Expert System to Determine Learning Style Using Forward Chaining Method

##plugins.themes.academic_pro.article.main##

Dela Yunita Cahya
Shinta Oktaviana

Abstract

Abstract - The expert system of learning modalities determination is a system that adopts the knowledge of an educational psychologist in determining the learning modalities that are appropriate to the child's personality. This expert system is made by forward chaining method and uses the expert Certainty Factor (CF) value. The purpose of this expert system is to prove that forward chaining method can be implemented in making this expert system. Furthermore, expert system can provide benefits to assist an educational psychology in Bahana Psikologi Pelangi (BPP) in performing the determination test of visual modalities, auditory or kinesthetic. Data obtained by conducting interviews and based on questionnaires in BPP in determining a person's learning modalities. Implementation of forward chaining method with the implementation of CF value is important in determining the conclusion of modalities and suggestions that will be recommended. The end result of this expert system is the highest CF value of each modality. Tests on the system performed by comparing the conclusions of modalities on expert systems with the conclusion of modalities on the calculation of manual questionnaires in BPP. Based on the 53 questionnaires used, there are 42 data showing the same modalities conclusion with manual process, while 11 of them show different result because of the priority of CF value in expert system.

##plugins.themes.academic_pro.article.details##

How to Cite
Cahya, D. Y., & Oktaviana, S. (2018). Expert System to Determine Learning Style Using Forward Chaining Method. MULTINETICS, 4(1), 49–56. https://doi.org/10.32722/multinetics.v4i1.1115

References

  1. Arisandi, D. And Saputra, A., 2015. Aplikasi Sistem Pakar Untuk Menentukan Gaya Belajar Anak Usia Sekolah Dasar. Digital Zone: Jurnal Teknologi Informasi Dan Komunikasi, 6(2).
  2. Broto, A. S., 2010. Perancangan Dan Implementasi Sistem Pakar Untuk Analisa Penyakit Dalam, Semarang: S.N.
  3. Dony Novaliendry. 2015. The Expert System Application For Diagnosing Human Vitamin Deficiency Through Forward Chaining Method. IEEE, P. 53.
  4. T.Sutojo., 2011. Kecerdasan Buatan. Yogyakarta: ANDI.
  5. Sachin Kamley, S. J. A. R. T., 2016. Performance Comparison Between Forward Chaining And Backward Chaining Rule Based Expert System Approaches Over Global Stock Exchanges. International Journal Of Computer Science AndInformation Security, Volume 14, P. 74.
  6. Lokman .2014. Personal Financial Planner: A Mobile Application That Implementation Forward Chaining Technique For Notification Mechanism.IEEE Symposium On Computer Application & Industrial Electronics (ISCAIE),P. 65
  7. Mohammad Mudassar. 2016. Computing The Impact Of Security Attack On Network Using Fuzzy Logic. International Research Journal Of EngineeringAnd Technology (IRJET), P. 1582.
  8. Norah Md Noor, 2014. Video Based Learning Embedded With Cognitive Load Theory: Visual, Auditory, And Kinaesthetic Learners' Perspectives.International Conference On Teaching And Learning In Computing And Engineering, P. 59.