Accuracy of Algorithm C4.5 to Study Data Mining Against Selection of Contraception

Suryani, Des and Labellapansa, Ause and Marsela, Eka (2018) Accuracy of Algorithm C4.5 to Study Data Mining Against Selection of Contraception. Springer.

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Abstract

Family planning is an attempt to infuse or plan the number and spacing of pregnancy using contraception. Contraception is a method or tool used to prevent pregnancy. Arrangements can be made with the use of contraceptives such as pills, spirals, implants. Patients may consult with the midwife or physician in choosing a contraceptive that is suitable or convenient to use. But in reality there are still many patients, especially patients at Clinic Pratama Hasanah Pekanbaru, who still hesitate in choosing contraceptives in accordance with the patient’s body condition. For that, writer was interested to do study data of contraception usage to patient at Clinic Pratama Hasanah Pekanbaru to get pattern of decision tree and its level of accuracy. Based on this, it is necessary to evaluate the data collection of contraceptive usage to determine the pattern of contraceptive selection. The data mining process uses the classification method with the Decision Tree C4.5 algorithm. The attributes used in determining the pattern of selection of contraceptives consist of nine regular attri�butes, i.e., age, term of usage, menstrual cycle, just married, just give birth, breastfeeding, already having offspring, health problems, and have more than four children, whereas the attribute label/class that is contraceptive used. This study resulted in recognition of contraceptive pattern selection with accuracy of 93.15% (excellent classification). With this level of accuracy, it will help the midwife to direct the patient in the selection of contraceptives based on the resulting pattern.

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