MyOLC: An Intelligent Learning Ecosystem with Automated Multi-Role Tracking for Non-Formal Education in the Society 5.0 Era

Authors

  • Zaeniah Zaeniah Universitas Teknologi Mataram
  • Ahmad Subki Universitas Teknologi Mataram

DOI:

https://doi.org/10.69916/jkbti.v5i3.603

Keywords:

Learning Management System, Tutoring, Optima Mataram, Intelligent Learning, Education

Abstract

Technological developments have brought significant changes in various fields, including education. Optima Mataram Tutoring is one of the non-formal educational institutions that is required to adapt to technological developments to improve the quality of learning services. Optima Mataram Tutoring is an educational institution that provides learning assistance services for students at various levels of education. However, the learning management process is still carried out conventionally, such as manual attendance recording, delivery of materials via instant messaging, and the collection of assignments that are not yet integrated, causing various obstacles to the effectiveness and efficiency of the teaching and learning process at Optima Mataram Tutoring. This condition causes difficulties in monitoring student progress and managing academic data, as well as slow and inaccurate information delivery. Therefore, in this study, a Learning Management System application was developed at Optima Mataram Tutoring that is able to support an integrated and effective learning process that is easy to access. The method used in developing this LMS is the waterfall method. This LMS is expected to meet the needs of students in receiving learning materials, the needs of teachers in conducting assessments, and the needs of parents in monitoring their children's activities during the learning process at Optima Mataram Tutoring.

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References

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Published

2026-09-18

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How to Cite

[1]
Z. Zaeniah and Ahmad Subki, “MyOLC: An Intelligent Learning Ecosystem with Automated Multi-Role Tracking for Non-Formal Education in the Society 5.0 Era”, JKBTI, vol. 5, no. 3, pp. 772–781, Sep. 2026.