JOURNAL ARTICLE

Indonesian Traditional Cake Classification Using Convolutional Neural Networks

Tita KarlitaBimo Prasetyo AfifIra Prasetyaningrum

Year: 2022 Journal:   Advances in Social Science, Education and Humanities Research/Advances in social science, education and humanities research

Abstract

In Indonesia, there are many types of cakes that are categorized as traditional snacks.Refer to the Kamus Besar Bahasa Indonesia; snacks are defined as foods that are peddled or mean bites.Snacks are classified based on how they are made, and some are based on the taste of the snacks.Traditional snacks are a part of Nusantara culture that is mandatory for those born and live in Indonesia to preserve them.But in reality, many people tend to consume and know more about modern snacks than traditional ones.In fact, not many people have even tried traditional snacks or even made their own at home.This application was developed to help people distinguish and recognize the various kinds of cakes on the market.With convolutional neural networks technology in machine learning, people can use image classification presented through mobile applications with accuracy above 90% for Indonesian traditional cake recognition.

Keywords:
Convolutional neural network Indonesian Computer science Artificial intelligence Artificial neural network Pattern recognition (psychology) Machine learning

Metrics

5
Cited By
5.42
FWCI (Field Weighted Citation Impact)
0
Refs
0.95
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Linguistics and Language Analysis
Social Sciences →  Arts and Humanities →  Language and Linguistics
© 2026 ScienceGate Book Chapters — All rights reserved.