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All Journal Building of Informatics, Technology and Science Journal of Computer System and Informatics (JoSYC) TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Teknik Informatika (JUTIF) KLIK: Kajian Ilmiah Informatika dan Komputer BEES: Bulletin of Electrical and Electronics Engineering Paradigma Bulletin of Informatics and Data Science Jurnal Informatika dan Rekayasa Perangkat Lunak
Arshad, Muhammad Waqas
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Aerospace Engineering Arts Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Social Sciences Veterinary Other

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Journal : Building of Informatics, Technology and Science

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Modification of the Grey Relational Analysis Method in Determining the Best Mechanic Arshad, Muhammad Waqas; Sulistiani, Heni; Maryana, Sufiatul; Palupiningsih, Pritasari; Rahmanto, Yuri; Setiawansyah, Setiawansyah
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.5678

Abstract

Determining the best mechanics in the industry has an important role to ensure the quality and reliability of the products and services offered. Competent and experienced mechanics are able to diagnose and repair accurately and efficiently, thereby minimizing operational downtime and increasing productivity. Without a structured system, mechanical performance appraisals tend to be subjective and inconsistent, which can lead to dissatisfaction among employees and customers. Mechanics may not get clear and constructive feedback on their performance, thus hindering skill development and professionalism. The purpose of the research of the modified Grey Relational Analysis (GRA) using standard deviation is to improve the accuracy and reliability of the decision-making process in situations where the data has a high degree of variability or significant uncertainty. By integrating standard deviations into the GRA, the study aims to account for variations and fluctuations in the data, which allows for more accurate and representative assessment of the criteria. This modification is expected to overcome the weaknesses of traditional GRAs that may not adequately consider data uncertainty, as well as produce more robust and realistic alternative rankings. The results of the best ranking of mechanics, Mechanic FR ranks first with a value of 0.11, followed by Mechanic HS with a value of 0.104. The third place was occupied by Mechanic AY with a score of 0.099.
Comparison of Certainty Factor, Dempster Shafer, and Bayes' Theorem in Expert Systems for Diagnosing Female Reproductive System Diseases Mesran, Mesran; Rasli, Roznim Mohamad; Setiawansyah, Setiawansyah; Arshad, Muhammad Waqas
Building of Informatics, Technology and Science (BITS) Vol 7 No 2 (2025): September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i2.8334

Abstract

Expert systems are one application of artificial intelligence used to mimic the ability of an expert in diagnosing a disease. This study aims to compare the performance of three inference methods Certainty Factor, Dempster-Shafer, and Bayes' Theorem in the diagnosis of female reproductive system diseases. Symptom data and expert knowledge values were obtained from medical experts to support the system's validity. Each method was implemented on the same symptom data, and the results were analyzed to assess the consistency of the diagnoses produced. The results show that the Certainty Factor method produced a diagnosis of Cervical Cancer with the highest confidence value of 0.9999, followed by the Dempster-Shafer method with the same diagnosis and a confidence value of 0.852. However, the Bayes Theorem method produced a different diagnosis, namely Ovarian Cyst, with a confidence value of 0.911. These differing results indicate that the characteristics and approaches of each method significantly influence the final diagnosis outcome. This study contributes insights to expert system developers regarding the strengths and weaknesses of each inference method. The selection of the appropriate method must be tailored to the system's requirements, data complexity, and the level of uncertainty in the medical information used.
Co-Authors Aditia Yudhistira Asistyasari, Ayuni Chandra, Iryanto Desyanti Gunawan, Rakhmat Dedi Heni Sulistiani Mesran, Mesran Nuryaman, Yosep Palupiningsih, Pritasari Putra, Ade Dwi Rasli, Roznim Mohamad Ryan Randy Suryono Sanriomi Sintaro Setiawansyah Setiawansyah Sitna Hajar Hadad Subhan Subhan Sufiatul Maryana Sumanto, Sumanto Tri Widodo Ulum, Faruk Very Hendra Saputra Wahyudi, Agung Deni Yuri Rahmanto