Komparasi Algoritma SVM Dan SVM Berbasis PSO Dalam Menganalisis Kinerja Guru SMAN 3 Selong
DOI:
https://doi.org/10.29408/jit.v2i2.1446Keywords:
PSO, SVM Algorithm, Teacher PerformanceAbstract
Teachers have an important role in printing quality students, so that there is a need for good performance. teacher performance is assessed from how the duties and responsibilities are carried out as educators. SMAN 3 selong is one of the educational institutions in East Lombok Regency, in measuring the performance of the headmaster of SMAN 3 Selong, usually looking at attendance data and the number of lesson hours, this causes the school principal to assess the teacher's performance is not effective so it needs to be built a system that can help school principals assess teacher performance. The purpose of this study is to analyze the performance of teachers of SMAN 3 Selong so that the performance criteria of teachers who teach well and are good enough can be known. To help the process of analyzing teacher performance accurately, a method of data mining is needed by applying a support vector machine (SVM) algorithm based on particle swarm optimization (PSO). Based on the results of the experiments conducted using the PSO-based SVM (support vector machine) method (particle swarm optimization), by training 55 data records, 29 teachers were expected to be good performing teachers, 25 teachers with fairly good performance and 1 teacher It is estimated that it is quite good but has a good performance, with an accuracy of 98.33%.
DOI : 10.29408/jit.v2i2.1446
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