Journal of Artificial Intelligence and Digital Business
Vol. 5 No. 1 (2026): Februari - April

The Effect of Workload and Work Stress on Employee Performance in Logistics Companies in Mojokerto

Kasnowo, Kasnowo (Unknown)



Article Info

Publish Date
24 Feb 2026

Abstract

This study aims to analyze the effect of workload and work stress on employee performance in logistics companies in Mojokerto using a quantitative research approach. Data were collected from 85 employees through structured questionnaires measured on a five-point Likert scale, reflecting perceptions related to task demands, psychological pressure, and performance outcomes in daily logistics operations. The analysis was conducted using SPSS version 25, including validity and reliability testing, classical assumption tests, multiple linear regression analysis, and hypothesis testing to ensure the robustness of the statistical model. The findings reveal that workload has a positive and significant effect on employee performance, indicating that appropriate task allocation can encourage productivity and efficiency, whereas work stress shows a negative and significant influence, suggesting that excessive pressure may reduce focus, motivation, and overall work quality. Simultaneously, workload and work stress significantly influence employee performance, with a coefficient of determination demonstrating that 31.5% of performance variation can be explained by these independent variables, while the remaining variation is influenced by other organizational and individual factors. The results highlight the importance of balanced workload management, effective stress control strategies, and supportive organizational practices in maintaining sustainable performance levels in the logistics sector, which is characterized by tight schedules and dynamic operational challenges. This study provides practical implications for managers in designing human resource policies that align operational demands with employee well-being and offers empirical evidence that can support future research development in human resource and organizational performance studies.

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Journal Info

Abbrev

RIGGS

Publisher

Subject

Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering

Description

Journal of Artificial Intelligence and Digital Business (RIGGS) is published by the Department of Digital Business, Universitas Pahlawan Tuanku Tambusai in helping academics, researchers, and practitioners to disseminate their research results. RIGGS is a blind peer-reviewed journal dedicated to ...