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All Journal Jurnal Informatika dan Teknik Elektro Terapan bit-Tech
Setiawan, Muhammad Surya Adhi
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Computer Science & IT

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PERANCANGAN SISTEM INFORMASI FITUR REKAP KAS DALAM PROSES BISNIS PADA STUDI KASUS TOKO KASIH IBU Fariz, Fariz; Hadi, Muhammad Nail; Sakti, Yudha Perwira Bima; Putra, Robby Alamsyah Satriya; Setiawan, Muhammad Surya Adhi; Fitri, Anindo Saka
Jurnal Informatika dan Teknik Elektro Terapan Vol. 11 No. 2 (2023)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v11i2.2888

Abstract

Penerapan sistem informasi merupakan bagian penting dalam era revolusi industri 4.0, penerapan tersebut seringkali memiliki pengaruh yang besar terhadap perusahaan dalam mengelola proses bisnisnya. Berbagai industri sudah mulai menerapkan pemanfaatan sistem ke dalam aktivitas bisnisnya, satu diantaranya industri toko kelontong. Toko Kasih Ibu sebagai salah satu toko kelontong yang bergerak di bidang bisnis dengan proses bisnis yang sama dengan toko kelontong lainnya memiliki salah satu proses bisnis yaitu rekapan kas. Rekapan kas pada Toko Kasih Ibu dilakukan dengan manual secara tertulis menggunakan buku dan kalkulasi menggunakan alat hitung dalam pencatatannya. Hal tersebut memunculkan berbagai kerugian dalam waktu dan kemungkinan data yang hilang akibat dari buku catatan hilang. Perubahan pada proses bisnis Toko Kasih Ibu dapat dilakukan dengan penerapan sistem informasi pada fitur perekapan datanya. Penelitian ini membahas tentang penerapan sistem perekapan kas yang dibutuhkan dengan menggunakan metode ICONIX process dan pemodelan Unified Modelling Language. Berbagai jenis diagram seperti Flowchart Diagram, Use Case Diagram, Robustness Diagram, Sequence Diagram serta Domain Model yang disertai dengan Graphical User Interface merupakan salah satu penggambaran sistem yang digunakan pada penelitian ini.
Performance Analysis of Reasoning Models in RAG-Based Question Answering System for University Admission Services Setiawan, Muhammad Surya Adhi; Pratama, Arista; Ananto, Prasasti Karunia Farista
bit-Tech Vol. 8 No. 3 (2026): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i3.3707

Abstract

Access to accurate, relevant, and timely information is crucial for prospective university students; however, conventional information services often struggle with high query volumes and the risk of generative hallucinations in automated systems. This study investigates whether reasoning-oriented large language models provide measurable improvements in response quality within a Retrieval-Augmented Generation (RAG) architecture for university admission services. The study hypothesizes that internal chain-of-thought reasoning improves factual grounding compared with non-reasoning models under identical retrieval conditions. A vector-based institutional knowledge base was constructed from 30 official admission sources using VoyageAI embeddings and evaluated on a multilingual dataset of 353 real-world inquiries in Indonesian, English, and Javanese dialects. To isolate the effect of reasoning capabilities, retrieval outputs and prompt configurations were controlled across all models. Performance was evaluated using the RAGAS framework across six models categorized as reasoning (DeepSeek-R1, Gemini-2.5-Flash, o4-mini) and non-reasoning (DeepSeek-V3, Gemini-2.0-Flash, GPT-4o-mini). The results show that reasoning models achieved a higher average RAGAS score (0.7772) than non-reasoning models (0.7289), representing a 6.63% improvement, with the largest gain observed in factual correctness (+15.95%). Additional multilingual benchmarking confirmed that reasoning models maintain more stable performance across languages. Gemini-2.5-Flash achieved the highest composite score (0.8207) while maintaining favorable cost efficiency. These findings indicate that reasoning-enabled models significantly improve factual reliability in domain-specific RAG systems, although overall system performance remains strongly dependent on retrieval quality.
Co-Authors Fariz Fitri, Anindo Saka Hadi, Muhammad Nail Prasasti Karunia Farista Ananto Pratama, Arista Putra, Robby Alamsyah Satriya Sakti, Yudha Perwira Bima