Sagita Charolina Sihombing, Dina Agnesia Sihombing
{"title":"苏门答腊岛北部社会福利水平的K-均值聚类分析","authors":"Sagita Charolina Sihombing, Dina Agnesia Sihombing","doi":"10.24198/jmi.v17.n2.35025.127-135","DOIUrl":null,"url":null,"abstract":"Grouping the level of community welfare in North Sumatra Province needs to be done to make it easier for the government to focus on development in cities / districts whose welfare levels are still low. In this study, the level of welfare of the people of North Sumatra was grouped based on several variables. The grouping is done using the K-means clustering method. K-means clustering is one of the clustering methods used to classify large amounts of data. This method produces groups of data based on the number of groups desired. In this study, to determine the best number of groups, the Elbow method was used. The first step in this study was to divide the data into groups of data for the number of groups (k) starting from k = 2 to k = 8. Next, calculate the SSE (Sum of Square Error) from cluster k = 2 to k = 8. After that, create an Elbow graph from the resulting SSE values to determine the most optimal amount of k. Data processing to obtain groups based on the number of clusters (k) was carried out using Matlab 2013b software. Group data from the software is stored in Ms.excel. Meanwhile, the resulting Elbow graphic display is created in the Matlab GUI. From the resulting elbow graph, it can be seen that the SSE value has decreased drastically when k = 2 to k = 5, while from k = 5 to k = 8, the decrease in the graph is not significant. From this we know that the optimal number of clusters is k = 5. So, from the elbow graph, the results show that the North Sumatran people are optimally grouped into five clusters. Cluster 1 is only filled by the city of Medan, cluster 2 consists of North Tapanuli Regency, Toba Regency, Simalungun Regency, Dairi Regency, Karo Regency, Langkat Regency, Humbang Hasundutan Regency, West Pakpak Regency, Samosir Regency, Serdang Bedagai Regency, Padangsidimpuan City, Kota Gunungsitoli, cluster 3 consists of Deli Serdang Regency, Pematangsiantar City, Tebingtinggi City, Binjai City, cluster 4 consists of Labuhanbatu Regency, Asahan Regency, Batu Bara Regency, South Labuhanbatu Regency, North Labuhanbatu Regency, Sibolga City, Tanjungbalai City, and cluster 5 consisting of Nias Regency, Mandailing Natal Regency, South Tapanuli Regency, Central Tapanuli Regency, South Nias Regency, North Padang Lawas Regency, Padang Lawas Regency, North Nias Regency, West Nias Regency.","PeriodicalId":53096,"journal":{"name":"Jurnal Matematika Integratif","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Pengelompokan Tingkat Kesejahteraan Masyarakat di Sumatera Utara dengan Metode K-Means Clustering\",\"authors\":\"Sagita Charolina Sihombing, Dina Agnesia Sihombing\",\"doi\":\"10.24198/jmi.v17.n2.35025.127-135\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Grouping the level of community welfare in North Sumatra Province needs to be done to make it easier for the government to focus on development in cities / districts whose welfare levels are still low. In this study, the level of welfare of the people of North Sumatra was grouped based on several variables. The grouping is done using the K-means clustering method. K-means clustering is one of the clustering methods used to classify large amounts of data. This method produces groups of data based on the number of groups desired. In this study, to determine the best number of groups, the Elbow method was used. The first step in this study was to divide the data into groups of data for the number of groups (k) starting from k = 2 to k = 8. Next, calculate the SSE (Sum of Square Error) from cluster k = 2 to k = 8. After that, create an Elbow graph from the resulting SSE values to determine the most optimal amount of k. Data processing to obtain groups based on the number of clusters (k) was carried out using Matlab 2013b software. Group data from the software is stored in Ms.excel. Meanwhile, the resulting Elbow graphic display is created in the Matlab GUI. From the resulting elbow graph, it can be seen that the SSE value has decreased drastically when k = 2 to k = 5, while from k = 5 to k = 8, the decrease in the graph is not significant. From this we know that the optimal number of clusters is k = 5. So, from the elbow graph, the results show that the North Sumatran people are optimally grouped into five clusters. Cluster 1 is only filled by the city of Medan, cluster 2 consists of North Tapanuli Regency, Toba Regency, Simalungun Regency, Dairi Regency, Karo Regency, Langkat Regency, Humbang Hasundutan Regency, West Pakpak Regency, Samosir Regency, Serdang Bedagai Regency, Padangsidimpuan City, Kota Gunungsitoli, cluster 3 consists of Deli Serdang Regency, Pematangsiantar City, Tebingtinggi City, Binjai City, cluster 4 consists of Labuhanbatu Regency, Asahan Regency, Batu Bara Regency, South Labuhanbatu Regency, North Labuhanbatu Regency, Sibolga City, Tanjungbalai City, and cluster 5 consisting of Nias Regency, Mandailing Natal Regency, South Tapanuli Regency, Central Tapanuli Regency, South Nias Regency, North Padang Lawas Regency, Padang Lawas Regency, North Nias Regency, West Nias Regency.\",\"PeriodicalId\":53096,\"journal\":{\"name\":\"Jurnal Matematika Integratif\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-01-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Jurnal Matematika Integratif\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.24198/jmi.v17.n2.35025.127-135\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal Matematika Integratif","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24198/jmi.v17.n2.35025.127-135","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Pengelompokan Tingkat Kesejahteraan Masyarakat di Sumatera Utara dengan Metode K-Means Clustering
Grouping the level of community welfare in North Sumatra Province needs to be done to make it easier for the government to focus on development in cities / districts whose welfare levels are still low. In this study, the level of welfare of the people of North Sumatra was grouped based on several variables. The grouping is done using the K-means clustering method. K-means clustering is one of the clustering methods used to classify large amounts of data. This method produces groups of data based on the number of groups desired. In this study, to determine the best number of groups, the Elbow method was used. The first step in this study was to divide the data into groups of data for the number of groups (k) starting from k = 2 to k = 8. Next, calculate the SSE (Sum of Square Error) from cluster k = 2 to k = 8. After that, create an Elbow graph from the resulting SSE values to determine the most optimal amount of k. Data processing to obtain groups based on the number of clusters (k) was carried out using Matlab 2013b software. Group data from the software is stored in Ms.excel. Meanwhile, the resulting Elbow graphic display is created in the Matlab GUI. From the resulting elbow graph, it can be seen that the SSE value has decreased drastically when k = 2 to k = 5, while from k = 5 to k = 8, the decrease in the graph is not significant. From this we know that the optimal number of clusters is k = 5. So, from the elbow graph, the results show that the North Sumatran people are optimally grouped into five clusters. Cluster 1 is only filled by the city of Medan, cluster 2 consists of North Tapanuli Regency, Toba Regency, Simalungun Regency, Dairi Regency, Karo Regency, Langkat Regency, Humbang Hasundutan Regency, West Pakpak Regency, Samosir Regency, Serdang Bedagai Regency, Padangsidimpuan City, Kota Gunungsitoli, cluster 3 consists of Deli Serdang Regency, Pematangsiantar City, Tebingtinggi City, Binjai City, cluster 4 consists of Labuhanbatu Regency, Asahan Regency, Batu Bara Regency, South Labuhanbatu Regency, North Labuhanbatu Regency, Sibolga City, Tanjungbalai City, and cluster 5 consisting of Nias Regency, Mandailing Natal Regency, South Tapanuli Regency, Central Tapanuli Regency, South Nias Regency, North Padang Lawas Regency, Padang Lawas Regency, North Nias Regency, West Nias Regency.