Classification of Lung TB Levels by Region in Medan City Using Logistic Regression Algorithm
DOI:
https://doi.org/10.30865/jurikom.v12i4.8914Keywords:
Classification, Pulmonary TB, Medan City, Logistic Regression, K-MeansAbstract
The Indonesia Smart Program is a cash assistance for education aimed at elementary, middle, and high school students aged 6-21 who come from underprivileged families. In the selection process for prospective recipients of the Indonesia Smart Program at SMA Negeri 1 Kutalimbaru, several problems arose due to the still conventional data processing. This issue is primarily caused by technological limitations and the absence of a computerized system to process that data. As a result, the process is time-consuming and prone to high error rates. Therefore, a computer-based system is needed to assist in the Recommendation of Prospective Recipients of the Indonesia Smart Program. In this study, a combination of two methods was used, namely the Rank Order Centroid (ROC) method for criterion weighting and Additive Ratio Assessment (ARAS) for ranking. Based on the tests conducted on 180 data of students eligible to receive the Program Indonesia Pintar at SMA Negeri 1 Kutalimbaru, the ranking results established Restu (A142) in the first position as the most recommended Candidate Recipient of the Program Indonesia Pintar with a final score of “1”, with criteria including having a KIP Card “Yes”, having a KKS Card “Yes”, being an orphan “Orphan”, number of dependents “2”, parental income “No Income’. Thus, the ROC and ARAS methods prove to be suitable in assisting decision-making for recommendations for Candidates to Receive the Program Indonesia Pintar.
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