Gilbert G. Hungilo

Work place: Department of Informatics Engineering, Graduate Program, University Atma Jaya Yogyakarta, Yogyakarta 55281, Indonesia

E-mail: gutabagaonline@gmail.com

Website:

Research Interests: Data Structures and Algorithms, Computational Learning Theory, Software Organization and Properties

Biography

Gilbert G. Hungilo is a master degree graduate from department of Informatics Engineering at the University Atma Jaya Yogyakarta, Indonesia. He received Bachelor of Science in Computer Science from the University of Dar es salaam, Tanzania. His research interests include technology adoption, big data analytics, and machine learning.

Author Articles
Predicting Students' Academic Performance in Educational Data Mining Based on Deep Learning Using TensorFlow

By Mussa S. Abubakari Fatchul Arifin Gilbert G. Hungilo

DOI: https://doi.org/10.5815/ijeme.2020.06.04, Pub. Date: 8 Dec. 2020

The study was aimed to create a predictive model for predicting students’ academic performance based on a neural network algorithm. This is because recently, educational data mining has become very helpful in decision making in an educational context and hence improving students’ academic outcomes. This study implemented a Neural Network algorithm as a data mining technique to extract knowledge patterns from student’s dataset consisting of 480 instances (students) with 16 attributes for each student. The classification metric used is accuracy as the model quality measurement. The accuracy result was below 60% when the Adam model optimizer was used. Although, after applying the Stochastic Gradient Descent optimizer and dropout technique, the accuracy increased to more than 75%. The final stable accuracy obtained was 76.8% which is a satisfactory result. This indicates that the suggested NN model can be reliable for prediction, especially in social science studies.

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