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All Journal IJIS - Indonesian Journal On Information System INTECH - Informatika Dan Teknologi
Soewoeh, Christian A. J.
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Computer Science & IT

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A GALAXY SCHEMA APPROACH FOR INTEGRATING HETEROGENEOUS MACROECONOMIC DATA INTO AN ANALYTICAL DASHBOARD Simanjuntak, Aurora Grace Valensia Pohan; Pinontoan, Benny; Soewoeh, Christian A. J.
IJIS - Indonesian Journal On Information System Vol 11, No 1 (2026): APRIL
Publisher : POLITEKNIK SAINS DAN TEKNOLOGI WIRATAMA MALUKU UTARA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36549/ijis.v11i1.471

Abstract

Local economic data in Jayawijaya Regency, such as Gross Regional Domestic Product (GRDP), poverty rates, Human Development Index (HDI), and unemployment statistics, is often scattered across different spreadsheets and standard documents. This scattering considerably hinders deep, multi-aspect assessment for regional leaders. This study aims to build and deploy a dynamic analytical dashboard that aggregates economic figures for the period 2020-2024. The design of this system employs a Data Warehouse with a multidimensional Galaxy Schema to merge indicators with distinct measurement types into a single central place. The Extract, Transform, Load (ETL) process was automated using Pentaho Data Integration, achieving 100% data matching accuracy with no data loss. Using Tableau Public as the visual display section, the dashboard functions through three subject-based views: Executive Summary, Economic Growth, and Social Welfare.Keywords: Analytical Dashboard, Data Warehouse, Galaxy Schema, Macroeconomic, Visualization
Pengembangan Chatbot Perpustakaan Berbasis Retrieval-Augmented Generation (RAG) pada Telegram Tutu, Elrica Meriana Isabel; Pinontoan, Benny; Tenda, Edwin; Soewoeh, Christian A. J.; Takaendengan, Mahardika I.; Ngangi, Stephano C. W.
INTECH Vol. 7 No. 1 (2026): INTECH (Informatika Dan Teknologi)
Publisher : Informatics Study Program, Faculty of Engineering and Computers, Baturaja University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54895/intech.v7i1.3435

Abstract

The library of Sam Ratulangi University (UNSRAT) has a large collection of books and academic resources; however, users still experience difficulties in obtaining book availability information quickly and efficiently. This study aims to develop and evaluate a Telegram-based chatbot using a Retrieval-Augmented Generation (RAG) approach integrated with the GPT-4.1-mini Large Language Model (LLM). The system was developed using the Waterfall method and implemented through the n8n workflow automation platform by integrating Telegram Bot, MySQL, and Pinecone as a vector database. The chatbot applies a Text-to-SQL RAG mechanism, where user questions are converted into embeddings, matched with database context, and transformed into SQL queries limited to SELECT operations. System evaluation was conducted using Black Box Testing, User Acceptance Testing (UAT), and RAG evaluation metrics consisting of Answer Relevancy and Faithfulness. The results show that the chatbot successfully performs its main functions and achieved a UAT score of 82.3%, while Answer Relevancy and Faithfulness obtained scores of 100%. The developed system is capable of providing relevant and interactive information regarding library collections.
Co-Authors Benny Pinontoan Ngangi, Stephano C. W. Simanjuntak, Aurora Grace Valensia Pohan Takaendengan, Mahardika I. Tenda, Edwin Tutu, Elrica Meriana Isabel