Article Per Year (5 Year)
p-Index From 2020 - 2025
0.61
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This Author published in this journals
All Journal Journal of Economics and Business UBS Journal of Digital Business and Data Science
Rudi Ferdiansah
Universitas Muhammadiyah Cirebon
Economics, Econometrics & Finance

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Mengidentifikasi Kecenderungan Pencarian Kata Kunci Berdasarkan Tren Pencarian Google untuk Meningkatkan Kualitas SEO Rudi Ferdiansah; Abi Surya Wijaya; Komarudin Komarudin; Muhammad Saied; Azka Muharam
Journal of Economics and Business UBS Vol. 12 No. 5 (2023): Special Issue
Publisher : UniSadhuGuna Business School

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52644/joeb.v12i5.465

Abstract

Penelitian ini bertujuan untuk mengidentifikasi kecenderungan pencarian kata kunci berdasarkan tren pencarian Google untuk meningkatkan kualitas SEO. Metode penelitian kualitatif digunakan dalam penelitian ini dengan teknik analisis konten yang mendalam pada 30 situs web di Indonesia yang berkaitan dengan topik yang dijadikan objek penelitian. Data yang dikumpulkan melalui wawancara mendalam dengan pemilik situs web dan pengguna internet di Indonesia. Hasil penelitian menunjukkan bahwa terdapat beberapa kata kunci yang paling banyak dicari pada tahun 2021 di Indonesia. Hasil analisis konten menunjukkan bahwa konten dengan kata kunci yang paling banyak dicari lebih cenderung untuk mendapatkan peringkat yang lebih tinggi dalam hasil pencarian Google. Selain itu, data dari wawancara menunjukkan bahwa kecenderungan pencarian kata kunci pada tahun 2021 telah berubah dan diperkirakan akan terus berubah di masa depan. Penelitian ini menyimpulkan bahwa penggunaan kata kunci yang paling banyak dicari dapat membantu meningkatkan kualitas SEO pada situs web di Indonesia. Oleh karena itu, situs web harus memperhatikan tren pencarian Google dan mengikuti perkembangan tren pencarian kata kunci untuk meningkatkan kualitas SEO pada situs web mereka.
Strategic Role of Artificial Intelligence in Reshaping Global Digital Marketing: Opportunities and Organizational Challenges Abdul Robi Padri; Mar’atus Solikhah; Rudi Ferdiansah
Journal of Digital Business and Data Science Vol. 2 No. 1 (2025): Journal of Digital Business And Data Science
Publisher : Politeknik Siber Cerdika Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/jdbs.v2i1.13

Abstract

This study explores the strategic role of artificial intelligence (AI) in transforming digital marketing practices across global companies. In the era of rapid technological advancement, AI offers innovative tools that redefine customer engagement, campaign effectiveness, and market competitiveness. Employing a qualitative case study approach, the research gathered data through interviews with marketing executives, employee questionnaires, and direct observation of AI-driven marketing operations in ten multinational companies. The findings reveal that AI significantly enhances campaign personalization and efficiency, with 70% of respondents noting improved product relevance and 80% citing better marketing budget optimization. Despite these benefits, companies face persistent challenges, particularly in integrating systems and preparing employees. Data privacy concerns and the need to strike a balance between automation and creativity also emerged as critical issues. This study concludes that AI, while transformative, requires careful strategic implementation to maximize its potential in global marketing contexts. The study’s implications include guidance on training needs, strategic alignment, and ethical compliance in the adoption of AI.
Data Science Utilization in Consumer Trend Prediction: A Qualitative Study on an e-commerce Market Research Team in Indonesia Mar’atus Solikhah; Rudi Ferdiansah; Arif Rohman Hakim
Journal of Digital Business and Data Science Vol. 2 No. 1 (2025): Journal of Digital Business And Data Science
Publisher : Politeknik Siber Cerdika Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/jdbs.v2i1.16

Abstract

In the era of digital transformation, the e-commerce industry in Indonesia faces great challenges in understanding and responding to changes in consumer behavior that are very dynamic. Data science is a strategic approach that can help companies analyze consumer data deeply and predict market trends accurately. This research aims to explore how market research teams in e-commerce companies utilize data science in the process of predicting consumer trends. A qualitative approach with a case study design was used in this research, involving in-depth interviews, questionnaires, and observations of market research teams from three major e-commerce companies in Indonesia, namely Tokopedia, Bukalapak, and Blibli. The results show that tools such as Python, Tableau, and BigQuery are widely used in the analytics process, from data cleansing to trend visualization. The research team has a good conceptual understanding of data science, although there are still gaps in coordination between divisions. The implementation of data science has proven to have a positive impact on the accuracy of marketing strategies and the efficiency of business decision-making. Obstacles faced include limited technical human resources and lack of standardized documentation. This research provides a practical contribution in developing a data-driven market research ecosystem in Indonesia's e-commerce industry and serves as a basis for further research with a broader scope
Co-Authors Abdul Robi Padri Abi Surya Wijaya Arif Rohman Hakim Azka Muharam Komarudin Komarudin Mar’atus Solikhah Muhammad Saied