STATISTIKA
Vol. 24 No. 1 (2024): Statistika

Analisis Ketertinggalan Desa di Provinsi Papua dan Papua Barat Menggunakan Association Rule Mining

Etsa Primanda (Politeknik Statistika STIS)
Siskarossa Ika Oktora (Politeknik Statistika STIS)



Article Info

Publish Date
29 May 2024

Abstract

ABSTRAK Pada hakikatnya, pembangunan dimaksudkan untuk mengupayakan kondisi kehidupan yang lebih layak. Namun, data Indeks Pembangunan Desa 2018 menunjukkan persentase desa tertinggal di Pulau Papua paling banyak dibandingkan pulau lainnya. Terlebih lagi, penelitian mengenai karakteristik utama ketertinggalan desa di wilayah tersebut belum dilakukan secara komprehensif. Oleh sebab itu, penelitian ini bertujuan untuk mengetahui gambaran umum desa tertinggal, serta menganalisis karakteristik utama ketertinggalan desa di Provinsi Papua dan Papua Barat. Sumber data yang digunakan adalah data indikator Indeks Pembangunan Desa 2018 yang diperoleh dari Subdirektorat Statistik Ketahanan Wilayah Badan Pusat Statistik (BPS) berdasarkan Pendataan Potensi Desa 2018. Metode analisis yang digunakan adalah analisis deskriptif menggunakan diagram batang dan peta tematik, serta teknik data mining menggunakan association rule mining. Hasil analisis menunjukkan Kabupaten Tolikara, Provinsi Papua dan Kabupaten Pegunungan Arfak, Provinsi Papua Barat memiliki persentase desa tertinggal yang tertinggi. Sebagian besar desa tertinggal di Provinsi Papua dan Papua Barat berada di wilayah dengan topografi dataran tinggi dan pegunungan. Hasil association rule mining menunjukkan karakteristik utama ketertinggalan desa sebagian besar kabupaten di Provinsi Papua adalah pelayanan kesehatan, sarana transportasi, dan infrastruktur ekonomi. Sementara itu, karakteristik utama ketertinggalan desa sebagian besar kabupaten di Provinsi Papua Barat adalah pelayanan kesehatan. ABSTRACT The goal of development is to seek more decent living conditions. However, the Village Development Index 2018 data shows that the percentage of rural underdevelopment on Papua Island is the highest compared to other islands. Moreover, researchers have yet to conduct comprehensive research in the region on the main characteristics of rural underdevelopment. Therefore, this study aims to observe the general description of rural underdevelopment and analyze the main characteristics of rural underdevelopment in Papua and West Papua Provinces. The data source used is the Village Development Index 2018 indicator data from the Regional Resilience Statistics Sub-Directorate of Badan Pusat Statistik (BPS) based on the Village Potential Data 2018. The analytical methods used are descriptive analysis using bar charts, thematic maps, and data mining techniques, namely association rule mining. The results show that the percentages of rural underdevelopment in Tolikara Regency, Papua Province, and Arfak Mountains Regency, West Papua Province, are higher among other regions. Areas characterized by highlands and mountainous terrain in Papua and West Papua Provinces concentrate most of the rural underdevelopment. Then, the results of association rule mining show that the main characteristics of rural underdevelopment in most districts in Papua Province are health services, transportation facilities, and economic infrastructure. Meanwhile, the main characteristic of rural underdevelopment in most districts in West Papua Province is health services.

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Journal Info

Abbrev

statistika

Publisher

Subject

Decision Sciences, Operations Research & Management Mathematics

Description

STATISTIKA published by Department of Statistics, Faculty of Mathematics and Natural Sciences, Bandung Islamic University as pouring media and discussion of scientific papers in the field of statistical science and its applications, both in the form of research results, discussion of theory, ...