Red Dragon Fruit (Hylocereus costaricensis) Ripeness Color Classification by Naïve Bayes Algorithm

Zilvanhisna Emka Fitri; Mega Silvia; Abdul  Madjid; Arizal Mujibtamala Nanda Imron; Lalitya Nindita Sahenda

doi:10.33086/atcsj.v5i1.3690

Authors

Zilvanhisna Emka Fitri Politeknik Negeri Jember
Mega Silvia Politeknik Negeri Jember
Abdul Madjid Politeknik Negeri Jember
AMN Imron Universitas Jember
Lalitya Nindita Sahenda Politeknik Negeri Jember

DOI:

https://doi.org/10.33086/atcsj.v5i1.3690

Keywords:

computer vision, dragon fruit, GLCM, Naive Bayes, Maturity

Abstract

Dragon fruit is a unique fruit that is popular in Indonesia. besides having a sweet taste, this fruit also contains fiber, vitamins and minerals that are good for health. Dinas Pertanian Kabupaten Banyuwangi noted that the total dragon fruit production was 906,511.61 tons and the total productivity was 261.14 Kw/Ha in 2018. This shows that Kabupaten Banyuwangi is one of the largest producers of red dragon fruit in East Java Province. One of the problems in determining the quality of dragon fruit is choosing the harvest time, considering that dragon fruit is a non-climatic fruit. Non-climateric fruit is when we harvest fruit in its raw state, the fruit will never become ripe, so determining the harvest time for dragon fruit is very important. The determination made by paying discoloration and sizes of dragon fruit that is considered less effective. To overcome this, a system was created that was able to determine the level of dragon fruit maturity automatically by utilizing digital image processing techniques and intelligent systems. The parameters used are color features and GLCM texture features using angles 0°, 45°, 90° and 135° These features are parameters in the classification process using the Naïve Bayes method. Naïve bayes is able to classify the level of maturity of red dragon fruit (Hylocereus costaricensis) with an accuracy rate of 87.37%.

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