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All Journal Aptisi Transactions on Technopreneurship (ATT) ADI Bisnis Digital Interdisiplin (ABDI Jurnal) International Transactions on Artificial Intelligence (ITALIC) Journal of Computer Science and Technology Application JOT
Anandha Fitriani
University of Raharja
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Library & Information Science Social Sciences Other

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Examining the Joint Effects of Air Quality, Socioeconomic Factors on Indonesian Health Ahmad Wijaya Kusuma; Yuwan Jumaryadi; Samidi; Richard; Anandha Fitriani
Aptisi Transactions On Technopreneurship (ATT) Vol 5 No 2sp (2023): Special Issue: Support Technopreneurship in the Medical
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v5i2sp.338

Abstract

 This study addresses the pressing need to comprehensively manage air pollution by examining the roles of local and national public agencies from the perspective of the general public. Air quality poses a critical challenge that profoundly impacts various aspects of human life. To enhance our understanding and generate both theoretical and practical insights for public management, this research introduces several key variables: the engagement of authorities in mitigating air pollution, citizen involvement in pollution reduction efforts, financial incentives for individuals and businesses to adopt air-friendly behaviors, urban green investments, the communal consequences of air pollution, and the necessity for industrial participation. Employing Partial Least Squares Structural Equation Modeling (PLS-SEM) as the research approach, data was gathered from residents of Indonesia's largest cities, where pollution significantly affects society and governing bodies. The findings are pertinent for public managers at both local and national levels, providing valuable input to enhance strategies for curbing air pollution, enhancing air quality, and ultimately improving the well-being of inhabitants.
Leveraging AI for Superior Efficiency in Energy Use and Development of Renewable Resources such as Solar Energy, Wind, and Bioenergy Umi Rusilowati; Hajra Rasmita Ngemba; Rio Wahyudin Anugrah; Anandha Fitriani; Eka Dian Astuti
International Transactions on Artificial Intelligence Vol. 2 No. 2 (2024): International Transactions on Artificial Intelligence
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v2i2.537

Abstract

Energy efficiency and the development of renewable resources are crucial issues in addressing the global energy crisis and climate change. This research explores the role of artificial intelligence (AI) in increasing energy efficiency and optimizing the development of renewable resources, such as solar energy, wind, and bioenergy. By using a mixed-methods approach that combines qualitative and quantitative methods, this research identifies concrete applications of AI in various renewable energy sectors. The results demonstrate that AI can significantly improve operational efficiency and reduce energy waste. Examples include optimizing solar panel placement, predictive maintenance of wind turbines, and optimizing fermentation processes in biogas production. The implementation of AI in renewable energy not only enhances efficiency but also reduces costs and supports sustainability. This research contributes to the field of energy efficiency and AI technologies by providing empirical evidence of the benefits of AI in the renewable energy sector. It is recommended that governments and the energy industry widely adopt AI, invest in technology and workforce training, and strengthen collaboration between the energy, technology, and academic sectors to develop innovative and applicable AI solutions. Further research should conduct broader and more comprehensive studies, including analysis of the long-term costs and benefits of AI implementation, as well as the integration of AI technology with existing energy management systems.
Analysis of User Perceptions on Interactive Learning Platforms Based on Artificial Intelligence Eirene Sana; Anandha Fitriani; Purwanti; Djoko Soetarno; Maulana Yusuf
CORISINTA Vol 1 No 1 (2024): February
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/corisinta.v1i1.12

Abstract

Education is one field that is increasingly adopting artificial intelligence (AI) technology in an effort to improve the learning experience. AI-based interactive learning platforms have become a significant trend in modern education. This research aims to analyze user perceptions of AI-based interactive learning platforms and identify factors that influence their acceptance of this technology. We conducted an analysis using the SmartPLS method to explore the relationship between variables that influence user perceptions of AI in education. Research data was collected through surveys given to educational participants using AI-based learning platforms. The results of this research include findings about the extent to which factors such as interaction quality, usability, and social factors influence user perceptions of AI-based learning platforms. The results of data analysis will provide valuable insight into how the educational community accepts and adopts AI technology in the learning process. It is hoped that this research will make a significant contribution to the understanding of the acceptance of AI technology in educational contexts, as well as provide guidance for the development of more effective interactive learning platforms. The findings of this research can also support decision making in implementing AI in educational settings.
The Application of Artificial Intelligence in HR Recruitment Strategies Impacts Startupreneur Buying Interest: Penerapan Kecerdasan Buatan dalam Strategi Rekrutmen SDM Berdampak pada Minat Beli Startupreneur Nuke Puji Lestari Santoso; Marviola Hardini; Maulana Faqih Farail; Anandha Fitriani; Kristina Vaher
ADI Bisnis Digital Interdisiplin Jurnal Vol 6 No 1 (2025): ADI Bisnis Digital Interdisiplin (ABDI Jurnal)
Publisher : ADI Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/abdi.v6i1.1233

Abstract

The development of Artificial Intelligence (AI) in Human Resource Management (HRM) provides an opportunity to increase efficiency and effectiveness in the recruitment process in the modern business era. In this context, AI supports the achievement of the Sustainable Development Goals (SDGs), especially goal 8, namely decent work and economic growth, and goal 10 on reducing inequal ity. AI allows companies to optimize the candidate selection process by using sophisticated algorithms that can analyze large amounts of data to find the most suitable candidates for the organization needs. Thus, AI plays an important role in creating a faster, more accurate, and bias-free recruitment process, which ultimately improves the quality of the workforce. However, the application of AI in recruitment also faces challenges related to technology integration, personal data protection, and potential bias in algorithmic decision-making. This study examines the role of AI in optimizing the recruitment process and its contribution to achieving the SDGs. The study also evaluates the impact of AI on recruitment decisions and company productivity and provides recommendations for more effective implementation in modern business.
Design and Evaluation of Emotionally Adaptive Chatbots to Promote Positive Mental Well-Being in Young Adults Novi Indah Susanthi; Muhammad Fadheel Djamaly; Anandha Fitriani; Mardiana Mardiana; Chua Toh Hua
Journal of Orange Technology Vol. 1 No. 2 (2025): April
Publisher : Sinar Mentari Sundara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.68012/jot.v1i2.14

Abstract

The increasing prevalence of mental health challenges among young adults has driven growing interest in affective computing technologies that foster emotional support and psychological well-being. This study aims to design and evaluate an emotionally adaptive chatbot that promotes positive mental well-being through empathetic and user-centered interactions. Grounded in affective and positive computing frameworks, this research examines the influence of Emotion-Adaptive Capability, Perceived Empathy of the Chatbot, and Usability & Interaction Quality on Positive Mental Well-Being. A quantitative approach was employed by distributing an online questionnaire to young adult respondents who had interacted with emotion-aware chatbot systems. The collected data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS to test the hypothesized relationships. The results are expected to demonstrate that chatbots with higher emotional adaptability, greater perceived empathy, and better usability significantly enhance users’ psychological well-being. This study contributes to the development of human-centered affective computing by providing empirical evidence on how emotionally intelligent chatbot design can positively influence mental health outcomes. The findings offer practical implications for designers and developers aiming to create AI systems that are not only functional but also emotionally supportive and aligned with humanistic technology values.
Co-Authors Ahmad Wijaya Kusuma Chua Toh Hua Djoko Soetarno Eirene Sana Eka Dian Astuti Hajra Rasmita Ngemba Jumaryadi, Yuwan Kristina Vaher Mardiana Mardiana Marviola Hardini Maulana Faqih Farail Maulana Yusuf Muhammad Fadheel Djamaly Novi Indah Susanthi Nuke Puji Lestari Santoso Purwanti Richard Rio Wahyudin Anugrah Rusilowati, Umi Samidi Samidi