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Nadya, Nadya Septiani
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Computer Science & IT

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Implementasi Data Mining Dalam Mengelompokkan Tingkat Kepuasan Pemakaian Jasa Cleaning Service Dengan Menggunakan Algoritma K-Means Clustering Nadya, Nadya Septiani; Wahyuni, Sri
Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v5i4.1729

Abstract

Pinang Jaya Abadi Indonesia is a company providing cleaning services to various sectors, including hospitals, commercial businesses, offices, and shopping centers. However, problems arise when complaints regarding the quality of service provided by its employees occur. To improve service quality and assess customer satisfaction with the offered services, a system capable of accurately and efficiently clustering customer satisfaction data is needed. As a solution, this study applies the K-Means Clustering algorithm in the field of Data Mining to cluster customer satisfaction data regarding the cleaning services provided by PT. Pinang Jaya Abadi Indonesia. The K-Means algorithm was chosen for its ability to cluster data quickly and effectively, and its proven efficiency in various data clustering cases. By using this algorithm, the study aims to produce more structured and informative data clusters, providing a clearer understanding of customer satisfaction levels. The results of this study show that the system designed using the K-Means Clustering algorithm can effectively cluster customer satisfaction data, yielding efficient and accurate results. This system can serve as a tool for PT. Pinang Jaya Abadi Indonesia to enhance service quality and minimize customer complaints by focusing more on clusters with low satisfaction levels.
Analisis Tren Pendaftaran Siswa Menggunakan Big Data di Yayasan Pendidikan Raksana Medan Nadya, Nadya Septiani; Iqbal, Muhammad
Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v5i4.1744

Abstract

Yayasan Pendidikan Raksana Medan is an educational institution encompassing SMP, SMA, SMK-1, and SMK-2 levels. With an increasing number of students each year, analyzing student enrollment data has become crucial for strategic planning and decision-making. This study aims to analyze student enrollment trends using a Big Data approach to identify enrollment patterns, study program preferences, and factors influencing the number of applicants. The data used includes enrollment information from the past five years, such as demographic data, program choices, and enrollment timing. The analysis was conducted using data mining methods and data visualization to identify specific trends and patterns. The results of the study indicate a significant increase in applicants to vocational programs, with the majority of applicants coming from areas around Medan. These findings are expected to assist Yayasan Pendidikan Raksana Medan in improving marketing strategies and curriculum adjustments based on student and community demand
Co-Authors Muhammad Iqbal Sri Wahyuni