Research Article
Particle Swarm Optimization Based C4.5 for Teacher Performance Classification
@INPROCEEDINGS{10.4108/eai.18-7-2019.2288586, author={Abdul Rahman Kadafi and Windu Gata}, title={Particle Swarm Optimization Based C4.5 for Teacher Performance Classification}, proceedings={Proceedings of The 2nd International Conference On Advance And Scientific Innovation, ICASI 2019, 18 July, Banda Aceh, Indonesia}, publisher={EAI}, proceedings_a={ICASI}, year={2019}, month={11}, keywords={data mining c45 pso soft competencies}, doi={10.4108/eai.18-7-2019.2288586} }- Abdul Rahman Kadafi
Windu Gata
Year: 2019
Particle Swarm Optimization Based C4.5 for Teacher Performance Classification
ICASI
EAI
DOI: 10.4108/eai.18-7-2019.2288586
Abstract
The role of teachers on management of learning to meet the standards of determined competence, is one of key to success. An integrated Islāmic school has a unique standard of teacher competence, there are soft competencies and hard competencies. This research has to get better of classification algorithm to find the pattern of linkage between soft competencies and teacher performance assessed based on hard competencies aspect. The algorithm used is C4.5 algorithm with attribute selection using particle swarm optimization (PSO). The results showed that C4.5 algorithm with PSO resulted accuracy 79.70% with kappa value of 0.528 and 0.19 (enough class). The soft competencies attribute has the highest influence on teacher performance is achievement orientation. From the result of accuracy and kappa, can be concluded that in classification data of teacher for performance aspect and soft competencies. The dominant factor that influence teacher performance base on soft competencies is achievement orientation, then conseptual thinking and concenrn for order, communication and organizational commitment.