SISTEM PEMANTAUAN PERTUMBUHAN BATITA MENGGUNAKAN METODE FUZZY TSUKAMOTO

Irma Anggraeni, Yusma Yanti

Abstract


The growth of children under the age of three (toddlers) is one of the determinants of children's development in the future. One of the parameters of toddler growth assessment is determined by gender, age, height and weight. This research makes a system that can monitor toddler growth with web-based. The research method used is the System Life Development Cycle, which consists of planning, analysis, design, implementation and use. This system also uses the Tsukamoto fuzzy method to determine the membership set of each input variable. The gender criteria are divided into two classes, male and female, the age criteria are divided into three classes, the height criteria are three classes, and the weight criteria are divided into three classes. Based on the division of classes, the output of this study is the growth status of toddlers, namely poor growth, poor, normal and more. Based on the results of input data criteria and calculations using Tsukamoto fuzzy, the output obtained in the form of the status of the child's growth.

 


Keywords


toddler. Fuzzy Tsukamoto, website

References


Peraturan Menteri Kesehatan Republik Indonesia Nomor 75 Tahun 2013 tentang Angka Kecukupan Gizi yang Dianjurkan bagi Bangsa Indonesia. Diakses melalui http://gizi.depkes.go.id/download/ Kebijakan%20Gizi/PMK%2075-2013. pdf.

Hoddinott, J., J.R. Behrman, J.A. Maluccio, P. Melgar, A.R. Quisumbing, M. Ramirezzea, et al., 2013. Adult Consequences of Growth Failure in Early Childhood. The American Journal of Clinical Nutrition. 98(5): 11701178.

Suharjito, Diana, Yulianto, Ariadi Nugroho. 2017. Mobile Expert System Using Fuzzy Tsukamoto forDiagnosing CattleDisease. 2nd International Conference On Computer Science And Computational Intelligence 2017.

Wiguna, R. Y., Haryanto, H., 2015, Sistem Berbasis Aturan Menggunakan Logika Fuzzy Tsukamoto Untuk Prediksi Jumlah Produksi Roti Pada CV.Gendis Bakery. Skripsi. Fakultas Ilmu Komputer, Universitas Dian Nuswantoro, Semarang.

Maryaningsih, Siswanto, Mesterjon, 2013. Metode Logika Fuzzy Tsukamoto Dalam Sistem Pengambilan Keputusan Penerimaan Beasiswa. Jurnal Media Infotama. 9(1), Hal 140-165.

[Ross, T. J. 2010. Fuzzy Logic With Engineering Applications (3 ed.). United Kingdom: John Wiley & Sons.

Sutoyo, T. M. 2011. Kecerdasan Buatan. Yogyakarta: C.V Andi Offset (Penerbit Andi).

Arief, M.Rudyanto. 2011. Pemograman WebDinamis Menggunakan PHP dan MySQL. Yogyakarta: Andi Offset.

Arsad RA (2006). Penilaian Status Gizi Anak, Staf Dinas Kesehatan, Kabupaten Polewali Mandar, Medan.

Fidiantoro, Nungki dan Tedy S. 2013. Model Penentuan Status Gizi Balita di Puskesmas. Jurnal Sarjana Teknik Informatika Universitas Ahmad Dahlan. 1 (1) Juni 2013.

Ikhwan Chandra. 2007. Sistem Adminitrasi Puskesmas Rawat Inap Merapi II menggunakan Metode TAS.

Nugroho, Bunafit. 2008. Latihan Membuat Aplikasi Web PHP dan MySQL dengan Dreamweaver MX(6, 7,2004) dan 8. Yogyakarta: Gava Media.

Ogunrinade. 2014. The Incidence of Malnutrition in Children (0-5 Yrs). Journal of Agriculture and Life Science. 1 (2) . Dec 2014.

SCN, 2004. 5th Report on the World Nutrition Situation: Nutrition for Improved Development Outcomes. United Nations System (online), (http://www.unsystem. org/scn/Publications/AnnualMeeting/SCN31/ SCN5Report.pdf) diakses pada tanggal 30 Juli 2018.

Vina Adelina, Dian Eka Ratnawati, M. Ali Fauzi. 2018. Klasifikasi Tingkat Risiko Penyakit Stroke Menggunakan Metode GAFuzzy Tsukamoto. Jurnal Pengembangan Teknologi.


Full Text: PDF

DOI: 10.33751/komputasi.v17i1.1749 Abstract views : 1114 views : 929

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.