DOI: https://doi.org/10.21456/vol7iss1pp24-31

Sistem Evaluasi Jaminan Mutu Menggunakan Rule Based System Untuk Monitoring Mutu Perguruan Tinggi

*Sri Hartono  -  Kopertis Wilayah V Semarang, Indonesia

Citation Format:
Abstract

The needs for continuous quality improvement resulting in the more complex. The research aims to develop system of quality assurance evaluation using rule based system to monitor the quality of higher education. This process of the research begins by documenting the daily activity of study program which consists of lecturer data, research data, service data, staff data, student data, and infrastructure data into a database. The data were evaluated by using rule based system  by adopting rules on quality standards of study program of National Accreditation Board for Higher Education as the knowledge base. Evaluation process was carried out by using the forward chaining methods by matching the existing data to the knowledge base to determine the quality status of each quality standard. While the reccomendation process was carried out by using the backward chaining methods by matching the results of quality status to the desired projection of quality status to determine the nearest target which can be achieved. The result of the research is system of quality assurance evaluation with rule based system that is capable of producing an output system in the form of internal evaluation report and recommendation system that can be used to monitor the quality of higher education. 

Fulltext View|Download
Keywords: Quality Assurance Evaluation System; Monitoring; Daily Activity; Rule Based System; Forward Chaining; Backward Chaining.
Funding: Kopertis Wilayah VI Jawa Tengah

Article Metrics:

Article Info
Section: Research Articles
Language : ID
Recent articles
Implementasi Simple Additive Weighting Untuk Monitoring Aktivitas Perkuliahan Dengan Menggunakan Radio Frequency Identification Rule Based Reasoning Untuk Monitoring Distribusi Bahan Bakar Minyak Secara Online dan Realtime menggunakan Radio Frequency Identification Implementasi Rule Based Expert Systems untuk Realtime Monitoring Penyelesaian Perkara Pidana Menggunakan Teknologi Radio Frequency Identification More recent articles
  1. A Al-ajlan, A. (2015). The Comparison between Forward and Backward Chaining. International Journal of Machine Learning and Computing, 5(2). http://doi.org/10.7763/IJMLC.2015.V5.492
  2. Critien, L., & Khuman, A. (2014). A rule based system for diagnosing and treating chronic heart failure. Centre for Computational Intelligence. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6930178
  3. Dahria, M. (2012). Implementasi Inferensi Backward Chaining Untuk Mengetahui Kerusakan Monitor Komputer. Saintikom, 11(73)
  4. Engin, G., Aksoyer, B., Avdagic, M., Bozanlı, D., Hanay, U., Maden, D., & Ertek, G. (2014). Rule-based Expert Systems for Supporting University Students. Procedia Computer Science, 31, 22–31. http://doi.org/10.1016/j.procs.2014.05.241
  5. Eshete, A. B. (2009). Integrated Case Based and Rule Based Reasoning for Decision Support. Norwegian University of Science and Technology -Department of Computer and Information Science, (July), 1–100
  6. Kandil, M. S., Hassan, A. E., Asem, A. S., & Ibrahim, M. E. (2010). Prototype of Web2-based system for Quality Assurance Evaluation Process in Higher education Institutions. International Journal of Electrical & Computer Sciences, 10(02), 1–8
  7. Lephoto, A., & Kogeda, O. P. (2014). Modelling a Rule Based System for Medical Underwriting in an Insurance Industry. Proceedings of the World Congress on Engineering and Computer Science, I, 22–24
  8. Liu, H., & Parashar, M. (2005). Rule-based monitoring and steering of distributed scientific applications. International Journal of High Performance Computing and Networking, 3(4), 272–282. Retrieved from http://inderscience.metapress.com/index/5p15hej4bckrrgvj.pdf
  9. Luger, G. F. (2005). Artificial Intelligence Structures and Strategies for Complex Problem Solving. In Addison-Wesley (5. edition). Addison-Wesley
  10. Lukasiewicz, W., Teymourian, K., & Paschke, A. (2014). A Rule-Based System for Monitoring of Microblogging Disease Reports. Semantic Web: Eswc 2014 Satellite Events, 8798, 401–406. http://doi.org/10.1007/978-3-319-11955-7_56
  11. Robinson, W. N. (2005). Implementing Rule-Based Monitors within a Framework for Continuous Requirements Monitoring. HICSS ’05: 38th Annual Hawaii International Conference on System Sciences, 00(C), 188a–188a. http://doi.org/10.1109/HICSS.2005.306
  12. Shafiullah, G. M., Shawkat Ali, a. B. M., Thompson, A., & Wolfs, P. J. (2010). Rule-based classification approach for railway wagon health monitoring. Proceedings of the International Joint Conference on Neural Networks. http://doi.org/10.1109/IJCNN.2010.5596624
  13. Skalka, J., Drlik, M., & Svec, P. (2012). E-learning courses quality evaluation framework as part of quality assurance in higher education. Interactive Collaborative Learning (ICL), 2012 15th International Conference on, 1–5. http://doi.org/10.1109/ICL.2012.6402173
  14. Sharma, T., Tiwari, N., Kelkar, D. (2012). Study Of Difference Between Forward And Backward Reasoning. International Journal of Emerging Technology and Advanced Engineering, 2(10), 271–273

Last update:

No citation recorded.

Last update:

No citation recorded.