Implementasi Sistem Pakar dengan Certainty Factor untuk Identifikasi Akurat Hama dan Penyakit Tanaman Jagung di Provinsi Gorontalo

Implementation of an Expert System with Certainty Factor for Accurate Identification of Corn Pests and Diseases in Gorontalo Province

Authors

  • Muhammad Iqbal Jafar Universitas Ichsan Gorontalo image/svg+xml
  • Zulfrianto Y Lamasigi Universitas Ichsan Gorontalo image/svg+xml
  • Indah Puspitasari Universitas Negeri Gorontalo
  • Mayasari Yamin Universitas negeri Gorontalo

DOI:

https://doi.org/10.30605/hkadzs91

Keywords:

Certainty Factor, sistem pakar, ketahanan pangan, tanaman jagung, identifikasi hama dan penyakit

Abstract

Penelitian ini bertujuan untuk mengembangkan dan menguji sistem pakar untuk mengidentifikasi hama dan penyakit pada tanaman jagung di Provinsi Gorontalo, Indonesia, dengan menerapkan metode Certainty Factor (CF). Sistem ini dibangun berdasarkan basis pengetahuan yang diperoleh dari wawancara mendalam dengan para ahli, termasuk akademisi, penyuluh pertanian, dan peneliti. Metode CF digunakan untuk mengatasi ketidakpastian dalam diagnosis dengan menghitung nilai kepercayaan dari kombinasi gejala yang diamati oleh pengguna (petani/penyuluh). Hasil uji menunjukkan kemampuan sistem untuk mendiagnosis penyakit seperti penggerek batang dengan tingkat kepercayaan hingga 98,5%. Analisis ini menegaskan efektivitas metode CF dalam memberikan diagnosis yang terukur dan akurat (>80%), yang difasilitasi oleh antarmuka yang ramah pengguna. Sistem ini berfungsi tidak hanya sebagai alat diagnostik cepat di lapangan tetapi juga sebagai media pendidikan, menjembatani kesenjangan pengetahuan antara para ahli dan petani. Keberhasilan implementasi merekomendasikan metode CF sebagai pendekatan yang layak untuk sistem identifikasi penyakit tanaman, dengan catatan bahwa basis pengetahuan memerlukan pembaruan berkala. Penelitian ini berkontribusi untuk meningkatkan upaya ketahanan pangan melalui deteksi dini yang tepat.

This study aims to develop and test an expert system for identifying pests and diseases in corn crops in Gorontalo Province, Indonesia, by applying the Certainty Factor (CF) method. The system was built on a knowledge base derived from in-depth interviews with experts, including academics, agricultural extension workers, and researchers. The CF method was employed to address uncertainty in diagnosis by calculating confidence values from combinations of symptoms observed by users (farmers/extension workers). Test results demonstrated the system's capability to diagnose diseases such as stem borer with a confidence level of up to 98.5%. The analysis confirms the effectiveness of the CF method in providing measurable and accurate diagnoses (>80%), facilitated by a user-friendly interface. This system functions not only as a rapid diagnostic tool in the field but also as an educational medium, bridging the knowledge gap between experts and farmers. The successful implementation recommends the CF method as a viable approach for plant disease identification systems, with the note that the knowledge base requires periodic updates. This research contributes to enhancing food security efforts through precise early detection.

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Published

2026-07-15

Issue

Vol. 14 No. 2 (2026): Perbal: Jurnal Pertanian Berkelanjutan

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Copyright (c) 2026 Muhammad Iqbal Jafar, Zulfrianto Y Lamasigi, Indah Puspitasari, Mayasari Yamin

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