Markov average-based weighted fuzzy time series model to predict PT Kimia farma Tbk stock price - Azzahra, Rediva; Firdaniza, Firdaniza; Gusriani, Nurul (Universitas Islam Negeri Raden Intan Lampung, 2021)
The COVID-19 pandemic impacted various activities in Indonesia, including the stock market. Despite the declining economic condition, people are increasingly interested in investing. Among other companies available on the Indonesia Stock Exchange, companies in the health sector have a particular appeal to potential investors, one of which is pharmaceutical companies. This research used a Markov Average-Based Weighted Fuzzy Time Series model applied to PT Kimia Farma Tbk stock price data. This model develops the previous Markov chain–Fuzzy Time Series model, which has not calculated the weights for recurring events and used the Sturgess rule to determine the interval length. In this research, each recurring event has given a different weight that provides different probability values for transitions from one state to another. The Average-Based method is used to determine the interval length that can reflect the fluctuation of the data used. The stock price prediction of PT Kimia Farma Tbk using this model is categorized as very accurate with a MAPE of 2.632%.