EFFICIENCY OF THE COURSE PRACTICUM ASSISTANT SELECTION PROCESS USING BAYESIAN ALGORITHMS

Hartatik Hartatik

doi:10.53067/ijomral.v1i3.32

Authors

Hartatik Hartatik Universitas Sebelas Maret, Surakarta, Indonesia

DOI:

https://doi.org/10.53067/ijomral.v1i3.32

Keywords:

Cource Practicum, Bigdata, Posterior, Prior, Efficiency, Bayesian

Abstract

The selection of the Practicum Assistant Course is the main problem in the process of selecting the role of the practicum assistant in big data. In the process of big data, the process of selecting assistant laboratorium subjects pay attention to the processes that occur before in the prospective assistant lab practicum (previous distribution). In this study we use the Bayesian classification method for the selection of practicum assistant courses. The Bayesian algorithm is applied in the process of selecting a practicum asiststen which is received with prior knowledge and posterior . In this consideration, the initial (prior) data is used as a consideration to determine whether a student in a certain semester can become a practicum assistant in the appropriate course of interest. The benefits obtained are efficiency in choosing a practicum assistant with consideration of previous events, P (θ | x). Based on the results obtained, the results of this study show the efficiency of the selection based on the previous few who became the background of the candidates for the practicum assistant course

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