Job Position Prediction Based on Skills and Experience Using Machine Learning Algorithm - Thesis Acknowledgement Abstract

Aug 5, 2026

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Intensifying competition in the job market makes it difficult for job seekers to determine the most suitable positions from their skills and experience. This research proposes a Job Position Prediction system using machine learning algorithms and LinkedIn profile/job posting data. The system preprocesses and analyzes LinkedIn pages to extract job titles, company names, experience years, qualifications, and skills, ensuring consistent representation for validation. Random Forest, Linear Regression, XGBoost, SVM, and a stacking ensemble are trained with a large dataset and evaluated using accuracy, precision, recall, F1 score, and cross-validation.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages5

Reading Time13 min

AccessFree to download

ACKNOWLEDGEMENT

ABSTRACT

TABLE OF CONTENT

CHAPTER ONE: INTRODUCTION

CHAPTER TWO: LITERATURE REVIEW

CHAPTER THREE: METHODOLOGY

Universiti Teknologi MARA Job Position Prediction Based on Skillsand Experience Using MachineLearning Algorithm Ezaryf bin Hamdan Thesis submitted in fulfilment of the requirementsfor Bachelor of Computer Science (Hons.) JULY 2024 ACKNOWLEDGEMENT First and foremost,praises and thanks to Allah because of His Almighty and Hisutmost blessings,I was able to finish this research within the time duration given.Without His support and guidance,this work would not have been possible.I wouldlike to express my deepest appreciation to all those who contributed to the completionof this research. Firstly,my special thanks go to my supervisor,Mrs.Norulhidayah Isa for her endlessguidance,encouragement,support,and knowledge that had been delivered throughoutthis project.Then,thank you to my CSP600 and CSP650 lecturer,Mrs.UmmuFatihah binti Mohd Bahrin that also give a comments and recommendation for all ofus and teach us to complete this project. No one has been more crucial to me in the pursuit of this project than my familymembers.I owe a special thank you to my beloved parents for their unwaveringsupport,both physically and mentally.They have provided me with encouragementand even financial assistance when I needed it the most.I am grateful to all those withwhom I have had the pleasure of working during this project.I would like to expressmy appreciation to my dearest classmates for their invaluable assistance and emotionalsupport in successfully completing the final year project. # ABSTRACT In response to the intensifying competition in the job market,job seekers oftengrapple with the challenge of identifying the most suitable positions based on theirskills and experience.This paper proposes a sophisticated Job Position Predictionsystem utilizing Machine Learning algorithms and leveraging data from LinkedInprofiles.The objective is to develop an innovative and user-friendly platformoffering accurate job position predictions to aid job seekers in finding optimal careeropportunities.The proposed system integrates data processing modules to preprocessand analyse LinkedIn job posting pages,extracting crucial information such as jobtitles,company names,years of experience,qualifications,and skills.Textpreprocessing ensures consistent data representation and facilitates validation.TheMachine Learning algorithm,comprising Random Forest,Linear Regression,XGBoost,SVM,and Stacking Ensemble,is embedded in the system for job positionpredictions based on the analysed data.The algorithm undergoes rigorous trainingwith a vast dataset to ensure high prediction accuracy and reliability.Accessiblethrough a desktop application,the Job Position Prediction System prioritizes user-friendliness for job seekers.Users input their job skills and years of experience,receiving personalized job position predictions as the system analyses the input andprovides the most suitable job positions based on LinkedIn data.The success of thisproject is evaluated using various metrics,including prediction accuracy,precision,recall,and F1 score.Cross-validation techniques are employed to validate themodel's performance and ensure robustness.The development and evaluation of theprediction system adhere to a comprehensive research methodology encompassingdata understanding,description,preprocessing,feature extraction,and modelevaluation.This research culminates in the creation of an efficient and accurate JobPosition Prediction System,empowering job seekers with valuable insights toenhance their job search process. TABLE OF CONTENT PAGE CONTENTS SUPERVISOR APPROVALSTUDENT DECLARATIONACKNOWLEDGEMENTABSTRACT iii iv V vi TABLE OF CONTENTLIST OF FIGURESLIST OF TABLESLIST OF ABBREVIATIONS vii xi xiv XV CHAPTER ONE:INTRODUCTION 1.1 Background of Study17 1.2 Problem Statement20 1.3 Objective 22 1.4 Project Scope23 1.5 Project Significance 25 1.6 Overview of Research Framework 27 30 1.7 Conclusion CHAPTER TWO:LITERATURE

FAQs

What problem does the job position prediction system address?

It addresses how job seekers struggle to identify the most suitable job positions based on their skills and experience.

What data source does the proposed system use?

The system leverages LinkedIn profiles and job posting pages to extract relevant job-related information.

Which machine learning models are used for job position predictions?

The system embeds Random Forest, Linear Regression, XGBoost, SVM, and a stacking ensemble for predictions.

Aug 5, 2026

Upload by Liam