Journal of Informatics, Electrical and Electronics Engineering
Fokus kajian Journal of Informatics, Electrical and Electronics Engineering, yaitu: 1. Control System, 2. Artificial Intelligence, 3. Informatics Engineering, 4. Electronics, 5. Advanced energy material, 6. Automatic power control, 7. Battery technology, 8. Distributed generation, 9. Distribution system, 10. Electric power generation, 11. Electric vehicle, 12. Electrical machine, 13. Energy optimization, 14. Energy conversion, 15. Energy efficiency, 16. Energy exploitation, 17. Energy exploration, 18. Energy management, 19. Energy mitigation, 20. Energy storage, 21. Energy system, 22. Fault diagnostics, 23. Green energy, 24. Green technology, 25. High voltage, 26. Insulation technology, 27. Intelligent power optimization, 28. Monitoring operation, 29. Motor drives, 30. Natural energy source, 31. Power control, 32. Power data transaction, 33. Power economic, 34. Power electronics, 35. Power engineering, 36. Power generation, 37. Power optimization, 38. Power quality, 39. Power system analysis, 40. Power system information, 41. Power system optimization, 42. Protection system, 43. Renewable energy, 44. SCADA, 45. Security operation, 46. Smart grid, 47. Stability system, 48. Storage system, and 49. Transmission system
Articles
5 Documents
Search results for
, issue
"Vol. 3 No. 2 (2023): Desember 2023"
:
5 Documents
clear
<![CDATA[Penerapan Metode Simple Additive Weighting dalam Penentuan Prioritas Program Pembangunan Daerah ]]>
<![CDATA[Siagian, Jaya Sari Anggraini]]>;
<![CDATA[Purba, Bister]]>;
<![CDATA[Ambarsari, Erlin Windia]]>;
<![CDATA[Rohayani, Hetty]]>
<![CDATA[ Journal of Informatics, Electrical and Electronics Engineering Vol. 3 No. 2 (2023): Desember 2023 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.47065/jieee.v3i2.1542
<![CDATA[Regional governments and institutions related to preparing regional development programs experience several obstacles in determining regional development work plans, one of which is difficulty in determining development priorities that are in line with regional regulations. The effectiveness and efficiency of implementing regional development programs depends on the accuracy of the data collected. One of the challenges faced by the Medan City Regional Development Planning Agency is the lack of consideration of the priority scale and fairness in the regional development stages, as well as the absence of a system that can help determine the priority scale. Therefore, this research requires a decision support system (DSS). In the SPK, there are many solution methods that can be used according to the needs of each problem. In this research, to determine regional development program priorities, the SAW method will be used. Of the 10 proposed regional programs, only one will be a priority development program. After applying the SAW method in making decisions, the development program that has the highest priority level is the highway construction program with the final result obtained, namely 0.77705.]]>
<![CDATA[Implementasi Metode EDAS Dalam Penilaian Kinerja Dosen Pada Masa Pandemi Covid-19 dengan Pembobotan Entropy ]]>
<![CDATA[Indini, Dwina Pri]]>;
<![CDATA[Siregar, Tesa Aurelia]]>;
<![CDATA[Utomo, Dito Putro]]>
<![CDATA[ Journal of Informatics, Electrical and Electronics Engineering Vol. 3 No. 2 (2023): Desember 2023 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.47065/jieee.v3i2.1613
<![CDATA[Along with the development of technology that makes online learning run well, but the enthusiasm for student learning is not like when face to face and there are still many students who do not take various courses so that students' knowledge abilities are greatly decreased. When online learning takes place, it is very necessary for a lecturer's performance to arouse students' enthusiasm in participating in online learning. Because during this pandemic the role of lecturers is very necessary to develop an innovation and be able to make students not bored in participating in online learning. And also in terms of the performance appraisal process, several problems often occur, namely the speed in the performance appraisal process and also the accuracy of the performance appraisal. In assessing the performance of lecturers during online learning, there are several criteria including Discipline, Delivery of Materials, Interaction, Discussion Questions and Answers and Punctuality. Based on these problems, a decision support system is needed as a problem solving technique and is assisted by a method that can produce an accurate final value. The method is the Evaluation Based On Distance From Average Solution (EDAS) and Entropy method which is very helpful in generating weight values ??from alternative data and criteria so as to get the final results obtained in Alternative L9 with a value of 0.31025 on behalf of Surya Darma Nst, M. Kom.]]>
<![CDATA[Optimalisasi Penerapan Metode TOPSIS dalam Penentuan Dosen Berprestasi ]]>
<![CDATA[Purba, Rohan Kristini]]>;
<![CDATA[Sitorus, Jepri Saprianto]]>;
<![CDATA[Syahrizal, Muhammad]]>
<![CDATA[ Journal of Informatics, Electrical and Electronics Engineering Vol. 3 No. 2 (2023): Desember 2023 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.47065/jieee.v3i2.1614
<![CDATA[The role of lecturers, especially for students, really determines the quality of the students themselves. Therefore, to create a quality future generation, qualified lecturers are also needed. However, currently there are many lecturers who only work as lecturers, but do not meet the criteria for a good lecturer. Giving awards to lecturers who excel is one of the efforts that can be done in order to create work motivation and increase the desire of every lecturer to become a lecturer who has good qualifications. However, the problem is to determine the best lecturers in a university, it will be very difficult if done manually. To make it easier for leaders to assess lecturers who deserve to be called achievers or not, a decision support system (SPK) is needed, where this SPK acts as a support for the leadership's reasons why the leader chooses someone as an outstanding lecturer. Decision Support System (DSS) is a system whose work uses a computer, where this system uses various methods which ultimately produce information in the form of a decision. the method used in this study is the TOPSIS method. The TOPSIS method is one of the DSS methods whose purpose is to produce an alternative with the highest value as an alternative recommendation. The results obtained in this study amounted to 0.5308 on behalf of Mesran as an alternative recommendation.]]>
<![CDATA[MCDM Using Multi-Attribute Utility Theory and PIPRECIA in Customer Loan Eligibility Recommendations ]]>
<![CDATA[Setiawansyah]]>;
<![CDATA[Sintaro, Sanriomi]]>;
<![CDATA[Aldino, Ahmad Ari]]>
<![CDATA[ Journal of Informatics, Electrical and Electronics Engineering Vol. 3 No. 2 (2023): Desember 2023 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.47065/jieee.v3i2.1628
<![CDATA[Customer loan eligibility recommendations are an important step in the risk and financial assessment process. To ensure business continuity and customer satisfaction, it is important for financial institutions to consider several key factors. Problems in determining lending include various aspects that include credit risk that is difficult to assess appropriately, insufficient information about potential borrowers, potential fraud that can harm lenders. Regardless, financial institutions must ensure sound risk management and comply with applicable regulations and compliance standards to minimize potential losses and maintain fairness in decision-making related to lending. Cooperatives act as institutions that provide access to loans with more flexible terms than conventional financial institutions. The loan application process involves evaluating the customer's eligibility, which includes an analysis of financial condition, credit history, and repayment capacity. The contribution of this study provides a recommendation for savings and loan cooperatives in lending to customers using a decision support system model. The purpose of this study is to evaluate and compare customer loan feasibility using a combination of Multi-Criteria Decision Making (MCDM) methods, namely Multi-Attribute Utility Theory (MAUT) and Pivot Pairwise Relative Criteria Importance Assessment (PIPRECIA). This study aims to determine the ability of both methods to provide a comprehensive understanding of loan feasibility by considering a number of relevant criteria. The results of the customer loan eligibility rating recommend rank 1 with a final value of 0.5127 obtained by Customer K, rank 2 with a final value of 0.432 obtained by Customer I, and rank 3 with a final value of 0.3559 obtained by Customer F.]]>
<![CDATA[Analisis Penerapan Data Mining Terhadap Kasus Positif Covid-19 Menggunakan Metode K-Means Clustering ]]>
<![CDATA[Azhari, Ridhan]]>;
<![CDATA[Hartama, Dedy]]>;
<![CDATA[Lubis, Muhammad Ridwan]]>;
<![CDATA[Nasution, Della Fatricia]]>;
<![CDATA[Windarto, Agus Perdana]]>
<![CDATA[ Journal of Informatics, Electrical and Electronics Engineering Vol. 3 No. 2 (2023): Desember 2023 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.47065/jieee.v3i2.1760
<![CDATA[This study has problems such as the absence of the use of the K-means clustering algorithm for data on positive COVID-19 cases in the Indonesian province. The purpose of this study is to apply the K-means clustering method in finding the closest distance to produce the lowest and highest clusters of data on positive COVID-19 cases in the Indonesian province. K-means is one of the algorithms in the non-hierarchical Clustering technique that tries to partition the existing data in the form of one or more clusters. The results obtained from the k-means clustering method produced 2 clusters, namely the lowest cluster C1 = 30 items while the highest cluster C2 = 4 items. This research can be used as a reference and can be further developed with other clustering methods or algorithms such as k-medoid in order to get a comparison of results and steps to use algorithms related to clustering.]]>
