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All Journal Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer JITK (Jurnal Ilmu Pengetahuan dan Komputer) Jurnal Pengabdian Masyarakat MIPA dan Pendidikan MIPA Jurnal Pengembangan Riset dan Observasi Teknik Informatika bit-Tech JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Jurnal Riset Multidisiplin dan Inovasi Teknologi
Barry Nuqoba, Barry
Universitas Airlangga Surabaya
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Languange, Linguistic, Communication & Media Public Health Social Sciences Other

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Enhancing Contractor Evaluation Using Fuzzy TOPSIS-Based Decision Support System Barry Nuqoba; Kartono; Faiz Haidar Satriani Adli; Faried Effendy; Taufik
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.2510

Abstract

Contractor evaluation remains a major challenge in safety-critical industries such as oil and gas, where the need to comply with stringent Health, Safety, and Environment (HSE) standards demands a robust and objective assessment mechanism. The existing manual evaluation methods are plagued by subjectivity, inconsistent data handling, and inability to resolve performance ties, leading to unreliable contractor differentiation. To address this problem, this study investigates how can a computational decision support framework minimize subjectivity and enhance ranking precision in contractor evaluations. It proposes a Decision Support System (DSS) based on the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) to improve the accuracy, transparency, and efficiency of evaluations within the Contractor Safety Management System (CSMS). The DSS integrates qualitative and quantitative criteria using fuzzy logic and expert-assigned linguistic weights. Developed following the Waterfall software development lifecycle, the system was validated using black box testing and applied to realistic simulated data from ten contractors evaluated across multiple criteria and subcriteria. Results demonstrate that the DSS effectively resolves score ties present in manual evaluations, enabling finer distinctions among contractors, with the highest closeness coefficient of 0.479 achieved by the top-ranked contractor. This value reflects a 47.9% closeness to the ideal performance profile, marking a significant improvement over binary or aggregate-based evaluation methods..User feedback confirmed high satisfaction with system usability and performance. The proposed DSS offers a robust and adaptable framework for contractor evaluation, enhancing decision-making accuracy and operational transparency in high-risk environments. Its novelty lies in the integration of fuzzy linguistic modeling within a CSMS context to operationalize HSE performance evaluations. Future research should focus on incorporating advanced fuzzy logic methods and artificial intelligence to facilitate real-time, dynamic contractor evaluations under uncertainty.
EXPERT SYSTEM FOR CLASSIFYING AUTISM CHILDREN’S INDEPENDENCE LEVEL FROM DAILY ACTIVITY USING FORWARD CHAINING Indah Werdiningsih; Fachrizal Fikri; Nania Nuzulita; Barry Nuqoba; Sigit Dani Perkasa
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 11 No. 4 (2026): JITK Issue May 2026
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v11i4.7866

Abstract

Children with Autism Spectrum Disorder (ASD) require early intervention during their developmental stages. Currently, the availability of experts capable of accurately classifying the independence levels of children with ASD remains limited. Determining these independence levels is crucial, as it serves as the basis for establishing appropriate early interventions. The system aims to assist specialists in conducting more consistent and efficient assessments. This study contributes a novel application of a forward chaining–based expert system for classifying ASD children’s independence levels, integrating rule-based reasoning with user-centered evaluation, which distinguishes it from previous studies that primarily focus on diagnosis rather than functional independence assessment. Data were collected from three institutions: two Public Special Need Schools and a Regional Technical Implementation Unit of Children with Special Needs in East Java. The dataset consists of 400 records encompassing five daily activities: eating, drinking, brushing teeth, dressing, and taking off clothes. The independence levels are classified into three categories: independent, partially independent, and dependent. This research consists of seven stages, namely data collection, rule based system using forward chaining, database design using CDM and PDM, user interface development, implementation of the Next.js framework system and PostgreSQL database, system testing, and system evaluation. The results of the study showed that the accuracy was 98.5% and the user satisfaction score was 80.85%. These results indicate that the proposed method is effective in supporting therapists in determining the level of independence of children with ASD based on rules established by experts.
Co-Authors Arif Djunaidy Army Justitia Fachrizal Fikri Faiz Haidar Satriani Adli Faried Effendy Faried Effendy Indah Werdinigsih Indah Werdiningsih Kartono Kartono Muhammadun Muhammadun, Muhammadun Nania Nuzulita Sembiring, Rinawati Sigit Dani Perkasa Sugeng Santoso Taufik Taufik Taufik