Fachri Putra Supriyandiari
Unknown Affiliation

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

PERAMALAN PRODUKSI PADI KABUPATEN KENDAL: PENDEKATAN FUZZY TIME SERIES CHENG Fachri Putra Supriyandiari; Wellie Sulistijanti
Agros Journal of Agriculture Science Vol 26, No 2 (2024): Edisi Juli
Publisher : Fakultas Pertanian, Universitas Janabadra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37159/jpa.v26i2.4654

Abstract

Central Java's rice production is in first place as the largest rice producer on the island of Java. One of the districts in Central Java that produces a lot of rice is Kendal District. Forecasting rice production is important to help agricultural planning and management. In this context, Cheng's fuzzy time series method can be an effective tool for forecasting rice production in Kendal Regency. Cheng's fuzzy time series method integrates the concept of fuzzy logic into time series analysis, which makes it possible to handle uncertainty and ambiguity in historical rice production data. This approach allows adaptive adjustment of the model to possible patterns in the data. In this research, rice production data from Kendal Regency used is from 2012 to 2023. The steps involved in this method include fuzzification, formation of a fuzzy relationship matrix, weighting, and defuzzification to obtain accurate forecasting results. It is hoped that the results of this research will produce useful data for stakeholders in agricultural planning in Kendal Regency. By having more accurate estimates of rice production, better decisions can be made regarding resource allocation, distribution and storage of rice and other agricultural policies. The results of testing using the fuzzy Cheng time series to predict Kendal Regency rice production from 2012 to 2023 produced an average MAPE value of 5.09% with a total of 5 intervals and the predicted results for Kendal Regency rice production in 2024 were 180,195.09 tons with accurate results. forecasting 94.91%, so the prediction is considered very good.Key-words: agriculture ;rice; forecasting.