# Composition Model of Organic Waste Raw Materials Image-Based to Obtain Charcoal Briquette Energy Potential
> Saptadi N.T.S.

URL kanonis: https://discover.unhas.ac.id/publications/composition-model-of-organic-waste-raw-materials-image-based-to-obtain-charcoal
Jurnal / Konferensi: International Journal on Informatics Visualization
Tahun terbit: 2023
DOI: https://doi.org/10.30630/joiv.7.3.1682
ISSN: 25499904
Kuartil SJR: Q3
Citations: 2

## Authors
- Saptadi N.T.S.

## Abstract
Indonesia needs new renewable energy as an alternative to fuel oil. The existence of organic waste is an opportunity to replace oil because it is renewable and contains relatively less air-polluting sulfur. Previous research that has been widely carried out still utilizes coconut shell raw materials, which are increasingly limited in number, so other alternative raw materials are needed. A model is needed to make a formulation that can optimize the composition of organic waste raw materials as a basic ingredient for making briquettes. The research objective was to determine the best raw material composition based on digital image analysis in processing organic waste into briquettes. An artificial intelligence approach with a Convolutional Neural Network (CNN) architecture can predict an effective object detection model. The image analysis results have shown an effective model in the raw material composition of 60% coconut, 20% wood, and 20% adhesive to produce quality biomass briquettes. Briquettes with a higher percentage of coconut will perform better in composition tests than mixed briquettes. The energy obtained from burning briquettes is useful for meeting household fuel needs and meeting micro, small, and medium business industries.

## Keywords
- Briquette
- Raw material
- Renewable energy
- Charcoal
- Environmental science
- Waste management
- Biomass (ecology)
- Pulp and paper industry
- Materials science
- Engineering
- Coal
- Chemistry
- Metallurgy
- Geology
- Organic chemistry
- Oceanography
- Electrical engineering

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Sumber: Discover Unhas — RIMS Universitas Hasanuddin.
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