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Gusthvi, Wickly
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Humanities Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media

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Performance of K-Means and DBSCAN Algorithm in Clustering Gross Regional Domestic Product Wororomi, Jonathan K.; Allo, Caecilia Bintang Girik; Paranoan, Nicea Roona; Gusthvi, Wickly
Journal of International Conference Proceedings Vol 6, No 5 (2023): 2023 UICEB Papua Proceeding
Publisher : AIBPM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32535/jicp.v6i5.2710

Abstract

Gross Regional Domestic Product (GRDP) is one of important indicator to determine the economic conditions of a region. GRDP are obtained from sum of value added produced by all unit of production in a region. This study use GRDP by production approach that grouped into seventeen categories of Industry. The government always put the big efforts to increase the economic growth after Covid-19 pandemic. According publication of BPS - Statistics Indonesian, in the year of 2021 and 2022 it’s growth between 3.70% and 5.31%. The aim of these study are determined the cluster GDRB based on province in Indonesia at current prices and analyses the performance of the cluster method. The results showed that by using the DBSCAN, two clusters were formed and one province can be detected as an outlier. On the other hands, performance of the method by K-Means showed two clusters. The silhouette value using K-Means is higher than the DBSCAN. For these case, the performance of K-Means is more appropriate than DBSCAN to use in clustering province in Indonesia based on GRDP at Current Market Prices. Moreover, performance of DBSCAN shows more sensitive on outliers detection.
Performance of K-Means and DBSCAN Algorithm in Clustering Gross Regional Domestic Product Wororomi, Jonathan K.; Allo, Caecilia Bintang Girik; Paranoan, Nicea Roona; Gusthvi, Wickly
Journal of International Conference Proceedings Vol 6, No 5 (2023): 2023 UICEB Papua Proceeding
Publisher : AIBPM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32535/jicp.v6i5.2710

Abstract

Gross Regional Domestic Product (GRDP) is one of important indicator to determine the economic conditions of a region. GRDP are obtained from sum of value added produced by all unit of production in a region. This study use GRDP by production approach that grouped into seventeen categories of Industry. The government always put the big efforts to increase the economic growth after Covid-19 pandemic. According publication of BPS - Statistics Indonesian, in the year of 2021 and 2022 it’s growth between 3.70% and 5.31%. The aim of these study are determined the cluster GDRB based on province in Indonesia at current prices and analyses the performance of the cluster method. The results showed that by using the DBSCAN, two clusters were formed and one province can be detected as an outlier. On the other hands, performance of the method by K-Means showed two clusters. The silhouette value using K-Means is higher than the DBSCAN. For these case, the performance of K-Means is more appropriate than DBSCAN to use in clustering province in Indonesia based on GRDP at Current Market Prices. Moreover, performance of DBSCAN shows more sensitive on outliers detection.
Co-Authors Allo, Caecilia Bintang Girik Caecilia Bintang Girik Allo Jonathan k. Wororomi Paranoan, Nicea Roona