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All Journal Jurnal Sisfokom (Sistem Informasi dan Komputer) The South East Asian Journal of Management Indonesian Journal of Statistics and Its Applications
Aryasa, Komang Budi
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Mathematics Other

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Entering the Global Market: The Role of Work Autonomy and Individual Global Mindset as Antecedents of Innovative Work Behavior in Defining Employee Task Performance Pusparini, Elok Savitri; Aryasa, Komang Budi
The South East Asian Journal of Management Vol. 15, No. 1
Publisher : UI Scholars Hub

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Abstract

Research Aims: This study aims to highlights the role of innovative work behavior (IWB) in determining task performance. The main antecedents of IWB, namely work autonomy and individual global mindset, are discussed, as well as how these two key factors will detemine the degree of individual innovative behavior. Design/Methodology/Approach: This study uses a cross-sectional design with convenience sampling methods to collect primary data and Structural Equation Modelling (SEM) to test the hypothetical model and analyse the data. Research Findings: As many as 309 points of data were received; following screening and selection protocols, the final dataset consisted of 284 responses from employees in innovation center units of a leading ICT company in Indonesia. Findings of this study indicate a positive effect of work autonomy, individual global mindset, and task performance with regard to the mediating effect of IWB. Theoretical Contribution/Originality: This study contributes in defining the positive effects of work autonomy and individual global mindset on IWB and closing the gap regarding the role of IWB in mediating the effect of work autonomy and individual global mindset upon task performance. Managerial Implications in the Southeast Asian Context: As the local market is no longer sufficient to achieve further growth, competing firms need to enter the international or global market; this can be achieved through improved performance resulting from highly innovative behavior. Research Limitations & Implications: Limitations include the limited response rate due to the work-from-home policy during the pandemic, as well as generalizability issues. The current study invite further exploration in terms of the possibilities to elaborate more antecedents for innovative work behavior.
Comparing Self-Paced Ensemble and RUSBoost for Imbalanced Poverty Classification in West Java Setiabudi, Nur Andi; Sartono, Bagus; Syafitri, Utami Dyah; Aryasa, Komang Budi
Indonesian Journal of Statistics and Applications Vol 9 No 2 (2025)
Publisher : Statistics and Data Science Program Study, SSMI, IPB University, in collaboration with the Forum Pendidikan Tinggi Statistika Indonesia (FORSTAT) and the Ikatan Statistisi Indonesia (ISI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v9i2p218-229

Abstract

Class imbalance remains a major challenge in classification modelling that frequently leads to biased predictive models. This study aimed to compare two ensemble techniques based on an undersampling approach, namely Self-Paced Ensemble and RUSBoost, for handling imbalanced classification in poverty identification in West Java. The results suggested that RUSBoost consistently outperformed Self-Paced Ensemble across the most critical metrics. It showed better balance in classification outcomes. When the objective is to maximize the identification of poor households, the default threshold in the RUSBoost model was prefered. On the other hand, if precision is prioritized due to limited resources, the Youden Index threshold offers a better alternative. Given the overall evaluation metrics, RUSBoost with the default threshold was suggested as the most reliable and well-balanced option among the compared models for classifying poor households in West Java under imbalanced data condition
Literature-Driven Contributions to the Development of LLM-Based Customer Insight Systems Nugroho, Irwan Andriyanto; Adi, Kusworo; Aryasa, Komang Budi
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 15 No. 01 (2026): JANUARY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v15i01.2534

Abstract

This research delineates the conceptual advancement of a sentiment analysis model employing Large Language Models (LLMs), augmented by a dynamic weighting system predicated on the strategic significance of product attributes. This research, based on a systematic review of seven recent studies predominantly utilizing conventional NLP methodologies discovers significant deficiencies, such as disjointed sentiment extraction and the absence of contextual, strategic weighting. Prior studies have established the efficacy of Natural Language Processing (NLP) techniques in evaluating customer satisfaction and online reviews; however, there has been a scarcity of initiatives that integrate sentiment analysis with product prioritization in decision-making processes. The suggested framework presents an innovative amalgamation of LLM-based sentiment analysis with a strategic weighting system that adapts in real-time according to business priorities, setting it apart from earlier customer analytics frameworks that consider sentiment and strategy in isolation. To conceptually validate this model, a thematic synthesis and comparative mapping approach were employed to assess the potential of the proposed components to enhance interpretability and alignment between customer feedback and product decisions. Initial conceptual analysis indicates that the framework may improve decision quality by integrating profound contextual sentiment insights with flexible business prioritization. The goal is to improve strategies for making products better, make sure that customer feedback is in line with strategic goals, and help businesses make decisions based on data in changing business environments.
Co-Authors Bagus Sartono Elok Savitri Pusparini, Elok Savitri Kusworo Adi Nugroho, Irwan Andriyanto Setiabudi, Nur Andi Utami Dyah Syafitri