Website-Based Kakaomu Application Development

The development of digital technology, especially in artificial intelligence (AI), has brought about major changes in various sectors of life, including agriculture. AI allows agricultural activities to be carried out more efficiently, accurately, and based on data. One of the agricultural commodities affected by this progress is cocoa. As one of the largest cocoa producers in the world, Indonesia has a great opportunity to develop this sector. However, the challenges in the field are still quite complex, especially in areas such as Pongo Village and North Luwu Regency. Cocoa farmers in this area face various problems, such as Helopeltis spp. pest attacks, declining plantation productivity, lack of market information, and lack of a comprehensive cocoa product tracking system. These problems result in suboptimal harvests and difficulty competing in the global market. To answer this challenge, the development of technology-based solutions is very important. One of the proposed innovations is the Kakaomu web application, which utilizes artificial intelligence to assist farmers in various aspects of agriculture. The main features of this application include pest identification and control, monitoring current market prices, recording production results, and a digital traceability system from the plantation to the end consumer. With the adoption of this technology, cocoa productivity, efficiency, and quality can increase significantly. In addition, this can also strengthen Indonesia's cocoa position in the world export market and encourage more modern and sustainable agriculture.

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Publication Details

Journal
Brilliance Research of Artificial Intelligence
Published
2025-07-14
DOI
https://doi.org/10.47709/brilliance.v5i1.6332
Primary Topic
Mobile and Web Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

Website-Based Kakaomu Application Development

Arjuna Haedar, Andi Nurlinda Thamrin, Rahmat Siswanto
Brilliance Research of Artificial Intelligence
Mobile and Web Applications
article

Website-Based Kakaomu Application Development

Arjuna Haedar, Andi Nurlinda Thamrin, Rahmat Siswanto
article en

Abstract

The development of digital technology, especially in artificial intelligence (AI), has brought about major changes in various sectors of life, including agriculture. AI allows agricultural activities to be carried out more efficiently, accurately, and based on data. One of the agricultural commodities affected by this progress is cocoa. As one of the largest cocoa producers in the world, Indonesia has a great opportunity to develop this sector. However, the challenges in the field are still quite complex, especially in areas such as Pongo Village and North Luwu Regency. Cocoa farmers in this area face various problems, such as Helopeltis spp. pest attacks, declining plantation productivity, lack of market information, and lack of a comprehensive cocoa product tracking system. These problems result in suboptimal harvests and difficulty competing in the global market. To answer this challenge, the development of technology-based solutions is very important. One of the proposed innovations is the Kakaomu web application, which utilizes artificial intelligence to assist farmers in various aspects of agriculture. The main features of this application include pest identification and control, monitoring current market prices, recording production results, and a digital traceability system from the plantation to the end consumer. With the adoption of this technology, cocoa productivity, efficiency, and quality can increase significantly. In addition, this can also strengthen Indonesia's cocoa position in the world export market and encourage more modern and sustainable agriculture.

Brilliance Research of Artificial IntelligenceVol. 5(1)
Muhammadiyah University of Makassar (ID)
Openalex Percentile: Top 74%
Mobile and Web Applications
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Website-Based Kakaomu Application Development — Arjuna Haedar, Andi Nurlinda Thamrin, et al. · Brilliance Research of Artificial Intelligence (2025) | TGRS Research Map | TGRS