ANALISA PERBANDINGAN ALGORITMA CLUSTERING UNTUK PEMETAAN STATUS GIZI BALITA DI PUSKESMAS PASIR JAYA

PANCARANI, TRISNANSITA KINTAN (2021) ANALISA PERBANDINGAN ALGORITMA CLUSTERING UNTUK PEMETAAN STATUS GIZI BALITA DI PUSKESMAS PASIR JAYA. S1 thesis, Universitas Mercu Buana Jakarta.

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Abstract

Nutritional conditions are very important for the human body, especially for infants under the age of 5 years, good nutrition will increase the body's resistance so that it is not susceptible to various diseases. increased work productivity and protected from chronic diseases and premature death due to disease. The problem of nutritional status in toddlers is still a major problem that needs attention, one of which is malnutrition. Malnutrition problems are directly caused by inadequate food intake, inadequate family economic factors, and caused by underlying diseases such as tuberculosis, heart disease or birth defects. The purpose of this study is to implement the clustering method with the K-Means and Fuzzy C-Means algorithms which aims to evaluate the nutritional status of children under five in general so that it can be used as a basis for early prevention for health workers at the puskesmas to overcome malnutrition. This study uses 4 parameters, namely height, weight, gender and age and uses a silhouette index validation calculation to measure the resulting cluster cohesiveness. From the results of the cluster analysis, the K-Means algorithm gets a validation result of 0.79 with 4 clusters and the Fuzzy C-Means algorithm gets a validation result of 0.78 with 4 clusters. From the two comparison algorithms, the K-Means algorithm gets the best validation because get the highest validation compared to the Fuzzy C-Means Algorithm Keywords: K-Means, Fuzzy C-Means, Clustering, Nutrition of children under five. Kondisi nutrisi sangat penting bagi tubuh manusia, terutama untuk bayi dibawah umur 5 tahun, gizi yang baik akan meningkatkan daya tahan tubuh sehingga tidak mudah terserang berbagai penyakit. produktivitas kerja meningkat serta terlindung dari penyakit kronis dan kematian dini akibat penyakit. Masalah status gizi pada balita masih menjadi masalah utama yang perlu diperhatikan, salah satunya adalah Gizi buruk. Masalah Gizi buruk secara langsung di sebabkan oleh asupan makanan yang gizinya tidak tercukupi, faktor ekonomi keluarga yang tidak memadai, dan disebabkan oleh penyakit yang mendasari seperti TBC, Jantung atau kelainan cacat pada saat lahir. Tujuan dari penelitian ini yaitu, Mengimplementasikan metode klasterisasi dengan algoritma K-Means dan Fuzzy C-Means yang bertujuan untuk mengevaluasi status gizi balita secara umum sehingga dapat dijadikan sebagai dasar pencegahan dini bagi petugas kesehatan di puskesmas untuk menanggulangi gizi buruk. Penelitian ini menggunakan 4 parameter yaitu tinggi badan, Berat badan, jenis kelamin dan umur dan menggunakan perhitungan validasi silhouette index untuk mengukur kekompakan cluster yang di hasilkan. Dari hasil dari analisa cluster, algoritma K-Means mendapatkan hasil validasi sebesar 0.79 dengan cluster sebanyak 4 dan algoritma Fuzzy C-Means mendapatkan validasi hasil validasi sebesar 0.78 dengan cluster sebanyak 4. Dari kedua perbandingan algoritma tersebut, algoritma K-Means mendapatkan validasi terbaik karena mendapatkan validasi tertinggi dibandingakan dengan Algoritma Fuzzy CMeans. Kata Kunci: K-Means, Fuzzy C-Means, Clustering, Gizi balita.

Item Type: Thesis (S1)
NIM/NIDN Creators: 41517010112
Uncontrolled Keywords: K-Means, Fuzzy C-Means, Clustering, Gizi balita.
Subjects: 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum
000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika
000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika > 004.2 Systems Analysis and Computer Design, Computer Architecture, Computer Performance Evaluation/Sistem Analis dan Desain Komputer, Arsitektur Komputer, Evaluasi Daya Guna dan Performa Komputer > 004.21 Systems Analysis and Computer Design/Sistem Analis dan Desain Komputer
500 Natural Science and Mathematics/Ilmu-ilmu Alam dan Matematika > 510 Mathematics/Matematika > 518 Numerical Analysis/Analisis Numerik, Analisa Numerik > 518.1 Algorithms/Algoritma
Divisions: Fakultas Ilmu Komputer > Informatika
Depositing User: ADELINA HASNA SETIAWATI
Date Deposited: 30 Nov 2023 05:45
Last Modified: 02 Dec 2023 03:03
URI: http://repository.mercubuana.ac.id/id/eprint/84449

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