Predictive model using a machine learning approach for enhancing the retention rate of students at-risk

HS Brdesee, W Alsaggaf, N Aljohani… - International Journal on …, 2022 - igi-global.com
Student retention is a widely recognized challenge in the educational community to assist
the institutes in the formation of appropriate and effective pedagogical interventions. This …

[PDF][PDF] K-Nearest Neighbor (K-NN) algorithm with Euclidean and Manhattan in classification of student graduation

N Hidayati, A Hermawan - Journal of Engineering and Applied …, 2021 - academia.edu
Student graduation rate is one of the indicators of the success of higher education. To
achieve a proper graduation rate, universities must plan the learning process so that …

Pola Prediksi Kelulusan Siswa Madrasah Aliyah Swasta dengan Support Vector Machine dan Random Forest

A Darmawan, I Yudhisari, A Anwari… - Jurnal Minfo …, 2023 - jurnal.polgan.ac.id
Kelulusan Siswa adalah salah satu indikator penting bagi kinerja keberhasilan sekolah.
Prediksi kelulusan siswa penting bagi sekolah untuk mengidentifikasi siswa yang beresiko …

Predictive model of graduate-on-time using machine learning algorithms

N Mohammad Suhaimi, S Abdul-Rahman… - Soft Computing in Data …, 2019 - Springer
In most universities, the number of students who graduated on time reflect tremendously on
their operation costs. In such cases, the high number of graduate-on-time or GOT students …

A deep learning approach to predict academic result and recommend study plan for improving student's academic performance

A Roy, MR Rahman, MN Islam, NI Saimon… - … Systems: Proceedings of …, 2021 - Springer
Predicting the academic results and preparing the study plan are crucial concerns for
students to improve their academic performance. The existing literature mainly focused to …

A New Binary Adaptive Elitist Differential Evolution Based Automatic k‐Medoids Clustering for Probability Density Functions

D Pham-Toan, T Vo-Van… - Mathematical …, 2019 - Wiley Online Library
This paper proposes an evolutionary computing based automatic partitioned clustering of
probability density function, the so‐called binary adaptive elitist differential evolution for …

[图书][B] Machine Learning aplicado al rendimiento académico en educación superior: factores, variables y herramientas

LE Contreras, GM Tarazona Bermúdez… - 2023 - books.google.com
Las herramientas de aprendizaje automático están siendo muy utilizadas por sus buenas
aproximaciones al predecir el rendimiento académico de los estudiantes. Se analiza …

An intelligent system for tourism management using k-medoids algorithm

R Deolekar, A Nerurkar… - 2019 6th International …, 2019 - ieeexplore.ieee.org
Travelling to places is really a joyful thing for all of us. The tedious job is to decide where to
go and what should be the places to visit. Ideally everyone would like to visit the most …

Early Prediction for Graduation of Private High School Students with Machine Learning Approach

FT Anggraeny, AK Darmawan, A Anekawati, I Yudhisari - 2023 - techniumscience.com
Graduation rates indicate school success. Predicting student graduation helps schools
identify students in danger of dropping out and intervene early to enhance academic …

[PDF][PDF] Research Article A New Binary Adaptive Elitist Differential Evolution Based Automatic k-Medoids Clustering for Probability Density Functions

D Pham-Toan, T Vo-Van, AT Pham-Chau… - 2019 - academia.edu
This paper proposes an evolutionary computing based automatic partitioned clustering of
probability density function, the so-called binary adaptive elitist differential evolution for …