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Alfira Nisa Fadhilah
Universitas Muhammadiyah Magelang
Humanities Computer Science & IT Environmental Science Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology

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Classification of Avocado Ripeness Levels using Naïve Bayes Method Ira Nuryani; Aldi Muhammad Nur Fadli; Nadila Dwi Saputri; Alfira Nisa Fadhilah; Muhammad Resa Arif Yudianto; M Maimunah
Prosiding University Research Colloquium Proceeding of The 15th University Research Colloquium 2022: Mahasiswa (Student Paper Presentation) B
Publisher : Konsorsium Lembaga Penelitian dan Pengabdian kepada Masyarakat Perguruan Tinggi Muhammadiyah 'Aisyiyah (PTMA) Koordinator Wilayah Jawa Tengah - DIY

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Abstract

During this time most people in determining the ripeness of avocados for personal consumption is not difficult because they can distinguish themselves but another case if used for production, which requires a lot of labor to group ripe and raw avocados. One of the innovations in information and communication technology in agriculture and plantations is the use of classification methods with naïve bayes algorithms. The formula of the problem in this study is how to do the classification on the ripeness of avocados and see the accuracy rate of the data. The purpose of this study is to classify avocado ripeness and to acquire intelligent systems, so that it becomes the first step towards the implementation stage. Based on the results and analysis that has been done, it can be concluded that the Naive Bayes method is considered capable in classifying avocado ripeness by using RGB color features. The accuracy in testing using Naïve Bayes method reached 83.34%. The performance obtained from this intelligent system is also effective and efficient so that the classification of avocado ripeness can be implemented.
Classification of Avocado Ripeness Levels using Naïve Bayes Method Ira Nuryani; Aldi Muhammad Nur Fadli; Nadila Dwi Saputri; Alfira Nisa Fadhilah; Muhammad Resa Arif Yudianto; M Maimunah
Prosiding University Research Colloquium Proceeding of The 15th University Research Colloquium 2022: Mahasiswa (Student Paper Presentation) B
Publisher : Konsorsium Lembaga Penelitian dan Pengabdian kepada Masyarakat Perguruan Tinggi Muhammadiyah 'Aisyiyah (PTMA) Koordinator Wilayah Jawa Tengah - DIY

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

During this time most people in determining the ripeness of avocados for personal consumption is not difficult because they can distinguish themselves but another case if used for production, which requires a lot of labor to group ripe and raw avocados. One of the innovations in information and communication technology in agriculture and plantations is the use of classification methods with naïve bayes algorithms. The formula of the problem in this study is how to do the classification on the ripeness of avocados and see the accuracy rate of the data. The purpose of this study is to classify avocado ripeness and to acquire intelligent systems, so that it becomes the first step towards the implementation stage. Based on the results and analysis that has been done, it can be concluded that the Naive Bayes method is considered capable in classifying avocado ripeness by using RGB color features. The accuracy in testing using Naïve Bayes method reached 83.34%. The performance obtained from this intelligent system is also effective and efficient so that the classification of avocado ripeness can be implemented.
Co-Authors Aldi Muhammad Nur Fadli Ira Nuryani Maimunah Muhammad Resa Arif Yudianto Nadila Dwi Saputri