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All Journal Journal of Mathematics, Computation and Statistics (JMATHCOS) Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam
Muhammad Ihwal
Halu Oleo University
Mathematics

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Clustering Districts/Cities In Southeast Sulawesi Province Using Fuzzy C-Means Based On Infectious Disease Cases I Kadek Aryandra Puja Karna; Gusti Ngurah Adhi Wibawa; Muhammad Ihwal
SAINSMAT: Jurnal Ilmiah Ilmu Pengetahuan Alam Vol. 14 No. 2 (2025): Volume 14 Nomor 2 (September 2025)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/5h3rph44

Abstract

This study aims to classify the regencies and cities in Southeast Sulawesi Province based on infectious disease cases. The data were obtained from the Southeast Sulawesi Provincial Health Office. The Fuzzy C-Means (FCM )method was applied because it allows each data point to belong to multiple clusters with varying degrees of membership, making it suitable for health data that often exhibit uncertainty and overlapping characteristics. The analysis results show that the regions in Southeast Sulawesi can be grouped into five clusters based on the level of infectious disease cases. Each cluster represents a different level of disease prevalence, which can serve as a foundation for developing more effective and targeted public health policy strategies.
Modeling the Percentage of Poor Population in Sulawesi Island Using Kernel Estimation in Priestley-Chao Semiparametric Regression Andi Tenri Ampa; Andi Tenri Pannangngareng Makkulau; Lilis La Ome; Muhammad Ihwal; Irma Yahya; Makkulau Makkulau
Journal of Mathematics, Computations and Statistics Vol. 8 No. 1 (2025): Volume 08 Nomor 01 (April 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i1.8761

Abstract

This study aims to model the data on the Percentage of Poor Population in Sulawesi Island in 2023, considering various factors that influence poverty. Eradicating extreme poverty has become a top priority to be achieved by 2030. This study examines the influence of several variables, such as Open Unemployment Rate, Human Development Index, Labor Force Participation Rate, Average Length of Schooling, Percentage of Access to Proper Sanitation, and Gross Regional Domestic Product, on the Percentage of Poor Population in Sulawesi Island, using the Kernel Priestley-Chao estimation in Semiparametric regression with an Ordinary Least Square approach. This study also applies the selection of optimal bandwidth using the minimum Generalized Cross Validation method with an optimal bandwidth of 0.991, resulting in a Mean Absolute Percentage Error value of 16.32%. The model shows excellent estimation results, with a residual coefficient value of 69% used to model the Percentage of Poor Population data with a high level of accuracy. The data used partially has a parametric pattern, while some do not have a specific pattern, and there are outliers.
Co-Authors Andi Tenri Ampa Andi Tenri Pannangngareng Makkulau Gusti Ngurah Adhi Wibawa I Kadek Aryandra Puja Karna Irma Yahya Lilis La Ome Makkulau Makkulau