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All Journal Journal of Social Science Journal of Social Science
Hasih Pratiwi
Faculty of Mathematics and Natural Sciences, Universitas Sebelas Maret, Central Java, Indonesia
Religion Humanities Chemistry Education Environmental Science Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Physics Social Sciences Other

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Indonesian Territory Clustering Based On Harvested Area and Rice Productivity Using Clustering Algorithm Imelda Putri Kurniawati; Hasih Pratiwi; Sugiyanto Sugiyanto
Journal of Social Science Vol. 4 No. 1 (2023): Journal of Social Science
Publisher : Syntax Corporation Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46799/jss.v4i1.510

Abstract

Rice (Latin: Oryza sativa) is one of the most important cultivated plants in civilization. This plant is the main commodity for almost all Indonesian people. Indonesia is in third place as the largest rice producing country in the world. However, based on data from the Statistics Indonesia, Indonesia will still import rice until 2022. The transfer of paddy fields is one of the reasons why Indonesia is still importing rice to this day. Many lands that used to be paddy fields have turned into airports, industrial land, housing, and so on. Rice production is one of the important topics to be discussed in order to develop rice production in areas that are still relatively low. The purpose of this research is to classify cities/regencies in Indonesia based on rice production data in 2021. In this study, three clustering methods were used, namely, Partitioning Around Medoid (PAM), Clustering Large Applications (CLARA) and Fuzzy C-Means (FCM). Then the three methods are compared based on their silhouette coefficient values. The best obtained method is FCM method with two clusters and a silhouette value of 0.828. Results clustering with the best method is used as a reference in making maps clustering. Areas that are still relatively low are expected to increase rice productivity.
Indonesian Territory Clustering Based On Harvested Area and Rice Productivity Using Clustering Algorithm Imelda Putri Kurniawati; Hasih Pratiwi; Sugiyanto Sugiyanto
Journal of Social Science Vol. 4 No. 1 (2023): Journal of Social Science
Publisher : Syntax Corporation Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (403.838 KB) | DOI: 10.46799/jss.v4i1.510

Abstract

Rice (Latin: Oryza sativa) is one of the most important cultivated plants in civilization. This plant is the main commodity for almost all Indonesian people. Indonesia is in third place as the largest rice producing country in the world. However, based on data from the Statistics Indonesia, Indonesia will still import rice until 2022. The transfer of paddy fields is one of the reasons why Indonesia is still importing rice to this day. Many lands that used to be paddy fields have turned into airports, industrial land, housing, and so on. Rice production is one of the important topics to be discussed in order to develop rice production in areas that are still relatively low. The purpose of this research is to classify cities/regencies in Indonesia based on rice production data in 2021. In this study, three clustering methods were used, namely, Partitioning Around Medoid (PAM), Clustering Large Applications (CLARA) and Fuzzy C-Means (FCM). Then the three methods are compared based on their silhouette coefficient values. The best obtained method is FCM method with two clusters and a silhouette value of 0.828. Results clustering with the best method is used as a reference in making maps clustering. Areas that are still relatively low are expected to increase rice productivity.
Co-Authors Imelda Putri Kurniawati Sugiyanto Sugiyanto