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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Proceeding of Community Service and Engagement
Nurjayanti Nurjayanti
Telkom University
Computer Science & IT Engineering

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PENGENALAN CODING BERBASIS GAME BAGI ANAK USIA DINI DI TK SARAH SHABRINA Nurjayanti Nurjayanti; Feddy Dea Reskyadita; Kusuma Ayu Laksitowening
The Proceeding of Community Service and Engagement (COSECANT) Seminar Vol. 4 No. 1 (2024): The Proceeding of Community Service and Engagement (COSECANT) Seminar
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/cosecant.v4i1.7799

Abstract

Kegiatan pelatihan coding berbasis game pada anak usia dini bertujuan untuk memperkenalkan dasar-dasar coding menggunakan aplikasi Scratch Junior (ScratchJr) di TK Sarah Shabrina. Pelatihan dimulai dengan pengenalan contoh proyek lomba lari yang kemudian di replikasi oleh siswa - siswa pada perangkat bergerak yang disediakan. Pembelajaran dilakukan secara berkelompok untuk mengembangkan kemampuan kerja sama dan eksplorasi dalam memahami aplikasi. Selain itu, siswa diberikan tantangan untuk mengeluarkan karakter dari suatu skenario game labirin secara mandiri. Hasil pelatihan menunjukkan bahwa siswa TK Sarah Shabrina memiliki kemampuan yang cukup baik dalam mengoperasikan perangkat bergerak dan menjalankan aplikasi ScratchJr dengan baik. Para siswa yang terbiasa bermain game pada perangkat bergerak, menunjukkan variasi dalam pemahaman konsep dasar coding serta tingkat keaktifan dalam mengikuti pelatihan. Meskipun demikian, semua siswa menunjukkan sikap positif, antusiasme dan keinginan untuk belajar lebih lanjut mengenai coding. Kegiatan pelatihan ini berhasil mencapai tujuannya, yaitu memberikan dasar pemahaman coding dan memotivasi siswa untuk mengembangkan keterampilan tersebut di masa depan.
Schema-Guided Prompt Strategies for Text-to-SQL over Relational Databases Using Local LLMs Nurjayanti Nurjayanti; Adiwijaya Adiwijaya; Ade Romadhony; Alfian Akbar Gozali
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 10 No 4 (2026): August 2026 (in progress)
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v10i4.6966

Abstract

Text-to-SQL systems translate natural language questions into executable SQL queries, allowing users without SQL expertise to access structured data stored in relational databases. Although Large Language Models (LLMs) have substantially improved SQL generation capabilities, many state-of-the-art Text-to-SQL approaches continue to rely on cloud-based models with high computational requirements. Such dependence limits their deployment in environments with limited computing resources. This study addresses this limitation by proposing schema-guided prompting strategies for Text-to-SQL generation using local LLMs. A chat-based application was developed using the Django Web Framework, while model inference was performed through the Ollama platform to enable the deployment of local LLMs. The proposed framework incorporates database schema information, including table structures and column attributes, into structured prompts to improve the alignment between natural language questions and SQL generation. Experiment results across multiple databases demonstrate that schema-guided prompting significantly improves Text-to-SQL performance. The highest accuracy was achieved by LLaMA 3 (8B) with objective-aware prompting, reaching an Exact Matching (EM) accuracy of 71.96%. These findings suggest that structured prompt engineering provides a practical alternative to model fine-tuning for locally deployed LLMs, offering an effective balance between SQL generation accuracy, computational efficiency, and data privacy. Future work will investigate fine-tuning strategies, example selection methods, and cross-domain evaluation to enhance SQL generation.
Co-Authors Ade Romadhony Adiwijaya Alfian Akbar Gozali Feddy Dea Reskyadita Laksitowening, Kusuma Ayu