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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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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
Implementasi Metode Multi-Attribute Utility Theory (MAUT) untuk Mengukur Kelayakan Pegawai Bidang Produksi pada PT. Inagrin Sitanggang, Lestari Pratiwi; Daely, Hele Dina; Sitompul, Pandapotan
Manajemen & Bisnis Jurnal Vol 11 No 1 (2025): Vol 11 No 1 (2025)
Publisher : Magister Manajemen Universitas Wisnuwardhana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37303/embeji.v11i1.222

Abstract

Decision Support System (DSS) is a tool that helps organizations make objective and structured data-driven decisions. One of the commonly used methods in DSS is the Multi-Attribute Utility Theory (MAUT), which enables the evaluation and comparison of alternatives based on multiple criteria with predetermined weights. This study aims to implement the MAUT method to assess employee eligibility in the production sector by considering factors such as technical knowledge, operational skills, time management, workplace safety, and work quality. By applying MAUT, companies can rank employees based on utility scores calculated through normalization and weighting. Data were collected from 30 production employees using observations and interviews to assess performance based on 12 key indicators. The results indicate that the MAUT method provides structured and accurate outcomes in determining the most eligible employees according to the specified criteria. Furthermore, this method supports more transparent and efficient decision-making, particularly in employee evaluation, promotion, and human resource management. This study concludes that implementing MAUT significantly contributes to assisting manufacturing and industrial companies in objectively managing employees and provides a foundation for developing AI-based employee evaluation models and machine learning applications in the future
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.
Tinjauan Literatur: Peran Pelatihan dan Pengembangan Sumber Daya Manusia dalam Meningkatkan Kinerja UKM di Era Revolusi Industri 4.0 Sihombing, Thomas H; Sitanggang, Lestari Pratiwi; Silalahi, Donalson; Sitompul, Pandapotan
Economics and Digital Business Review Vol. 6 No. 1 (2025): Agustus - January
Publisher : STIE Amkop Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37531/ecotal.v6i1.2249

Abstract

Pelatihan dan pengembangan Sumber Daya Manusia (SDM) memainkan peran penting dalam meningkatkan kinerja organisasi, terutama di Era Revolusi Industri 4.0. Teknologi yang berkembang pesat menuntut organisasi, termasuk UKM, untuk beradaptasi dengan cepat. UKM sering menghadapi tantangan keterbatasan anggaran dan akses teknologi untuk pelatihan yang efektif. Literatur ini mengeksplorasi peran pelatihan dalam meningkatkan produktivitas dan kinerja UKM serta tantangan yang dihadapi dalam mengimplementasikan pelatihan berbasis teknologi. Temuan penelitian menunjukkan bahwa meskipun pelatihan dapat meningkatkan kinerja, banyak UKM kesulitan mengakses teknologi terbaru. Oleh karena itu, penerapan metode pelatihan berbasis teknologi dan analisis kebutuhan pelatihan yang tepat menjadi solusi penting. Penelitian ini juga mengidentifikasi kesenjangan dalam literatur terkait UKM, yang memerlukan penelitian lebih lanjut mengenai pelatihan yang efisien dan terjangkau. Temuan ini diharapkan dapat memberikan kontribusi praktis bagi kebijakan pelatihan di UKM dan memberi wawasan untuk penelitian lebih lanjut
Perancangan Perangkat Lunak Kelayakan Pemberian Kredit Mobil dengan Menggunakan Metode Analytic Hierarcy Process (AHP) Sitanggang, Lestari Pratiwi
MEANS (Media Informasi Analisa dan Sistem) Volume 4 Nomor 2
Publisher : LPPM UNIKA Santo Thomas Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (507.848 KB) | DOI: 10.54367/means.v4i2.565

Abstract

Research with the title "Designing software for providing car credit worthiness using the Analytic Hiercy Process (AHP) method" was made with the main goal of building a software that is expected to help determine whether a person is worthy of credit, where this software is formed from a system decision support and to evaluate the feasibility of someone in receiving credit that will help decision makers in determining credit lending decisions by analyzing credit terms that have met the Five C requirements, namely customer character (Character), capacity to pay off credit (Capacity), the ability of capital to be customer owned (Capital), collateral owned by the customer to bear credit risk (Collateral), and the customer's financial condition (Condition).
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