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All Journal Marine Research in Indonesia JIEB : Jurnal Ilmiah Ekonomi Bisnis Jurnal Syntax Imperatif : Jurnal Ilmu Sosial dan Pendidikan Jurnal Al Azhar Indonesia Seri Ilmu Sosial Journal of Islamic Economics and Philanthropy International Journal Law and Legal Ethics (IJLLE) Journal of Hospitality Accommodation Management Journal Hotspot (jh) Jurnal Pengabdian Masyarakat STIE Surakarta (DIMASETA) Journal of Society Bridge Journal of Commerce Management and Tourism Studies Journal of Information Technology and society (JITS) Social Sciences Insights Journal Research of Islamic Economics (RIE) Jurnal Ilmu Politik dan Studi Sosial Terapan Indonesian Journal of Applied Accounting and Finance Journal of Sharia Economics, Banking and Accounting Indonesian Tourism Journal LinguaEducare: Journal of English and Linguistic Studies Inflasi : Jurnal Ekonomi, Manajemen dan Perbankan Expert Net: Exploration Journal of Technological Education Trends Alkasb: Journal of Islamic Economics Jurnal Ilmu-Ilmu Pertanian Jurnal Sosial & Humaniora (Silatene) Journal of Economics, Management and Accounting (JEMA) Journal of Economic and Business Jurnal Penelitian Ilmu Pariwisata JEIZA: Jurnal Ekonomi Islam Az-Zain
Koswara, Asep
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Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences Other

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Empowering Educators with AI: A Review of Google's 'Generative AI for Educators' Free Online Course Koswara, Asep
Expert Net: Exploration Journal of Technological Education Trends Vol. 2 No. 1 (2025): Edisi Juni
Publisher : Yayasan Insan Mulia Bima

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59923/expertnet.v2i1.390

Abstract

The Generative AI for Educators training program by Google provides teachers with essential AI tools to enhance instruction, automate administrative tasks, and personalize student learning experiences. This study evaluates the program’s effectiveness by analyzing its content, strengths, and areas for improvement. Findings indicate that the course significantly boosts educators' efficiency, with most participants reporting time savings and increased confidence in using AI. The program’s accessibility ensures that teachers across disciplines can integrate AI without prior technical expertise. However, the study also highlights areas needing enhancement, such as deeper content exploration, interactive elements, and long-term support for participants. Addressing these gaps would maximize the program’s impact and sustainability in educational settings. The study underscores the importance of AI in modern teaching and suggests further research on AI-driven pedagogical strategies. Ultimately, refining AI training programs will empower educators to leverage technology effectively, fostering innovative and student-centered learning environments.
Forecasting and Predicting Indonesia’s Digital Loan Trends via Google Search and Machine Learning Koswara, Asep
Jurnal Teknologi Informasi dan Masyarakat Vol 3 No 1 (2025): Journal of Information Technology and Society (JITS)
Publisher : Universitas Muhammadiyah Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35438/jits.v3i1.1417

Abstract

Public interest in financial technology, especially in digital loans, has grown rapidly in Indonesia over the past five years. This study analyzes weekly Google Trends data from June 2020 to June 2025, focusing on the keywords “pinjaman online” and “pinjol.” The research aims to understand usage patterns, identify interest spikes, and build predictive models for public attention using ARIMA and various machine learning methods. The ARIMA model, used as a baseline, produced a Mean Absolute Error (MAE) of 2.88 and Root Mean Square Error (RMSE) of 3.61. In contrast, the XGBoost model yielded superior accuracy, with an MAE of 1.39 and RMSE of 2.03. Among all models tested, XGBoost most accurately captured the volatility of online interest, especially during peak periods like October 2021 and January 2023. Findings confirm that “pinjol” outperforms “pinjaman online” in search frequency, driven by informal usage and media coverage. These insights have implications for financial regulators, fintech marketers, and social scientists studying digital behavior, suggesting machine learning models provide a more reliable approach to forecasting online public interest.
The Evolution of Advertising Language in the Age of Generative AI: A Sociolinguistic Approach Koswara, Asep
Jurnal Silatene Sosial Humaniora Vol. 3 No. 1 (2025): Maret
Publisher : Suwaib Amiruddin Foundation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53611/jrj5g534

Abstract

The rapid advancement of generative AI has significantly transformed advertising language, reshaping communication strategies and consumer engagement. This study examines the linguistic shifts introduced by AI-generated advertisements through a sociolinguistic perspective. The research highlights how AI-driven advertising optimizes personalization and efficiency while often lacking the emotional depth and rhetorical nuance of human-crafted content. By comparing traditional and AI-generated advertising discourse, this study identifies emerging linguistic trends and their implications for audience reception and brand authenticity. Additionally, ethical concerns surrounding privacy and manipulation in AI-generated content are explored. The findings suggest that while AI enhances advertising scalability, balancing automation with human creativity remains crucial for maintaining consumer trust and engagement. This research contributes to the broader discourse on digital communication, providing insights into the evolving role of AI in shaping persuasive language.
The New Cooperative Program ‘KMP’ And The Indonesian Pancasila Economy: A Legal And Philosophical Approach Koswara, Asep
International Journal of Law and Legal Ethics Vol 6 No 1 (2025): Vol 6 Issue 1 April 2025
Publisher : Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47701/ijlle.v6i1.4858

Abstract

The new emergence of Koperasi Merah Putih (KMP) reflects Indonesia’s renewed effort to realign its economic development with the foundational values of Pancasila. Despite the country’s rich history of cooperative movements, legal fragmentation and philosophical detachment have hindered their transformative potential. This paper aims to analyze KMP as both a legal and philosophical manifestation of Indonesia’s economic identity. Using a descriptive qualitative approach, the study examines existing legal frameworks, the integration of Pancasila values into cooperative practice, and the institutional dynamics surrounding KMP implementation. Key findings show that while KMP has a strong normative foundation rooted in Law No. 25/1992 and the 1945 Constitution, its practical application faces challenges in regulatory adaptation, institutional synergy, and philosophical consistency. The research highlights the importance of reconstructing legal instruments to support village-based economic democracy and advocates for embedding justice, solidarity, and identity within the cooperative structure. This study concludes that KMP can serve as a strategic model for reimagining Indonesia’s future economy—one that is community-centered, ethically grounded, and constitutionally aligned.
Leveraging TikTok virtual gifts for rural infrastructure funding: A case study from Sampang Village, East Java, Indonesia Koswara, Asep
Social Sciences Insights Journal Vol. 3 No. 1 (2025): Social Sciences Insights Journal
Publisher : MID Publisher International

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60036/jj6hx682

Abstract

This study explores the use of TikTok virtual gifts as a novel approach to funding rural infrastructure projects in East Java, Indonesia, focusing on the village of Sampang. The initiative, driven by local residents, utilized funds gathered from viral TikTok donations to repair damaged roads in the region. Through qualitative observation and thematic analysis of secondary data from news sources like Detik.com, this research examines the dynamics of community-led funding, social media influence, and the limitations of traditional government support. The findings highlight the significant role of digital platforms in empowering rural communities, overcoming bureaucratic delays, and fostering collective action. Despite the success of this initiative, questions remain regarding sustainability, transparency, and the future role of digital fundraising in rural development. This paper contributes to the understanding of how digital media can support grassroots development efforts and the challenges involved.
The Intersection of Generative AI and Applied Linguistics in Modern Marketing & Advertising Practices Koswara, Asep
LinguaEducare: Journal of English and Linguistic Studies Vol. 2 No. 1 (2025): LinguaEducare: Journal of English and Linguistic Studies
Publisher : Cipta Pustaka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63324/3vbkft90

Abstract

This study explores the intersection of generative AI and applied linguistics in modern marketing and advertising. Generative AI has revolutionized content creation by enabling hyper-personalization, optimizing audience engagement, and improving linguistic adaptability. Using a qualitative research methodology, this study employs content analysis and case studies to examine AI-driven marketing strategies, their implications on consumer behavior, and the ethical considerations surrounding automated content generation. While AI offers efficiency and innovation, challenges such as linguistic biases and ethical transparency persist. The study highlights advancements in natural language processing, the role of AI in shaping persuasive messaging, and the necessity for responsible AI implementation. Through an in-depth analysis, the research underscores the need for continued development in AI-human linguistic collaboration, ensuring inclusivity and authenticity in AI-generated marketing. Future prospects include the integration of multimodal AI, creating more immersive and interactive marketing experiences. The findings contribute to a deeper understanding of AI’s role in marketing, offering insights into its evolving impact on advertising communication and consumer interaction.
A Collaborative Model for Funding Indonesia’s MBG Program Through Government and Philanthropy Partnerships Koswara, Asep; Herlina, Lina
Journal of Islamic Economics and Philanthropy Vol. 7 No. 4 (2025): May
Publisher : Universitas Darussalam Gontor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21111/jiep.v7i4.13960

Abstract

Indonesia’s Makan Bergizi Gratis (MBG) program faces significant funding constraints, making its long-term sustainability uncertain. Given the limitations of government financing, this study explores a collaborative funding model that integrates public, philanthropic, and private sector contributions. Using a literature review and case study analysis, the research examines funding mechanisms from successful international programs and assesses their applicability to Indonesia. Findings highlight effective public-philanthropy partnerships in countries such as Brazil, India, and the UK. Brazil’s Fome Zero program successfully reduced hunger through strong government commitment and private sector engagement. India’s Akshaya Patra Foundation scaled its school meal initiative by leveraging corporate social responsibility (CSR) funding, while the UK’s Magic Breakfast demonstrated how philanthropy can complement government efforts in ensuring food security for students. These cases illustrate how multi-sectoral collaboration enhances financial stability, operational efficiency, and program reach. This study provides practical recommendations for policymakers and philanthropic organizations to optimize financial contributions and governance structures. By fostering strong multi-sectoral collaboration, this model can serve as a replicable framework for other large-scale social programs.
Geospatial analysis of Islamic business trends: Mapping global interest via google search query clustering Koswara, Asep
Alkasb: Journal of Islamic Economics Vol. 4 No. 1 (2025)
Publisher : Islamic Economics Study Program, Faculty of Sharia and Islamic Economics, Universitas Annuqayah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59005/alkasb.v4i1.632

Abstract

The Islamic economy, encompassing sectors such as finance, halal food, tourism, and fintech,  has expanded rapidly worldwide in recent years. Yet, global public interest trends in these sectors remain underexplored, particularly from a digital behavior standpoint. This study investigates Islamic business trends by analyzing and clustering Google search data (2020–2025) to uncover geographic and thematic interest patterns. Using geospatial mapping and unsupervised machine learning, it evaluates Google Trends data to reveal temporal and spatial shifts in engagement. Findings show Islamic finance interest is concentrated in regions with mature Shariah-compliant systems, while halal food attracts global attention beyond Muslim-majority demographics. Halal tourism and Sharia fintech, though niche, exhibit untapped growth potential. The study demonstrates how digital trace data can enhance real-time economic trend analysis, with regional variations reflecting cultural and institutional influences. By combining digital analytics, economic geography, and Islamic business research, this work provides actionable insights for policymakers and investors to identify market opportunities. Additionally, it introduces a pioneering framework integrating geospatial and machine learning methods to track global business trends, advocating for broader use of digital data in economic studies.
Identifying high-value keywords for Bali tourism: A machine learning approach Koswara, Asep
Journal of Commerce, Management, and Tourism Studies Vol. 4 No. 2 (2025): Aug 2025
Publisher : YAYASAN MITRA PERSADA NUSANTARA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58881/jcmts.v4i2.334

Abstract

This study explores how machine learning techniques, specifically K-Means Clustering, can be applied to identify high-value tourism-related keywords for Bali using Google Keyword Planner data. By analyzing normalized search volume, cost-per-click (CPC), and competition scores, the keywords were grouped into three meaningful clusters: (1) high-volume, high-CPC keywords such as Bali luxury resorts and honeymoon in Bali, (2) low-volume, high-CPC keywords like eco-retreat Bali and private villa Ubud, and (3) high-volume, low-CPC keywords including Bali itinerary and Bali beach names. The Elbow Method confirmed that three clusters offered the optimal segmentation. Findings show that luxury and culturally immersive travel themes yield the highest marketing value, while niche keywords offer untapped advertising potential. Seasonal analysis revealed peaks in keyword interest during mid-year and year-end holiday seasons, aligning with international travel patterns. The machine learning approach enhanced keyword structuring and revealed strategic timing opportunities for content deployment. The study concludes that data-driven keyword targeting can significantly improve the effectiveness and sustainability of digital marketing in Bali’s tourism sector. Recommendations include focusing on premium and niche clusters, while future research may integrate social media trends and geospatial analysis to deepen keyword relevance and behavioral insights.
Digital Banking Rivalry in Indonesia: ML-Powered Analysis and Forecasting Using Search Data for Top 5 Banks Koswara, Asep
AKUMULASI: Indonesian Journal of Applied Accounting and Finance Vol. 4 No. 1 (2025): June
Publisher : Vocational School, Universitas Sebelas Maret (UNS), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/akumulasi.v4i1.2360

Abstract

The growing adoption of digital banking in Indonesia has heightened competition among financial institutions, prompting the need for data-driven insights to understand consumer behavior. This research investigates public interest in Indonesia’s five leading digital banks: SeaBank, Bank Jago, Bank Neo Commerce (BNC), blu by BCA Digital, and Allo Bank. The analysis utilized Google Trends data from 2019 to 2024. The primary goal is to explore how search behavior reflects market competition, regional adoption, and potential strategies for stakeholder decision-making. To achieve this, this research employed a quantitative approach using descriptive analysis, time-series forecasting, and clustering. ARIMA and Prophet models were applied to forecast future interest trends, while clustering techniques identified similarities in regional and temporal patterns. ARIMA is found to be more accurate for stable trends, whereas Prophet effectively detects seasonal variations. Google Trends data, while innovative and timely, has limitations as a proxy for actual consumer behavior. However, it provides valuable directional insights. For instance, SeaBank and Bank Jago show sustained interest due to their integration with ecosystem like Shopee and Gojek, respectively. In contrast, Allo Bank's popularity appears to be mostly driven by events, making it more short-lived. This research, theoretically, contributes to the fields of fintech and consumer analytics by demonstrating that search interest reflects engagement with digital banking. Practically, it provides strategic recommendations for geo-targeted marketing, ecosystem partnerships, and identification of underserved areas. These findings can help digital banks enhance their regional outreach and establish a strong brand presence in Indonesia's evolving financial landscape.
Co-Authors Aditya, Vishnu Arief Rachman Hikmah Thoha Lina Herlina Neni Kurniawati Nurul Fitriya Siti Marpuah, Siti Tumpak Sidabutar