Claim Missing Document
Check
Articles

Found 2 Documents
Search

Factors Influencing Generative AI Adoption in Government: A Case Study in BPS-Statistics of Indonesia Mutia Sayyidah; Sofian Lusa; Muhammad Rizki; Nurcholis Ramlan; Dana Indra Sensuse
Jurnal Impresi Indonesia Vol. 5 No. 4 (2026): Jurnal Impresi Indonesia
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/jii.v5i4.7666

Abstract

Rapid technological developments hold great potential, one of which is generative AI. Technology that is easily accessible and user-friendly tends to spread quickly, and BPS-Statistics of Indonesia is no exception. The challenges currently faced by BPS-Statistics of Indonesia, such as rapid data growth, high data demand, and data analysis and representation, encourage the institution to be adaptive to new technologies that can accelerate work processes. This research aims to determine the factors influencing the acceptance and use of generative AI (GenAI), such as ChatGPT, Gemini, and others, among BPS-Statistics of Indonesia employees, using Behavioral Intention as the central mediating variable that bridges the influence of these predictor factors on Use Behavior. The model also examines the relationships between external factors, such as Social Influence and Trust, and Perceived Usefulness and Perceived Ease of Use, as well as their effects on Attitude. Additionally, it evaluates the influence of Hedonic Motivation, Facilitating Conditions, Perceived Severity, and Perceived Vulnerability on Behavioral Intention. Based on a survey of 166 respondents at BPS-Statistics of Indonesia, the results reveal that Attitude has a significant influence on Behavioral Intention, while Perceived Severity has a significant negative influence on Behavioral Intention. Furthermore, Behavioral Intention is also shown to have a significant positive influence on Use Behavior. These findings contribute theoretically to the development of technology adoption models in the public sector and have practical implications for BPS-Statistics of Indonesia in formulating AI usage policies.
Developing a Conceptual Model for Knowledge Capture and Knowledge Sharing in Indonesia’s Higher Education Government Using Soft Systems Methodology Sidig Agung Sutrisno; Mutia Sayyidah; Dana Indra Sensuse; Sofian Lusa; Icha Mailinda; Novi Sofia Fitriasari
Information Technology Education Journal Vol. 5, No. 2, May (2026)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v5i2.280

Abstract

Purpose – This study aims to formulate a conceptual framework for knowledge capture and sharing in higher education governance in Indonesia. It addresses persistent challenges, including fragmented information systems, inadequate documentation of tacit knowledge, and the loss of institutional memory due to organizational restructuring and frequent staff turnover. Design/methods/approach – This study employs a qualitative case study approach, with Soft Systems Methodology (SSM) as the primary analytical framework. Data were gathered through semi-structured interviews with five informants purposively selected from a Directorate at the Echelon II level, which refers to a mid-to senior-level managerial unit within the Indonesian government structure. The analysis integrated thematic coding with the stages of SSM, such as rich picture development, CATWOE analysis, PQR formulation, and conceptual model construction, through which knowledge capture and knowledge sharing were identified as the principal themes. Findings – The findings indicate that current knowledge management practices are largely informal, fragmented, and heavily reliant on individuals. Tacit knowledge is rarely documented, while information exchange primarily occurs through personal interactions and meetings. To address these issues, the proposed conceptual model outlines structured processes for capturing, validating, storing, and disseminating knowledge through a centralized repository, supported by appropriate regulatory mechanisms. This approach provides a conceptual foundation for enhancing efficiency, efficacy, and overall effectiveness by reducing reliance on individual memory and ensuring knowledge continuity amid organizational change. Research implications/limitations - This study is limited to a single directorate and a relatively small group of informants, which may constrain the generalizability of the findings. Furthermore, the proposed model has not yet undergone empirical implementation or testing. Originality/value – This research contributes to the field by applying Soft Systems Methodology (SSM) within the complex context of public-sector higher education government. It also puts forward a structured, context-sensitive model that integrates human factors, processes, technological components, and governance mechanism to strengthen institutional knowledge management.