IMPLEMENTASI METODE DECISION TREE C4.5
SEBAGAI PENENTU STATUS GIZI BALITA (STUDY KASUS PUSKESMAS DUKUH KUPANG SURABAYA)
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Institusion
Universitas Muhammadiyah Gresik
Author
SARI, FEBRIANA IKA
Subject
Informatics Engineering
Datestamp
2019-07-16 02:48:56
Abstract :
Puskesmas Dukuh Kupang has one of the roles in the health sector that is managing the data collection of nutrition status of children. Reporting of nutrition data of toddlers that have been running in puskesmas is data of anthropometry measurement of children from posyandu cadres are recorded using form sheets provided by the puskesmas. The biggest obstacle is the health center must be careful in calculating the results of anthropometry measurement of the toddler because the work is done with a simple calculation, so that the health center staff must be thoroughly in classifying the nutritional status of children. This research applies classification data mining technique by using decision tree C4.5 method to determine nutrition grade of toddler that is less class or good class. Attributes used in this study consisted of 5 variables, namely sex, age, weight, height, and head circumference. Testing the system performed as much as six times the test. The data used is taken from the data of children under five at Puskesmas Dukuh Kupang Surabaya, in September 2014 as many as 131 data.
Puskesmas Dukuh Kupang has one of the roles in the health sector that is managing the data collection of nutrition status of children. Reporting of nutrition data of toddlers that have been running in puskesmas is data of anthropometry measurement of children from posyandu cadres are recorded using form sheets provided by the puskesmas. The biggest obstacle is the health center must be careful in calculating the results of anthropometry measurement of the toddler because the work is done with a simple calculation, so that the health center staff must be thoroughly in classifying the nutritional status of children. This research applies classification data mining technique by using decision tree C4.5 method to determine nutrition grade of toddler that is less class or good class. Attributes used in this study consisted of 5 variables, namely sex, age, weight, height, and head circumference. Testing the system performed as much as six times the test. The data used is taken from the data of children under five at Puskesmas Dukuh Kupang Surabaya, in September 2014 as many as 131 data.
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