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Implementasi Forward Chaining Untuk Mendeteksi Kerusakan Komputer Septian Isna, Rhaka Hade; Ardiansyah, Temi
JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) Vol. 9 No. 1 (2024): JUSTINDO
Publisher : Universitas Muhammadiyah Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32528/justindo.v9i1.1224

Abstract

Kerusakan komputer dapat disebabkan oleh berbagai faktor, mulai dari masalah perangkat keras hingga perangkat lunak. Sistem Pakar merupakan jenis aplikasi kecerdasan buatan yang dirancang untuk meniru kemampuan pemecahan masalah dan pengambilan keputusan manusia dalam suatu domain tertentu. Penelitian ini bertujuan untuk menggunakan metode Forward Chaining dalam menentukan diagnosa kerusakan komputer berdasarkan gejala atau masukan yang ditemui sehingga akan menghasilkan jenis kerusakan yang dialami. Hasil pengujian yang telah dilakukan dengan menggunakan confusion matrix didapat accuracy yang baik sebesar 88,7% dapat mengidentifikasi instance positif dengan baik denga nilai recall sebesar 86,9%, dan F1 Score yang tinggi sebesar 85,06% menunjukkan bahwa model memiliki keseimbangan yang baik antara precision dan recall untuk sistem pakar diagnosa kerusakan komputer dengan menggunakan metode Forward Chaining.
Penerapan Kombinasi Multi Objective Optimization on the basis of Ration Analysis dan Metode Pembobotan RECA Untuk Pemilihan Sales Berprestasi Sari, Putri Mayang; Ardiansyah, Temi
Building of Informatics, Technology and Science (BITS) Vol 7 No 1 (2025): June (2025)
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i1.7190

Abstract

This research proposes the application of a combination of Multi-Objective Optimization by Ratio Analysis (MOORA) and Respond to Criteria Weighting (RECA) methods for a more objective and transparent sales performance assessment system. MOORA is used to evaluate alternatives based on various criteria through a ratio normalization process, while RECA determines the weight of criteria proportionally by considering the contribution level of each criterion. The combination of these two methods is designed to reduce subjectivity in the evaluation process and produce a systematic and measurable ranking of salespeople. The results show that the integration of MOORA and RECA is able to provide an accurate solution in determining sales achievers, by considering various performance indicators such as sales volume, customer satisfaction, and the ability to build long-term relationships. The results of the study show that the combination of these two methods can produce transparent rankings. With the following ranking results, the first rank with a total final score of 0.514 by Sample, the second rank with a total final score of 0.314 by Jinilianty, the third rank with a total final score of 0.308 by Rudi Hartono. The system not only increases salesperson motivation to achieve targets, but also provides structured feedback for self-development. With a transparent and accountable approach, the company is able to improve. The system not only increases salespeople's motivation to achieve targets, but also provides structured feedback for self-development. With a transparent and accountable approach, the company can increase sales team loyalty, customer satisfaction, and overall profitability. The results of this study can also serve as a reference for other companies in developing a more effective sales performance evaluation system.