Erwin Dwika Putra, M. H. Rifqo, Dwita Deslianti, Krismiyani Krismiyani
{"title":"基于k -均值方法的主题聚类算法分析","authors":"Erwin Dwika Putra, M. H. Rifqo, Dwita Deslianti, Krismiyani Krismiyani","doi":"10.53697/jkomitek.v2i2.884","DOIUrl":null,"url":null,"abstract":"The title of this research is the analysis of the thesis theme clustering algorithm using the k-means method. The main problem is how we can find out which theme is most in demand by thesis students at the Faculty of Engineering, University of Muhammadiyah Bengkulu. This clustering uses the K-means method. The K-Means method was chosen because this method is one of the non-hierarchical data clustering methods that seeks to partition data into two or more clusters with the same characteristics included in the same cluster. The purpose of this research is to help prospective students who will write their thesis in knowing which themes are more interested in them.","PeriodicalId":371693,"journal":{"name":"Jurnal Komputer, Informasi dan Teknologi (JKOMITEK)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Analysis of The Theme Clustering Algorithm Using K-Means Method\",\"authors\":\"Erwin Dwika Putra, M. H. Rifqo, Dwita Deslianti, Krismiyani Krismiyani\",\"doi\":\"10.53697/jkomitek.v2i2.884\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The title of this research is the analysis of the thesis theme clustering algorithm using the k-means method. The main problem is how we can find out which theme is most in demand by thesis students at the Faculty of Engineering, University of Muhammadiyah Bengkulu. This clustering uses the K-means method. The K-Means method was chosen because this method is one of the non-hierarchical data clustering methods that seeks to partition data into two or more clusters with the same characteristics included in the same cluster. The purpose of this research is to help prospective students who will write their thesis in knowing which themes are more interested in them.\",\"PeriodicalId\":371693,\"journal\":{\"name\":\"Jurnal Komputer, Informasi dan Teknologi (JKOMITEK)\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Jurnal Komputer, Informasi dan Teknologi (JKOMITEK)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.53697/jkomitek.v2i2.884\",\"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 Komputer, Informasi dan Teknologi (JKOMITEK)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.53697/jkomitek.v2i2.884","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analysis of The Theme Clustering Algorithm Using K-Means Method
The title of this research is the analysis of the thesis theme clustering algorithm using the k-means method. The main problem is how we can find out which theme is most in demand by thesis students at the Faculty of Engineering, University of Muhammadiyah Bengkulu. This clustering uses the K-means method. The K-Means method was chosen because this method is one of the non-hierarchical data clustering methods that seeks to partition data into two or more clusters with the same characteristics included in the same cluster. The purpose of this research is to help prospective students who will write their thesis in knowing which themes are more interested in them.