A Greedy-based Algorithm in Optimizing Student’s Recommended Timetable Generator with Semester Planner

Abstract

Semester planner plays an essential role in students’ society that might help students have self-discipline and determination to complete their studies. However, during the COVID-19 pandemic, they faced difficulty organizing time management and doing a manual schedule. It resulted in substantial disruptions in learning, internal assessment disturbances, and the cancellation of public evaluations. Hence, this research aims to optimize the recommended semester planner, Timetable Generator using a greedy algorithm to increase student productivity. We identified three-set control functions for each entered information: 1) validation for the inserted information to ensure valid data and no redundancy, 2) focus scale, and 3) the number of hours to finish the activity. We calculate the priority task sequence to achieve the best optimal solution. The greedy algorithm can solve the optimization problem with the best optimal solution for each situation. Then, we executed it to make a recommended semester planner. From the test conducted, the functionality shows all the features successfully passed. We validate using test accuracy for the system’s reliability by evaluating it compared to the Brute Force algorithm, and the trends increase from 60% to 100%.