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All Journal PUBLIKASI PENELITIAN TERAPAN DAN KEBIJAKAN Prosiding Seminar Nasional Official Statistics
Erwin Tanur
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Economics, Econometrics & Finance Environmental Science Public Health Social Sciences

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Klasterisasi Wilayah Rentan Bencana Alam Berupa Gerakan Tanah Dan Gempa Bumi Di Indonesia I Nyoman Setiawan; Dewi Krismawati; Setia Pramana; Erwin Tanur
Seminar Nasional Official Statistics Vol 2022 No 1 (2022): Seminar Nasional Official Statistics 2022
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (437.82 KB) | DOI: 10.34123/semnasoffstat.v2022i1.1538

Abstract

Indonesia is one of the countries prone to natural disasters, such as soil movements and earthquakes. The people of Indonesia have felt various kinds of impacts caused by the disaster, both in the form of losing their jobs, their homes, and even their beloved family members. However, this impact can certainly be minimized with good disaster management. Therefore, the author focuses on the clustering of earthquake-prone areas in Indonesia using Density-based Spatial Clustering of Application with Noise (DBSCAN), Common Nearest Neighbor Clustering (CNN), and K-Medoids. The results of the clustering show that the soil movement-prone cluster formed from the DBSCAN algorithm is centered on the islands of Java and Bali, as well as along the western part of North Sumatra to Lampung, while the earthquake-prone areas formed from the K-Medoids algorithm are spread over the area traversed by the Pacific Ring of Fire.
Kategori Unggulan di Provinsi Sumatera Selatan Pasca Covid-19 dan Pengelompokan Kabupaten Kota Menggunakan K-Means Clustering Lismiana Lismiana; Erwin Tanur; Yuliana Ria Uli Sitanggang
Publikasi Penelitian Terapan dan Kebijakan Vol 6 No 2 (2023): Publikasi Penelitian Terapan dan Kebijakan
Publisher : Badan Penelitian dan Pengembangan Daerah Provinsi Sumatera Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46774/pptk.v6i2.548

Abstract

Determining the leading sector is very important as a basis for policy making to improve the economy of a region. This research aims to identify leading sectors before and after the Covid-19 pandemic in South Sumatra using the Location Quotient (LQ), Dynamic Location Quotient (DLQ), Klassen Typology Analysis and Shift Share methods. This research groups districts/cities based on their GRDP contribution using K-Means Clustering. This research shows that the leading sectors before the pandemic were Mining; Water Supply, and Real Estate. During the pandemic, the contribution of agriculture actually increased from the previous year. So after the Covid-19 pandemic occurred, the Agriculture, Mining and Real Estate categories became the leading sectors. Grouping districts/cities produces three clusters. The cluster that has the lowest GRDP contribution is in cluster 1 with 14 members from 17 districts/cities in South Sumatra, the cluster that has the very highest GRDP contribution is in cluster 2 with 1 district/city and the rest with high GRDP contributions are in cluster 3 as many as 2 districts/cities. The agricultural category is the basic and prospective category for 64 percent of members in cluster 1. The government should prioritize increasing leading sectors, especially agriculture, to boost the economy in South Sumatra Province.
Co-Authors Dewi Krismawati I Nyoman Setiawan Lismiana Lismiana Setia Pramana Yuliana Ria Uli Sitanggang