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All Journal Jurnal Teknik Mesin, Industri, Elektro dan Informatika
Cecilia D. P. Binti Gabriel
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Computer Science & IT Electrical & Electronics Engineering Industrial & Manufacturing Engineering

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Application of Case Based Reasoning in a Website-based Expert System for Diagnosing Diseases in Catfish Marselina Anjelina Nuhi; Cecilia D. P. Binti Gabriel; Lidia Lali Momo
Jurnal Teknik Mesin, Industri, Elektro dan Informatika Vol. 4 No. 1 (2025): JURNAL TEKNIK MESIN, INDUSTRI, ELEKTRO DAN INFORMATIKA
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jtmei.v4i1.4722

Abstract

Diseases in catfish often become a significant problem in fish farming, which can cause major losses for farmers. To overcome this problem, a system is needed that can help diagnose diseases in catfish accurately and quickly. This research aims to develop a website-based expert system that uses the Case Based Reasoning (CBR) method to diagnose diseases in catfish. The CBR method allows the system to identify disease by comparing the symptoms experienced by catfish with data on previous cases that already exist in the knowledge base. This system consists of several main components, namely input data on catfish symptoms, case matching process, and presentation of disease diagnoses and solutions. System testing was carried out using symptom data collected from various cases of catfish disease that occurred in the field. The results of this research show that the CBR-based expert system is able to provide diagnoses that are appropriate to existing cases, and can be a useful tool for catfish farmers in detecting disease early and providing appropriate treatment. This system can be accessed online, making it easy for users to access information anytime and anywhere.
Sistem Pemesanan Produk pada PT. Talasi Weetabula Berbasis Web Lidia Kartini Ina; Cecilia D. P. Binti Gabriel; Maria Wilda Malo
Jurnal Teknik Mesin, Industri, Elektro dan Informatika Vol. 4 No. 1 (2025): JURNAL TEKNIK MESIN, INDUSTRI, ELEKTRO DAN INFORMATIKA
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jtmei.v4i1.4723

Abstract

A decision support system (DSS) is a tool that helps decision makers choose the optimal option based on predetermined standards. In human resource management, determining the eligibility of ASN (State Civil Servants) employees to receive pensions is crucial because it has an impact on worker welfare, career prospects, and state budget management. This study suggests the use of the Multi-Attribute Decision Making (MADM) approach to build a decision support system for assessing the eligibility of ASN employee pensions. The MADM method is a decision-making process that produces the best choices by considering a number of criteria and options. Retirement age, length of service, work performance, health, and other variables related to the applicable pension policy are some of the criteria considered in this study to assess pension eligibility. The system methodology consists of a number of steps, including determining the criteria, assigning weights to each criterion, and assessing alternatives based on these criteria using computational methods such as TOPSIS (Technique for Order Preference by Samelight to Ideal Solution) and AHP (Analytical Hierarchy Process). The evaluation findings will provide advice on employee eligibility for retirement or ability to continue working. By offering transparent and objective analysis, the developed technology is expected to direct the ASN employee retirement decision-making process and ensure that the decision-making is more accurate and in accordance with related regulations. Therefore, this approach can improve the effectiveness and efficiency of human resource management in government agencies.
Co-Authors Lidia Kartini Ina Lidia Lali Momo Maria Wilda Malo Marselina Anjelina Nuhi