TY  - THES
ID  - eprintuntirta51674
Y1  - 2025/06/03/
A1  - AZIZI, SAID RAHMAN
PB  - Fakultas Teknik Universitas Sultan Ageng Tirtayasa
AV  - restricted
UR  - https://eprints.untirta.ac.id/51674/
M1  - sarjana
TI  - ANALISIS KLASIFIKASI KUALITAS KABEL TEGANGAN MENENGAH ISOLASI XLPE DENGAN ALGORITMA K - NEAREST NEIGHBOR
N2  - 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.
EP  - 53
ER  -