scholarly journals An Absolute Differences K-Means Clustering Approach on Determining Intervals to Optimize Fuzzy Time Series Markov Chain Model

2022 ◽  
Vol 15 (1) ◽  
Keyword(s):  
Time Series ◽  
Markov Chain ◽  
Markov Chain Model ◽  
Fuzzy Time Series ◽  
Chain Model ◽  
Clustering Approach

scholarly journals Disaster Forecasting Approach In Indonesia: A Fuzzy Time Series - Markov Chain Model

2019 ◽  
Author(s):  
Rahmad Syah
Keyword(s):  
Time Series ◽  
Markov Chain ◽  
Natural Disasters ◽  
Markov Chain Model ◽  
Volcanic Eruptions ◽  
Fuzzy Time Series ◽  
Chain Model ◽  
The Past ◽  
The Future ◽  
Transport Accidents

The concept of Fuzzy Time Series to predict things that will happen based on the data in the past, while Markov Chain assist in estimating the changes that may occur in the future. With methods are used to predict the incidence of natural disasters in the future. From the research that has been done, it appears the change, an increase of each disaster, like a tornado reaches 3%, floods reaches 16%, landslides reaches 7%, transport accidents reached 25% and volcanic eruptions as high as 50%.

scholarly journals A FUZZY TIME SERIES-MARKOV CHAIN MODEL TO FORECAST FISH FARMING PRODUCT

Kursor ◽  
2019 ◽  
Vol 9 (4) ◽  
Author(s):  
Bagus Dwi Saputra
Keyword(s):  
Time Series ◽  
Markov Chain ◽  
Time Series Data ◽  
Markov Chain Model ◽  
Fish Farming ◽  
Fuzzy Time Series ◽  
Series Data ◽  
Percentage Error ◽  
Chain Model ◽  
Price Fluctuations

Price is one of the important things that need to concern as defining factor of the profit or loss of product selling as the result of price fluctuations that are very difficult to control. Price fluctuations are caused by many factors including weather, stock availability, demand and others. One of the steps to solve the price fluctuations problem is by making a forecast of fish incoming prices. The purpose of this study is to apply Markov chain’s fuzzy time series to forecast farming fish prices. Markov chain fuzzy time series is one of the prediction methods to predict time series data that has advantages in the implentation of historical data, flexible, and high level of data forecasting accuracy. This study used fish prices at November 2018. The results showed that markov chain fuzzy time series showed very accurate forecasting results with a mean error percentage of absolute percentage error (MAPE) of 1.4% so the accuracy of the Markov chain fuzzy time series method is 98, 6%.

Higher order multivariate Markov chain model for fuzzy time series

2016 ◽  
Vol 19 (1) ◽  
pp. 21-35 ◽  
Author(s):  
S. Suresh ◽  
K. Senthamarai Kannan ◽  
P. Venkatesan
Keyword(s):  
Time Series ◽  
Markov Chain ◽  
Markov Chain Model ◽  
Higher Order ◽  
Fuzzy Time Series ◽  
Chain Model

scholarly journals IMPLEMENTASI FUZZY TIME SERIES MARKOV CHAIN MODEL (FTSMCM) DALAM PREDIKSI JUMLAH PRODUKSI AYAM POTONG

2017 ◽  
Vol 2 (2) ◽  
pp. 45-50
Author(s):  
Desy Ika Puspitasari ◽  
Mochammad Arif Afianto
Keyword(s):  
Time Series ◽  
Markov Chain ◽  
Markov Chain Model ◽  
Fuzzy Time Series ◽  
Chain Model

Pola konsumsi masyarakat akan produk hasil ternak semakin meningkat, tak terkecuali konsumsi ayam potong (broiler). Tingginya tingkat konsumsi masyarakat akan ayam potong otomatis akan memicu para produsen ternak untuk meningkatkan produksinya. Produksi ayam potong dapat diprediksi, salah satunya menggunakan Fuzzy Time Series. Perkembangan metode peramalan data time series yang cukup pesat mengakibatkan terdapat banyak pilihan metode yang dapat digunakan untuk meramalkan, salah satunya yaitu metode Fuzzy Time Series Markov Chain Model. Konsep Markov Chain digunakan dalam proses prediksi jumlah produksi ayam potong dengan menggunakan matriks transisi. Dengan Fuzzy Time Series Markov Chain Model, yang merupakan gabungan dari konsep metode fuzzy time series dengan model Markov, diharapkan dapat mendatangkan hasil analisis prediksi yang lebih akurat. Penelitian ini diharapkan dapat membantu proses analisis prediksi, sehingga proses analisis prediksi dapat dilakukan secara lebih efisien, teliti, mudah, dan praktis.

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