eprintid: 51674
rev_number: 15
eprint_status: archive
userid: 16250
dir: disk0/00/05/16/74
datestamp: 2025-07-16 02:06:38
lastmod: 2025-07-16 02:06:38
status_changed: 2025-07-16 02:06:38
type: thesis
metadata_visibility: show
creators_name: AZIZI, SAID RAHMAN
creators_id: 3332210079
contributors_type: http://www.loc.gov/loc.terms/relators/THS
contributors_type: http://www.loc.gov/loc.terms/relators/THS
contributors_name: Otong, Muhamad
contributors_name: Martiningsih, Wahyuni
contributors_id: 197203192005011001
contributors_id: 196303132001122001
corp_creators: Universitas Sultan Ageng Tirtayasa
corp_creators: Fakultas Teknik
corp_creators: Jurusan Teknik Elektro
title: ANALISIS KLASIFIKASI KUALITAS KABEL TEGANGAN MENENGAH ISOLASI XLPE DENGAN ALGORITMA K - NEAREST NEIGHBOR
ispublished: pub
subjects: T1
divisions: Elektro
full_text_status: restricted
abstract: Over time, the quality of the cable decreases. This study conducted a cable assessment test and the results were classified using the K-Nearest Neighbor algorithm to make it easier to determine quality. The cable conditions were divided into 5 classes and the evaluation was carried out by testing the model performance using accuracy, precision, recall, and F1-score. The test results show that increasing the amount of training data can improve classification performance. With the addition of 100 training data, the K-NN algorithm with K=2 achieved the highest accuracy of 92.86%, precision 0.96, recall 0.9333, and F1-score 0.9378. These results indicate that K-NN can be used to classify underground cables, if supported by sufficient data and the selection of the right K parameters.
date: 2025-06-03
date_type: published
pages: 53
institution: Fakultas Teknik Universitas Sultan Ageng Tirtayasa
department: Teknik Elektro
thesis_type: sarjana
thesis_name: sarjana
citation:   AZIZI, SAID RAHMAN  (2025) ANALISIS KLASIFIKASI KUALITAS KABEL TEGANGAN MENENGAH ISOLASI XLPE DENGAN ALGORITMA K - NEAREST NEIGHBOR.  S1 thesis, Fakultas Teknik Universitas Sultan Ageng Tirtayasa.   
document_url: https://eprints.untirta.ac.id/51674/1/Said%20Rahman%20Azizi_3332210079_Fulltext.pdf
document_url: https://eprints.untirta.ac.id/51674/2/Said%20Rahman%20Azizi_3332210079_01.pdf
document_url: https://eprints.untirta.ac.id/51674/3/Said%20Rahman%20Azizi_3332210079_02.pdf
document_url: https://eprints.untirta.ac.id/51674/4/Said%20Rahman%20Azizi_3332210079_03.pdf
document_url: https://eprints.untirta.ac.id/51674/5/Said%20Rahman%20Azizi_3332210079_04.pdf
document_url: https://eprints.untirta.ac.id/51674/6/Said%20Rahman%20Azizi_3332210079_05.pdf
document_url: https://eprints.untirta.ac.id/51674/7/Said%20Rahman%20Azizi_3332210079_Ref.pdf
document_url: https://eprints.untirta.ac.id/51674/8/Said%20Rahman%20Azizi_3332210079_Lamp.pdf
document_url: https://eprints.untirta.ac.id/51674/9/Said%20Rahman%20Azizi_3332210079_CP.pdf