# Classification on passion fruit's ripeness using K-means clustering and artificial neural network
> Sidehabi S.

URL kanonis: https://discover.unhas.ac.id/publications/classification-on-passion-fruits-ripeness-using-k-means-clustering-and-artificia
Jurnal / Konferensi: 2018 International Conference on Information and Communications Technology Icoiact 2018
Tahun terbit: 2018
DOI: https://doi.org/10.1109/ICOIACT.2018.8350728
Citations: 38

## Authors
- Sidehabi S.

## Abstract
This purpose of this study is to identify the level of ripeness of the passion fruit. The levels are classified into three distinguished stages: fruit in a ripe stage, a nearly ripe stage, and an unripe stage. The passion fruit-sorting system with artificial intelligence is an innovation of fruit sorting technology for industrial markets because it is very cost efficient and effective for a large production process instead of relying on manual labor process. The method used in this research is K-Means Clustering to perform passion fruit segmentation and Artificial Neural Network for classification based on RGB and A features. The input data is passion fruit video from 6 different sides. This study uses 75 passion fruit videos as training data and 20 videos as data testing with duration 5 seconds per video. The result achieves system accuracy of 90% with classification errors occur in the nearly ripe and unripe fruit due to the color closeness.

## Keywords
- Ripeness
- Passion
- Artificial intelligence
- Sorting
- Passion fruit
- Cluster analysis
- Artificial neural network
- Computer science
- Closeness
- Process (computing)
- Stage (stratigraphy)
- Segmentation
- RGB color model
- Pattern recognition (psychology)
- Machine learning
- Computer vision
- Mathematics
- Horticulture
- Algorithm
- Ripening
- Psychology
- Operating system
- Paleontology
- Psychotherapist
- Biology
- Mathematical analysis

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Sumber: Discover Unhas — RIMS Universitas Hasanuddin.
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