Analisis Time Series ARIMA untuk Memprediksi Jumlah Peserta KB Baru Pasca Persalinan di Jawa Timur - Rohyatul Fadhila Diningestu; Mahmudah Mahmudah (Media Gizi Kesmas, 2024)
Background: Time series forecasting methods are still being used. Time-series analysis was used to analyze the data, considering the time factor. Autoregressive Integrated Moving Average (ARIMA) is a time-series model that does not require a specific pattern in the data. The number of new postpartum family planning (KB) participants in East Java has both increased and decreased. Objectives: This study aimed to determine the number of new postpartum family planning (KB) participants in East Java. Methods: This study used non-reactive research methods. The secondary data used were the number of new postpartum family planning participants in East Java between January 2017 and December 2021. The data were obtained from the BKKBN website. Results: In this study, the ARIMA method produced the best model, namely, ARIMA (1,1,1), with an AR parameter value (1) of 0.413 and an MA parameter value (1) of 0.914. The resulting Mean Square Error (MSE) was 935,384, and the Mean Absolute Percentage Error (MAPE) was 4,671. Conclusions: The prediction results for the number of new postpartum family planning participants in East Java by 2022 increased every month. In January, there were 14,523 participants, and in December, it increased to 15,127 participants. The family planning program will continue to increase the number of postpartum family planning users.