Multi Criteria Decision Making (MCDM) Study for Job Market Place Recommender System

<br /> <br /> <br /> Indonesia is a country with many labor force. The number of labor force urges the existance of job market place which is a place where job applicants and job providers (companies) who offer job vacancies meet. The problem that emerges is that sometimes it is...

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Main Author: AKHIRO (NIM 23506038), RIDHO
Format: Theses
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/9079
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:9079
spelling id-itb.:90792017-09-27T15:37:07ZMulti Criteria Decision Making (MCDM) Study for Job Market Place Recommender System AKHIRO (NIM 23506038), RIDHO Indonesia Theses INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/9079 <br /> <br /> <br /> Indonesia is a country with many labor force. The number of labor force urges the existance of job market place which is a place where job applicants and job providers (companies) who offer job vacancies meet. The problem that emerges is that sometimes it is difficult for applicants to decide which job vacancies to apply and the job providers themselves sometimes having difficulties to find the right candidates. <br /> <br /> <br /> <br /> This thesis attempts to employ recommender system to solve such problem. This system is expected to help applicants or job providers to receive good recommendations. This thesis uses content-based recommender system and multi criteria decision making (MCDM) technique for providing the recommendations. <br /> <br /> <br /> <br /> The thesis process is started with literature study about recommender system, decision making theory, and theory about employee selection. Furthermore, problem analysis in order to apply recommender system in job market place is conducted. MCDM method selection is conducted and the Weighted Product Model (WPM) is choosen as the selected method. <br /> <br /> <br /> <br /> Evaluation of the designed algorithms is conducted by experiment which use data consist of curriculum vitae (CV) and job vacancies advertisements. The results of the experiments show that the WPM-based algorithms can be used to generate recommendations better than the Weighted Sum Model (WSM). Nevertheless, the experiments also show a special case in which the system may produce bad recommendations. <br /> <br /> text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description <br /> <br /> <br /> Indonesia is a country with many labor force. The number of labor force urges the existance of job market place which is a place where job applicants and job providers (companies) who offer job vacancies meet. The problem that emerges is that sometimes it is difficult for applicants to decide which job vacancies to apply and the job providers themselves sometimes having difficulties to find the right candidates. <br /> <br /> <br /> <br /> This thesis attempts to employ recommender system to solve such problem. This system is expected to help applicants or job providers to receive good recommendations. This thesis uses content-based recommender system and multi criteria decision making (MCDM) technique for providing the recommendations. <br /> <br /> <br /> <br /> The thesis process is started with literature study about recommender system, decision making theory, and theory about employee selection. Furthermore, problem analysis in order to apply recommender system in job market place is conducted. MCDM method selection is conducted and the Weighted Product Model (WPM) is choosen as the selected method. <br /> <br /> <br /> <br /> Evaluation of the designed algorithms is conducted by experiment which use data consist of curriculum vitae (CV) and job vacancies advertisements. The results of the experiments show that the WPM-based algorithms can be used to generate recommendations better than the Weighted Sum Model (WSM). Nevertheless, the experiments also show a special case in which the system may produce bad recommendations. <br /> <br />
format Theses
author AKHIRO (NIM 23506038), RIDHO
spellingShingle AKHIRO (NIM 23506038), RIDHO
Multi Criteria Decision Making (MCDM) Study for Job Market Place Recommender System
author_facet AKHIRO (NIM 23506038), RIDHO
author_sort AKHIRO (NIM 23506038), RIDHO
title Multi Criteria Decision Making (MCDM) Study for Job Market Place Recommender System
title_short Multi Criteria Decision Making (MCDM) Study for Job Market Place Recommender System
title_full Multi Criteria Decision Making (MCDM) Study for Job Market Place Recommender System
title_fullStr Multi Criteria Decision Making (MCDM) Study for Job Market Place Recommender System
title_full_unstemmed Multi Criteria Decision Making (MCDM) Study for Job Market Place Recommender System
title_sort multi criteria decision making (mcdm) study for job market place recommender system
url https://digilib.itb.ac.id/gdl/view/9079
_version_ 1820664588886081536