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All Journal EINSTEIN (E-JOURNAL) Journal of Computer Science and Technology Application
Yul Ifda Tanjung
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Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Electrical & Electronics Engineering Materials Science & Nanotechnology Mechanical Engineering Physics Other

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PROTOTIPE SAJADAH OTOMATIS ARAH KIBLAT DENGAN MIKROKONTROLER ARDUINO Abdul Rafid Fakhrun Gani; Yul Ifda Tanjung; Abdul Rasyid Fakhrun Gani; Aji Ibnu Khair; Muhammad Jaka Maulana; Ilham Sidiq
EINSTEIN (e-Journal) Vol 10, No 1 (2022): EINSTEIN (e-Journal)
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (305.455 KB) | DOI: 10.24114/einstein.v10i1.27801

Abstract

Prayer is an obligation for Muslims in the context of worship, which means that a Muslim is obliged to pray even though he is in a vehicle. In carrying out prayers, there are several conditions for valid prayer, including facing the Qibla direction, scholars argue that facing the Qibla direction is a valid condition for prayer. However, when a Muslim prays in a vehicle, the relative qibla direction of the place changes as the vehicle turns direction. With the aim of making it easier for Muslims to carry out prayers in a vehicle "automatic prayer rug prototype with an Arduino microcontroller" using a CMPS 12 sensor as a Qibla direction detector and assisted by a dc motor that can direct the Qibla direction when the vehicle turns automatically.
A Framework for Mining Customer Data in Management Information Systems Untung Rahardja; Lutfiani, Ninda; Agung Rizky; Yul Ifda Tanjung; Evans, Richard
CORISINTA Vol 3 No 1 (2026): February
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/m5qymx32

Abstract

The exponential growth of customer data within Management Information Systems (MIS) has generated an urgent need for structured analytical approaches capable of transforming raw information into valuable insights that support decision-making across various organizational processes. This study aims to develop a comprehensive and systematic framework for mining customer data in MIS by integrating preprocessing procedures, machine learning algorithms, and model evaluation techniques into a unified analytical workflow. Using the Design Science Research methodology, the framework was designed based on existing data mining standards, developed through iterative refinement, and demonstrated using a customer-behavior dataset processed with clustering, classification, and association rule mining techniques. The findings reveal that the proposed framework improves data quality, enhances segmentation accuracy, and strengthens predictive capability, enabling MIS to deliver deeper insights into customer behavior, purchasing tendencies, and potential churn risks. Experimental results show that combining K-Means, Random Forest, and Apriori algorithms yields more comprehensive and reliable patterns compared to using a single analytical technique. The outcomes of this research highlight the practical significance of applying an integrated data mining approach in MIS, allowing organizations to optimize marketing strategies, personalize services, and make more informed managerial decisions. Overall, this study contributes to the field by offering a scalable, adaptable, and effective framework for implementing customer data mining within real-world MIS environments.
Co-Authors Abdul Rafid Fakhrun Gani Abdul Rasyid Fakhrun Gani Agung Rizky Aji Ibnu Khair Evans, Richard Ilham Sidiq Muhammad Jaka Maulana Ninda Lutfiani Untung Rahardja