Fuzzy Time Series Saxena Easo on Forecasting the Number of Dengue Hemorrhagic Fever Cases in Bengkulu Province - Damayanti, Septri; Yosmar, Siska; Hidayati, Nurul; Widayati, Ratna; Warrahma, Bunga Aulya (Jurnal Matematika, Statistika dan Komputasi, 2025)
Dengue Hemorrhagic Fever (DHF) is a viral infectious disease that is transmitted through mosquitoes and is a public health problem in the world. Untreated Dengue Hemorrhagic Fever (DHF) can trigger extraordinary events (KLB), severe dengue and even cause death. Tropical countries like Indonesia cause cases of Dengue Hemorrhagic Fever (DHF) to be found in almost all provinces. This disease is endemic, especially in Bengkulu Province. The increase and decrease in the number of cases can also be seen using forecasting methods. The time series forecasting method used in this research is the Saxena-Easo fuzzy time series. Where this method is a modification and refinement of the previous method, namely the Stevenson & Porter fuzzy time series method. The Stevenson & Porter method changes the actual data into percentage change which was then developed by Saxena Easo with modifications to the number of data intervals. The data developed by Saxena Easo is dividing the number of intervals into sub-intervals based on the number of frequencies. This research aims to predict the number of Dengue Hemorrhagic Fever cases in Bengkulu Province from the 1st week of 2022 to the 24th week of 2024, and compare it with existing data on the number of cases. Based on the research, the results of the accuracy level of the Mean Absolute Percentage Error (MAPE) in forecasting the number of cases of Dengue Hemorrhagic Fever in Bengkulu Province using the FTS Saxena Easo method obtained a value of 0.359637893 or 3.5%, so the forecast accuracy value obtained is included in the criteria for very good forecasting, because it has an accuracy value below 10%. It can be said that the comparison between actual data and forecasts is not much different.