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All Journal Jurnal Matematika JOURNAL SCIENTIFIC OF MANDALIKA (JSM)
I Komang Gede Sukarsa
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Humanities Languange, Linguistic, Communication & Media Mathematics Other

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ESTIMATOR KERNEL DALAM MODEL REGRESI NONPARAMETRIK I Komang Gede Sukarsa; I Gusti Ayu Made Srinadi
Jurnal Matematika Vol 2 No 1 (2012)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2012.v02.i01.p21

Abstract

Analisis regresi nonparametrik merupakan metode pendugaan kurvaregresi yang digunakan jika tidak ada informasi sebelumnya te,ntang benttrk kurvaregresi atau tidak terikat pada asumsi bentuk fungsi tertentu. Estimasi fungsiregresi nonparametrik dilakukan berdasarkan daA pengamatan dengan menggunakanteknik pemulusan (smoothing). Penelitian ini bertujuan untuk memperlihatkanpendekatan estimator kernel dalam regresi nonparametik padadata sekunder,yaitu data motorcycle. Hasil penelitian ini menunjukkan batrwa penggunaanfungsi kernel yang berbda yaitu fungsi kernel Triangle dan kernel Gaussian denganbandwidth optimal menghasilkan estimasi kurva regresi yang hanrpir saura, sehinggadapat dituojukkan bahwa pemilihan bandwidth lebih penting dibandingkandengan pernilihan fungsi kernel.
Pengelompokan Provinsi Di Indonesia Berdasarkan Indikator Kesehatan Balita Menggunakan Metode Agglomerative Clustering Ana Fikria; I Komang Gede Sukarsa; I Putu Winada Gautama; Made Ayu Dwi Octavanny; Anggun Yuliarum Qur’ani; Desak Putu Eka Nilakusmawati
Journal Scientific of Mandalika (JSM) e-ISSN 2745-5955 | p-ISSN 2809-0543 Vol. 7 No. 1 (2026)
Publisher : Institut Penelitian dan Pengembangan Mandalika Indonesia (IP2MI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/10.36312/vol7iss1pp71-80

Abstract

Child Health is a crucial indicator in assessing the overall health of a population. However, there are disparities between provinces in terms of healthcare access, immunization coverage, and child nutrition status. Therefore, this study aims to cluster 38 provinces in Indonesia based on infant health indicators using the Agglomerative Hierarchical Clustering method. The data used is sourced from the 2023 Indonesian Health Profile Report, with variables including neonatal visit coverage, complete basic immunization, infant weighing, and the prevalence of infants with severe underweight, stunting, and malnutrition. The five agglomerative methods applied in this study are Single Linkage, Complete Linkage, Average Linkage, Centroid, and Ward. The results indicate disparities in child health conditions across provinces, with clusters representing regions with good, moderate, and poor conditions. These findings can serve as a reference for the implementation of the Free Nutritious Meal Program (MBG) in 2025 to better target areas with high vulnerability, in order to reduce stunting rates and improve overall child nutritional status.
Co-Authors Ana Fikria Anggun Yuliarum Qur’ani Desak Putu Eka Nilakusmawati I Gusti Ayu Made Srinadi I Putu Winada Gautama MADE AYU DWI OCTAVANNY