Implementasi algoritma decision tree C4.5 untuk mengidentifikasi gizi balita berdasarkan indeks antropometri: studi kasus posyandu Seruni

Marsita, Merry (2018) Implementasi algoritma decision tree C4.5 untuk mengidentifikasi gizi balita berdasarkan indeks antropometri: studi kasus posyandu Seruni. Diploma thesis, UIN Sunan Gunung Djati Bandung.

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Abstract

Status gizi balita menjadi salah satu permasalahan kesehatan di Indonesia, karena kenaikan dan penurunan jumlah balita yang mengalami permasalahan status gizi tiap tahun tidak menentu. Penilaian status gizi balita dapat ditentukan melalui pengukuran tubuh manusia yang dikenal dengan istilah “Antropometri”. Di Indonesia penilaian status gizi pada anak mengacu pada standar World Health Organization (WHO)-2005. Untuk melakukan pemeriksaan dan pengukuran antropometri agar dapat mengetahui status gizi balita dapat mendatangi tempat pelayanan kesehatan masyarakat seperti salah satunya yaitu posyandu. Posyandu SERUNI merupakan posyandu yang berada di kelurahan Buaran Indah kota Tangerang. Di posyandu ini laporan data balita di simpan pada buku catatan dengan jumlah data yang banyak, sehingga mengalami kendala saat mengklasifikasi status gizi balita. Tujuan dari penelitian ini akan menguji coba model untuk klasifikasi status gizi balita berdasarkan baku rujukan WHO-2005 dengan memanfaatkan teknik data mining menggunakan metode Decision Tree Algoritma C4.5. Dengan menggunakan151 data training dan 151 data testing, algoritma C4.5 mampu mengklasifikasi data dengan tingkat akurasi sebesar 62.91% untuk klasifikasi gizi berdasarkan indeks BB/U dan 45.63% untuk indeks BB/TB. The nutritional status of toddlers is one of the health problems in Indonesia, because of the increase and decrease in the number of children under five years old who experience uncertain nutritional status every year. Assessment of nutritional status of children can be determined through measurements of the human body known as "anthropometry". In Indonesia the assessment of nutritional status in children refers to the standards of the World Health Organization (WHO) -2005. To conduct an examination and anthropometric measurement in order to find out the nutritional status of a toddler, we can go to a public health service such as Posyandu. SERUNI Posyandu is a posyandu in the village of Buaran Indah, Tangerang city. In this posyandu the data on children under five years old is kept in a notebook with a large amount of data, so they have problems when classifying the nutritional status of children. The purpose of this study is to test the classification model of nutritional status of children under the WHO-2005 reference standard by utilizing data mining techniques using the C4.5 Decision Tree Algorithm method. By using 151 training data and 151 data testing, C4.5 algorithm is able to classify data with an accuracy rate of 62.91% for nutritional classification based on BB / U index and 45.63% for BB / TB index.

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