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All Journal Brilliance: Research of Artificial Intelligence Kalbisocio: Jurnal Bisnis dan Komunikasi
Pratiwi, Kuniarti
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Humanities Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Evaluasi Sistem Manajemen Persediaan untuk Mencegah Stockout Dan Mencapai Kepuasan Pelanggan (Studi Kasus Industri Distribusi Listrik) Pratiwi, Kuniarti; Nurjanah, Siti
KALBISOCIO Jurnal Bisnis dan Komunikasi Vol. 12 No. 1 (2025): KALBISOCIO Jurnal Bisnis dan Komunikasi
Publisher : Research and Community Service UNIVERSITAS KALBIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53008/kalbisocio.v12i1.4526

Abstract

Inventory management plays a vital role in ensuring product availability and customer satisfaction, particularly in the electrical distribution industry, where demand tends to be dynamic. This study aims to evaluate the effectiveness of inventory management systems at PT XYZ, which has implemented an ERP system integrated with e-Kanban, yet still faces challenges in fulfilling customer demand on time. A key issue identified is the high rate of delivery delays, reaching 61%, primarily caused by manual buffer stock management and inconsistent forecasting accuracy. The analysis methods employed include the calculation of Economic Order Quantity (EOQ), Safety Stock (SS), Reorder Point (ROP), and Mean Absolute Percentage Error (MAPE) to measure forecasting accuracy. The results show that EOQ ranges from 102 to 207 units per order, with significant potential for reducing ordering costs. However, 62.5% of products have actual Safety Stock below optimal levels, increasing the risk of stockouts. The current ROP has not effectively triggered timely reorder due to a lack of consideration for weekly demand fluctuations. The average MAPE value of 14.19% indicates sufficient forecast accuracy, though several products exceed 30%, reflecting notable discrepancies between forecasted and actual demand. In conclusion, the current inventory system at PT XYZ requires improvement, especially in the adjustment of SS and ROP based on real-time data and the automation of buffer stock management. These measures are expected to reduce the risk of stockouts, improve inventory cost efficiency, and maintain customer satisfaction.
From Observation to Co-Creation: A Netnographic Review of AI-Driven Consumer Behavior Mundzir, Ahmad; Pratiwi, Kuniarti
Brilliance: Research of Artificial Intelligence Vol. 5 No. 1 (2025): Brilliance: Research of Artificial Intelligence, Article Research May 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i1.5885

Abstract

As artificial intelligence (AI) continues to transform the landscape of digital consumer experiences, traditional netnographic methods face significant disruption—both in terms of methodological execution and theoretical framing. This systematic review explores how the growing presence of AI, functioning not only as a technological tool but also as an agentic participant, reshapes the way netnography is practiced in marketing and consumer behavior research. Recognizing a widening gap in the literature, the study aims to synthesize current conceptual and methodological advancements at the intersection of ethnographic inquiry and intelligent systems. Employing the PRISMA 2020 protocol for systematic reviews, 43 peer-reviewed journal articles published between 2013 and 2024 were retrieved from Scopus and Web of Science databases. A thematic synthesis of these articles reveals five dominant themes: the methodological evolution of netnography within online consumer communities; the role of AI in predictive personalization; emerging patterns of consumer–AI value co-creation; new relational models of human–AI interaction; and ethical and epistemological challenges posed by AI-augmented ethnography. These themes collectively inform the development of a novel conceptual framework, AI-Netnography which positions both human and algorithmic agents as co-constructors of meaning, identity, and experience. By reimagining netnographic inquiry for AI-mediated environments, this review not only advances the field of qualitative marketing research but also proposes new pathways for ethically responsible and epistemologically inclusive digital consumer studies.
Co-Authors Mundzir, Ahmad Siti Nurjanah