Jurnal Sosioteknologi

Balinese Small Entrepreneurs’ Self-Concept Behind the Adoption Levels of Social Media Innovation for Promotion

2025-08-15T15:16:17+07:00

This study aims to understand the Level of social media adoption for promotion and to identify the self-concept behind each stage among small business owners of the digital immigrant generation in Bali. The background of this research is the challenges small entrepreneurs face in adapting to the digital environment, where promotional issues are a significant obstacle. The digital divide and Indonesia's strong collective culture also influence the rate of innovation adoption. A qualitative approach was employed, involving interviews with 26 small business owners in Bali who are part of the digital immigrant generation, specifically Generation X (born between 1967 and 1980). Data were processed with NVivo 12 Pro software for analysis and visualization. The results show the highest adoption rate is at the Late Majority level (47%), followed by Early Adopters (19%), and Innovators and Laggards (14% each). There is a correlation between self-concept and adoption level. Early Adopters are characterized by initiative, hard work, and planning. Laggards are influenced by external factors, such as input from close family, and feel anxious about the rapid pace of technological development. The study concludes that innovation adoption is influenced by self-concept and collective culture. The Majority of entrepreneurs in the Late Majority stage show potential for adaptation. However, their process is often hindered by self-negotiation and dependence on social proof from those closest to them.

Attitudes and Intentions of Cross-Generational Employees toward the Utilization of AI in Universities

2025-08-08T17:15:54+07:00

This study investigates the attitudes and intentions of cross-generational employees toward the utilization of artificial intelligence (AI) in universities. Using data from 40 staff of research department as a respondents measured with a Likert scale, results show that attitudes toward AI were generally neutral, leaning positive (mean 3.33), while intentions to use AI were relatively high (mean 3.55). Despite attitudes not being fully positive, intentions remained strong, suggesting a readiness to adopt AI if organizational support is provided. No statistically significant differences were found between Generations X, Y, and Z in either attitudes or intentions, although minor variations existed. The findings indicate that AI adoption in universities has the potential for broad cross-generational support, particularly if accompanied by targeted training, education, and communication strategies. Tailored approaches for older generations can help reduce resistance, while Millennials and Gen Z can be empowered as agents of change. Cross-generational mentoring and equal access to AI-related learning opportunities are essential to foster a technology-inclusive workplace in higher education.

When Humor Gets Found (or Lost): Evaluating ChatGPT and Gemini’s Culture-Specific Humor Translation Strategies

2025-08-02T15:20:11+07:00

Preserving humor effect that arises from flouting conversational principles in culture-specific texts poses significant challenges when dealing with regional languages deeply rooted in linguistic and cultural variation. This type of humor depends on complex linguistic, cultural, and situational contexts resulting in difficulty to replicate the same effect in the target language. This study examines humor translation strategies and quality of two advanced AI language models i.e. ChatGPT 4.0 and Gemini 2.5 in rendering culture-specific humor that deliberately violates Grice's maxims of cooperation and Leech's politeness principles. Chiaro’s four-option humor translation framework is utilized to analyze the strategies employed, while Larson’s scales of clarity, accuracy, and naturalness are used to assess translation quality. Adopting a descriptive qualitative approach, this study investigates 20 humorous texts from the Sundanese’s Cangehgar (collection of humor) characterized by intentional violations of conversational and politeness principles. The study reveals that while both models employ distinct translation strategies, their effectiveness in preserving the humor's original intent varies. ChatGPT reveals a stronger ability to maintain the structure and essence of the humor in the punchline while Gemini's adaptations often dilute the comedic impact. This study contributes to the growing discourse on AI's role in humor translation and its broader implications for cross-cultural communication.

Quality Control Automation Based on YOLO Algoritm: Visual Defect Detection in Fusible Interlining Materials

2025-07-31T09:41:28+07:00

The fashion industry faces great challenges in maintaining product quality to face competition in the global industry. In addition to quality, the impact on the environment must also be considered, including minimizing waste and creating durable products. One of the important components in fashion, which is fusible interlining material that is usually used as a fabric lining material, requires strict quality control to ensure there are no product defects. This research aims to develop a quality control automation system based on YOLO v11 (You Only Look Once) technology to detect product defects in fusible interlining materials efficiently and accurately. This system is expected to improve the efficiency of the quality control process by reducing time and costs compared to manual methods, improve the accuracy of visual defect detection through the application of YOLO technology, and support the sustainability of the fashion industry by minimizing waste from defective materials. The research will be conducted through dataset collection in the form of photos/images of fusible interlining materials with various types of defects, data labeling to train the YOLO model, development of an optimized detection model, and testing the automation system in a real production environment to measure its performance. The strength of this research lies in the integration of the latest technology with the pressing needs of the fashion industry, namely efficiency, accuracy, and sustainability.

Ethics and Work Design in AI Integration in the Era of Industry 5.0: A Human-Centric Study of the Gojek Case

2025-07-28T20:06:00+07:00

The integration of Artificial Intelligence (AI) in the era of Industry 5.0 has triggered profound shifts in how organizations design work, approach ethics, and uphold human values. This study critically explores the alignment between AI implementation and human-centric principles through a qualitative literature review supported by thematic analysis and a case study of Gojek. The analysis identifies four core dimensions: the disruption of labor caused by AI, the conceptual development of human-centered work systems, ethical and inclusive organizational responses, and strategic practices that foster long-term adaptation. The Gojek case illustrates how digital firms can balance technological innovation with stakeholder well-being through partner training, data protection, and inclusive design. Findings highlight that successful AI integration in Industry 5.0 requires a deliberate shift from automation to the augmentation of human capabilities, guided by ethical governance and inclusive strategies. This research contributes to the discourse on sustainable digital transformation by offering a sociotechnical framework that places humans at the center of innovation. Its implications are particularly relevant for organizations operating in rapidly developing economies across the Global South.