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All Journal SAINSMAT Edu Society: Jurnal Pendidikan, Ilmu Sosial dan Pengabdian Kepada Masyarakat SAINSMAT: Jurnal Ilmiah Ilmu Pengetahuan Alam ARUS JURNAL SAINS DAN TEKNOLOGI Journal of Mathematics, Computation and Statistics (JMATHCOS) Diophantine Journal of Mathematics and Its Applications
Ihwal, Muhammad
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Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Industrial & Manufacturing Engineering Mathematics Physics Social Sciences Other

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Journal : Journal of Mathematics, Computation and Statistics (JMATHCOS)

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Otokorelasi Spasial pada Prevalensi Balita Stunting, Wasting, Underweight, dan Overweight di Pulau Sulawesi Tahun 2022 Baharuddin; Yahya, Irma; Ihwal, Muhammad
Journal of Mathematics, Computations and Statistics Vol. 7 No. 2 (2024): Volume 07 Nomor 02 (Oktober 2024)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v7i2.2408

Abstract

Prevalensi balita stunting, wasting, underweight, dan overweight setiap kabupaten/kota tidaklah sama. Ada kemungkinan bahwa angka prevalensi balita di suatu daerah terkait dengan angka prevalensi balita di daerah yang berdekatan. Penelitian ini bertujuan menguji adanya otokorelasi spasial pada prevalensi balita stunting, wasting, underweight, dan overweight di Pulau Sulawesi. Data yang dipakai adalah data sekunder berupa prevalensi balita setiap kabupaten/kota yang merupakan hasil Survei Status Gizi Indonesia (SSGI) tahun 2022. Karena beberapa kabupaten/kota terpisah oleh lautan dengan Pulau Sulawesi maka kami memakai matriks pembobot spasial berbasis k-tetangga terdekat. Hasil pengujian dengan indeks Moran menunjukkan bahwa terdapat otokorelasi spasial positif pada prevalensi balita stunting, wasting, underweight, dan overweight. Sebaran angka prevalensi membentuk pola sistematik yang mengelompok di suatu kawasan pada masing-masing provinsi.
Modeling the Percentage of Poor Population in Sulawesi Island Using Kernel Estimation in Priestley-Chao Semiparametric Regression Ampa, Andi Tenri; Makkulau, Andi Tenri Pannangngareng; Ome, Lilis La; Ihwal, Muhammad; Yahya, Irma; 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 Adhi Wibawa, Gusti Ngurah Andi Tenri Ampa Arianti, Refika Allya Baharuddin Bahriddin Abapihi Dewintha, Astyan Indrawati, Wa Ode Irma Yahya K, Raida Lilis Laome Makkulau Makkulau Makkulau Makkulau, Andi Tenri Pannangngareng Ningtyas, Rita Ayu Ome, Lilis La Puja Karna, I Kadek Aryandra Ruslan Salsabilah, Adelfina Umi, Enggar Cahyani Wibawa, Gusti Ngurah Adhi