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Journal : Journal Of Information System And Artificial Intelligence

SISTEM PEMETAAN DAN REKOMENDASI UNTUK OBJEK WISATA DI KABUPATEN BOYOLALI BERDASARKAN SIG (SISTEM INFORMASI GEOGRAFIS) Setiawan, Ferry Illham; Muqorobin, Muqorobin; Efendi, Tino Feri
Journal Of Information System And Artificial Intelligence Vol. 6 No. 1 (2025): Vol. 6 No.1(2025): Journal of Information System and Artificial Intelligence Vo
Publisher : Universitas Mercu Buana Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26486/jisai.v6i1.249

Abstract

Boyolali Regency has various interesting tourist attractions, but limited information and tourist recommendations are an obstacle for tourists in planning a visit. Geographic Information System (GIS) can be a solution to present tourist location information visually and provide recommendations based on certain criteria such as distance, tourist category, and popularity. This research aims to develop a GIS that is able to recommend tourist attractions in Boyolali Regency. By utilizing spatial data and interactive features, this system is expected to facilitate tourists in finding and selecting tourist destinations that suit their preferences. The implementation results show that this GIS is effective in providing tourism recommendations and improving the accessibility of tourism information in Boyolali.
Implementasi Sistem Pakar Berbasis Web untuk Diagnosis Kerusakan Mesin Menggunakan Metode Backward Chaining dan Certainty Factor Marso, Ammar Kholaf Abdur Robbibi; Muqorobin, Muqorobin; Pakarti, Moch Bagoes
Journal Of Information System And Artificial Intelligence Vol. 7 No. 2 (2026): Vol.7 No. 2 (2026): Journal of Information System and Artificial Intelligence V
Publisher : Universitas Mercu Buana Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26486/jisai.v7i2.250

Abstract

PT Hardo Soloplast is a manufacturing company that produces plastic products using various advanced machinery. A recurring issue in the production process is the sudden malfunction of machines, which disrupts operations and increases repair costs. To address this, this study proposes a web-based expert system for machine fault diagnosis using the Backward Chaining reasoning method and Certainty Factor approach. The system is implemented using PHP, HTML, CSS, and JavaScript, and stores knowledge in JSON format. It is accessible via web browser for field technicians. The system covers five main machines: Extruder Starex 1500, Laminating HL-2000, Printing Roto-Gravure, Slitting Rewinder RS-3000, and Blown Film Extrusion Machine. The knowledge base consists of 65 rules and symptoms, collected from interviews and documentation. Backward Chaining was chosen for its efficiency in goal-driven reasoning, while Certainty Factor is applied using the formula CFcombine = CF1 + CF2 × (1 − CF1), with a threshold of 0.75 for reliable results.Testing was conducted by comparing system diagnoses with actual technician assessments, achieving accuracy between 75% and 92.58% . This system contributes to the digitalisation efforts at PT Hardo Soloplast by accelerating diagnosis, improving maintenance response time, and reducing dependence on manual fault identification.