PERBANDINGAN JARAK EUCLIDEAN, MANHATTAN, CHEBYSHEV PADA KLASIFIKASI STATUS GIZI BALITA MENGGUNAKAN METODE K-NEAREST NEIGHBORS (KNN)

Uni Umamatun Nysa, Junia (2023) PERBANDINGAN JARAK EUCLIDEAN, MANHATTAN, CHEBYSHEV PADA KLASIFIKASI STATUS GIZI BALITA MENGGUNAKAN METODE K-NEAREST NEIGHBORS (KNN). Skripsi thesis, Institut Teknologi Nasional Malang.

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Abstract

Penelitian ini membandingkan keakuratan jarak Euclidean, Manhattan, dan Chebyshev dalam klasifikasi status gizi balita menggunakan metode K-Nearest Neighbors (KNN). Data status gizi anak balita dari Posyandu digunakan untuk melatih model KNN dan membandingkan keakuratan ketiga metode jarak. Tujuan penelitian ini adalah membandingkan keakuratan jarak dan mengembangkan sistem pendukung keputusan berbasis web untuk kader Posyandu. Metodologi penelitian mencakup studi literatur, pengumpulan data, perancangan sistem, implementasi, dan pengujian sistem. Hasilnya diharapkan memberikan informasi mengenai metode jarak yang optimal dalam penentuan status gizi balita dengan KNN.

Item Type: Thesis (Skripsi)
Additional Information: Junia Uni Umamatun Nysa (1918112)
Uncontrolled Keywords: jarak euclidean, jarak chebyshev, jarak manhattan, K-Nearest Neighbors (KNN), sistem pendukung keputusan, status gizi balita
Subjects: Engineering > Informatics Engineering
Divisions: Fakultas Teknologi Industri > Teknik Informatika S1 > Teknik Informatika S1(Skripsi)
Depositing User: Junia Uni Umamatun Nysa
Date Deposited: 11 Sep 2023 05:41
Last Modified: 26 Oct 2023 05:01
URI: http://eprints.itn.ac.id/id/eprint/12888

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