Abstract: Campus placement plays a vital role in every educational institution in helping students to achieve their goals. All students dream to obtain a job offer in their hands before they leave their college. In this paper, a predictive model is designed which can predict whether a student get placed or not. The main objective of this project is to analyze the student’s academics data, aptitude data and predict the placement possibilities of students to have an idea about where they stand and what to be done to obtain a good placement. Which also aids to increase the placement percentage of the institutions? The data has been collected by the institution for which prediction is going to be done and by applying suitable data pre-processing techniques. The model is built by both training and test set which gives accuracy in prediction. Here we use a single supervised machine learning algorithm named support vector machine algorithm. This algorithm independently predicts the results and we then compare the efficiency of the algorithm, which is based on the dataset. This model will help the placement cell to focus on the potential students and help them to improve their technical and other skills.

Keywords: Prediction, SVM, Data mining, Logistic Regression, Decision tree, Random Forest.

| DOI: 10.17148/IJIREEICE.2021.9507