Prediksi Pertumbuhan Jumlah Penduduk Kota Malang menggunakan Metode Average-based Fuzzy Time Series - Pricielya Alviyonita; Muhammad Tanzil Furqon; Marji Marji (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2020)
The population growth in Indonesia continues to increase every year, making Indonesia as the 4th country with the largest population in the world. High population growth will greatly affect several aspects, such as the economy, the quality of people's lives, health and development planning. Prediction of population growth is needed to anticipate the negative affects of population growth which is expected to assist the government in making future urban planning plans. The Population and Civil Registry Office also needs these predictions to make a draft budget of needs such as e-KTP blanks, birth certificates, and others. Average-based fuzzy time series is one method of forecasting the results of the development of fuzzy time series. The fuzzy time series method based on average is able to determine the length of the effective interval so that it can produce predictions with a low error rate. By using time series data, the population of Malang City per month with a total of 123 data, this study implements the average-based fuzzy times series method to predict population growth. Based on testing in this study it can be concluded that the amount of training data has an influence on the value of MAPE produced, but the use of training data that is increasingly not always in line with the lower error value and the lowest Mean Absolute Percentage Error (MAPE) value of 0.02810%.