FORECASTING RICE PRICES IN TRADITIONAL MARKETS IN BANYUMAS REGENCY USING FUZZY TIME SERIES CHEN
Indonesia is one of those countries where a majority of its population earns a living through agriculture. One of Indonesia's largest commodities is rice. Rice prices are a significant indicator in the economy, especially in agrarian areas like Banyumas Regency. Fluctuating rice prices can impa...
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Universitas Pattimura
2025-01-01
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| Online Access: | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/14570 |
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| author | Dian Kartika Sari Aminatus Sa'adah |
| author_facet | Dian Kartika Sari Aminatus Sa'adah |
| author_sort | Dian Kartika Sari |
| collection | DOAJ |
| description | Indonesia is one of those countries where a majority of its population earns a living through agriculture. One of Indonesia's largest commodities is rice. Rice prices are a significant indicator in the economy, especially in agrarian areas like Banyumas Regency. Fluctuating rice prices can impact the economic livelihoods of both farmers and consumers in the region. The rapid fluctuations in rice prices and the uncertainty in the future necessitate the need for rice price forecasting. This study employs fuzzy time series to forecast rice prices. The fuzzy time series model used is the Chen model, and the accuracy of the predictions will be evaluated using the MAPE value. Based on the forecasting results using the fuzzy time series method with the Chen model, the predicted rice price for May 2024 is Rp 14,082. Furthermore, the accuracy level of the rice price forecasting using the fuzzy time series method with the Chen model shows highly accurate predictions, with an error based on the MAPE value of 0.957539%. The limitations of this study lie in the use of limited historical data and the assumption that price patterns will follow similar trends in the future. The contribution of this study is the application of the fuzzy time series method to rice commodities in Indonesia, which demonstrates high accuracy in conditions of high price fluctuation, thus providing valuable insights for policymakers and market participants in economic planning within the agricultural sector. |
| format | Article |
| id | doaj-art-7a7d06c6dd2240c389e9421f4e445d99 |
| institution | Kabale University |
| issn | 1978-7227 2615-3017 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Universitas Pattimura |
| record_format | Article |
| series | Barekeng |
| spelling | doaj-art-7a7d06c6dd2240c389e9421f4e445d992025-08-20T03:37:34ZengUniversitas PattimuraBarekeng1978-72272615-30172025-01-0119150351010.30598/barekengvol19iss1pp503-51014570FORECASTING RICE PRICES IN TRADITIONAL MARKETS IN BANYUMAS REGENCY USING FUZZY TIME SERIES CHENDian Kartika Sari0Aminatus Sa'adah1Data Science Department, Faculty of Informatics, Telkom University, IndonesiaInformatics Engineering Department, Faculty of Informatics, Telkom University, IndonesiaIndonesia is one of those countries where a majority of its population earns a living through agriculture. One of Indonesia's largest commodities is rice. Rice prices are a significant indicator in the economy, especially in agrarian areas like Banyumas Regency. Fluctuating rice prices can impact the economic livelihoods of both farmers and consumers in the region. The rapid fluctuations in rice prices and the uncertainty in the future necessitate the need for rice price forecasting. This study employs fuzzy time series to forecast rice prices. The fuzzy time series model used is the Chen model, and the accuracy of the predictions will be evaluated using the MAPE value. Based on the forecasting results using the fuzzy time series method with the Chen model, the predicted rice price for May 2024 is Rp 14,082. Furthermore, the accuracy level of the rice price forecasting using the fuzzy time series method with the Chen model shows highly accurate predictions, with an error based on the MAPE value of 0.957539%. The limitations of this study lie in the use of limited historical data and the assumption that price patterns will follow similar trends in the future. The contribution of this study is the application of the fuzzy time series method to rice commodities in Indonesia, which demonstrates high accuracy in conditions of high price fluctuation, thus providing valuable insights for policymakers and market participants in economic planning within the agricultural sector.https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/14570forecastingfuzzy time series chenrice prices |
| spellingShingle | Dian Kartika Sari Aminatus Sa'adah FORECASTING RICE PRICES IN TRADITIONAL MARKETS IN BANYUMAS REGENCY USING FUZZY TIME SERIES CHEN Barekeng forecasting fuzzy time series chen rice prices |
| title | FORECASTING RICE PRICES IN TRADITIONAL MARKETS IN BANYUMAS REGENCY USING FUZZY TIME SERIES CHEN |
| title_full | FORECASTING RICE PRICES IN TRADITIONAL MARKETS IN BANYUMAS REGENCY USING FUZZY TIME SERIES CHEN |
| title_fullStr | FORECASTING RICE PRICES IN TRADITIONAL MARKETS IN BANYUMAS REGENCY USING FUZZY TIME SERIES CHEN |
| title_full_unstemmed | FORECASTING RICE PRICES IN TRADITIONAL MARKETS IN BANYUMAS REGENCY USING FUZZY TIME SERIES CHEN |
| title_short | FORECASTING RICE PRICES IN TRADITIONAL MARKETS IN BANYUMAS REGENCY USING FUZZY TIME SERIES CHEN |
| title_sort | forecasting rice prices in traditional markets in banyumas regency using fuzzy time series chen |
| topic | forecasting fuzzy time series chen rice prices |
| url | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/14570 |
| work_keys_str_mv | AT diankartikasari forecastingricepricesintraditionalmarketsinbanyumasregencyusingfuzzytimeserieschen AT aminatussaadah forecastingricepricesintraditionalmarketsinbanyumasregencyusingfuzzytimeserieschen |