PERBANDINGAN AKURASI PREDIKSI HARGA DAGING MENGGUNAKAN FUZZY TIME SERIES MODEL CHENG DAN MARKOV CHAIN

Abstract

Meat is an important food to supplies vitamin, protein, and carbohydrate for our body and that’s why the meat price should be maintained to stable. Fuzzy time series (FTS )is a method known as soft computing that can be used for prediction, many researches has been developed this method and to compare the accuracy metode of Fuzzy time series, in this case Fuzzy time series Cheng and Markov Chain method will be used and will be compared with Mean Absolute Percentage Error (MAPE) based on meat price data 2016 in Tanjungpinang City. Fuzzy time series Cheng method predicted that fresh beef has a 1,22% of MAPE value and fuzzy time series Markov Chain's Method result show 1,03% of MAPE value, The results show that Markov Chain fuzzy time series has the best Acuraccy for prediction.