MODEL ARIMA (p, d, q) PADA DATA KEMATIAN IBU HAMIL (STUDI KASUS DI RSUD ULIN BANJARMASIN) - Dewi Anggraini; Faisal Faisal (EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN, 2009)
Time series analysis is a sequence of quantitative observation at a certain timeinterval, such as daily, monthly, yearly, etc. This analysis has been used foridentifying the characteristic, pattern, and model of observed data in the specifiedpast period that leads to predict the future observation values. Applications oftime series analysis include all aspects such as, meteorology, economy, andmedical area. The deaths prevalence of pregnancy women at delivering process isstill very high. This leads to a significant medical problem in Indonesia. In 2003,this case has been reported 20 women, including 3 cases due to blooding, 3 casesdue to eclampsy, and 14 cases due to other factors. This research is conducted togive an appropriate model to predict the deaths of pregnancy women in the future.The method of this research is using purposive sampling technique, which isgathering 72 secondary data of monthly deaths pregnancy women from2003 - 2008 in the midwife room of Ulin Hospital, Banjarmasin. The experimentprocedures are identifying the appropriate ARIMA model to give the trendmonthly deaths description of pregnancy women, and evaluating the fitted ARIMAmodel to forecast monthly deaths of pregnancy women in the future 10 yearsbased on the given historical data.Based on the conducted analysis, it is found that monthly deaths of pregnancywomen between 2003 and 2008 in Ulin Hospital, Banjarmasin has experienceda slightly increase. The data are discrete with monthly expected value equal to0.625, where the smallest and biggest deaths are 0 and 3 people, respectively.Beside this, it has been investigated that ARIMA (0, 0, 0) or ARMA (0, 0) is thebest ARIMA model for this case because it results the minimum value of AICC.