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All Journal JTP - Jurnal Teknologi Pendidikan Journal of Innovation and Future Technology (IFTECH)
Aila Gema Safitri
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Computer Science & IT Education Electrical & Electronics Engineering Engineering Library & Information Science

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Automated Assessment of Students' Attitudes and Academic Resilience Through Learning Management System Data Integration Dianti Eka Aprilia; Sutadi Triputra; Rika Dwi Agustiningsih; Aila Gema Safitri
JTP - Jurnal Teknologi Pendidikan Vol. 26 No. 3 (2024): Jurnal Teknologi Pendidikan
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat, Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/jtp.v26i3.51055

Abstract

One of the online platforms used to support learning activities is the Learning Management System (LMS). LMS supports the evaluation of cognitive aspects but not affective ones. As learning is mostly asynchronous, it presents challenges for lecturers in assessing students' attitudes. However, LMS generates data that can potentially be used to evaluate student attitudes and academic resilience. With the system log on the LMS, we can process data into information on the level of understanding, learning attitude, and persistence of students. This research is related to the design of an analytic dashboard that is integrated with LMS using Moodle. The dashboard will display an evaluation of student learning activities from the attitudinal aspects of motivation, discipline, responsibility, and academic resilience aspects consisting of persistence, reflecting and asking for help, and negative affect and emotional response. The study involved 160 new students, with data collected from 130 participants. The method used is a Research and Development (R&D) approach, which includes three stages: introduction, development, and testing. Data triangulation was used for validation by comparing online assessments with student self-evaluations. The final stage visualizes the results of system log analysis through the analytic dashboard. Findings showed that motivation scores from self-assessment correlated with LMS data, while discipline and responsibility assessments yielded different results. Academic resilience measures also showed discrepancies between student and mentor assessments. This research highlights the potential to visualize affective learning aspects within LMS platforms, providing lecturers with valuable insights into both cognitive and affective dimensions of student performance.
ANALISIS POLA PEMBELIAN EMAS DENGAN ALGORITMA APRIORI: STRATEGI BUNDLING PRODUK UNTUK EOA GOLD BANDUNG Aila Gema Safitri; Luthfi Faris; Taufik Rahmat Kurniawan; Ririn Suharsih
Journal of Innovation And Future Technology Vol. 7 No. 2 (2025): Vol 7 No 2 (Agustus 2025): Journal of Innovation and Future Technology (IFTECH)
Publisher : LPPM Unbaja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/4cx5r492

Abstract

This research employs the Apriori algorithm to examine gold sales data at EOA Gold Bandung, with the objective of identifying association patterns in sales transactions that can enhance marketing strategies and optimise inventory management. The dataset employed comprises sales transactions from July 2023 to July 2024, encompassing purchase date, customer information, invoice number, and the type of gold purchased, with a weight ranging from 0.025 grams to 10 grams. The application of the Apriori algorithm with a minimum support value of 10% and a minimum confidence of 30% revealed a significant purchase pattern: namely, that 1-gram and 2-gram gold bars are often purchased together in a single transaction. The findings provide valuable insights for EOA Gold Bandung in designing a product bundling offering strategy, which can improve customer satisfaction, increase sales volume and enhance stock management efficiency. It is anticipated that the results of this analysis will contribute to the optimisation of data-driven business strategies in the gold sales sector.
Co-Authors Agustiningsih, Rika Dwi Dianti Eka Aprilia Luthfi Faris Ririn Suharsih Sutadi Triputra Taufik Rahmat Kurniawan