PREDICTION OF SUSTAINABILITY OF FAMILY PLANNING PARTICIPANTS BASED ON DEMOGRAPHIC CHARACTERISTICS USING RANDOM FOREST
Keywords:
Family Planning, Family Planning Continuity, Prediction, Random ForestAbstract
Family Planning (KB) is one of the government programs aimed at controlling population growth and improving family welfare. However, some Family Planning participants discontinued the use of contraceptives, which may affect the success of the program. Therefore, this study aims to develop a prediction system for the continuity of Family Planning participants in Cot Girek District using the Random Forest algorithm. The study used 1,000 Family Planning participant records containing demographic, socioeconomic, and contraceptive-related attributes. After the data preprocessing stage, 998 records were used to construct the prediction model. The research involved data preprocessing, Random Forest model construction, and model evaluation using Hold-Out Validation and 5-Fold Cross Validation. The results showed that the Age of the Youngest Child attribute had the highest Gini Gain value of 0.3486, indicating that it was the most influential factor in predicting the continuity of Family Planning participants. The model achieved an Accuracy of 93%, Precision of 93.33%, Recall of 96.18%, and F1-Score of 94.74%, while 5-Fold Cross Validation produced an average accuracy of 97.40% with a standard deviation of ±4.95%. In addition, Black Box Testing confirmed that all system functions are operated according to user requirements. These findings indicate that the Random Forest algorithm can effectively predict the continuity of Family Planning participants and can be used as a decision-support tool to assist Family Planning officers in monitoring and providing more targeted assistance to participants.
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