[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-227860-en":3,"doc-seo-227860-105":30,"detail-sidebar-cat-0-en-105":97},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},227860,962084928904,"Jake","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","Optimizing Human Resource Selection Through TOPSIS-Based Multi-Criteria Decision Making","Human resource quality drives organizational success, yet recruitment frequently suffers from subjectivity, inefficiency, and assessment bias. This study introduces a Decision Support System (DSS) that applies TOPSIS to rank applicants using four Indonesian recruitment criteria: General Intelligence Test (30%), National Insight Test (10%), field ability test (20%), and Interview Performance (40%). TOPSIS orders candidates by geometric distance from ideal solutions, achieving 90% alignment with historical decisions and improving decision effectiveness by 98.78% while shortening the recruitment timeline by 30%.","| Optimizing Human Resource Selection Through TOPSIS-Based\u003Cbr>Multi-Criteria Decision Making\u003Cbr>Astrid Noviana Paradhita1, Myrtana Pusparisti2, Agustin Amborowati3\u003Cbr>1,2,3Vocational School, Universitas Sebelas Maret, Indonesia |  |\n| --- | --- |\n| Article Info ABSTRACT |  |\n| Article history:\u003Cbr>Received 05 20, 2026 Revised 06 02, 2026 Accepted 06 20, 2026\u003Cbr>Keywords:\u003Cbr>Decision Support System Human Resource Selection TOPSIS Method\u003Cbr>Unit Testing Empirical Testing | Human resource quality is a pivotal determinant of organizational success, yet recruitment often suffers from subjectivity and inefficiency. This study addresses challenges in applicant mapping and assessment bias by implementing a Decision Support System (DSS) using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) . The research utilizes four selection criteria based on standard Indonesian recruitment frameworks : General Intelligence Test (30%), National Insight Test (10%), fild ability test (20%), and Interview Performance (40%) . Methodologically, the TOPSIS method was employed to rank candidates based on their geometric distance from the positive and negative ideal solutions. Results demonstrate that the TOPSIS-based DSS achieved 90% alignment with historical corporate hiring decisions. Furthermore, the system improved decision-making effectiveness by 98.78%, accelerating the overall recruitment timeline by 30% . This study contributes to the field of HR technology by providing a scalable, objective framework for multi-criteria candidate evaluation. By integrating mathematical rigor into personnel selection, the proposed system minimizes human error and optimizes organizational efficiency in the Indonesian corporate context. |\n| This is an open access article under the CC BY-SA license.\u003Cbr>|  |\n| Corresponding Author:\u003Cbr>Astrid Noviana Paradhita\u003Cbr>Vocational School\u003Cbr>Universitas Sebelas Maret\u003Cbr>Surakarta, Indonesia\u003Cbr>Email: [astrid.noviana@staff.uns.ac.id](astrid.noviana@staff.uns.ac.id)\u003Cbr>© The Author(s) 2026 |  |\n| 1. Introduction\u003Cbr>Companies require integrated tools to manage internal business processes, particularly Human Resources (HR) management. HR serves as the foundational “root” of an organization [1], where specific competencies and skills must align with corporate strategic needs [2][3] . As a primary determinant of profitability, institutional existence, and long-term development, employees are the “spearhead” of organizational success [4][5] . Consequently, the recruitment process is the vital first step in securing this success and must be conducted comprehensively by evaluatingapplicant competencies againts rigorous qualification standard [6][7] .\u003Cbr>However, the complexity of modern recruitment presents a significant risk of selection error [8] . This challenge is evident at Company X, a State Owned Enterprise (BUMN) in Surakarta, which consistently attracts thousands-sometimes millions-of applicants. This overwhelming volume makes it difficult for the organization to identify candidates who meet specific criteria[9] . Currently, the selection process involves four stages : administrative screening, the general intelligence test (TIU), the national insight test (TWK), the field ability test (TKB), and an interview (TW) . Despite utilizing computer-based testing, the company faces\u003Cbr>255 |  |\n\nJurnal Teknologi dan Open Source, Vol. 9, No. 1, June 2026: 255-270  \npersistent decision-making hurdles. Recruiter often suffer from fatigue, which can lead to subjectivity [10] Furthermore, screening based solely on TIU, TWK, and TKB scores is suboptimal for capturing qualifications, and differing perspectives during interviews often lead to conflicting decisions. This prolonged process, which can last months, result in substantial recruitment costs.  \nAdvancements in technology offer an opportunity to automate and optimize these through Decision Support Systems (DSS) . A DSS provides recommendations to help decis","cbCaiomhHncyGdkA","https://ap.wps.com/l/cbCaiomhHncyGdkA","pdf",1580818,1,16,"English","en",105,"# Introduction\n## Research Method","[{\"question\":\"What decision-making approach does the study use for HR selection?\",\"answer\":\"The study uses a Decision Support System (DSS) implementing the TOPSIS method to rank candidates.\"},{\"question\":\"Which criteria and weightings are used in the applicant evaluation?\",\"answer\":\"The evaluation uses four criteria: General Intelligence Test (30%), National Insight Test (10%), field ability test (20%), and Interview Performance (40%).\"},{\"question\":\"How does the proposed TOPSIS-based DSS improve recruitment outcomes?\",\"answer\":\"It ranks candidates based on distance from positive and negative ideal solutions, achieving 90% alignment with historical hiring decisions, 98.78% improved effectiveness, and 30% faster recruitment timeline.\"}]","Optimizing Human Resource Selection Through 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