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All Journal Journal of Data Science and Software Engineering
Yenni Rahman
FMIPA ULM
Computer Science & IT

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ANALISIS PERBANDINGAN METODE FUZZY TIME SERIES DAN FUZZY TIME SERIES CHENG PADA PREDIKSI TANAMAN JAGUNG Yenni Rahman; M. Reza Faisal; Dwi Kartini; Andi farmadi; Friska Abadi
Journal of Data Science and Software Engineering Vol 2 No 01 (2021)
Publisher : Fakultas MIPA Universitas Lambung Mangkurat

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Abstract

Domestic maize production for several years has not been able to meet the needs on a national scale. Many aspects affect this. This problem can be overcome by increasing production. One of the efforts to increase production is to predict future annual maize production using time series data. The time series data in question is data on corn production taken from the Ministry's Website. In this study, there are two prediction methods used to determine the annual maize yield for the coming year. Fuzzy Time Series and Fuzzy Time Series Cheng methods are the best prediction methods to be used in time series data where there are different stages between the two methods at the time of the formation of FLRG. In addition, researchers also used MAPE to compare the results of the accuracy of predicting corn production against the two methods. The corn production data used during 1970-2019 were 48 data. From the results of the tests carried out, the prediction results using the fuzzy time series method have a higher level of accuracy with the results of the corn accuracy value is 95.12% with a MAPE of 4.88% compared to the Fuzzy Time Series Cheng method with a result of 91,37%. with a MAPE of 8,63%.
Co-Authors Andi Farmadi Dwi Kartini Friska Abadi Muhammad Reza Faisal, Muhammad Reza