Analysis of the Influence of Training on Civil Servant Competency Using Apriori Algorithm

Raudatul Jannah; Novriyenni; Rusmin Saragih

doi:10.59934/jaiea.v5i3.2490

Authors

Raudatul Jannah STMIK KAPUTAMA
Novriyenni STMIK KAPUTAMA
Rusmin Saragih STMIK KAPUTAMA

DOI:

https://doi.org/10.59934/jaiea.v5i3.2490

Keywords:

Data Mining, Apriori Algorithm, Training, ASN Competencies

Abstract

Improving the competence of the State Civil Apparatus (ASN) is one of the important factors in supporting the effectiveness of the performance of government organizations and improving the quality of public services to the community. Good ASN competencies can help achieve organizational goals optimally. One of the efforts made to improve the competence of ASN is through the implementation of various training programs that are tailored to job needs and technological developments. However, not all training programs implemented are able to have an optimal impact on improving the competence of ASN. Therefore, an analysis is needed to find out the relationship between the training followed and the competencies produced. This study aims to analyze the influence of training on ASN competencies and apply an A priori algorithm in finding patterns of relationships between the type of training, the field of training, the level of relevance, and the competence of ASN in the Binjai City BKPSDM. The method used in this study is data mining with the association rule technique using an A priori algorithm. The ASN training data used comes from the Binjai City BKPSDM and is processed using the RapidMiner application. The analysis process was carried out based on support, confidence, and lift ratio values to produce association rules that show the relationship between research variables. The results showed that the best association rule obtained was "If the Relevance Level is Very Relevant, the Competence is Very Good" with a support value of 54%, confidence of 100%, and a lift ratio of 1.54. These results show a strong relationship between the level of relevance of training and the improvement of ASN competence. The more relevant the training provided to the ASN field of duties, the higher the competence that can be achieved. Thus, the A priori algorithm can be used effectively to analyze the influence of training on ASN competencies and assist the Binjai City BKPSDM in developing a training program that is more targeted, effective, and in accordance with the needs of ASN competency development.

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