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All Journal ADI Bisnis Digital Interdisiplin (ABDI Jurnal) JOT
Elisa Ananda Natalia
Sundara Group
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Library & Information Science

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Implemetation of ROP In Stock Control to Minimize Losses Due to Expiry Lukmanul Hakim Aziz; Richard Andre Sunarjo; Muhammad Ramdani; Qurotul Aini; Elisa Ananda Natalia; Lily Maria
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.
Sentiment Aware Chatbots as Companions for Reducing Loneliness through Positive Computing Heni Nurhaeni; Sandy Kosasi; Made Bunga Thalia; Elisa Ananda Natalia; John Edwards
Journal of Orange Technology Vol. 1 No. 1 (2024): October
Publisher : Sinar Mentari Sundara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.68012/jot.v1i1.10

Abstract

Loneliness has increasingly emerged as a global mental health concern, particularly among vulnerable populations such as the elderly, students in remote learning environments, and individuals experiencing social isolation in urban societies. Advances in affective and positive computing offer promising solutions for addressing these challenges by creating empathetic digital companions capable of responding to human emotions in real time. This study aims to evaluate the effectiveness of sentiment-aware chatbots as digital companions in reducing loneliness and enhancing emotional well-being through positive computing principles. A quantitative experimental approach was employed, integrating sentiment analysis algorithms with Natural Language Processing (NLP) to detect emotional cues from user input and generate empathetic responses. The chatbot system was tested with 150 participants over a six-week period using standardized psychometric instruments, including the UCLA Loneliness Scale and the WHO-5 Well-Being Index. Statistical analysis using paired-sample t-tests, ANOVA, and Structural Equation Modeling (SEM) revealed significant improvements in loneliness reduction and psychological well-being among participants interacting with the sentiment-aware chatbot. Furthermore, perceived empathy and user satisfaction were found to mediate these effects, highlighting the emotional quality of human AI interaction as a crucial determinant of positive outcomes. Findings provide empirical evidence that sentiment-aware chatbots can function as effective digital companions, reducing loneliness and fostering psychological resilience. By integrating affective and positive computing principles, this study contributes to the advancement of compassionate AI systems designed to promote human well-being and support broader societal goals.
Co-Authors Heni Nurhaeni John Edwards Lily Maria Lukmanul Hakim Aziz Made Bunga Thalia Muhammad Ramdani Qurotul Aini Richard Andre Sunarjo Sandy Kosasi