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Analysis and Visualization of Advertising Sales Data Using Python Software Through an Internship Program Ardiansyah, Muhammad Naufal; kalfin
International Journal of Mathematics, Statistics, and Computing Vol. 2 No. 2 (2024): International Journal of Mathematics, Statistics, and Computing
Publisher : Communication In Research And Publications

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijmsc.v2i2.76

Abstract

This research discusses the use of data visualization as a tool for analyzing and presenting information effectively. The main goal of this research is visualization that allows better understanding of complex data. In this context, research explores various data visualization techniques, including the use of bar charts, correlation heatmaps, and interactive technology to present information intuitively. In improving decision-making abilities, identifying patterns or trends, and exploring relationships and insights contained in large and heterogeneous datasets. The research methodology includes comparative analysis of various visualization methods, user experiments, and the application of new techniques to evaluate the effectiveness and usefulness of data visualization in advertising video sales data at PT XXX. Based on the research results, it was found that data visualization involves presenting data information in graphic or image form to facilitate understanding. This helps in explaining the facts and determining the steps that need to be taken. The research results are expected to provide in-depth insight into the development of data visualization techniques. The results of this data visualization can be widely applied in various fields, especially creative, marketing and sales management.
Sistem Deteksi Gerakan Kecurangan UTBK Real-Time dengan YOLOv8 dan Optical Flow Ardiansyah, Muhammad Naufal; Suryahadi, Farrel Zikri; Pratama, Hendrico Edhent Surya; Sari, Anggraini Puspita
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 11 No. 1 (2026): January 2026
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiska.5365

Abstract

Integrity and honesty are fundamental aspects of education, including the implementation of the Computer-Based Written Examination (UTBK). Conventional exam supervision is considered less effective in monitoring participants’ behavior due to the limitations in human observation capabilities and consistency. This study develops a real-time cheating-detection system based on camera input by integrating the YOLOv8 algorithm with Farnebäck optical flow. The YOLOv8 algorithm identifies participants’ body poses and activities directly from video footage, while Optical Flow analyzes the direction and motion patterns between frames over time. The system is designed to recognize various suspicious poses such as head-turning, bowing, and cheating-related gestures that indicate potential dishonesty. All detection results are automatically recorded in an SQLite database, complete with timestamps and visual evidence. Experimental results show that the system achieves 94.3% accuracy in detecting suspicious movements. The combination of both methods also helps maintain detection stability when keypoints are not consistently captured in some frames. Additionally, the system is equipped with a graphical user interface (GUI) to facilitate easier monitoring and analysis. These results demonstrate that a pose-and-motion analysis-based approach offers an intelligent and efficient solution for enhancing digital supervision of UTBK examinations.