Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
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All Journal UNP Journal of Statistics and Data Science
Muhammad Arief Rivano
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management Mathematics Social Sciences

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Application of K-Modes Clustering Method to Identify Low Birth Weight Factors in Central Sulawesi Province Aprotama, Celsy; Yenni Kurniawati; Muhammad Arief Rivano; Devi Yopita Sipayung
UNP Journal of Statistics and Data Science Vol. 3 No. 2 (2025): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol3-iss2/357

Abstract

Low birth weight (LBW) has long-term effects on maternal and child health, with a high prevalence in Central Sulawesi Province. This study aims to identify factors influencing the occurrence of LBW in the region using the k-modes clustering method. The data used in this research is derived from the 2017 Indonesian Demographic and Health Survey. The analyzed variables include the husband's education level, miscarriage rate, maternal smoking habits, child's gender, husband's occupation, type of residence, and wealth index. The analysis revealed two distinct clusters. The first cluster mainly consisted of husbands with a secondary education level or equivalent to junior high school, working in the agricultural sector, residing in urban areas, and having a medium wealth index. In contrast, the second cluster was dominated by husbands with only primary education or equivalent to elementary school, living in rural areas, and having a very low wealth index. The findings of this study emphasize the need for comprehensive efforts to improve education, enhance environmental conditions, and expand healthcare access to reduce poverty and lower the incidence of LBW in Central Sulawesi. This research also contributes to initiatives aimed at improving maternal and child health in the region.
Comparison of K-Means and Ward Methods in Clustering Indonesian Provinces Based on Household Basic Service Access Mulya, Nurul; Fajri Juli Rahman Nur Zendrato; Muhammad Arief Rivano; Zamahsary Martha; Tessy Octavia Mukhti
UNP Journal of Statistics and Data Science Vol. 4 No. 1 (2026): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol4-iss1/449

Abstract

Disparities in household basic service access across provinces in Indonesia remain a key issue in regional development. Basic services such as access to improved drinking water, proper sanitation, electricity, and adequate housing are essential indicators of household welfare, making regional classification necessary to identify similarities and disparities among provinces. This study aims to cluster Indonesian provinces based on household basic service access indicators and to compare the performance of the K-Means method and Hierarchical Clustering using the Ward approach. The analysis was conducted using numerical data with Euclidean distance as a measure of similarity. The optimal number of clusters was determined using the Silhouette plot and further validated using the Silhouette Coefficient. The results indicate that both K-Means and Ward methods produce two optimal clusters representing provinces with relatively high and relatively low levels of household basic service access. Centroid analysis reveals clear differences between clusters across all indicators, particularly in electricity access and sanitation. Furthermore, the evaluation of clustering quality shows that the Ward method yields a higher Silhouette Coefficient than the K-Means method, indicating more compact clusters and better separation between clusters. Therefore, the Ward method is considered more effective in mapping patterns of household basic service access across provinces. The findings of this study can support regional planning by providing a clearer understanding of disparities in household basic service access in Indonesia.
Co-Authors Aprotama, Celsy Devi Yopita Sipayung Fajri Juli Rahman Nur Zendrato Mulya, Nurul Tessy Octavia Mukhti Yenni Kurniawati Zamahsary Martha