Predict MUET Result based on kNN Algorithm

1. kNN

1.1. 1. Automated web usage data mining and recommendation system using K-Nearest Neighbor (KNN) classification method (Adeniyi, 2016)

1.2. 2. Implementation of K-NN Fingerprint Method on Receiving Server for Indoor Mobile Object Tracking (Gempita, 2019)

1.3. 3. Comparative Analysis of K-Nearest Neighbor and Modified K-Nearest Neighbor Algorithm for Data Classification (Okfalisa et al., 2018)

1.4. 4. Prediction of Eye State Using KNN Algorithm (Adil et al., 2018)

1.5. 5. Trending Topic Prediction by Optimizing K-Nearest Neighbor Algorithm (Syarif et al., 2018)

2. Prediction in various area

2.1. 1. Prediction of Surrounding Vehicles Lane Change Intention Using Machine Learning (Benterki et al., 2019)

2.2. 2. Feature Extraction of Numerical Weather Prediction Results Toward Reliable Wind Power Prediction (Higashiyama et al., 2017)

2.3. 3. Location prediction on Twitter using machine learning Techniques (Indira et al., 2019)

2.4. 4. A Robust Model for Churn Prediction using Supervised Machine Learning (Bhatnagar & Srivastava, 2019)

2.5. 5. Online News Popularity Prediction (Namous et al., 2018)

3. MUET Examination

3.1. 1. Research Monograph: A Correlation Study between MUET and IELTS (Siti Jamilah Bidin, Zuraidah Mohd Don, Abdul Halim Abdul Raof, Ainol Madziah Zubairi, Nor Idayu Mahat,)

3.2. 2. Predicting MUET Question (Choi Jien Ping, 2015)

3.3. 3. MyMUET: A Design of a Mobile based Crowdsourced Assessment for Malaysia University English Test with Non-Synchronous Participant Interaction (Yarshini a/p Thamilarasan, Raja Rina Raja Ikram, 2019)

4. Prediction of exam result

4.1. 1. Data mining in hybrid learning: possibility to predict the final exam result (Gamulin et al., 2013)

4.2. 2. A Preliminary Implementation of Data Mining Approaches for Predicting The Results of English Exit Exam (Puarungroj et al., 2017)

4.3. 3. Using TOEFL Sub-Scores to Predict SPEAK Test Outcome: A Multivariate Bayesian Model (Mercado, 2017)

4.4. 4. Predicting and analyzing secondary education placement-test scores: A data mining approach (Delen et al., 2012)

4.5. 5. An overview and comparison of supervised data mining techniques for student exam performance prediction (Tomasevic, 2020)