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IMPLEMENTASI METODE FUZZY TIME SERIES CHEN DAN MARKOV CHAIN DALAM MEMPREDIKSI HARGA DAGING AYAM DI KOTA PALEMBANG
Predicting chicken meat price is done to get over the problems of frequent and unpredictable chicken meat price changes. This study discusses the implementation of Fuzzy Time Series Chen and Fuzzy Time Series Markov Chain for predicting the price of chicken meat in Palembang city. Both methods of Fuzzy Time Series are used based on the difference in calculations. In calculating prediction, Fuzzy Time Series Chen is not affected by previous values while Fuzzy Time Series Markov Chain is affected by previous values. This study aims to find out the best method between Fuzzy Time Series Chen and Fuzzy Time Series Markov Chain in predicting the price of chicken meat. D1, D2, and a number of an interval are used as parameters for calculating prediction. The effects of using these parameters are on forming interval lengths, fuzzification, and prediction results. Based on the test results, the lowest MSE and MAPE for Fuzzy Time Series Chen are 7199707,14 and 6,67% by using parameters D1=5000, D2=350, and a number of an interval=14. The lowest MSE and MAPE Fuzzy Time Series Markov Chain are 2004422,3 and 3,45% by using parameters D1=400, D2=350, and a number of an interval =15.
Inventory Code | Barcode | Call Number | Location | Status |
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2307000138 | T86147 | T861472022 | Central Library (Referens) | Available but not for loan - Not for Loan |
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