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All Journal Jurnal Biometrika dan Kependudukan (Journal of Biometrics and Population)
Mahmudah Mahmudah
Department of Biostatistics and Population, Faculty of Public Health, Universitas Airlangga, 60115 Surabaya, East Java, Indonesia

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DECOMPOSITION METHOD FOR FORECASTING THE NUMBER OF PARTICIPANTS OF NEW FAMILY PLANNING IN SURABAYA Dinana Izzatul Ulya; Mahmudah Mahmudah
Jurnal Biometrika dan Kependudukan (Journal of Biometrics and Population) Vol. 9 No. 1 (2020): JURNAL BIOMETRIKA DAN KEPENDUDUKAN
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jbk.v9i1.2020.36-43

Abstract

Indonesia is a country that has a large population and Family Planning Program was initially designed to control the population. This study aimed to forecast new Family Planning Program participants in the city of Surabaya in 2019 using the decomposition method. This study used secondary data, which is the number of participants for new Family Planning Program in January 2014 to December 2018 (60 plots of data) obtained from the PCWECP Surabaya. The researcher chose decomposition method in this study because decomposition is a one-time series method that has rarely been applied in a research. Based on the results of the study, the number of participants for new Family Planning Program from January to December 2019 was 2,776; 2,663; 2,504; 2,340; 2,440; 1,912; 2,034; 2,291; 2,223; 2,123; 2,123; 2,130 and 2,560 participants. The error value generated by this study is MAPE of 9, MAD of 365, MSD 197,738, and MSE of 2.1675. The best error value is the one that has the smallest value, so the MSE is the best model.
PREDICTION MODEL FOR THE NUMBER OF ARI CASES IN CHILDREN IN SURABAYA USING ARIMA METHOD Alvin Zulhazmi Priambodo; Mahmudah Mahmudah
Jurnal Biometrika dan Kependudukan (Journal of Biometrics and Population) Vol. 9 No. 1 (2020): JURNAL BIOMETRIKA DAN KEPENDUDUKAN
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jbk.v9i1.2020.18-26

Abstract

Forecasting is an important element in planning decision-making related to estimating future events. Forecasting techniques that are often developed and used today are the Time Series. Time series is a measurement of events through the stages of time in hours, days, months, and years format. This research uses the ARIMA time series method. The ARIMA method is used to model acute respiratory infections (ARI) in children. The best model is determined using the smallest error through the Mean Absolute Percentage Error (MAPE). The study aims to predict the number of ARI cases in children in Surabaya. This research is an unobtrusive/nonreactive research. The researcher conditioned the subjects to not being aware that the subject is being studied and therefore, left the subject uninterrupted. The data used was the number of ARI cases in children from January 2014 to December 2018. The data was obtained from the monthly report of the Health Information System Unit (HIS) of the Surabaya Health Office. The conclusion from this study showed that the ARIMA method obtained the best model results, namely ARIMA (2,1,2) with a MAPE value of 15.024. Forecasting results fluctuated and a downward trend in the case of ARI children in Surabaya. In certain months, the number of acute respiratory infections has increased significantly, including in February and March. 
Co-Authors Alvin Zulhazmi Priambodo Dinana Izzatul Ulya