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UPT Publikasi Ilmiah, Universitas Islam Bandung. Jl. Tamansari No. 20, Bandung 40116, Indonesia, Tlp +62 22 420 3368, +62 22 426 3895 ext. 6891
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Bandung Conference Series: Statistics
Published by Universitas Islam Bandung
ISSN : -     EISSN : 2828206X     DOI : https://doi.org/10.29313/bcss.v2i2
Core Subject : Science, Education,
Decision Sciences, Operations Research & Management Education Mathematics
Bandung Conference Series: Statistics (BCSS) menerbitkan artikel penelitian akademik tentang kajian teoritis dan terapan serta berfokus pada Statistika dengan ruang lingkup sebagai berikut: Alternating Least Square, Analisis Konjoin, Autoregressive, Auxiliary Variabel, Baby Birth, Block Maxima, Churn Distribusi Skellam, Cox Regression, Data spasial, DBD Ordinal Logistic Regression, Diagram kendali, Discrete Choice Experiment Method, Discrete Time Logistic, empirical likelihood, Fisher Scoring, Generalized Structured Component Analysis, Geographically Weighted Regression, GEV, GJR GARCH, Infant Mortality Preferensi, Insurance Claim, Kaplan-Meier, Kernel Bi-Square, Gaussian, Logistic Regression, Maternal Mortality, Mixed Geographically Weighted Regression Model GSTAR, MLE, Model ARIMAX, MSE. Multiple linear regression analysis, Nadaraya Watson, Newton Raphson Method, Nonparametrik Spline Confidence Interval, Optimasi Multi-Objek, orde Spasial, Outlier, Pareto Optimal, Partial Proportional Odds Model, Pemodelan Indeks Pembangunan Manusia. Penduga Rasio dan Produk Tipe Eksponensial, Peramalan, Poisson Bivariate Regression, Poisson Regression, Rata-rata Populasi berhingga, Regresi, Return Period Exogenous Variable, RMSE, Structural Equation Modeling, Survival Analysis, Threshold, Vibrasi Bearing, zero-inflated. Prosiding ini diterbitkan oleh UPT Publikasi Ilmiah Unisba. Artikel yang dikirimkan ke prosiding ini akan diproses secara online dan menggunakan double blind review minimal oleh dua orang mitra bebestari.
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 1 Documents
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Klasifikasi Provinsi di Indonesia Berdasarkan IPM 2025 Menggunakan K-Medoids Clustering Zakiyah Romadhoni; Reny Rian Marliana
Bandung Conference Series: Statistics 143-150
Publisher : UNISBA Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/bcss.v6i2.24814

Abstract

Abstract. The rapid development of information technology and the availability of large-scale data have encouraged the application of analytical methods to better understand social conditions and human development. This study aims to classify the provinces of Indonesia based on the 2025 Human Development Index (HDI) indicators using the K-Medoids Clustering method. Secondary data obtained from Statistics Indonesia (Badan Pusat Statistik) include four variables: Life Expectancy at Birth (LEB), Mean Years of Schooling (MYS), Expected Years of Schooling (EYS), and Adjusted Per Capita Expenditure (APCE). The analysis involved data preprocessing, including missing value detection, outlier identification using the Z-Score method, data standardization. The results showed no missing values or multicollinearity, although several outliers were identified. Based on the highest silhouette coefficient (0.263), three optimal clusters were obtained: a good cluster (5 provinces), a moderate cluster (16 provinces), and a poor cluster (17 provinces). These clustering results can serve as a reference for formulating more targeted regional development policies to improve equity in education, health, and community welfare across Indonesia.Abstrak. Perkembangan teknologi informasi dan ketersediaan data dalam skala besar mendorong penerapan berbagai metode analisis untuk memahami kondisi sosial dan pembangunan manusia. Penelitian ini bertujuan mengelompokkan provinsi di Indonesia berdasarkan indikator Indeks Pembangunan Manusia (IPM) tahun 2025 menggunakan metode K-Medoids Clustering. Data yang digunakan merupakan data sekunder dari Badan Pusat Statistik yang meliputi Usia Harapan Hidup (UHH), Rata-Rata Lama Sekolah (RRLS), Harapan Lama Sekolah (HLS), dan Pengeluaran Per Kapita yang Disesuaikan (PPKD). Tahapan analisis meliputi pemeriksaan missing value, penanganan outlier menggunakan metode Z-Score, standarisasi data. Hasil penelitian menunjukkan tidak terdapat missing value maupun multikolinearitas, meskipun ditemukan beberapa outlier. Berdasarkan nilai silhouette coefficient tertinggi sebesar 0,263, diperoleh tiga cluster optimal, yaitu cluster baik (5 provinsi), cluster cukup (16 provinsi), dan cluster kurang baik (17 provinsi). Hasil pengelompokan ini diharapkan menjadi acuan dalam penyusunan kebijakan pembangunan daerah yang lebih tepat sasaran guna meningkatkan pemerataan pendidikan, kesehatan, dan kesejahteraan masyarakat di Indonesia.

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