Analisis Analisis Potensi DuckDuckGo: Studi Literatur Mesin Pencari Aman sebagai Alternatif Edukatif bagi Mahasiswa di Era Digital

Authors

  • Randi Khansa Yafi Khalid Universitas Dian Nuswantoro
  • Annas Javier Saputra Universitas Dian Nuswantoro
  • DINAR ANANDA RIZQI FIRMANSYAH DINAR UNIVERSITAS DIAN NUSWANTORO

DOI:

https://doi.org/10.33633/joins.v10i2.13296

Keywords:

DuckDuckGo, filter bubble, privasi digital, mesin pencari, literasi informasi

Abstract

Kekhawatiran tentang privasi data dan fenomena filter bubble telah muncul sebagai akibat dari dominasi mesin pencari konvensional yang menggunakan algoritma personalisasi. Hal ini dapat membatasi keanekaragaman informasi akademik dan mempengaruhi kemampuan siswa untuk berpikir kritis. Penelitian ini bertujuan untuk mengkaji DuckDuckGo sebagai alternatif mesin pencari berbasis privasi yang memiliki kemampuan untuk mendukung lingkungan pembelajaran digital yang lebih netral dan etis. Penelitian ini menerapkan metode Systematic Literatur Review (SLR) dengan menelaah berbagai artikel ilmiah dan sumber yang dapat dipercaya mengenai DuckDuckGo, fenomena filter bubble, serta implikasi etis dalam pencarian informasi akademik. Temuan Studi menunjukkan bahwa mekanisme tanpa pelacakan (non-tracking) dan hasil pencarian yang seragam DuckDuckGo efektif mengurangi bias konfirmasi dan mendukung literasi data yang lebih baik. Akibat dominasi pasar yang kuat Google dan kurangnya kesadaran mahasiswa tentang pentingnya privasi digital, ini masih sulit diterapkan di institusi pendidikan tinggi. Sebagai kesimpulan, DuckDuckGo memiliki potensi yang luar biasa sebagai alat bantu penelitian akademik yang objektif. Namun, untuk mendorong adopsinya, pemerintah harus menawarkan dukungan pendidikan.

References

A. Saravanos et al., “Reputation, Risk, and Trust on User Adoption of Internet Search Engines: The Case of DuckDuckGo,” Nov. 2022, doi: 10.1007/978-3-031-19679-9_87.

A. G. Ekström, G. Madison, E. J. Olsson, and M. Tsapos, “The search query filter bubble: effect of user ideology on political leaning of search results through query selection,” Inf Commun Soc, vol. 27, no. 5, pp. 878–894, 2024, doi: 10.1080/1369118X.2023.2230242.

Q. M. Areeb et al., “Filter Bubbles in Recommender Systems: Fact or Fallacy -- A Systematic Review,” Jul. 2023, [Online]. Available: http://arxiv.org/abs/2307.01221

A. Akbar, S. Caton, and R. Bierig, “Personalised Filter Bias with Google and DuckDuckGo: An Exploratory Study,” in Communications in Computer and Information Science, Springer Science and Business Media Deutschland GmbH, 2023, pp. 502–513. doi: 10.1007/978-3-031-26438-2_39.

O. R. Azubuike, “Students’ Use Of Search Engines As Correlate Of Students Academic Performance In Senior Secondary Schools In Ogidi Education Zone,” 2024. [Online]. Available: https://www.mdrdji.org

S. Schultheiß, “How search engine marketing influences user knowledge gain: Development and empirical testing of an information search behavior model,” in CHIIR 2023 - Proceedings of the 2023 Conference on Human Information Interaction and Retrieval, Association for Computing Machinery, Inc, Mar. 2023, pp. 475–478. doi: 10.1145/3576840.3578297.

A. Hajian Hoseinabadi and M. CheshmehSohrabi, “Proposing a New Combined Indicator for Measuring Search Engine Performance and Evaluating Google, Yahoo, DuckDuckGo, and Bing Search Engines based on Combined Indicator,” Journal of Librarianship and Information Science, vol. 56, no. 1, pp. 178–197, Mar. 2024, doi: 10.1177/09610006221138579.

Jon Sidor, “Is DuckDuckGo safe? A comprehensive review,” Surfshark. Accessed: Nov. 27, 2025. [Online]. Available: https://surfshark.com/blog/is-duckduckgo-safe

Brave Software, “Brave vs DuckDuckGo browser,” Brave. Accessed: Nov. 27, 2025. [Online]. Available: https://brave.com/compare/duckduckgo-browser-vs-brave/

Maria Harutyunyan, “DuckDuckGo Statistics: Why it Matters in 2025? ,” loopexdigital. Accessed: Nov. 27, 2025. [Online]. Available: https://www.loopexdigital.com/blog/duckduckgo-statistics

G. Edelman, “DuckDuckGo’s Quest to Prove Online Privacy Is Possible,” WIRED. Accessed: Jun. 22, 2025. [Online]. Available: https://www.wired.com/story/duckduckgo-quest-prove-online-privacy-possible/?utm_source

J. P. Mello Jr, “Search Milestone Gives DuckDuckGo Something to Quack About,” E-Commerce Times. Accessed: Jun. 23, 2025. [Online]. Available: https://www.ecommercetimes.com/story/search-milestone-gives-duckduckgo-something-to-quack-about-86986.html?utm_source

C. Kacperski, M. Bielig, M. Makhortykh, M. Sydorova, and R. Ulloa, “Examining bias perpetuation in academic search engines: An algorithm audit of Google and Semantic Scholar,” First Monday, Nov. 2024, doi: 10.5210/fm.v29i11.13730.

Spread Privacy, “Measuring the ‘Filter Bubble’: How Google is influencing what you click,” Spread Privacy. Accessed: Jun. 23, 2025. [Online]. Available: https://spreadprivacy.com/google-filter-bubble-study/?utm_source=

Cornell University, “How does DuckDuckGo’s privacy features affect search engine algorithms like PageRank?,” Cornell University. Accessed: Jun. 23, 2025. [Online]. Available: https://spreadprivacy.com/google-filter-bubble-study/?utm_source=

Fetchserp, “Unlock the Power of DuckDuckGo Search for Academic Research,” fetchSERPAPI. Accessed: Jun. 23, 2025. [Online]. Available: https://fetchserp.com/duckduckgo-search-for-academic-research?utm_source=

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Published

2025-12-09

How to Cite

[1]
R. K. Y. . Khalid, A. J. . Saputra, and D. A. R. F. DINAR, “Analisis Analisis Potensi DuckDuckGo: Studi Literatur Mesin Pencari Aman sebagai Alternatif Edukatif bagi Mahasiswa di Era Digital”, Journal of Information System, vol. 10, no. 2, pp. 148–156, Dec. 2025.

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