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Forecasting is a systematic attempt to predict future events using past data, based on scientific and qualitative methods. For the maternal health program, forecasting is important as its process consist s of planning, targetting and achievement. Based on data from the Ministry of Health , the quality of antenatal care in Indonesia was still low (87.48 percent) compared to that of the national target (95 percent). This study aims to apply the methods of artificial neural network in predicting the antenatal care (K4). This applied research used a descriptive method with secondary data in the form of monthly antenatal care visits (K4) from the year of 2012 to 2015 obtained from the Provincial Health Office of East Java, with a case study in Bondowoso. The forecasting result in 2016 based on the 12-4-1 network architecture was 9533.5698, with the value of Mean Square Error (MSE) of 3091.84404. The average percentage of error d based on a comparison with the actual data is 0.1854 or reaching the accuracy of 99.8 1 percent. The conclusion of this study is that a neural network has a low error value and a high accuracy . Therefore, forecasting results can be used as an input in the planning program.

The Application of Artificial Neural Network Method in Forecasting the Number of Pregnant Woman Visits (K4)