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ROC and COPRAS Algorithms in a Decision Support System for Employee Career Assessment Ritonga, Fazrul Umri; Fakhriza, M.; Harahap, Aninda Muliani
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 4 (2024): Articles Research October 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i4.4716

PT. Union Confectionery, a long-established company in the confectionery production industry, had encountered significant challenges in managing employee career progression, including transfers, demotions, and promotions. The primary issue faced was the difficulty in conducting objective employee performance assessments and determining the appropriate criteria for career development. These assessments involved various complex factors such as work experience, discipline, education level, age, job performance, attendance, teamwork, and work ethics. To address these challenges, this study proposed the implementation of a web-based Decision Support System (DSS) utilizing the Rank Order Centroid (ROC) method for criteria weighting and the Complex Proportional Assessment (COPRAS) method for ranking decisions. The implementation of this system was expected to assist the management of PT. Union Confectionery in making more accurate and transparent decisions, while also improving employee satisfaction and operational efficiency. This research also compared previous studies that used similar methods for performance assessment, albeit with a narrower focus, specifically at the supervisory level. The findings from this study were anticipated to provide a comprehensive and innovative solution for employee career management across all levels of PT. Union Confectionery’s organization, as well as contribute to the development of more effective human resource management practices.

Mobile Platform for Building Applications at the Integrated Services Office Medan City Astuti, Andriani Dwi; Fakhriza, M.; Harahap, Aninda Muliani
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 4 (2024): Articles Research October 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i4.4769

The advancement of computer technology has developed rapidly and has been applied in various aspects of life. At that time, computers were considered one of the most efficient tools in supporting technological development. At the Office of Investment and One-Stop Integrated Services (OI-OIS) in Medan City, the process of applying for Building Permits (BP) was still conducted manually and had not been computerized, resulting in slow and inefficient licensing processes. Applicants were required to fill out forms manually and deliver physical documents to the village and sub-district offices, which extended processing times. Furthermore, application reports were often piled up, hindering prompt and accurate handling. The lack of efficiency in managing applicant data further exacerbated the situation and slowed down the completion of applications. Therefore, an integrated digital system was needed to expedite and facilitate the submission and management of IMB applications. This research aimed to develop an Android-based Information System for Building Permit Applications at DPMPTSP in Medan City using the R&D (Research and Development) method. It was hoped that this application would make it easier for staff to manage IMB application data. The research results indicated that the development of the Android-based Information System for Building Permit Applications successfully addressed the issues encountered in the previously manual IMB application process. This application expedited and simplified the filling out and submission of applications, eliminating the need for applicants to deliver physical documents. Additionally, the management of applicant data became more efficient and computerized, reducing the backlog of reports and speeding up the verification process.

The Application of the FMADM Electre Algorithm in Diagnosing the Level of Drug Addiction in Adolescents Muchain, Alfira Nafhan; Zufria, Ilka; Fakhriza, M.
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 1 (2025): Article Research January 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i1.5151

Drug abuse among adolescents was difficult to identify early without official examinations, while manual methods were often inaccurate. The process of determining rehabilitation also faced challenges due to the lack of technology-based support systems capable of effectively analyzing the level of addiction and type of drug used, resulting in rehabilitation that was often not well-targeted. To address this issue, the algorithm was utilized to diagnose drug addiction in adolescents by providing scores or rankings indicating addiction levels: scores of 1 and 2 represented mild addiction, 3 and 4 indicated moderate addiction, and 5 or higher represented severe addiction. The FMADM-ELECTRE algorithm recommended various types of rehabilitation actions for recovery. It offered precise evaluation ranges and scores, simplifying the classification and determination of appropriate detoxification measures for each type of drug-addicted adolescent. This system classified three levels of drug addiction among adolescents, corresponding to three stages of rehabilitation for drug addicts: non-medical (social) rehabilitation, medical rehabilitation (detoxification), and aftercare (post-rehabilitation). Additionally, the web-based support system was designed to be accessible across various devices, including laptops, computers, tablets, and smartphones, facilitating quicker and more efficient decision-making for relevant institutions. This approach also integrated multi-criteria methods to ensure fairness and accuracy in analysis, supporting a comprehensive rehabilitation process.

Application of Data Mining with C5.0 Algorithm to Recommend Prosperous Family Card (KKS) Recipients Fadilla, Nurul; Zufria, Ilka; Fakhriza, M.
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 2 (2025): Research Article, Volume 7 Issue 2 April, 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i2.5913

Poverty is a social problem that still often occurs in various regions in Indonesia, including in Silau Laut District which consists of several villages such as Bangun Sari, Silo Bonto, Silo Lama, Lubuk Palas, and Silo Baru. Although the area is quite large, there are still many families who are classified as poor and unable to meet their basic needs. To overcome this, the government launched the Prosperous Family Card (KKS) program as a form of social assistance. However, the process of determining prospective KKS recipients still faces various obstacles, such as a random selection method based on data sent by each village to the central government. This raises concerns about the inaccuracy of the target in the distribution of aid, so that the aid is not received by families who really need it. In addition, a lot of data has not been utilized optimally in the selection process. Therefore, this study aims to design a website-based information system that can help Silau Laut District in providing recommendations for prospective KKS assistance recipients by utilizing data mining techniques. The algorithm used is C5.0, because it is able to produce a decision tree with high accuracy, while the system development method used is Rapid Application Development (RAD) to accelerate the system development process. The result of this research is an information system that can process community data and provide recommendations for prospective KKS assistance recipients in a more objective and targeted manner in the next period.

Expert System Based on K-Nearest Neighbor for Oil Palm Fertilizer Application Optimization Triutami, Anggun; Fakhriza, M.
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 3 (2025): Articles Research July 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i3.6092

This study aims to develop an expert system utilizing the K-Nearest Neighbor (KNN) algorithm to recommend suitable fertilizers for oil palm plants based on soil conditions, climate, and plant age. A quantitative approach was employed, involving literature review, data collection, model development, and evaluation. Data were obtained from PT. Nusantara Plantation IV Torgamba Plantation, including variables such as soil pH, dolomite, NPK, urea application, and crop yields. The KNN model was optimized with a K-value of 6 and evaluated using metrics including accuracy (63.63%), precision, recall, F1-score, Mean Absolute Error (MAE: 1995.38), and Mean Squared Error (MSE: 5,257,254.73). The system demonstrates the ability to provide fertilizer recommendations by identifying similarities in historical data, though further accuracy improvements are possible. The practical implications of this research include assisting farmers in optimizing fertilizer selection, enhancing productivity, and minimizing environmental impact. Future studies could explore the integration of additional variables or alternative algorithms such as Decision Tree or Naive Bayes to improve performance.

Apriori Algorithm to Predict Availability of Beauty Products Hasibuan, Maria Hikmah; Fakhriza, M.
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4259

This study introduces the Apriori algorithm in beauty product availability prediction system as a solution to enhance stock prediction accuracy and mitigate inventory risks in the beauty industry. By applying data mining technology, specifically the Apriori algorithm, Kazana Kosmetik aims to gain insights into consumer purchasing patterns to optimize operations. The research analyzes transaction data to identify key buying patterns and improve stock management strategies. The results reveal seven main purchasing patterns with an average confidence value of 0.414, offering valuable guidance for Kazana Kosmetik in inventory control and marketing tactics. By leveraging data mining techniques, companies like Kazana Kosmetik can streamline sales strategies and enhance customer satisfaction. This research underscores the effectiveness of the Apriori algorithm in predicting beauty product availability and its potential to revolutionize operational efficiency in the cosmetics market.

ROC and COPRAS Algorithms in a Decision Support System for Employee Career Assessment Ritonga, Fazrul Umri; Fakhriza, M.; Harahap, Aninda Muliani
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 4 (2024): Articles Research October 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i4.4716

PT. Union Confectionery, a long-established company in the confectionery production industry, had encountered significant challenges in managing employee career progression, including transfers, demotions, and promotions. The primary issue faced was the difficulty in conducting objective employee performance assessments and determining the appropriate criteria for career development. These assessments involved various complex factors such as work experience, discipline, education level, age, job performance, attendance, teamwork, and work ethics. To address these challenges, this study proposed the implementation of a web-based Decision Support System (DSS) utilizing the Rank Order Centroid (ROC) method for criteria weighting and the Complex Proportional Assessment (COPRAS) method for ranking decisions. The implementation of this system was expected to assist the management of PT. Union Confectionery in making more accurate and transparent decisions, while also improving employee satisfaction and operational efficiency. This research also compared previous studies that used similar methods for performance assessment, albeit with a narrower focus, specifically at the supervisory level. The findings from this study were anticipated to provide a comprehensive and innovative solution for employee career management across all levels of PT. Union Confectionery’s organization, as well as contribute to the development of more effective human resource management practices.

Mobile Platform for Building Applications at the Integrated Services Office Medan City Astuti, Andriani Dwi; Fakhriza, M.; Harahap, Aninda Muliani
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 4 (2024): Articles Research October 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i4.4769

The advancement of computer technology has developed rapidly and has been applied in various aspects of life. At that time, computers were considered one of the most efficient tools in supporting technological development. At the Office of Investment and One-Stop Integrated Services (OI-OIS) in Medan City, the process of applying for Building Permits (BP) was still conducted manually and had not been computerized, resulting in slow and inefficient licensing processes. Applicants were required to fill out forms manually and deliver physical documents to the village and sub-district offices, which extended processing times. Furthermore, application reports were often piled up, hindering prompt and accurate handling. The lack of efficiency in managing applicant data further exacerbated the situation and slowed down the completion of applications. Therefore, an integrated digital system was needed to expedite and facilitate the submission and management of IMB applications. This research aimed to develop an Android-based Information System for Building Permit Applications at DPMPTSP in Medan City using the R&D (Research and Development) method. It was hoped that this application would make it easier for staff to manage IMB application data. The research results indicated that the development of the Android-based Information System for Building Permit Applications successfully addressed the issues encountered in the previously manual IMB application process. This application expedited and simplified the filling out and submission of applications, eliminating the need for applicants to deliver physical documents. Additionally, the management of applicant data became more efficient and computerized, reducing the backlog of reports and speeding up the verification process.

The Application of the FMADM Electre Algorithm in Diagnosing the Level of Drug Addiction in Adolescents Muchain, Alfira Nafhan; Zufria, Ilka; Fakhriza, M.
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 1 (2025): Article Research January 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i1.5151

Drug abuse among adolescents was difficult to identify early without official examinations, while manual methods were often inaccurate. The process of determining rehabilitation also faced challenges due to the lack of technology-based support systems capable of effectively analyzing the level of addiction and type of drug used, resulting in rehabilitation that was often not well-targeted. To address this issue, the algorithm was utilized to diagnose drug addiction in adolescents by providing scores or rankings indicating addiction levels: scores of 1 and 2 represented mild addiction, 3 and 4 indicated moderate addiction, and 5 or higher represented severe addiction. The FMADM-ELECTRE algorithm recommended various types of rehabilitation actions for recovery. It offered precise evaluation ranges and scores, simplifying the classification and determination of appropriate detoxification measures for each type of drug-addicted adolescent. This system classified three levels of drug addiction among adolescents, corresponding to three stages of rehabilitation for drug addicts: non-medical (social) rehabilitation, medical rehabilitation (detoxification), and aftercare (post-rehabilitation). Additionally, the web-based support system was designed to be accessible across various devices, including laptops, computers, tablets, and smartphones, facilitating quicker and more efficient decision-making for relevant institutions. This approach also integrated multi-criteria methods to ensure fairness and accuracy in analysis, supporting a comprehensive rehabilitation process.

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