IMPLEMENTASI ALGORITMA FORWARD CHAINING PADA SISTEM PAKAR DIAGNOSA HAMA DAN PENYAKIT TANAMAN PISANG

The management of banana pest and disease outbreaks in Ngada Regency since 2022 has been hindered by farmers' lack of knowledge about early detection of symptoms and the limited availability of agricultural extension workers, which accelerates the spread and increases losses in agricultural land. This study aims to develop a web-based expert system to assist farmers in diagnosing banana pests and diseases quickly and accurately. The research methods involved data collection through field observations, interviews with farmers and agricultural experts, and literature studies from relevant references. The system design employs the waterfall development model, which includes requirements analysis, system design, implementation, and testing. The knowledge base of the system is designed using the forward chaining algorithm with 9 types of diseases and 40 symptoms. Implementation results indicate that the system was successfully tested using the black-box method with a 100% success rate, while the usability and responsiveness aspects scored 98% based on user evaluations. In conclusion, the forward chaining algorithm serves as an effective methode to support the diagnosis of banana pests and diseases and to enhance farmers' knowledge, thereby reducing losses caused by pest and disease attacks.

Authors

Publication Details

Journal
Jurnal Teknik Informasi dan Komputer (Tekinkom)
Published
2024-12-31
DOI
https://doi.org/10.37600/tekinkom.v7i2.1683
Primary Topic
Edcuational Technology Systems
Type
article
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article

IMPLEMENTASI ALGORITMA FORWARD CHAINING PADA SISTEM PAKAR DIAGNOSA HAMA DAN PENYAKIT TANAMAN PISANG

Karina Dhena Goda, Victoria Coo Lea, Yuliana Ule
Jurnal Teknik Informasi dan Komputer (Tekinkom)
Edcuational Technology Systems
article

IMPLEMENTASI ALGORITMA FORWARD CHAINING PADA SISTEM PAKAR DIAGNOSA HAMA DAN PENYAKIT TANAMAN PISANG

Karina Dhena Goda, Victoria Coo Lea, Yuliana Ule
article en

Abstract

The management of banana pest and disease outbreaks in Ngada Regency since 2022 has been hindered by farmers' lack of knowledge about early detection of symptoms and the limited availability of agricultural extension workers, which accelerates the spread and increases losses in agricultural land. This study aims to develop a web-based expert system to assist farmers in diagnosing banana pests and diseases quickly and accurately. The research methods involved data collection through field observations, interviews with farmers and agricultural experts, and literature studies from relevant references. The system design employs the waterfall development model, which includes requirements analysis, system design, implementation, and testing. The knowledge base of the system is designed using the forward chaining algorithm with 9 types of diseases and 40 symptoms. Implementation results indicate that the system was successfully tested using the black-box method with a 100% success rate, while the usability and responsiveness aspects scored 98% based on user evaluations. In conclusion, the forward chaining algorithm serves as an effective methode to support the diagnosis of banana pests and diseases and to enhance farmers' knowledge, thereby reducing losses caused by pest and disease attacks.

Jurnal Teknik Informasi dan Komputer (Tekinkom)Vol. 7(2)
Openalex Percentile: Top 75%
Edcuational Technology Systems
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