Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal IKRA-ITH Informatika : Jurnal Komputer dan Informatika Karimah Tauhid
Abubakar Basri
Universitas Djuanda
Computer Science & IT Economics, Econometrics & Finance Education Law, Crime, Criminology & Criminal Justice Neuroscience Social Sciences

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Menggali Bahasa Pemrograman Populer: Karakteristik Utama dan Penggunaan yang Luas M Riziq Sirfatullah Alfarizi; Muhammad Angga Nugraha; Abubakar Basri; Muhammad Rival Pratama; Ardiansyah Putra Pratama; Muhammad Jiddan Kalam; Ryandra Putra; Rangga Ash Raffy Jannuarta; Gheryyan Washesya Syagara
KARIMAH TAUHID Vol. 2 No. 4 (2023): Karimah Tauhid
Publisher : Universitas Djuanda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30997/karimahtauhid.v2i4.8816

Abstract

Dalam dunia pemrograman, bahasa pemrograman memiliki peran krusial dalam pengembangan perangkat lunak dan aplikasi. Artikel ini bertujuan untuk mengedukasi mengenai karakteristik utama dari bahasa pemrograman populer dan melihat berbagai penggunaan yang luas di industri teknologi. Penelitian ini menggunakan metode library research, yang melibatkan pengumpulan dan analisis data dari berbagai sumber terpercaya. Hasil penelitian menunjukkan bahwa bahasa pemrograman populer seperti Python, JavaScript, Java, C++, dan C# memiliki karakteristik unik yang membedakan mereka satu sama lain, dan digunakan secara luas dalam pengembangan aplikasi web, analisis data, kecerdasan buatan, permainan, serta pengembangan perangkat keras. Kesimpulan dari penelitian ini menggarisbawahi pentingnya pemilihan bahasa pemrograman yang tepat sesuai dengan kebutuhan pengembangan perangkat lunak.
EVALUASI KUANTITATIF RELIABILITAS DAN KECEPATAN INFERENSI PADA TIGA ARSITEKTUR LARGE LANGUAGE MODEL (ChatGPT, DeepSeek, Gemini) MENGGUNAKAN METRIK NLP BERBASIS PYTHON Abubakar Basri
IKRA-ITH Informatika : Jurnal Komputer dan Informatika Vol. 10 No. 2 (2026): IKRAITH-INFORMATIKA Vol 10 No 2 Juli 2026
Publisher : Fakultas Teknik Universitas Persada Indonesia YAI

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

Abstract

The massive adoption of Large Language Models (LLMs) across sectors demands an in-depthevaluation of the systems' intrinsic capabilities, particularly in responding to ambiguousinstructions. This study presents a structured comparative analysis of three leading LLMarchitectures ChatGPT, DeepSeek, and Gemini focusing on factual reliability and computationalefficiency (inference latency) as a direct consequence of prompt-ambiguity manipulation. Themethodology adopts a Black-Box Testing approach combined with quantitative analysis,systematically applied to 100 prompts classified into eight complexity categories. Factual reliabilitywas measured using a TF-IDF-based Cosine Similarity metric against ground truth, while latencywas recorded through end-to-end stopwatch measurement and processed with Python scripts onGoogle Colab. Results show that Gemini achieved the highest average accuracy (66.91%), followedby DeepSeek (64.89%) and ChatGPT (62.10%), while DeepSeek led in average inference speed(2.84 seconds) owing to its Mixture-of-Experts architecture. Pearson correlation tests for all threemodels produced negative coefficients (ChatGPT −0.200; Gemini −0.194; DeepSeek −0.030),disproving the traditional speed–accuracy trade-off hypothesis. These findings are expected to serveas an empirical compass for users selecting models with precision and as evaluative literature fordevelopers building more robust and efficient AI systems.
Co-Authors Ardiansyah Putra Pratama Gheryyan Washesya Syagara M Riziq Sirfatullah Alfarizi Muhammad Angga Nugraha Muhammad Jiddan Kalam Muhammad Rival Pratama Rangga Ash Raffy Jannuarta Ryandra Putra