UMM Institutional Repository

SISTEM CERDAS UNTUK DIAGNOSA PENYAKIT HIPOTERMIA PADA BAYI YANG BARU LAHIR MENGGUNAKAN METODE KNEAREST NEIGHBOUR (K-NN)

Wicaksono, Muhammad Fiqhi (2018) SISTEM CERDAS UNTUK DIAGNOSA PENYAKIT HIPOTERMIA PADA BAYI YANG BARU LAHIR MENGGUNAKAN METODE KNEAREST NEIGHBOUR (K-NN). Bachelors Degree (S1) thesis, University of Muhammadiyah Malang.

[img]
Preview
Text
PENDAHULUAN.pdf

Download (557kB) | Preview
[img]
Preview
Text
BAB 1.pdf

Download (151kB) | Preview
[img]
Preview
Text
BAB 2.pdf

Download (618kB) | Preview
[img]
Preview
Text
BAB 3.pdf

Download (491kB) | Preview
[img] Text
BAB 4.pdf
Restricted to Registered users only

Download (956kB)
[img] Text
BAB 5.pdf
Restricted to Registered users only

Download (36kB)
[img] Text
LAMPIRAN.pdf
Restricted to Registered users only

Download (189kB)

Abstract

Hypothermia is a major cause of morbidity and mortality in newborns in developing countries. But there is no application that diagnoses hypothermia. The purpose of this study is to make it easier for parents to know the baby is exposed to hypothermia or not. K-Nearest Neighbor (K-NN) is a method that uses a supervised algorithm in which the results of the new test sample are classified by the majority of the training data categories. The algorithm is to classify new objects based on attributes and sample exercises. Applications used using Hypertext Preprocessor (PHP) The goal is to implement the application in order to provide a decision to determine the disease of hypothermia in newborns whether hypothermia NORMAL, MEDIUM, and HEAVY. The results with K-Nearest Neighbor (K-NN) algoitma and Hypertext Preprocessor (PHP) applications run well with 86% presentation.

Item Type: Thesis (Bachelors Degree (S1))
Student ID: 201210130311003
Keywords: hypothermia in newborns, K-Nearest Neighbor (K-NN)
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Engineering > Department of Electrical Engineering (20201)
Depositing User: CKO Repository
Date Deposited: 01 Nov 2018 02:36
Last Modified: 01 Nov 2018 02:36
URI : http://eprints.umm.ac.id/id/eprint/39048

Actions (login required)

View Item View Item
UMM Official

© 2008 UMM Library. All Rights Reserved.
Jl. Raya Tlogomas No 246 Malang East Java Indonesia - Phone +62341464318 ext. 150, 151 - Fax +62341464101
E-Mail : infopus[at]umm.ac.id - Website : http://lib.umm.ac.id - Online Catalog : http://laser.umm.ac.id - Repository : http://eprints.umm.ac.id

Web Analytics

UMM Institutional Repository is powered by :
EPrints Logo