Open AccessWATER CONSUMPTION PREDICTION USING FUZZY TIME SERIES - A CASE STUDY IN PRIVATE COMPANY OF TANGERANG DISTRICT INDONESIA
Author(s) -
Diah Septiyana
Publication year - 2020
Publication title -
j@ti undip
Language(s) - English
Resource type - Journals
eISSN - 2502-1516
pISSN - 1907-1434
DOI - 10.14710/jati.15.3.203-208
Subject(s) - series (stratigraphy) , time series , fuzzy logic , statistics , consumption (sociology) , population , volume (thermodynamics) , visibility , mean absolute percentage error , computer science , econometrics , mathematics , mean squared error , geography , artificial intelligence , meteorology , paleontology , social science , physics , demography , quantum mechanics , sociology , biology
Consumption of water in the Tangerang Regency continuously increases from year to year due to the increasing population and birth rates an average increase of 3% every year. So, the water demand prediction to be important to meet customer or community needs. The private water utility company needs to use a new method for predicting future monthly water consumption values and improves accuracy when forecasting time series using a visibility graph and presents to make more accurate predictions. In this study, we aim to measure the trend analysis volume of water consumption prediction by Fuzzy Time Series versus actual usage volume. Fuzzy Time Series (FTS) is a concept plan method that uses fuzzy logic that is able to provide predictions (estimates) of time series data analysis for the next several periods. Mean Absolute Percentage Error (MAPE) is obtained for different configurations of the input sets and of the FTS model structure. From the results of the average value error accuracy was only 4.5% using FTS Chen Method and included in the low category and water consumption actual versus prediction with the FTS Chen method shown related stable.