Published: 2025-04-01
Classification of Apple Ripeness Detection System Using Self-Organizing Map (SOM) Method
DOI: 10.35870/ijsecs.v5i1.3734
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Abstract
Apple (Malus Domestica) is one of the most popular types of fruit and is in high demand by the public because of its varied flavors. Apples have many nutrients and various vitamins including healthy fats, carbohydrates, proteins, vitamins and many more. The Apple is one of the apple varieties developed in Batu City, Malang and planted in several areas with suitable agroclimates for apple growth. This research uses Anna apple images as datasets. Various ways can be employed to distinguish Anna apples' maturity, including through color image analysis. But to the naked eye, Anna apples are often difficult to distinguish. This research classifies the maturity of Anna apples based on color analysis with the Self-Organizing Map method. Using Google Colab and Python programming language and datasets from kaggle.com as many as 139 datasets, 46% training data, 54% validation data. The Self-Organizing Map method was chosen because of its ability to recognize visual patterns accurately. The accuracy of the results based on the SOM Method performance evaluation metrics namely Quantization Error, Silhouette Score and Topographic Error. Quantization Error RGB (0.004737) is lower than HSV (0.073178) which indicates RGB's ability is effective in representing data in SOM. Silhouette Score HSV (0.704204) is higher than RGB (0.599846) indicating the ability of HSV is slightly better in grouping objects.
Keywords
Classification of Ripeness Accuracy ; Apple Fruit (Malus Domestica) ; Self Organizing Map
Article Information
This article has been peer-reviewed and published in the International Journal Software Engineering and Computer Science (IJSECS). The content is available under the terms of the Creative Commons Attribution 4.0 International License.
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Issue: Vol. 5 No. 1 (2025)
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Section: Articles
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Published: %750 %e, %2025
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License: CC BY 4.0
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Copyright: © 2025 Authors
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DOI: 10.35870/ijsecs.v5i1.3734
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Tundo
Informatics Engineering Study Program, Faculty of Computer Technology, Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika, East Jakarta City, Special Capital Region of Jakarta, Indonesia
Shindy Apriani
Informatics Engineering Study Program, Faculty of Computer Technology, Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika, East Jakarta City, Special Capital Region of Jakarta, Indonesia
Sugeng
Informatics Engineering Study Program, Faculty of Computer Technology, Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika, East Jakarta City, Special Capital Region of Jakarta, Indonesia
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