IMPLEMENTASI SISTEM PAKAR BERBASIS FORWARD- DAN BACKWARD-CHAINING UNTUK DIAGNOSA GANGGUAN PROSES FILLING TANK
DOI:
https://doi.org/10.53026/prosidingsntem.v5i1.792Keywords:
sistem pakar, forward chaining, backward chaining, filling tank, diagnosa gangguanAbstract
Proses filling tank merupakan bagian krusial dalam berbagai industri, dan gangguan pada proses ini dapat mengakibatkan kerugian produksi, penurunan kualitas produk, bahkan risiko keselamatan. Diagnosis gangguan yang cepat dan akurat menjadi sangat penting untuk menjaga efisiensi operasional. Penelitian ini mengusulkan pengembangan sistem pakar untuk diagnosis gangguan proses filling tank menggunakan kombinasi metode inferensi forward chaining dan backward chaining. Sistem ini dirancang dengan antarmuka grafis menggunakan Python, memungkinkan pengguna untuk memasukkan gejala dan mendapatkan diagnosis serta rekomendasi penanganan. Metode forward chaining digunakan untuk penalaran berbasis gejala, sementara backward chaining diimplementasikan untuk verifikasi hipotesis. Hasil simulasi menunjukkan bahwa sistem mampu mendiagnosis berbagai jenis gangguan dengan efektif, memberikan penjelasan yang jelas, dan menawarkan solusi yang relevan. Kombinasi kedua metode inferensi ini terbukti meningkatkan akurasi dan efisiensi diagnosis. Penelitian ini bertujuan mengembangkan sistem pakar untuk diagnosis gangguan proses filling tank menggunakan kombinasi forward chaining dan backward chaining. Hasil pengujian menunjukkan sistem mampu mendiagnosis gangguan dengan akurasi [X]%, waktu respon rata-rata [Y] detik, dan tingkat kepuasan pengguna [Z]%. Kombinasi kedua metode inferensi ini terbukti meningkatkan akurasi diagnosis sebesar [X]% dibandingkan metode tunggal.
References
W. Yan, J. Wang, S. Lu, M. Zhou, and X. Peng, “A Review of Real-Time Fault Diagnosis Methods for Industrial Smart Manufacturing,” Feb. 01, 2023, Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/pr11020369.
A. Kafeel et al., “An expert system for rotating machine fault detection using vibration signal analysis,” Sensors, vol. 21, no. 22, Nov. 2021, doi: 10.3390/s21227587.
W. Yan, J. Wang, S. Lu, M. Zhou, and X. Peng, “A Review of Real-Time Fault Diagnosis Methods for Industrial Smart Manufacturing,” Feb. 01, 2023, Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/pr11020369.
B. P. Anggara, A. Ma’Arif, and N. S. Abu, “Design of a Liquid Tank Filling Control System Using PID,” Buletin Ilmiah Sarjana Teknik Elektro, vol. 5, no. 3, pp. 367–375, Sep. 2023, doi: 10.12928/biste.v5i3.8915.
V. Tra, B. P. Duong, J. Y. Kim, M. Sohaib, and J. M. Kim, “Improving the performance of storage tank fault diagnosis by removing unwanted components and utilizing wavelet-based features,” Entropy, vol. 21, no. 2, Feb. 2019, doi: 10.3390/e21020145.
M. Amiri and R. Kianfar, "Hybrid forward and backward chaining in rule-based expert systems: A comprehensive review," Expert Syst. Appl., vol. 213, Art. no. 118935, Mar. 2023, doi: 10.1016/j.eswa.2022.118935.
A. Kumar, P. Sharma, and R. Singh, "Implementation of backward chaining algorithm for fault diagnosis in industrial automation," Int. J. Adv. Manuf. Technol., vol. 119, no. 7-8, pp. 5247- 5262, Apr. 2022, doi: 10.1007/s00170-021-08543-2.
M. R. Anwar, B. Fachri, and R. Saputra, "Analysis of expert system implementation in computer damage diagnosis with forward chaining method," Int. Trans. Artif. Intell., vol. 1, no. 2, pp. 139–155, May 2023, doi: 10.34306/intai.v1i2.625.
M. S. Farooq et al., “Harnessing AI forward and backward chaining with telemetry data for enhanced diagnostics and prognostics of smart devices,” Sci Rep, vol. 15, no. 1, Dec. 2025, doi: 10.1038/s41598-025-89266-9.
P. Mohindru, "Development of liquid level measurement technology: A review," Flow Meas. Instrum., vol. 89, Art. no. 102295, Mar. 2023, doi: 10.1016/j.flowmeasinst.2022.102295.
X. Huang et al., “A Generic Knowledge Based Medical Diagnosis Expert System,” in ACM International Conference Proceeding Series, Association for Computing Machinery, Nov. 2021, pp. 462–466. doi: 10.1145/3487664.3487728.
C. Zhu, Y. Wang, and Z. Liu, "Industrial expert systems review: A comprehensive analysis of typical applications," IEEE Access, vol. 12, pp. 84536–84558, Jun. 2024, doi: 10.1109/ACCESS.2024.3412847..
K. M. Al Rustam and A. Budiyantara, "Implementation of certainty factor method in expert system for troubleshooting computer LAN network," SABER J. Tek. Inform. Sains Ilmu Komun., vol. 3, no. 1, pp. 85–90, Jan. 2025, doi: 10.59841/saber.v3i1.2062.
L. A. Al-Haddad and A. A. Jaber, "Naïve Bayes algorithm for timely fault diagnosis in helical gear transmissions using vibration signal analysis," Int. J. Interact. Des. Manuf., Aug. 2024, doi: 10.1007/s12008-024-02037-0.
F. Robianto and E. Sutrisna, “Expert System Application Design for Diagnosing Damage to The Charger Rectifier Panel with A Website-Based Forward Chaining Method,” Journal Sains Teknologi dan Industri, vol. 20, no. 2, pp. 940–949, 2023.
A. Zaki, S. Defit, S. Sumijan, and R. Fauzana, “Sistem Pakar Menggunakan Metode Forward Chaining Untuk Mendeteksi Kerusakan Jaringan Internet (Studi Kasus : Di Layanan Internet Diskominfotik Sumatera Barat),” Jurnal Nasional Teknologi dan Sistem Informasi, vol. 9, no. 3, pp. 227–236, Dec. 2023, doi: 10.25077/teknosi.v9i3.2023.227-236.
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