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

Asep Afandi, Noviana Noviana, Deti Nurdianah
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引用次数: 1

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
出生数据分类中的朴素贝叶斯方法和C4.5
关于楠榜孕妇的出生和生产年龄的数据仍然很高。了解孕妇的生产年龄、是否满足母亲怀孕的最低和最高要求以及婴儿出生标准的比较。数据处理的结果将被用作咨询母亲的数据来源,特别是Banjar Kertahayu村的居民。数据处理需要一种特殊的方法,以便结果成为以后决策的基准,例如数据挖掘。用于数据处理的方法是朴素贝叶斯和C4.5算法。所使用的数据是2017-2021年的出生数据,该数据来源于Banjar Village Midlife Central Lampung Regency的数据。研究结果方法C4.5中年具有0.3324138的优势年龄类别值。其中最高值出现在2017年,2017-2021年数据的准确率为100%。使用Naïve Bayes类方法的婴儿体重标准的主要中年类别值为0.09675,为2017年的最高值。根据2017-2021年的出生数据,5年的准确率为92.84%
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