{"title":"PREDIKSI HARGA PANGAN KOTA BANDUNG MENGGUNAKAN METODE GATED RECURRENT UNIT","authors":"Matthew Oni, Manatap Dolok Lauro, Teny Handhayani","doi":"10.24912/jiksi.v11i2.26014","DOIUrl":null,"url":null,"abstract":"Food problems often occur among the community, this occurs due to a lack of predictions made to determine future food prices. Food prices can be achieved if the government can provide sufficient food supplies both in terms of quality and quantity. The availability of sufficient food is an important factor in maintaining the health and welfare of the community. However, the high price fluctuations of staple foods in traditional markets have a negative impact on the availability and quality of food for the community, especially those with low incomes. This was caused by various factors such as rising raw material prices, the influence of weather factors, and changes in people's consumption patterns. In addition, the process of distribution and marketing of staple foods in traditional markets in Bandung City, which still relies on manual processes and is less structured, can also cause high price fluctuations. Therefore we need an application to predict staple food needs for the future accurately and effectively. This study uses the Gated Recurrent Unit method. This method is used because the Gated Recurrent Unit method has good performance in making predictions and fits the data used for this study. In this study, there were 5 types of commodities used, namely rice, chicken meat, chicken eggs, shallots, and garlic. All datasets used were taken from the website of the National Strategic Food Price Information (PIHPSNasional, https://www.bi.go.id/hargapangan). Predictive results by evaluating MAE and MAPE for rice 12.8, and 0.10, for chicken meat 12.8 , and 0.10, for chicken egg 244.5, and 0.64, for onion 296.9, and 1.05, for garlic 602.8, and 1.32.","PeriodicalId":34309,"journal":{"name":"Jurnal Sisfokom","volume":"6 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal Sisfokom","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24912/jiksi.v11i2.26014","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Food problems often occur among the community, this occurs due to a lack of predictions made to determine future food prices. Food prices can be achieved if the government can provide sufficient food supplies both in terms of quality and quantity. The availability of sufficient food is an important factor in maintaining the health and welfare of the community. However, the high price fluctuations of staple foods in traditional markets have a negative impact on the availability and quality of food for the community, especially those with low incomes. This was caused by various factors such as rising raw material prices, the influence of weather factors, and changes in people's consumption patterns. In addition, the process of distribution and marketing of staple foods in traditional markets in Bandung City, which still relies on manual processes and is less structured, can also cause high price fluctuations. Therefore we need an application to predict staple food needs for the future accurately and effectively. This study uses the Gated Recurrent Unit method. This method is used because the Gated Recurrent Unit method has good performance in making predictions and fits the data used for this study. In this study, there were 5 types of commodities used, namely rice, chicken meat, chicken eggs, shallots, and garlic. All datasets used were taken from the website of the National Strategic Food Price Information (PIHPSNasional, https://www.bi.go.id/hargapangan). Predictive results by evaluating MAE and MAPE for rice 12.8, and 0.10, for chicken meat 12.8 , and 0.10, for chicken egg 244.5, and 0.64, for onion 296.9, and 1.05, for garlic 602.8, and 1.32.