COMPARISION OF RICE PRICE PREDICTION RESULTS IN EAST JAVA USING FOURIER SERIES ESTIMATOR AND GAUSSIAN KERNEL ESTIMATOR SIMULTANEOUSLY

Extreme weather changes and the El Nino phenomenon in 2023 will cause drought, resulting in a decrease in rice production and an increase in rice prices. It has significantly impacted East Java Province as it is the most extensive rice supplier in Indonesia. This study aims to predict the price of...

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Main Authors: Adnan Syawal Adilaha Sadikin, Aqil Azmi Reswara, M. Fariz Fadillah Mardianto, Ardi Kurniawan
Format: Article
Language:English
Published: Universitas Pattimura 2024-07-01
Series:Barekeng
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Online Access:https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/12712
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author Adnan Syawal Adilaha Sadikin
Aqil Azmi Reswara
M. Fariz Fadillah Mardianto
Ardi Kurniawan
author_facet Adnan Syawal Adilaha Sadikin
Aqil Azmi Reswara
M. Fariz Fadillah Mardianto
Ardi Kurniawan
author_sort Adnan Syawal Adilaha Sadikin
collection DOAJ
description Extreme weather changes and the El Nino phenomenon in 2023 will cause drought, resulting in a decrease in rice production and an increase in rice prices. It has significantly impacted East Java Province as it is the most extensive rice supplier in Indonesia. This study aims to predict the price of rice with six different qualities using the Fourier series estimator and Gaussian kernel function simultaneously. The results show that the Gaussian kernel method, with a bandwidth value of 1, produces a better model with a MAPE value of 0.228259% than the sine function Fourier series method in predicting rice prices based on six different qualities. The prediction results using the Gaussian kernel function method are categorized as highly accurate because they are less than 10%. This research accelerates the realization of SDG 2 related to "Zero Hunger" through government policies to control the high price of rice in Indonesia. Recommendations that can be given through the research results include cooperation with the government, which can help access information and resources needed to manage price risks.
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issn 1978-7227
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language English
publishDate 2024-07-01
publisher Universitas Pattimura
record_format Article
series Barekeng
spelling doaj-art-e780d2b77a3d4933a89c02cdc2b1fabc2025-08-20T01:47:54ZengUniversitas PattimuraBarekeng1978-72272615-30172024-07-011831963197410.30598/barekengvol18iss3pp1963-197412712COMPARISION OF RICE PRICE PREDICTION RESULTS IN EAST JAVA USING FOURIER SERIES ESTIMATOR AND GAUSSIAN KERNEL ESTIMATOR SIMULTANEOUSLYAdnan Syawal Adilaha Sadikin0Aqil Azmi Reswara1M. Fariz Fadillah Mardianto2Ardi Kurniawan3Statistics Study Program: Department of Mathematics, Faculty Sains & Technology, Universitas Airlangga, IndonesiaStatistics Study Program: Department of Mathematics, Faculty Sains & Technology, Universitas Airlangga, IndonesiaStatistics Study Program: Department of Mathematics, Faculty Sains & Technology, Universitas Airlangga, IndonesiaStatistics Study Program: Department of Mathematics, Faculty Sains & Technology, Universitas Airlangga, IndonesiaExtreme weather changes and the El Nino phenomenon in 2023 will cause drought, resulting in a decrease in rice production and an increase in rice prices. It has significantly impacted East Java Province as it is the most extensive rice supplier in Indonesia. This study aims to predict the price of rice with six different qualities using the Fourier series estimator and Gaussian kernel function simultaneously. The results show that the Gaussian kernel method, with a bandwidth value of 1, produces a better model with a MAPE value of 0.228259% than the sine function Fourier series method in predicting rice prices based on six different qualities. The prediction results using the Gaussian kernel function method are categorized as highly accurate because they are less than 10%. This research accelerates the realization of SDG 2 related to "Zero Hunger" through government policies to control the high price of rice in Indonesia. Recommendations that can be given through the research results include cooperation with the government, which can help access information and resources needed to manage price risks.https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/12712fourier seriesrice pricekernel gaussianmapezero hunger
spellingShingle Adnan Syawal Adilaha Sadikin
Aqil Azmi Reswara
M. Fariz Fadillah Mardianto
Ardi Kurniawan
COMPARISION OF RICE PRICE PREDICTION RESULTS IN EAST JAVA USING FOURIER SERIES ESTIMATOR AND GAUSSIAN KERNEL ESTIMATOR SIMULTANEOUSLY
Barekeng
fourier series
rice price
kernel gaussian
mape
zero hunger
title COMPARISION OF RICE PRICE PREDICTION RESULTS IN EAST JAVA USING FOURIER SERIES ESTIMATOR AND GAUSSIAN KERNEL ESTIMATOR SIMULTANEOUSLY
title_full COMPARISION OF RICE PRICE PREDICTION RESULTS IN EAST JAVA USING FOURIER SERIES ESTIMATOR AND GAUSSIAN KERNEL ESTIMATOR SIMULTANEOUSLY
title_fullStr COMPARISION OF RICE PRICE PREDICTION RESULTS IN EAST JAVA USING FOURIER SERIES ESTIMATOR AND GAUSSIAN KERNEL ESTIMATOR SIMULTANEOUSLY
title_full_unstemmed COMPARISION OF RICE PRICE PREDICTION RESULTS IN EAST JAVA USING FOURIER SERIES ESTIMATOR AND GAUSSIAN KERNEL ESTIMATOR SIMULTANEOUSLY
title_short COMPARISION OF RICE PRICE PREDICTION RESULTS IN EAST JAVA USING FOURIER SERIES ESTIMATOR AND GAUSSIAN KERNEL ESTIMATOR SIMULTANEOUSLY
title_sort comparision of rice price prediction results in east java using fourier series estimator and gaussian kernel estimator simultaneously
topic fourier series
rice price
kernel gaussian
mape
zero hunger
url https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/12712
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