# Coffee Bean Quality Classification Using the Variational Autoencoder and Support Vector Machine Algorithms
> Kadang M.O.

URL kanonis: https://discover.unhas.ac.id/publications/coffee-bean-quality-classification-using-the-variational-autoencoder-and-support
Jurnal / Konferensi: 2025 7th International Conference on Cybernetics and Intelligent System Icoris 2025
Tahun terbit: 2025
DOI: https://doi.org/10.1109/ICORIS67789.2025.11296134
Citations: 0

## Authors
- Kadang M.O.

## Abstract
The conventional process for sorting coffee bean quality on a large scale in the downstream coffee industry is still prone to human error, labour-intensive, and time-consuming. This research utilises autoencoder and support vector machine (SVM) techniques to develop a coffee bean quality classification model with four categories: ripe, unripe, non-coffee, and damaged beans. Additionally, this study aims to evaluate the model's performance using F1 score metrics, confusion matrix analysis, and k-fold cross-validation. A total of 1,000 image samples were used and evenly distributed into four classes. This was then further divided into a training subset of 70%, a validation subset of 20%, and a testing subset of 10%. The proposed model achieved a classification accuracy of 96%, demonstrating a high level of reliability. Additionally, the weighted average F1 score of 0.961 indicates a strong balance between precision and recall values across all classes. VAE + SVM outperformed the baseline CNN in classifying coffee bean quality, increasing accuracy by 3% from 93% to 96%. These results confirm the model's ability to effectively predict coffee bean quality and highlight its potential as a robust solution for automating the sorting process in real-world coffee.

## Keywords
- Autoencoder
- Support vector machine
- Sorting
- Artificial intelligence
- Confusion matrix
- Pattern recognition (psychology)
- Computer science
- Machine learning
- Precision and recall
- Quality (philosophy)
- Process (computing)
- F1 score
- Algorithm
- Coffee grounds
- Scale (ratio)
- Statistical classification
- Coffee bean
- Data mining
- Mathematics
- Encoder
- Baseline (sea)
- Green coffee
- Sorting algorithm
- Encoding (memory)
- Confusion
- Cross-validation

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Sumber: Discover Unhas — RIMS Universitas Hasanuddin.
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