Spices Identification in Essential Oil Producers using Comparasion of KNN and Naïve Bayes Classifier

DOI

10.2991/978-94-6463-288-0_51How to use a DOI?

Keywords

Spices; Essential Oils; Classification; Identification of spices; machine learning

Abstract

Indonesia is a spice-growing country, providing a variety of spices with numerous health advantages. Aside from being a producer, Indonesia is the world’s largest supplier of spices. Spices have a wide range of usage, including food ingredients, herbal medicines, and essential oils. Essential oils are generally used as binders in the aromatherapy, perfume, cosmetic and pharmaceutical manufacturing industries. With so many types of essential oil production, it is necessary to know which spices are ingredients in the production of the appropriate types of essential oils, so that a classification system for types of spices is desirable. Machine learning was utilized in this study to analyze spice’s image. Machine learning’s K-NN and Naive Bayes algorithms were selected as classification techniques. The goal of this study is to identify spices using a machine learning method, which is projected to develop into a system that assists farmers and the larger community in growing or creating essential oils that are suited by employing the right spices. The K-NN method achieved better accuracy with a value of K = 3 obtaining an accuracy of 100%, while Naïve Bayes achieved 96% accuracy. This research highlights the need for a classification system to improve the quality of essential oils for farmers and communities.

Copyright

© 2023 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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TY  - CONF
AU  - Fifin Ayu Mufarroha
AU  - Achmad Zain Nur
AU  - Mohammad Rizal Rahabillah
AU  - Achmad Jauhari
AU  - Devie Rosa Anamisa
AU  - Mulaab
PY  - 2023
DA  - 2023/11/19
TI  - Spices Identification in Essential Oil Producers using Comparasion of KNN and Naïve Bayes Classifier
BT  - Proceedings of the 4th International Conference on Informatics, Technology and Engineering 2023 (InCITE 2023)
PB  - Atlantis Press
SP  - 618
EP  - 627
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-288-0_51
DO  - 10.2991/978-94-6463-288-0_51
ID  - Mufarroha2023
ER  -