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All Journal Jurnal Informatika Upgris JSAI (Journal Scientific and Applied Informatics) Jurnal Teknologi Informasi dan Pendidikan Bulletin of Information Technology (BIT) Journal Geuthee of Engineering and Energy RJOCS (Riau Journal of Computer Science) Jurnal Informatika Polinema (JIP) Jurnal Teknologi Informasi Indonesia IECON: International Economics and Business Conference
Sulistiawati Rahayu Ahmad
Institut Teknologi Sains Dan Bisnis Muhammadiyah Selayar
Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Library & Information Science

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Optimizing CCTV Damage Diagnosis with Backward Chaining Based Expert System Marlin Lasena; Sulistiawati Rahayu Ningsi Ahmad
Bulletin of Information Technology (BIT) Vol 6 No 2: Juni 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i2.1964

Abstract

The use of CCTV systems in daily life is increasingly widespread, along with the growing need for security and surveillance. However, malfunctions in both hardware and software components of CCTV devices remain a challenge, especially for technicians and non-technical users who lack sufficient expertise. This study aims to develop an expert system using the Backward Chaining method to assist technicians and users in accurately and efficiently diagnosing various types of CCTV malfunctions. The Backward Chaining method is employed due to its ability to trace symptoms back to the root cause using a rule-based logical inference approach. The system is implemented as a mobile application for Android platforms, with a knowledge base constructed from the expertise of CCTV technicians at PT. Smart CCTV Indonesia. The results of the study indicate that the expert system provides significant ease in diagnosing CCTV issues and offers relevant recommendations to both technicians and users. Thus, this system is expected to enhance efficiency in troubleshooting processes and support better decision-making in the management of digital security systems
Analisis Komparatif Algoritma Klasifikasi untuk Prediksi Kelulusan Tepat Waktu Mahasiswa Hariati Husain; sulistiawati Rahayu Ahmad; Muh Salim
Bulletin of Information Technology (BIT) Vol 7 No 1: Maret 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v7i1.2619

Abstract

- Timely student graduation is an important indicator in assessing the quality of higher education management. However, not all students are able to complete their studies within the prescribed study period, making it necessary to implement data-driven predictive approaches to identify students at risk of delayed graduation. This study aims to compare the performance of the Decision Tree and Naïve Bayes algorithms in classifying timely student graduation based on academic data. The dataset consists of alumni records from the Informatics Engineering Study Program for the 2015–2016 cohorts, totaling 610 valid records after data cleaning and attribute selection. Predictor variables include gender, class type, and Semester Grade Point Index (IPS) from semester 1 to semester 5, while the target variable is graduation status. Model evaluation was conducted using an 80% training and 20% testing split, and performance was measured through a confusion matrix to obtain accuracy, precision, and recall values. The results show that the Decision Tree achieved an accuracy of 69.54%, while Naïve Bayes achieved 68.38%. The 1.16% difference indicates that the Decision Tree performs slightly better for this dataset. These findings suggest that early semester academic performance significantly contributes to predicting timely graduation and can support data-driven academic decision-making.
Sistem Pendukung Keputusan Kelayakan Pemberian Kredit Nasabah Dengan Metode Electre Marlin Lasena; Sulistiawati Rahayu Ahmad
Bulletin of Information Technology (BIT) Vol 4 No 2: Juni 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i2.690

Abstract

PT Hasjrat Abadi has collaborated with a financing institution to provide opportunities for vehicle ownership through credit facilities. The credit system offered by the financing institution can boost vehicle sales. However, before that, the lender must conduct a thorough consumer data analysis. This is crucial to ensure that potential customers can repay the approved vehicle loans, thereby avoiding the risk of loan defaults in the future. The process of consumer data analysis is time-consuming due to the abundance of documents involved. Additionally, field surveys are necessary to validate consumer data by applying the 5C Bank Principles (character, capital, capacity, collateral, and condition). Research Objective By implementing the Electre (Elimination and Choice Translation Reality) method in the decision support system, we can provide quick, accurate, and precise information to determine whether potential customers are eligible to purchase vehicles from PT Hasjrat Abadi through credit. This method utilizes the 5C Bank Principles (character, capital, capacity, collateral, and condition) to evaluate consumers. The method used is Research and Development (R&D), which aims to develop specific products and test their effectiveness. The research findings indicate that this system can enhance the services provided to customers at PT Hasjrat Abadi's branch in Gorontalo. Based on the data input by credit analysts, it was found that only 50 percent of the total potential customer data could be approved using the Electre method for credit applications. This facilitates faster, more accurate, and more reliable decision-making for customers.
Co-Authors Abdul Ma’arief Al Imran Ali Asgar Zainal Abidin Danial Saleh Hariati Husain Jorry Karim M Salim M Salim M. Salim Marlin Lasena Marlin Lasena Misrawati Aprilyana Puspa Muh Salim Muh Salim Muhammad Ihsan Maro Muhammad Ihsan Maro Mursyid Ardiansyah Nur Insani R Dalai, Hastuti Saleh, Danial Salim, M Salim, M. salim, Muh Salma P. Nua Salma PNua Syaifuddin Syaifuddin Utiarahman, Siti Andini yulanda yunus