Proceedings of the 2nd International Conference on Neural Networks and Machine Learning 2023 (ICNNML 2023)

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Specialty Coffees Classification Utilizes Feature Selection and Machine Learning

Authors
Nelly Oktavia Adiwijaya1, Riyanarto Sarno2, *
1Informatics Department, Faculty of Computer Science, University of Jember, Jember, Indonesia
2Informatics Department, Faculty of Intelligent Electrical and Informatics Technology, Institut Teknologi Sepuluh Nopember (ITS), Surabaya, Indonesia
*Corresponding author. Email: riyanarto@if.its.ac.id
Corresponding Author
Riyanarto Sarno
Available Online 29 June 2024.
DOI
10.2991/978-94-6463-445-7_11How to use a DOI?
Keywords
Specialty coffee classification; machine learning models; feature selection; cupping quality assesment
Abstract

An important factor that influences the price of coffee bean commodities is their quality. Specialty coffee beans are the quality of coffee beans with the highest price. Determining the quality of specialty coffee beans is determined through a long and complicated series of physical tests and cupping test by an expert called Qgrader. This research proposes classifying specialty coffee beans using several machine learning methods. The first step taken was to label the data in accordance with the Specialty Coffee Association of America standard rules. The coffee classes used in this research are Grade 1, Grade 2 and Grade 3. Next, feature selection was carried out using correlation analysis and important features which resulted in 6 features out of 11 features. This study compares the results of classification using 3 different models, namely Support Vector Machine (SVM), K-Nearest Neighbor (KNN) and Random Forest (RF) with accuracy results of 78%, 100% and 100% respectively.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2nd International Conference on Neural Networks and Machine Learning 2023 (ICNNML 2023)
Series
Advances in Intelligent Systems Research
Publication Date
29 June 2024
ISBN
978-94-6463-445-7
ISSN
1951-6851
DOI
10.2991/978-94-6463-445-7_11How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Nelly Oktavia Adiwijaya
AU  - Riyanarto Sarno
PY  - 2024
DA  - 2024/06/29
TI  - Specialty Coffees Classification Utilizes Feature Selection and Machine Learning
BT  - Proceedings of the 2nd International Conference on Neural Networks and Machine Learning 2023 (ICNNML 2023)
PB  - Atlantis Press
SP  - 94
EP  - 101
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-445-7_11
DO  - 10.2991/978-94-6463-445-7_11
ID  - Adiwijaya2024
ER  -