Naive Bayes Method and C4.5 in Classification of Birth Data

Abstract

Data on the birth and productive age of a mother to get pregnant in Lampung is still high. to find out the comparison of the productive age of pregnant women and whether they have met the minimum and maximum requirements for a mother to become pregnant, and the criteria for babies born. Where the results of data processing will be used as a source of data for counseling mothers, especially for residents of Banjar Kertahayu village. The data processing requires a special method so that the results become a benchmark for a decision later, such as Data Mining. The method used for data processing used is Naive Bayes and C4.5 Algorithm. The data used is birth data in 2017-2021, the source of data from the Banjar Village Midwife-Central Lampung Regency. Research Results Method C 4.5 Middle age has a dominant age category value of 0.3324138. where the highest value is in 2017, and accuracy is 100 percent from the 2017-2021 data. The baby weight criterion using the Naïve Bayes Class Method has a dominant Middle-aged category value of 0.09675, the highest value in 2017, The results of accuracy for 5 years have accuracy of 92.84% based on 2017-2021 birth data

Application of the K-Means Method for Clustering Best Selling Products in Ice Cream Sales

“…K-Means is a non-hierarchical data clustering method that tries to partition existing data into one or more clusters or groups. Determining The initial centroid, this determination is done randomly on existing data tables [19]. This method partitions into clusters or groups so that data that have the same characteristics are grouped into one cluster, and those that have different characteristics are grouped into a different cluster.…”