{"title":"PREDIKSI HARGA CABAI MERAH MENGGUNAKAN SUPPORT VECTOR REGRESSION","authors":"Domi Sepri, Ahmad Fauzi","doi":"10.33884/cbis.v8i2.1921","DOIUrl":null,"url":null,"abstract":"The aim of the research is to make a model to predict the national price of the red chili pepper using Support Vector Regression (SVR). Data used to make model are the price of red chili from January 2017 to December 2019. For finding the best parameter of the hyperplane, the research uses Grid Search Algorithm. The best parameter of the hyperplane is C=1000, epsilon=5, and Gamma =1 . The result shows the MAPE for data training is 4.07% and the MAPE for data testing is 9.11%.","PeriodicalId":413767,"journal":{"name":"Computer Based Information System Journal","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Based Information System Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33884/cbis.v8i2.1921","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
PREDIKSI HARGA CABAI MERAH MENGGUNAKAN SUPPORT VECTOR REGRESSION
The aim of the research is to make a model to predict the national price of the red chili pepper using Support Vector Regression (SVR). Data used to make model are the price of red chili from January 2017 to December 2019. For finding the best parameter of the hyperplane, the research uses Grid Search Algorithm. The best parameter of the hyperplane is C=1000, epsilon=5, and Gamma =1 . The result shows the MAPE for data training is 4.07% and the MAPE for data testing is 9.11%.
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