The classification process often needs help with suboptimal accuracy values, which can be
attributed to various factors, including the dataset's wide range of attribute values …

In a higher education environment that carries out tridharma obligations, one of the roles of a
lecturer is to be a researcher. Collaboration between researchers who have different …

Recommendation systems are widely used in domains such as e-commerce, social media
networks, news portals, educational platforms, and other related fields. This survey presents …

Major recommendation systems have been widely used to assist prospective students in
choosing major that matches their interests and potential. In an effort to improve the …

Research conducted to predict the incidence of stunting in toddlers, using data mining
methods such as Naive Bayes and the C4. 5 algorithm has been applied to analyze health …

This research aims to apply machine learning techniques in classifying student satisfaction
levels at the Faculty of Science and Technology, using the K-Nearest Neighbors (KNN) and …

Large book data stores were beneficial for our support systems but posed significant
challenges for useful information retrieval. This issue was resolved by collaboratively …

In an effort to find a solution for determining the best administrators, Islamic boarding school
administrators try to determine the nominations for the best administrators using existing …

The Naive Bayesian classifier is a popular classification method employing the Bayesian
paradigm. The concept of having conditional dependence among input variables sounds …

The recommendation system is a mechanism for filtering a batch of data into numerous data
sets based on what the user wants. Cosine similarity is one of the algorithms used in …