Klasifikasi Buah Jeruk Segar dan Busuk Berdasarkan RGB dan HSV Menggunakan Metode KNN

Authors

  • Stifani Napitu Universitas Negeri Medan
  • Rini Paramita Panjaitan Universitas Negeri Medan
  • Putri Aisyah Nulhakim Universitas Negeri Medan
  • Muaz Khalik Lubis Universitas Negeri Medan

DOI:

https://doi.org/10.33020/saintekom.v13i2.420

Keywords:

Clasification, RGB, HSV, KNN, Orange Fruit

Abstract

Fruits are a group of agricultural commodities in Indonesia. The demand for domestic fruit commodities is quite high, this is indicated by the large number of fruits available in modern markets and traditional markets. In this research, a classification process will be carried out between fresh oranges and rotten oranges based on RGB (Red, Green, Blue) and HSV (Hue, Saturation, Value) color extraction. This study uses the K-Nearest Neighbor classification algorithm with a value of k = 1; 2; 3; 4; 5; 6; and 7. The dataset used consists of 146 training data and 88 testing data. The purpose and benefits of this research are to save time and facilitate classification according to the wishes of fruit growers. The final result of the test accuracy is 88.95%. Based on the test, this system can be said to be quite good at classifying fresh and rotten citrus fruits.

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References

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Published

30-09-2023

How to Cite

Napitu, Stifani, Rini Paramita Panjaitan, Putri Aisyah Nulhakim, and Muaz Khalik Lubis. 2023. “Klasifikasi Buah Jeruk Segar Dan Busuk Berdasarkan RGB Dan HSV Menggunakan Metode KNN”. Jurnal Saintekom : Sains, Teknologi, Komputer Dan Manajemen 13 (2):214-21. https://doi.org/10.33020/saintekom.v13i2.420.

Issue

Vol. 13 No. 2 (2023): September 2023

Section

Articles

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Copyright (c) 2023 Stifani Napitu, Rini Paramita Panjaitan, Putri Aisyah Nulhakim, Muaz Khalik Lubis

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