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All Journal MEANS (Media Informasi Analisa dan Sistem) Economics and Digital Business Review Jurnal Akuntansi, Manajemen dan Ilmu Ekonomi (JASMIEN) eMBeJi : Manajemen dan Bisnis Jurnal
Sitanggang, Lestari Pratiwi
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Social Sciences

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Journal : Jurnal Akuntansi, Manajemen dan Ilmu Ekonomi (JASMIEN)

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Implementasi Sistem Pendukung Keputusan Berbasis Topsis untuk Optimalisasi Rotasi dan Promosi Karyawan di Bidang Marketing dan Penjualan Sitanggang, Lestari Pratiwi; Trisanti, Ayu; Sirait, Ritawati; Simbolon, Oslan Juliana; Tarigan, Miska Irani Br; Haloho, Elizabeth
Jurnal Akuntansi, Manajemen dan Ilmu Ekonomi (Jasmien) Vol. 5 No. 02 (2025): Jurnal Akuntansi, Manajemen dan Ilmu Ekonomi (Jasmien) : Desember-Febuari
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jasmien.v5i02.1137

Abstract

Human resource management (HRM) in the field of marketing and sales is an essential aspect of achieving organizational goals. The process of employee rotation and promotion is often carried out based on managerial intuition, which can lead to subjectivity and unfair decision-making. This study aims to implement a Decision Support System (DSS) based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to assist in the employee rotation and promotion process in an objective and systematic manner. The research methodology uses a quantitative approach with a case study in a company operating in the marketing sector. Data were collected through surveys, interviews with HR managers, and historical employee data analysis based on five key criteria: sales performance, creativity, communication skills, work experience, and loyalty. The findings indicate that the TOPSIS method provides accurate recommendations in determining the best candidates based on their relative proximity to the ideal solution. The analysis also identifies that sales performance is the most dominant factor in decision-making, with the highest weight of 35%. The implementation of a TOPSIS-based DSS enhances decision-making efficiency and accuracy while reducing subjectivity in the employee rotation and promotion process. The study concludes that this system can be an effective solution in supporting HR decision-making based on data-driven analysis and objective evaluation
The Impact of Implementing Human Resource Analytics on Human Resource Management Decision Making Trisanti, Ayu; Sitanggang, Lestari Pratiwi; Manjorang, Nesa Repinalia Br; Simbolon, Oslan Juliana; Sitompul, Pandapotan
Jurnal Akuntansi, Manajemen dan Ilmu Ekonomi (Jasmien) Vol. 5 No. 02 (2025): Jurnal Akuntansi, Manajemen dan Ilmu Ekonomi (Jasmien) : Desember-Febuari
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jasmien.v5i02.1221

Abstract

HR Analytics has become a strategic tool in Human Resource Management (HRM), enabling organizations to make data-driven decisions that enhance operational effectiveness and efficiency. This study aims to analyze the impact of HR Analytics implementation on decision-making in HRM, considering both supporting and inhibiting factors of its implementation. The research uses a quantitative approach, surveying HR professionals across various industries. The findings show that the application of HR Analytics significantly contributes to improving decision-making accuracy, particularly in recruitment, performance management, and employee retention. However, challenges such as limited data literacy, technological infrastructure, and resistance to change remain key barriers to the optimal use of HR Analytics. The study provides implications for organizations to invest more in developing HR analytical competencies and fostering a data-driven decision-making culture. These findings align with the hypothesis that HR Analytics has a positive impact on decision-making and that HR analytical competence strengthens this relationship, while resistance to change weakens its effectiveness. Ultimately, organizations can maximize the benefits of HR Analytics by enhancing analytical skills and minimizing resistance to change.
Co-Authors Daely, Hele Dina Manjorang, Nesa Repinalia Br Sihombing, Thomas H Silalahi, Donalson Simbolon, Oslan Juliana Sirait, Ritawati Sitompul, Pandapotan Tarigan, Miska Irani Trisanti, Ayu