Article Per Year (5 Year)
p-Index From 2021 - 2026
1.318
P-Index
This Author published in this journals
All Journal Journal Hotspot Jurnal Ilmu Politik dan Studi Sosial Terapan Journal of Sharia Economics, Banking and Accounting Inflasi : Jurnal Ekonomi, Manajemen dan Perbankan Journal of Economics, Management and Accounting (JEMA) Journal of Economic and Business ASEAN Journal of Halal Study Applied Environmental Sustainability And Technology (AEST)
Asep Koswara
IKOPIN University
Economics, Econometrics & Finance Education Environmental Science Law, Crime, Criminology & Criminal Justice Social Sciences

Published : 8 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 8 Documents
Search

 1 
The Anatomy of Viral TikTok Ads: Sentiment and Semantic Analysis of Top-Performing Keywords Asep Koswara
Journal of Economics, Management and Accounting (JEMA) Vol. 2 No. 01 (2024): Journal of Economics, Management and Accounting (JEMA)
Publisher : Devitara Innovations

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study analyzed the anatomy of viral TikTok advertisements by examining the sentiment and semantic characteristics of top-performing keywords in the Indonesian market. The research utilized data from TikTok’s Keyword Insights platform, focusing on metrics such as popularity, click-through rate, conversion rate, and cost per acquisition. The analysis revealed that viral keywords predominantly exhibited neutral sentiment and were closely linked to culturally relevant terms reflecting local consumer interests. The dataset included over 700 million impressions and revealed that keywords such as pria (man), diskon 50% (50% discount), and sepatu (shoes) dominated virality with popularity scores reaching up to 40,000 and engagement rates exceeding 25%. Sentiment analysis showed that all top viral keywords carried a neutral sentiment. Correlation analysis indicated a strong positive relationship (r = 0.94) between engagement metrics and virality, while click-through rates negatively correlated with virality (r = -0.54). Cultural factors, including keywords related to modest fashion like hijab (headscarf) and gamis (muslim dress), were significant in shaping consumer behavior. The study demonstrates that viral success on TikTok in Indonesia relies on a combination of semantic relevance, cultural context, and interactive engagement, providing strategic insights for data-driven and culturally tailored marketing campaigns.  
The Halal Perspective on AI Voice Over Usage in Marketing and Advertising: Ethical and Sustainable Insights Asep Koswara; lina herlina
ASEAN Journal of Halal Study Vol. 1 No. 2 (2024)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/ajhs.v1i2.36471

Abstract

This paper explores the ethical, cultural, and sustainability implications of using AI voiceovers in marketing from an Islamic perspective. AI voiceover technology, which utilizes complex algorithms and deep learning to replicate human voices, has gained popularity for applications in advertising, customer service, and entertainment. While AI voiceovers offer significant benefits such as cost-effectiveness, efficiency, and accessibility, their usage raises concerns regarding ethical standards, environmental impact, and cultural sensitivity. This study highlights how Islamic teachings on justice, respect, and sustainability can guide the responsible use of AI voiceovers. By examining key issues such as energy consumption in AI systems and the importance of cultural inclusivity, this paper emphasizes the need for businesses to adopt practices that align with both ethical and environmental principles. It also stresses the importance of avoiding cultural insensitivity and stereotypes when using AI voices across different regions. The paper concludes with practical recommendations for marketers and suggestions for future research on the long-term impacts of AI voiceovers, offering a balanced approach to integrating this technology in a way that benefits society while upholding Islamic values.
The Growth of Digital Financial Services (DFS) in Indonesia Amid Tight Regulations: Drivers and Barriers Analysis Asep Koswara
Inflasi : Jurnal Ekonomi, Manajemen dan Perbankan Vol. 1 No. 2 (2024): Inflasi - November
Publisher : PT. Faaslib Serambi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66341/inflasi.v1i2.44

Abstract

This study explores the dynamics of digital financial services (DFS) growth in Indonesia amidst increasing regulatory challenges. Using a qualitative observational approach, the research investigates the key drivers and barriers to DFS expansion in the country. The findings reveal that the gross transaction value (GTV) of online payments in Indonesia reached $286 billion in 2022, with projections to grow by 19% annually to $404 billion by 2024. Similarly, the online lending sector saw an increase in loan balances, from $5 billion in 2022 to an expected $9 billion by 2024. The research identifies key drivers such as technological advancements, the increasing smartphone penetration, and a more supportive regulatory environment as factors contributing to the sector’s growth. However, challenges /barrier remain, particularly in terms of regulatory constraints, digital literacy gaps, and infrastructure limitations in rural areas. This paper also explores the potential implications of stricter regulations on fintech innovation and its effects on market competition. It concludes by offering recommendations for enhancing digital financial inclusion, including the need for targeted policy reforms, investment in digital literacy, and improved internet infrastructure.
The Future of Smart Tourism: Integrating AI, IoT, and Big Data for Enhanced Travel Experiences Asep Koswara
Journal Hotspot Vol. 3 No. 1 (2025): March
Publisher : Politeknik Pariwisata Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The rapid advancement of Artificial Intelligence (AI), the Internet of Things (IoT), and Big Data is transforming the tourism industry into a highly interconnected and intelligent ecosystem. This study, using a qualitative descriptive method, explores the contributions, benefits, challenges, and strategic implementation of these technologies in smart tourism. AI enhances personalization through chatbots, virtual assistants, and automated recommendations, while IoT enables seamless travel experiences through smart hotels and connected transportation. Big Data provides valuable insights for predictive analytics and demand forecasting, optimizing tourism management. Despite the advantages, challenges such as data privacy concerns, cybersecurity risks, and digital inequality remain significant barriers to adoption. Strategic implementation requires collaboration between governments, businesses, and technology providers, as well as investments in digital infrastructure and workforce training. By integrating these technologies effectively, the tourism industry can enhance visitor experiences, improve operational efficiency, and promote sustainable tourism development while ensuring an inclusive and secure smart tourism ecosystem.
Nowcasting Green Investment Sentiment from Google Trends: An Environmental Economic Analysis Using Machine Learning Asep Koswara
Applied Environmental Sustainability and Technology Vol. 1 No. 1 (2025): Applied Environmental Sustainability and Technology
Publisher : Prodi Ilmu Lingkungan Fakultas Sains dan Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24090/aest.v1i1.14080

Abstract

This study investigates global public sentiment toward green investment by analyzing five years (2020–2024) of Google Trends data using machine learning. A Green Investment Sentiment Index (GISI) was constructed from five key search terms: green finance, green investment, climate finance, ESG investing, and sustainable investing. Results show that green finance consistently dominated search interest, with a mean index score of 38.5 and a maximum of 100. GISI rose significantly from 35 in 2020 to 68 in 2024—an increase of 94%—with major spikes during COP26 (2021) and COP28 (2023). The LSTM model outperformed XGBoost and Random Forest in forecasting sentiment patterns, achieving the lowest RMSE (6.8), MAE (5.0), and MAPE (9.8%), with the highest R² (0.93), indicating strong predictive performance. The model captured both seasonal peaks (Q4 increases of 20–25%) and event-driven surges (+42% in climate finance during COP26). This research contributes a novel real-time approach to environmental sentiment monitoring, offering scalable tools for aligning policy interventions with public awareness. It provides actionable insights for policymakers, ESG investors, and sustainability communicators. Future research should expand by integrating social media and news data and adopting interpretable AI for transparent forecasting.
Predicting Trends in Islamic Banking & Finance: A Big Data Analysis Using Google Trends and AI Asep Koswara
Journal of Sharia Economics, Banking and Accounting Vol 2, No 2: 2025
Publisher : STAI Nurul Islam Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52620/jseba.v2i2.199

Abstract

This study employs big data analysis and AI forecasting to predict global public interest trends in Islamic Banking and Finance over the period 2020 to 2025, using Google Trends data and the artificial intelligence (NeuralProphet) model. Five key terms—Islamic finance, Islamic banking, sukuk, takaful, and halal investment—were analyzed to capture diverse sector dynamics. Forecasts reveal varying trends: takaful shows the highest predicted interest (85.6) with strong seasonal fluctuations, Islamic finance and halal investment exhibit steady growth with moderate seasonality, while sukuk and Islamic banking display irregular, event-driven patterns. Model evaluation via MAE (0.41–5.03), RMSE (0.49–6.95), and R² (0.16–0.67) reflects differing predictive accuracies, highlighting stable sectors versus more volatile markets. These findings underscore the potential of integrating big data and AI to enhance strategic planning and responsiveness in Islamic finance, supporting tailored, data-driven decision-making aligned with evolving market behavior.
#KaburAjaDulu: Analisis Fenomena Media Sosial sebagai Ekspresi Kekecewaan Masyarakat terhadap Kondisi Ekonomi, Sosial, dan Keadilan di Indonesia Asep Koswara; Lina Herlina
Jurnal Ilmu Politik dan Studi Sosial Terapan Vol 4 No 1 (2025): Maret 2025
Publisher : PT Polstac Repositori Riset

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65974/jiposster.v4i1.18

Abstract

Fenomena #KaburAjaDulu mencerminkan meningkatnya keresahan masyarakat terhadap kondisi ekonomi, sosial, dan keadilan di Indonesia. Penelitian ini bertujuan untuk menganalisis faktor pendorong tren ini, peran media sosial dalam membangun narasi kritik sosial, respons pemerintah dan masyarakat, serta dampaknya terhadap persepsi publik mengenai masa depan Indonesia. Metode penelitian yang digunakan adalah analisis isi terhadap unggahan di platform media sosial seperti X (Twitter), TikTok, threads, facebook dan Instagram, serta kajian pustaka dari penelitian terdahulu yang relevan. Analisis temuan penelitian ini dihubungkan dengan teori sosial, terutama dalam melihat bagaimana perubahan sosial dan ekspresi ketidakpuasan masyarakat terjadi melalui media digital. Hasil penelitian menunjukkan bahwa #KaburAjaDulu dipengaruhi oleh ketidakstabilan ekonomi, sulitnya akses terhadap pekerjaan, serta ketidakpuasan terhadap kebijakan pemerintah. Media sosial berperan dalam mempercepat penyebaran kritik sosial dan memperkuat wacana ketidakadilan. Respons pemerintah cenderung defensif, sementara masyarakat terpolarisasi antara yang mendukung atau mengkritik tren ini. Temuan ini diharapkan dapat memberikan wawasan bagi pembuat kebijakan dalam merumuskan langkah-langkah yang lebih responsif terhadap aspirasi masyarakat.
Persaingan Dompet Digital di Indonesia: Analisis Tren Google dan Machine Learning pada GoPay, OVO, dan DANA Asep Koswara
Journal of Economic and Business Vol 2 No 1 (2025): Maret
Publisher : Universitas Nazhatut Thullab Al-Muafa Sampang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52298/joebis.v2i1.89

Abstract

Penelitian ini menganalisis lanskap persaingan tiga platform dompet digital teratas di Indonesia—GoPay, OVO, dan DANA—dengan menggunakan data Google Trends dari Mei 2020 hingga Mei 2025. Melalui pendekatan kuantitatif dan analisis deskriptif berbasis machine learning, seperti klasterisasi K-Means, dekomposisi musiman, dan teknik peramalan (model ARIMA dan Prophet), penelitian ini menelusuri minat publik berdasarkan volume pencarian sebagai proksi perhatian pengguna. Hasil menunjukkan bahwa DANA unggul secara signifikan, mencapai puncaknya pada 100 poin pencarian pada Februari 2025, serta menunjukkan amplitudo musiman tertinggi (51,79) dan dominasi tren terbesar (77,49%). GoPay tetap stabil dengan variasi musiman yang rendah (amplitudo: 3,97; dominasi tren: 26,60%), sedangkan OVO mengalami penurunan konsisten, dengan minat pencarian yang stabil di kisaran 4–6 poin setelah tahun 2023 dan dominasi tren sebesar 60,94%. Hasil peramalan menunjukkan pertumbuhan berkelanjutan DANA, stagnasi GoPay, dan penurunan OVO. Model Prophet secara efektif menangkap tren naik nonlinier dan puncak musiman DANA.
Co-Authors lina herlina Lina Herlina