Hirzil Kaisan, NIM.: 21106050078 (2026) RANCANG BANGUN EXTENSION VSCODE UNTUK CODE REVIEW OTOMATIS BERBASIS AI GENERATIF Sebagai Memenuhi Persyaratan Mencapai Derajat Sarjana (S1). Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.
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Text (RANCANG BANGUN EXTENSION VSCODE UNTUK CODE REVIEW OTOMATIS BERBASIS AI GENERATIF Sebagai Memenuhi Persyaratan Mencapai Derajat Sarjana (S1))
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Text (RANCANG BANGUN EXTENSION VSCODE UNTUK CODE REVIEW OTOMATIS BERBASIS AI GENERATIF Sebagai Memenuhi Persyaratan Mencapai Derajat Sarjana (S1))
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Abstract
This research designs and develops a Visual Studio Code extension powered by generative AI for automated code review. The extension enables users to select AI models and review concepts (e.g., clean code principles) as well as determine whether to review the entire code or specific lines. The review results are presented through an interactive Webview, with an option to save suggested code improvements. With the integration of the GROQ API and an interactive interface, this extension is expected to assist novice programmers in understanding their code quality, detecting and fixing code violations, and improving coding efficiency and productivity. Literature suggests that low-quality code may contain up to fifteen times more bugs than clean code, highlighting the potential of this tool to reduce software defects and accelerate the review and debugging process. This study contributes practically by supporting beginners in writing high-quality code and academically by providing a baseline for implementing AI-driven code review as a novel approach in programming education and software industry practice. Additionally, the extension features an interactive chat that allows users to ask follow-up questions to the AI for further clarification or explanation of the review results.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information / Supervisor: | Ir. Aulia Faqih Rifa'i, M.Kom. |
| Uncontrolled Keywords: | VSCode extension; AI generatif; code review otomatis; code quality; code inefficiency; clean code |
| Subjects: | 000 Ilmu Komputer, Ilmu Informasi, dan Karya Umum > 000 Karya Umum > 004 Pemrosesan Data, Ilmu Komputer, Teknik Informatika |
| Divisions: | Fakultas Sains dan Teknologi > Informatika (S1) |
| Depositing User: | Muchti Nurhidaya [muchti.nurhidaya@uin-suka.ac.id] |
| Date Deposited: | 22 Jul 2026 09:28 |
| Last Modified: | 22 Jul 2026 09:28 |
| URI: | http://digilib.uin-suka.ac.id/id/eprint/77599 |
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