University of Bunda Mulia

Developmental crisis episodes are common during emerging adulthood. Evidence from existing research suggests that existential concerns about life’s meaning are prominent during crisis episodes in emerging adulthood, but little quantitative research exists on this topic. The current cross-cultural study investigated the relationships between components of developmental crisis (measured using the 3-factor Developmental Crisis Questionnaire), and meaning in life (measured using the Meaning in Life Questionnaire, which has two factors: search for and presence of meaning in life). The sample comprised 1967 emerging adults across eight countries (Brazil, Czechia, Greece, India, Indonesia, Pakistan, Turkey and the United Kingdom). Two components of developmental crisis – being in transition/turning point and feeling disconnected/distressed – were positively associated with a search for meaning in life. Feeling disconnected/distress and lacking clarity/control were negatively associated with a presence of meaning in life. The findings emphasize the need for organizations and services that focus on supporting young adults in crisis, and that these should provide help with the often-hidden existential sense that life may be lacking meaning, and the corresponding endeavour to search for meaning.

The rapid adoption of Artificial Intelligence in financial technology demands governance mechanisms that go beyond ethical guidelines and fragmented risk controls. This study proposes a novel risk based AI governance model by operationalizing ISO/IEC 42001:2023 and systematically integrating it with the NIST Artificial Intelligence Risk Management Framework (AI RMF) to address AI risks across the entire lifecycle. Using a mixed methods approach, quantitative data were collected from a survey of 123 respondents who actively use fintech and AI enabled services to capture user perceived AI risks. Qualitative insights were obtained through semi structured interviews with fintech governance stakeholders and refined through expert judgement to assess governance maturity and implementation gaps. The results indicate that cybersecurity, platform operation, and credit risks are perceived as the most critical technical risks, while governance, ethical, and socio economic risks represent high impact strategic concerns. The novelty of this study lies in translating ISO/IEC 42001:2023 from a normative management standard into an operational, risk driven governance model by empirically mapping user risk perceptions, organizational practices, and expert judgement to ISO/IEC 42001:2023 clauses and NIST AI RMF functions. Based on this integration, the study delivers a structured AI governance model comprising strategic governance, risk and compliance management, lifecycle-based operational control, performance evaluation, and continuous improvement. The proposed model provides an auditable, human-centric, and scalable governance framework that strengthens compliance readiness, accountability, and trust in AI-driven fintech services.

The rapid development of artificial intelligence has accelerated the adoption of chatbots in organizations in Indonesia. But there is no systematic synthesis of the development of this technology in Indonesian context. This research provides a systematic review of the development and implementation of AI chatbots in Indonesia in 2021–2025, with the aim of filling the research gap related to sectoral applications, technological trajectories, and contextual challenges. A systematic literature review was conducted following the PRISMA 2020 guidelines on the Scopus, Google Scholar and arXiv databases to collect 257 initial records. After duplicate removal and a multi-step screening process, 16 high-quality studies were included in the final synthesis. Thematic analysis identified four main findings: (1) AI Chatbots are found in higher education, healthcare, banking, public services, fintech, e-commerce, and SMEs; (2) The technology has evolved from rule-based approaches (AIML, TF-IDF) to machine learning (Seq2Seq LSTM, Rasa+IndoBERT) and the latest large language model integration (GPT-3.5, Vertex AI); (3) Reported impacts include improved user satisfaction (SUS scores 80.1), operational efficiency, and 24/7 service availability; and (4) Existing challenges include accuracy in Indonesian language processing, complexities in system integration, data privacy issues, and varied levels of digital literacy. This review is the first systematic mapping of Indonesia’s AI chatbot landscape and makes evidence-based recommendations for the development of locally-adapted, culturally-sensitive models. Results show that future chatbot development should emphasize Indonesian language datasets and hybrid architectures that combine automation and human oversight.

The rapid evolution of smart city infrastructure demands governance frameworks that are simultaneously adaptive, transparent, and resilient. This paper proposes a novel framework integrating Adaptive Artificial Intelligence (AI) Governance with Digital Twin (DT) technology to address the complex, dynamic challenges of modern urban systems. The framework leverages real-time data streams from IoT sensors, GIS layers, and municipal databases to continuously synchronize physical and virtual city models, enabling predictive decision-support and policy simulation before live deployment. Empirical evaluation across five years (2020-2024) of smart city deployment data demonstrates marked improvements: Digital Twin coverage expanded from 18.4% to 84.3%, AI-assisted decision rates rose from 34.2% to 89.7%, emergency incident response times reduced by 67.1%, and citizen satisfaction scores increased from 61.5% to 91.8%. The governance architecture incorporates five core dimensions, transparency, accountability, fairness, security, and adaptability, each reinforced through DT-enabled simulation and monitoring. Comparative analysis against existing frameworks confirms superior performance in accuracy (97.4%), latency (12.3ms), and governance scoring (4.7/5.0). The findings position the proposed framework as a scalable and replicable model for data-driven smart city governance.

This study discusses the representation of Maslow’s love and belongingness needs in the movie Better Off Dead (2025) by Kristo Immanuel. Although many critics have highlighted the issue of social acceptance in the Better Off Dead movie, unfortunately, existing research on the film remains strictly confined to technical production dimensions. The writer examines how the characters Gema, Danu, Adriana, and Pak Cokro deal with their unmet needs in the workplace by using a qualitative approach. The findings show that each character engages in performative behaviors to fulfil love and belongingness needs. Gema, motivated by earlier family neglect, turns to fabricating his, his family’s, and his pet’s deaths to gain sympathy and attention from colleagues. Similarly, Danu and Adriana use false personas aligned with Gen Z social trends—such as fake international travel and coffee culture—to maintain relevance and social connection. Lastly, Pak Cokro shifts his choice of words to narrow generational gaps and be accepted by his younger colleagues. Beyond the cinematic text, this study underscores the broader psychological reality that unmet belongingness needs directly trigger performative behaviors and identity shifts within modern organizational settings.