JSAI (Journal Scientific and Applied Informatics)
Vol 7 No 2 (2024): Juni

Analisis Performa Metode Klasifikasi Dataset Multi-Class Kanker Kulit Menggunakan KNN dan HOG

Rahayu, Sarwati (Unknown)
Sandiwarno, Sulis (Unknown)
Dwika Putra, Erwin (Unknown)
Utami, Marissa (Unknown)
Setiawan, Hadiguna (Unknown)



Article Info

Publish Date
07 Jun 2024

Abstract

Detection of skin cancer in its early phase is a challenge even for dermatologists. This study aims to analyze the performance of classification methods on multiclass skin cancer datasets using K-nearest neighbor (KNN) and histogram of oriented gradients (HOG). The dataset is taken publicly under the name Skin Cancer MNIST dataset: HAM10000 dataset totaling 10,015 data. The first experiment used the pixels per cell parameter of 8.8 and cells per block of 2.2 to get an accuracy of 60.58%. The second experiment used the pixels per cell parameter of 8.8 and cells per block of 2.2 to get an accuracy of 60.58%. The last experiment using the pixels per cell parameter of 8.8 and cells per block of 2.2 got the best accuracy of 61.43%.

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Journal Info

Abbrev

JSAI

Publisher

Subject

Computer Science & IT

Description

Jurnal terbitan dibawah fakultas teknik universitas muhammadiyah bengkulu. Pada jurnal ini akan membahas tema tentag Mobile, Animasi, Computer Vision, dan Networking yang merupakan jurnal berbasis science pada informatika, beserta penelitian yang berkaitan dengan implementasi metode dan atau ...