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All Journal BRITech : Jurnal Ilmiah Ilmu Komputer, Sains dan Teknologi Terapan Journal of Artificial Intelligence and Digital Business Innovative: Journal Of Social Science Research West Science Interdisciplinary Studies West Science Interdisciplinary Studies The Eastasouth Journal of Information System and Computer Science Innotech Jurnal Sistem Informasi Komputer
Wardhani, Diky
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Humanities Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Other

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Journal : West Science Interdisciplinary Studies

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The Impact of Data Engineering Maturity and Analytics Pipeline Automation on Operational Prediction Accuracy through Data Quality in Warehousing Logistics in Tangerang Wardhani, Diky; Bunyamin, Ilham Akbar; Andiani, Paramita
West Science Interdisciplinary Studies Vol. 4 No. 04 (2026): West Science Interdisciplinary Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsis.v4i04.2787

Abstract

This study aims to examine the effect of data engineering maturity levels and analytics workflow automation on operational prediction accuracy through the mediating role of data quality in warehouse logistics in Tangerang. A quantitative research approach was employed using data collected from 75 respondents involved in warehouse operations. The data were gathered through a structured questionnaire based on a Likert scale and analyzed using Structural Equation Modeling–Partial Least Squares (SEM-PLS 3). The results indicate that data engineering maturity levels have a positive and significant effect on data quality, and analytics workflow automation also significantly influences data quality. Furthermore, data quality has the strongest positive effect on operational prediction accuracy. Direct effects show that data engineering maturity and analytics workflow automation also significantly influence prediction accuracy, although their effects are weaker compared to the indirect effects through data quality. Mediation analysis confirms that data quality partially mediates these relationships. These findings highlight that improving operational prediction accuracy in warehouse logistics is not solely dependent on advanced analytical tools but is strongly influenced by the quality of data generated through mature data engineering practices and automated analytics workflows. This study contributes to the literature by integrating technological capability and data quality perspectives and provides practical implications for logistics companies in enhancing data-driven decision-making and operational efficiency.
Co-Authors Akhmad Pandhu Wijaya, Akhmad Pandhu Andiani, Paramita Arisanti, Ivon Arnes Yuli Vandika Bunyamin, Ilham Akbar Chandrasekar, Dito Fahreza, Muhammad Reza Faiz Muqorrir Kaaffah Judijanto, Loso Mardiani, Eri Nevandri, Rifqi Nadhir Prialam , Abdi Rika Astuti Safarudin, Muhamad Sigid Santi Diwyarthi, Ni Desak Made Saputra, Dedi Dwi Simarangkir, Manase Sahat H