Comparative Analysis Of CNN Algorithm And MLP Neural Algorithm In Waste Image Classification

JTM : Jurnal TIMES [ISSN Print 2337-3601] [ISSN Online 2549-015X]
March 5, 2022 by
Comparative Analysis Of CNN Algorithm And MLP Neural Algorithm In Waste Image Classification
kelvin leonardi

Abstract


According to the World Bank report, waste is one of the problems that the world is facing. Image classification is one of the fields of machine learning that is capable of classifying waste based on its type. One of the most widely popular used classifications is the CNN algorithm which is a deep learning algorithm. In this study, we will perform a comparative analysis of the performance of the CNN algorithm with the MLP algorithm in terms of classifying waste types. From the research we did, CNN got a better performance where the results of precision, recall, f1-score, and accuracy were 0.98 and the CNN model was more effective in classifying waste based on its class.

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Kelvin Leonardi Kohsasih

Universitas Potensi Utama

Veronica Wijaya

Universitas Potensi Utama

Muhammad Dipo Agung Rizky

Universitas Potensi Utama

Tasya Fahriyani

Universitas Potensi Utama

Rika Rosnelly

Universitas Potensi Utama


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Citation:
K. L. . Kohsasih, M. D. Agung Rizky, T. FAHRIYANI, V. Wijaya, dan R. Rosnelly, “ANALISIS PERBANDINGAN ALGORITMA CONVOLUTIONAL NEURAL NETWORK DAN ALGORITMA MULTI-LAYER PERCEPTRON NEURAL DALAM KLASIFIKASI CITRA SAMPAH”, JTM, vol. 10, no. 2, hlm. 22–28, Jan 2022.
Publication:
Vol 10 No 2 (2021): Jurnal TIMES
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Copyright (c) STMIK TIME
Comparative Analysis Of CNN Algorithm And MLP Neural Algorithm In Waste Image Classification
kelvin leonardi March 5, 2022
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