{"title":"数据挖掘在南苏拉威西省外国游客访问聚类中的应用使用 K-Means 和 SVM 对南苏拉威西省的外国游客进行聚类","authors":"Nero Caesar Gosari, Rismayani Rismayani","doi":"10.30591/jpit.v8i3.4554","DOIUrl":null,"url":null,"abstract":"Indonesia's exchange rate can rise due to foreign tourist visits, which can also benefit the local economy. The provincial capital. South Sulawesi is Makassar which is one of the locations for tourist visits. There are 11 main tourist attractions in Prov. South Sulawesi according to sulselprov 1) Maritime Tourism, 2) Losari Beach, 3) Rotterdam Fort, 4) Somba opu Fort, 5) Takabonerate Marine Park, 6) Bantimurung National Park, 7) Malino, 8) Tanjung Bira Beach, 9) Kesu Tourism, 10) Londa Tourism, 11) Pallawa Tourism. The purpose of this study is to analyze the application of data mining in classifying the number of foreign tourists visiting the prefecture. South Sulawesi uses k-means. The data used comes from BPS Prov. South Sulawesi. The data is grouped into two clusters. That is, the most tourists as C1 with results from Malaysia, and low tourist arrivals as C0 with results from Singapore, Japan, South Korea, Taiwan, China, India, the Philippines, Hong Kong, Thailand, Australia, USA, UK, Netherlands, Germany, France, Russia, Saudi Arabia, Egypt, United Arab Emirates, Pearl of the Persian Gulf, and Switzerland then I use and process this data again with SVM to look for precision, precision and recall values and get 100.00% accuracy in the RapidMiner application.","PeriodicalId":503683,"journal":{"name":"Jurnal Informatika: Jurnal Pengembangan IT","volume":"7 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Penerapan Data Mining Dalam Mengelompokkan Kunjungan Wisatawan Mancanegara Di Prov. Sulawesi Selatan Dengan K-Means Dan SVM\",\"authors\":\"Nero Caesar Gosari, Rismayani Rismayani\",\"doi\":\"10.30591/jpit.v8i3.4554\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Indonesia's exchange rate can rise due to foreign tourist visits, which can also benefit the local economy. The provincial capital. South Sulawesi is Makassar which is one of the locations for tourist visits. There are 11 main tourist attractions in Prov. South Sulawesi according to sulselprov 1) Maritime Tourism, 2) Losari Beach, 3) Rotterdam Fort, 4) Somba opu Fort, 5) Takabonerate Marine Park, 6) Bantimurung National Park, 7) Malino, 8) Tanjung Bira Beach, 9) Kesu Tourism, 10) Londa Tourism, 11) Pallawa Tourism. The purpose of this study is to analyze the application of data mining in classifying the number of foreign tourists visiting the prefecture. South Sulawesi uses k-means. The data used comes from BPS Prov. South Sulawesi. The data is grouped into two clusters. That is, the most tourists as C1 with results from Malaysia, and low tourist arrivals as C0 with results from Singapore, Japan, South Korea, Taiwan, China, India, the Philippines, Hong Kong, Thailand, Australia, USA, UK, Netherlands, Germany, France, Russia, Saudi Arabia, Egypt, United Arab Emirates, Pearl of the Persian Gulf, and Switzerland then I use and process this data again with SVM to look for precision, precision and recall values and get 100.00% accuracy in the RapidMiner application.\",\"PeriodicalId\":503683,\"journal\":{\"name\":\"Jurnal Informatika: Jurnal Pengembangan IT\",\"volume\":\"7 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-09-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Jurnal Informatika: Jurnal Pengembangan IT\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.30591/jpit.v8i3.4554\",\"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 Informatika: Jurnal Pengembangan IT","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30591/jpit.v8i3.4554","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Penerapan Data Mining Dalam Mengelompokkan Kunjungan Wisatawan Mancanegara Di Prov. Sulawesi Selatan Dengan K-Means Dan SVM
Indonesia's exchange rate can rise due to foreign tourist visits, which can also benefit the local economy. The provincial capital. South Sulawesi is Makassar which is one of the locations for tourist visits. There are 11 main tourist attractions in Prov. South Sulawesi according to sulselprov 1) Maritime Tourism, 2) Losari Beach, 3) Rotterdam Fort, 4) Somba opu Fort, 5) Takabonerate Marine Park, 6) Bantimurung National Park, 7) Malino, 8) Tanjung Bira Beach, 9) Kesu Tourism, 10) Londa Tourism, 11) Pallawa Tourism. The purpose of this study is to analyze the application of data mining in classifying the number of foreign tourists visiting the prefecture. South Sulawesi uses k-means. The data used comes from BPS Prov. South Sulawesi. The data is grouped into two clusters. That is, the most tourists as C1 with results from Malaysia, and low tourist arrivals as C0 with results from Singapore, Japan, South Korea, Taiwan, China, India, the Philippines, Hong Kong, Thailand, Australia, USA, UK, Netherlands, Germany, France, Russia, Saudi Arabia, Egypt, United Arab Emirates, Pearl of the Persian Gulf, and Switzerland then I use and process this data again with SVM to look for precision, precision and recall values and get 100.00% accuracy in the RapidMiner application.