Sistem Pakar Penilaian Resiko Joint Closure pada Infrastruktur Fiber Optik Menggunakan Forward Chaining
DOI:
https://doi.org/10.46880/jmika.Vol10No2.pp645-654Keywords:
Information Systems, Fiber Optics, Joint Closure, Expert Systems, Forward ChainingAbstract
The manual management of Fiber optic infrastructure data at PT Aplikanusa Lintasarta has the potential to cause data duplication, recording errors, difficulty in information retrieval, and inconsistencies in Joint Closure risk assessments. These problems can affect the effectiveness of decision-making related to network infrastructure maintenance. This study aims to design and build a Fiber Optic Infrastructure Information System equipped with a Joint Closure Risk Assessment Expert System feature using the Forward Chaining method. This method is used to determine the risk level based on location conditions, installation age, and disruption history represented in the form of expert knowledge-based rules. The Forward Chaining method is implemented using 26 rules that represent expert knowledge in determining the Joint Closure risk level. System evaluation is carried out through Black Box testing, System Usability Scale (SUS), and expert validation. The results of the study indicate that the system runs according to its function with a Black Box test success rate of 100%, obtaining a SUS score of 71.83 which is included in the Good and Acceptable categories, and a level of conformity with expert validation results of 100%. Based on these results, the system built is able to support infrastructure data management and Joint Closure risk assessment in an effective, consistent, and structured manner.
References
Ajayi, W., Omoghene, E., Arowosegbe, S., & Isaac, O. (2023). Data Management Challenges and Resolutions in the Telecommunication Industry. International Journal of Emerging Trends in Engineering Research, 103–110. https://doi.org/10.30534/ijeter/2023/031132023
Asemi, A., Ko, A., & Nowkarizi, M. (2021). Intelligent libraries: a review on expert systems, artificial intelligence, and robots. Library Hi Tech, 39(2), 412–434. https://doi.org/10.1108/LHT-02-2020-0038
De Iuliis, M., Kammouh, O., Cimellaro, G. P., & Tesfamariam, S. (2021). Quantifying restoration time of power and telecommunication lifelines after earthquakes using Bayesian belief network model. Reliability Engineering & System Safety, 208, 107320. https://doi.org/10.1016/j.ress.2020.107320
Hidayat, T., & Ramsari, N. (2023). Sistem Pakar Diagnosa Awal Penyakit Ginjal Menggunakan Metode Forward Chaining: Expert System for Early Diagnosis of Kidney Disease Using Forward Chaining Method. MALCOM: Indonesian Journal of Machine Learning and Computer Science, 3(2), 125–135. https://doi.org/10.57152/malcom.v3i2.887
Iddrisu, W. A., & Gedel, I. A. (2023). Modeling the downtime severity of telecommunication networks using discrete-time Markov chains. International Journal of Advanced Technology and Engineering Exploration, 10(101). https://doi.org/10.19101/IJATEE.2022.101004
Insani, K., & Alijoyo, F. A. (2024). Bisnis Jaringan Internet Fiber Optic di Era Digitalisasi untuk Pemerataan Infrastruktur Telekomunikasi. Jurnal Teknologi dan Sistem Informasi Bisnis, 6(4), 799–805.
https://doi.org/10.47233/jteksis.v6i4.1572
Khawar, M. K., Wajiha, S., Shaheen, S., Shakil, A. Iftikhar, F., & Faisal, K. I. (2024). Investigating the Most Effective AI/ML-Based Strategies for Predictive Network Maintenance to Minimize Downtime and Enhance Service Reliability. Spectrum of Engineering Sciences, 2(4),115–132.
Megawaty, M., & Ulfa, M. (2020). Decision Support System Methods: A Review. Journal of Information Systems and Informatics, 2(1), 192–201. https://doi.org/10.33557/journalisi.v2i1.63
Mukarrom, A., Wulandari, A., Estianto, D., Parwanto, K., Ulfah, M., Ekawati, R., ... & Ilhami, M. A. (2025). Strategi Pemilihan Pemasok Menggunakan Metode Weighted Scoring Model (WSM) dan Implementasi Manajemen Kontrak Dalam Rantai Pasok PT AAA. Teknologi Nusantara, 7(2), 1-9.
Reddy, B., & Fields, R. (2022). From past to present: a comprehensive technical review of rule-based expert systems from 1980--2021. Proceedings of the 2022 ACM Southeast Conference, 167–172.
Šarūnienė, I., Martišauskas, L., Krikštolaitis, R., Augutis, J., & Setola, R. (2024). Risk assessment of critical infrastructures: A methodology based on criticality of infrastructure elements. Reliability Engineering & System Safety, 243, 109797.
https://doi.org/10.1016/j.ress.2023.109797
Solecha, K., Jefi, Hendri, Badri, E., & Haidir, A. (2021). Sistem pakar untuk mendeteksi kerusakan komputer dengan metode forward chaining. Jurnal Infortech, 3(2). https://doi.org/10.31294/infortech.v3i2.11801
Zaki, A., Defit, S., Sumijan, S., & Fauzana, R. (2023). 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, 9(3), 227–236. https://doi.org/10.25077/TEKNOSI.v9i3.2023.227-236
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