Prediction of the Birth Rate of Babies at Regional Hospitals in Salatiga City Using the Naïve Bayes Algorithm

Adelliya Dewi Saputri; Hendry Hendry

doi:10.26877/asset.v6i2.18466

Prediction of the Birth Rate of Babies at Regional Hospitals in Salatiga City Using the Naïve Bayes Algorithm

Adelliya Dewi Saputri, Hendry Hendry

Abstract

Birth rates have a significant impact on population growth and large populations can be a burden on development. In the Salatiga City Regional Hospital, the numbers tend to change every year, with the current population density making it a special concern for the City of Salatiga. Therefore, it is hoped that the application of Data Mining Techniques with the Naive Bayes algorithm can help predict the number of births in the future using the RapidMiner Application. In this research, the population used was Population Data from Salatiga City with a total of 989,674 residents. Then the sample used was 4699 babies from the Salatiga City Regional Hospital. All data was taken from 2019 – 2023 by conducting observations, literature studies and documentation. By analyzing the pattern of each variable and testing the training data against the testing data, a calculation was produced which shows the Testing Data Prediction, namely the "High" label with the number 4.77192E-06, with this the predicted result of the Baby Birth Rate in the Salatiga City Regional Hospital which is influenced by Population Density in 2024 it will be even higher.

Keywords

Naïve Bayes, Baby Birth, Population Density, Prediction

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DOI: https://doi.org/10.26877/asset.v6i2.18466

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Advance Sustainable Science, Engineering and Technology (ASSET)

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