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All Journal Dinamik JOIV : International Journal on Informatics Visualization Journal of Feminism and Gender Studies Antasena: Governance and Innovation Journal
Setiawan, Dandi
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Humanities Computer Science & IT Education Environmental Science Social Sciences Other

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Journal : Dinamik

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Comparasi Model DeepSeek dan OpenAI dalam Meningkatkan Efisiensi Pencarian Informasi pada Sistem Pencarian Algoritma Mahenra, Ridwan; Setiawan, Dandi
Dinamik Vol 31 No 1 (2026)
Publisher : Universitas Stikubank

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35315/dinamik.v31i1.10287

Abstract

This study evaluates the efficiency of two artificial intelligence models, DeepSeek and OpenAI, in generating code for algorithmic systems. Efficiency is assessed through execution speed, code accuracy, and the number of code characters produced. Data were collected from 100 tests covering search, sorting, graph, dynamic programming, optimization, data processing, text, and machine learning algorithms. The objective is to compare the performance of both models to support the development of efficient information retrieval systems. The method involves algorithm testing with statistical analysis of execution time, accuracy, and code length. Results indicate that DeepSeek has an average execution time of 28.74 seconds, slightly slower than OpenAI’s 28.49 seconds. However, DeepSeek’s accuracy (85.88%) surpasses OpenAI’s (85.03%). The average number of code characters is identical at 96.35 characters. The study concludes that DeepSeek excels in accuracy, while OpenAI is faster in certain cases, providing valuable insights for developers in selecting AI models for information retrieval applications.
Co-Authors Adzania, Keisya Hilda Aliftania, Desti Astuti, Soekma Yeni Bambang Wibisono Damayanti Damayanti Heniasari, Radeva Desika Joko Tri Nugraha Mahenra, Ridwan Megawaty, Dyah Ayu Permata, Permata Setiawansyah Setiawansyah Sumanto, Sumanto