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All Journal Prosiding Seminar Nasional Official Statistics
Yohannes Kevin
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Humanities Computer Science & IT Economics, Econometrics & Finance Social Sciences

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Klusterisasi Kabupaten/Kota Berbasis Produk Domestik Regional Bruto: Pendekatan Machine Learning Self-Organizing Map Yohannes Kevin; Bagus Sumargo; Dania Siregar
Seminar Nasional Official Statistics Vol 2026 No 1 (2026): Seminar Nasional Official Statistics 2026
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2026i1.2671

Abstract

East Java is province with 38 regencies/cities and second-largest contribution to Gross Regional Domestic Product in 2023. With it’s economy dispersed across regions, this study purposes are cluster the economic characteristics of East Java Province to seek economics of scale between regencies/cities. The method used cluster analysis with Self-Organizing Map based on machine learning. The analysis conducted on 17 economic sectors of GRDP production approaches. Before analysis, number of clusters used through internal validation determined. The results: first cluster consists of 34 regencies/cities (excluding Surabaya City and Sidoarjo Regency), characterized predominantly by agriculture, forestry, and fisheries sector as well as mining and quarrying sector. Second cluster consists of Surabaya City and Sidoarjo Regency, characterized by sectors other than those dominant in the first cluster. When the cluster were visualized using the SOM U- matrix and Codes Plot, significant differences were observed between Surabaya City and Sidoarjo Regency compared with other regencies/cities.
Co-Authors Bagus Sumargo Dania Siregar