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All Journal Aptisi Transactions on Management ADI Bisnis Digital Interdisiplin (ABDI Jurnal)
Maria, Lily
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Library & Information Science

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A Structural Framework for Effective Time Management in Dynamic Work Environments Sana, Eirene; Jacqueline, Greisy; Nathalie, Julia; Maria, Lily; Callula, Brigitta
APTISI Transactions on Management (ATM) Vol 8 No 2 (2024): ATM (APTISI Transactions on Management: May)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v8i2.2256

Abstract

This paper presents a structural framework to enhance time management profi- ciency within dynamic work environments. The framework integrates prioritization techniques, task scheduling methods, delegation strategies, and technology utilization to optimize time allocation and productivity. The evaluation demonstrates significant improvements in time management efficiency and client satisfaction across various professional contexts.  For instance, by employing the eisenhower Matrix and Pareto Principle, project managers achieved a 20% im- provement in project completion times. The framework’s adaptability is further highlighted by a 25% reduction in project turnaround time in a marketing agency and a 30% increase in project visibility in a startup. These findings underscore the framework’s practical implementation as a holistic approach to managing time effectively and achieving long-term success. Continuous refinement, real- time feedback integration, and exploring the impact of emerging technologies are recommended for further enhancing the framework’s effectiveness. This research contributes valuable insights for organizations aiming to navigate the complexities of modern work environments.
Leveraging Artificial Intelligence for Competitive Advantage in Indonesian SMEs Jaya, Aswadi; Cahyono, Dwi; Maria, Lily
APTISI Transactions on Management (ATM) Vol 9 No 3 (2025): ATM (APTISI Transactions on Management: September)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v9i3.2524

Abstract

Artificial Intelligence (AI) has emerged as a transformative force in modern business, offering significant opportunities to enhance operational efficiency, improve customer engagement, and foster innovation. In Indonesia, Small and Medium Enterprises (SMEs) play a crucial role in driving economic growth and employment, yet their adoption of AI technologies remains limited due to resource constraints, lack of expertise, and uncertainty about return on investment. This study aims to investigate how AI adoption can be leveraged to achieve competitive advantage in Indonesian SMEs. Using a mixed-methods approach, data were collected through surveys and in-depth interviews with SME owners across various sectors. The findings indicate that AI applications such as predictive analytics, chatbot-based customer service, and demand forecasting have contributed to increased productivity, cost efficiency, and market competitiveness. The study provides a practical framework for AI implementation tailored to the needs and capacities of Indonesian SMEs, offering insights for business practitioners, policymakers, and researchers seeking to advance digital transformation in the SME sector.
Implemetation of ROP In Stock Control to Minimize Losses Due to Expiry Aziz, Lukmanul Hakim; Sunarjo, Richard Andre; Ramdani, Muhammad; Natalia, Elisa Ananda; Maria, Lily; Aini, Qurotul
ADI Bisnis Digital Interdisiplin Jurnal Vol 6 No 2 (2025): ADI Bisnis Digital Interdisiplin (ABDI Jurnal)
Publisher : ADI Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/abdi.v6i2.1337

Abstract

Managing inventory with a limited shelf life is a crucial challenge in the supply chain, particularly in sectors where products are susceptible to rapid quality deterioration. Inaccuracies in ordering timing often lead to excess stock, which leads to financial losses due to product destruction, increased storage costs, and negative environmental impacts. This situation demands the implementation of more integrated and data-driven inventory control methods to optimize the procurement cycle sustainably. This study aims to analyze the effectiveness of implementing the Reorder Point (ROP) method integrated with historical demand and lead time data in minimizing the percentage of expired items. The main focus of the study is to establish ROP as a precise ordering timing mechanism, so that Safety Stock (SS) functions as an emergency buffer against uncertainty, rather than as excess inventory at risk of expiring. The research methodology includes analytical calculations of ROP, SS to mitigate demand and lead time variability, and Economic Order Quantity (EOQ) to determine the most economical order quantity. In addition, a literature review on the implementation of First Expired, First Out (FEFO) and First In, First Out (FIFO) systems is used as internal operational standards to ensure optimal stock rotation. The analysis results show that accurate ROP implementation is a key pillar in preventing expired goods. An optimal strategy requires synergy between prevention through precise ordering timing, internal control through strict stock rotation, and risk mitigation through proactive discount programs for products nearing expiration. The integration of ROP, SS, and EOQ has proven effective in reducing operational losses and supporting modern, efficient and sustainable inventory management practices.
Co-Authors Aswadi Jaya, Aswadi Aziz, Lukmanul Hakim Callula, Brigitta DWI CAHYONO Jacqueline, Greisy Natalia, Elisa Ananda Nathalie, Julia Qurotul Aini Ramdani, Muhammad Sana, Eirene Sunarjo, Richard Andre