Predictive Modelling to Predict Absenteeism in MNC’s

Abstract

It is rightly said: “Data is the new oil.” The future will move around generation of enormous amount of data which needs to be critically analyzed for the benefit of mankind, industry, academics, defense, intelligence, disaster management and counter terrorism. Managers and organizational practitioners need a detailed method for measuring absenteeism loss as well as other measures needed for managerial evaluation to decrease absenteeism rate and compare the effectiveness of absence/attendance policy from period to period. Our aim is to predict the absenteeism for MNCs by the previous recorded datasets. For this we will use predictive analysis using machine learning. For faster processing of massive dataset, the data has to be analyzed efficiently so that we have the minimum response time and turn-around time, which is only possible when we use the right set of algorithms and by hard wiring of program. By looking at the results of each technique we can make some insights about the problem. The methods used in the project include Linear Regression and Logistic Regression.