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This Author published in this journals
All Journal IAIC Transactions on Sustainable Digital Innovation (ITSDI) Asian Journal of Management, Entrepreneurship and Social Science
Veera Pandiyan Kaliani Sundram
Universiti Teknologi MARA Malaysia
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Library & Information Science Materials Science & Nanotechnology Social Sciences

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The Effect of Human Resource Information Systems (HRIS) and Artificial Intelligence on Defense Industry Performance Tessa Handra; Veera Pandiyan Kaliani Sundram
IAIC Transactions on Sustainable Digital Innovation (ITSDI) Vol 4 No 2 (2023): April
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/itsdi.v4i2.584

Abstract

The purpose of this research is to analyze the effect of the Human Resource Information System (HRIS) on the performance of the defence industry and the influence of artificial intelligence on the performance of the defence industry during the disruption era. This study uses a quantitative research approach. The samples processed were 160 defence industry employees. The primary data collection technique is done by distributing questionnaires to respondents. The questionnaire uses a Likert scale as a measure of data. Data analysis was carried out through structural equation modelling with SmartPLS 3.0 software. The dependent variable is the employee performance variable, and the independent variable is the HRIS and job satisfaction variables. The results of data analysis in this study and the significance value obtained prove that HRIS is significantly related to employee performance. The more accurate, precise and complete the HRIS application, the higher the employee's performance in completing their work assignments and improving the process of the defence industry in making human resource decisions through systematic HRIS procedures, which include data collection, data storage, data maintenance, data retrieval, and data validation. Its strategic plan influences the progress of the defence industry in utilizing human resources quantitatively, and understanding environmental conditions can provide an overview of the future of the defence industry. Artificial Intelligence (AI) is significantly related to employee performance.
POM-QM Utilization On Healthcare-Utensils Demand Identification And Distribution In Indonesia Mohammad Annas; Humairoh Humairoh; Veera Pandiyan Kaliani Sundram; Siti Norida Wahab
Asian Journal of Management, Entrepreneurship and Social Science Vol. 3 No. 01 (2023): Pebruary,Asian Journal of Management, Entrepreneurship and Social Science
Publisher : Cita Konsultindo Research Center

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Abstract

The study aims at healthcare utensils and the most accurate solutions to healthcare-utensils distributed by major logistics providers in Indonesia. The fast-moving utensils the logistics providers had identified are then being treated as a priority process and must be delivered to the intended region fulfillment possible due to the high urgency of the fulfillment. The study occurred in five capital cities of Indonesia, where those logistics providers operated. Primary and secondary data were used to support the analysis, and the methodology of procurement forecasting was implemented to support the research recommendations. The analysis was done by implementing features of POM-QM, particularly the feature of forecasting methods. The result showed that fluctuating demands and procurement of healthcare utensils gave huge problems to logistics providers as they had to arrange the transporter and its schedule in advance. Only one method, the linear trend line, with the least value of MAD, MSE, and MAPE below 5%, was found suitable to measure and anticipate the demands of healthcare utensils. Unfortunately, this method was never done by the logistics providers during the pandemic due to a loss of knowledge and insights into statistical methodologies.
Co-Authors Humairoh Humairoh Mohammad Annas Siti Norida Wahab Tessa Handra