Implementation of Process Mining to Discover Student Learning Patterns using Fuzzy Miner Algorithm (Case Study: Learning Management System (LMS) Telkom University)

Valensia, Larasati; Andreswari, Rachmadita; Fauzi, Rahmat

doi:10.1109/icera53111.2021.9538789

Cited by 3 publications

(2 citation statements)

References 9 publications

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“…The study also considers the effect of changes in the importance level of criteria on alternative rankings by performing a one-at-a-time sensitivity analysis. Valensia et al (2021) utilized the fuzzy miner algorithm to discover student learning patterns in the Learning Management System (LMS) of Telkom University. They used historical data stored in the system and three tools, Jupyter Notebook, Disco, and ProM, to process and analyze the data.…”

Section: Introductionmentioning

confidence: 99%

For Loan Processing a Fuzzy Process Mining

YAZICI

Engin

2023

Journal of Advanced Research in Natural and Applied Sciences

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Process mining has been used extensively in recent years to develop the steps of the business and it is an important technique to remove waste and reduce process costs. The aims of this study indicate that congestion, workflow which lived a long time, and stuff or system statistics in the banking real estate transaction process. The process mining practice is applied in bank business loans. In the bank process, the most used and more complicated business is a bank loan transaction. The process mining implementation pattern is created with sample and flow gains of process development. Then, the new workflow is designed and the pattern is executed. In the first stage of the total loan period, 7.84 hours of earnings are obtained. Visualizations of the process have been affected with the help of fuzzy model algorithms necessary for a huge number of incidents and activities. Workflow analysis and gathering information for studies were to be effortless with the support of fuzzy models. As a result of the analysis based on the flows, the knowledge pool is created by getting the knowhow such as the average duration of the process and the deviations in the users or systems. The results indicated that process mining is a significant methodology for developing bank loan transactions and enhancement their performance.

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Section: Introductionmentioning

confidence: 99%

For Loan Processing a Fuzzy Process Mining

YAZICI

Engin

2023

Journal of Advanced Research in Natural and Applied Sciences

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“…Previously related research [5]. This study implements process mining with fuzzy miner to overcome the "spaghetti-like" process model using data from the Website Application Development and Enterprise Systems course for the first semester of 2020/2021.…”

Section: Introductionmentioning

confidence: 99%

Process Mining using Inductive Miner Algorithm to Determine the actual Business Process Model

2022

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At the beginning of 2019, the COVID-19 pandemic entered the country of Indonesia resulting in all learning activities being carried out online in all cities of Indonesia. Likewise, Telkom University concentrates all teaching and learning activities online using the CeLOE Learning Management System. Learning Management System is a system that helps lecturers in managing teaching and learning activities independently in educational institutions. CeLOE is a learning management system of Telkom University developed based on Moodle. In this study, we analyse the CeLOE event log using the process mining method. The goal is to find out the learning patterns of students using CeLOE during the COVID-19 pandemic. This research case study focuses on the activities of students of the Telkom University S1 Informatics study program for the first semester of 2020/2021 in using CeLOE LMS. The analysis of this study conducted a comparison of the performance of three variants of the inductive miner (IM) algorithm through conformance checking values. The results of the analysis obtained are value of conformance checking from the three variants of the inductive miner (IM) algorithm have an average fitness value of up to 1 prove that the inductive miner (IM) algorithm can make a model based on the event log well. Besides that, it has a fairly high precision value with a value range of 0.750-0.850 shows that the inductive miner (IM) makes a process model with relatively many variations of activities outside the event log and the IM process model is "overfit-ting" for all variants of the IM algorithm. Inductive miner (IM) is the best inductive miner (IM) algorithm variant with a fitness value of 1.0, precision value of 0.750, and the generalization value of this algorithm is relatively high (0.984). It is hoped that this research can contribute to the addition of new perspectives related to the implementation of process mining using inductive miner (IM) algorithm in the field of education

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Process Mining-Based Behavioral Modeling of Learners in Self-paced Learning Environment

Thiyagarajan

Prasanna

2023

Lecture Notes in Electrical Engineering

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Implementation of Process Mining to Discover Student Learning Patterns using Fuzzy Miner Algorithm (Case Study: Learning Management System (LMS) Telkom University)

Cited by 3 publications

References 9 publications

For Loan Processing a Fuzzy Process Mining

For Loan Processing a Fuzzy Process Mining

Process Mining using Inductive Miner Algorithm to Determine the actual Business Process Model

Process Mining-Based Behavioral Modeling of Learners in Self-paced Learning Environment

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