Application of Data Mining to Predict Birth Rates in Medan City Using the K-Nearest Neighbor Method - Putri, Alma Irawanti; Furqan, Mhd.; Suhardi, Suhardi (Journal of Computer Science, Information Technology and Telecommunication Engineering, 2024)
The birth rate of babies in Indonesia tends to increase every month, based on this fact, the population in Indonesia is increasing over time. One of the contributing factors is increasingly sophisticated technology, so that a country's birth rate can be accelerated, and if this event occurs continuously it will have an impact on population density which will occur notlonly inlIndonesia, butlalso throughoutylthelworld. Therefore, birth rate predictions are needed for planning and public policy in the fields of health and social welfare. One of them is using data mining techniques to predict the number of births in Medan City using the KNN method. KNN is a classification method based on the neighborhood value between training data and test data. Thelpredictioniresults will beicompared withlactual datalto measure thekaccuracy of predictions on birth data totaling 131 data. The accuracy results obtained were 83.9% with a total of 4,413 births and 8,485 pregnant women