학술논문

Prediction of Unemployment using Machine Learning Approach
Document Type
Conference
Source
2022 OITS International Conference on Information Technology (OCIT) OCIT Information Technology (OCIT), 2022 OITS International Conference on. :1-5 Dec, 2022
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Power, Energy and Industry Applications
COVID-19
Support vector machines
Machine learning algorithms
Pandemics
Employment
Machine learning
Prediction algorithms
Unemployment
machine learning model
Decision Tree
k-Nearest Neighbour
Supervised Learning
Language
Abstract
Unemployment is a circumstance which arises when people above a specific age are not engaged in any kind of activities which contribute to the economic welfare of the individual and country. Unemployment is becoming a rising concern which is making the daily life of people difficult. Unemployment causes poverty and depression among the citizens. Nowadays there are different opportunities in different sectors. But people are not aware of those opportunities. Different states are there where there is a lack of skilled labour whereas many states are there that have skilled labour but less opportunities. Another reason for unemployment since 2020 is the COVID-19 pandemic. We have selected this topic to spread awareness among the citizens. This work attempts to detect the states of India which are in serious need of increasing employment opportunities. We have applied the concept of Supervised Machine Learning algorithms to detect the states with the lowest employment rate. The data visualization gives a better picture of the trends in unemployment rate over years. There has been a use of different popular algorithms like Logistic Regression, Support Vector Machine, K-nearest neighbors (kNN) Algorithm and Decision Tree. In the end we have tried to find the algorithm which is going to give us more accuracy so that necessary steps can be taken for the employment of the eligible and deserving people.