silhouette score shows the optimal number of clusters. The cluster on the geographical map shows most earthquakes' distribution in Northen Lombok Island with cluster 1 consisting of 145 earthquakes, while cluster 2 consists of 3 earthquakes. In addition, the earthquake's damage based on its magnitude scale, there were four different kinds of earthquake damage: slight, limited, minor, and severe damage that have occurred for the last ten years in Lombok Island. Minor and Slight damages were dominant, respectively. However, severe damage occurred in the northern part of Lombok Island due to an earthquake in 2018.
APPLICATION OF THE GUSTAFSON–KESSEL ALGORITHM FOR IDENTIFYING SPATIAL PATTERNS OF NATURAL DISASTERS IN EAST NUSA TENGGARA Mitha Rabiyatul Nufus; Chandrawati; Erlyne Nadhilah Widyaningrum
Jurnal Statistika dan Aplikasinya Vol. 9 No. 2 (2025): Jurnal Statistika dan Aplikasinya
Publisher : LPPM Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.09205

Abstract

This study examines spatial patterns of disaster vulnerability across districts and cities in East Nusa Tenggara Province, one of Indonesia’s most disaster-prone regions. Although previous studies have highlighted the province’s exposure to multiple hazards, limited attention has been given to clustering methods capable of capturing non-homogeneous and elliptical data structures. This research aims to classify regional disaster vulnerability based on the characteristics of disaster occurrences and to provide empirical support for more targeted mitigation strategies. Secondary data on floods, forest fires, hurricanes, and landslides recorded in 2023 were analyzed using the adaptive Gustafson–Kessel clustering algorithm. The optimal number of clusters was determined using the Silhouette validity index. The results identify three distinct vulnerability groups: regions highly prone to multiple types of disasters, regions predominantly affected by a single hazard, and regions with relatively low disaster risk. The resulting spatial patterns reveal clear differences in disaster intensity and complexity among regions, emphasizing the need for location-specific disaster management policies. This study contributes to disaster risk analysis by demonstrating the applicability of the Gustafson–Kessel algorithm in capturing complex spatial vulnerability patterns that are often overlooked by conventional clustering approaches.
Implementasi Fuzzy Possibilistic C-Means untuk Pengelompokan Kabupaten/Kota di Provinsi Nusa Tenggara Barat Muhammad Gazali; Chandrawati Chandrawati; Ertina Septia Adini
Teorema: Teori dan Riset Matematika Vol 11, No 1 (2026): Maret
Publisher : Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/teorema.v11i1.20886

Abstract

Pemetaan wilayah berdasarkan kondisi kesehatan penting untuk mengidentifikasi ketimpangan pelayanan dan menentukan prioritas intervensi. Provinsi Nusa Tenggara Barat menghadapi tantangan berupa distribusi fasilitas kesehatan yang belum merata serta peningkatan kasus penyakit menular. Penelitian ini bertujuan mengelompokkan Kabupaten/Kota berdasarkan ketersediaan fasilitas kesehatan dan prevalensi penyakit menular menggunakan metode Fuzzy Possibilistic C-Means (FPCM). Variabel yang digunakan meliputi jumlah puskesmas, rumah sakit, serta kasus tuberkulosis, HIV/AIDS, demam berdarah, dan diare. Evaluasi hasil klasterisasi menggunakan Partition Entropy (PE), Partition Coefficient (PC), dan Modified Partition Coefficient (MPC) menunjukkan konfigurasi optimal pada tiga cluster (PE = 0.6125239, PC = 0.9798644, dan MPC = 0.9697966). Profilisasi hasil klaster menunjukkan bahwa Cluster 1 terdiri dari daerah-daerah dengan ketersediaan fasilitas kesehatan yang relatif rendah serta tingkat prevalensi penyakit menular yang tinggi. Cluster 3 mencakup wilayah dengan fasilitas kesehatan yang lebih memadai, namun tetap menghadapi beban penyakit menular yang signifikan. Cluster 2 mencakup wilayah dengan fasilitas kesehatan yang tinggi sedangkan kasus penyakit menular yang rata-rata rendah. Temuan ini menunjukkan pentingnya pendekatan berbasis data dalam mendukung perencanaan intervensi kesehatan yang lebih terfokus dan responsif terhadap kebutuhan masing-masing wilayah di Provinsi Nusa Tenggara Barat.
Co-Authors Alissa Chintyana Basirun Basirun Erlyne Nadhilah Widyaningrum Ertina Septia Adini Kertanah Mitha Rabiyatul Nufus Muhammad Gazali Mutia Rosiana Nita Putri Nasibatul Mahmudah