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All Journal JOMLAI: Journal of Machine Learning and Artificial Intelligence Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
Sundari Retno Andani
STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
Computer Science & IT Control & Systems Engineering Engineering

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Journal : JOMLAI: Journal of Machine Learning and Artificial Intelligence

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Implementation of K-Means Algorithm for Clustering Books Borrowing in School Libraries Daud Siburian; Sundari Retno Andani; Ika Purnama Sari
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 2 (2022): June
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (594.364 KB) | DOI: 10.55123/jomlai.v1i2.725

Abstract

The school library is an important resource in an effort to support the process of improving the quality of education in schools. Through the library a lot of information can be extracted and used for educational purposes. The library is expected to play its function as a vehicle for education, research, preservation, information, and recreation to improve the nation's intelligence. This study aims to cluster the borrowing of library books at SMA Assisi Pematangsiantar. The research data was obtained from the school library. The algorithm used for the clustering process is K-Means Clustering which is one of the data mining algorithms. The data was processed using Microsoft Excel and Rapid Miner 5.3 to determine the value of the centroid in 2 clusters, namely the highest and lowest clusters. Based on manual calculations with Microsoft Excel and testing with Rapid Miner, this study resulted in the same value, namely the highest cluster produced 6 types of books including Mathematics,. Geography, Chemistry, Civics, Physical Education and Computers. As for the lowest cluster, there are 6 types of books, namely Indonesian, English, Biology, Physics, Religion and Cultural Arts. So it can be concluded that the K-Means method in this study can cluster school library book borrowing well, referring to manual calculations and testing which have the same results
Implementation of the SMART Algorithm in Determining Patient Satisfaction Levels with Outpatient Services Patar Simbolon; Muhammad Zarlis; Sundari Retno Andani; Fitri Anggraini
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 2 No. 1 (2023): March
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jomlai.v2i1.159

Abstract

This study aims to implement the SMART algorithm in determining the level of patient satisfaction with outpatient services at Vita Insani Hospital Pematangsiantar. This study uses four evaluation criteria, namely speed of service, friendliness of staff, clarity of information, and comfort of the room. There are nine alternatives evaluated, namely registration, polyclinic, doctor, cashier, laboratory, radiology, pharmacy, emergency room, and security guard. This study uses the SMART method (Simple Multi-Attribute Rating Technique) in determining the level of patient satisfaction with outpatient services. Calculations are performed either manually or computerized. The results showed that the two calculation methods yielded the same results, namely alternative A9 (Security Guard) was selected as an alternative that needed to improve its services in improving outpatient services at Vita Insani Hospital. By using the SMART algorithm, it is hoped that the hospital can identify service areas that need to be improved to increase patient satisfaction in outpatient services. This research provides valuable information for hospital management in making strategic decisions to improve service quality and meet patient expectations.
Co-Authors Daud Siburian Fitri Anggraini Ika Purnama Sari Muhammad Zarlis Patar Simbolon