Kodrat Mahatma
Universitas Teknologi Digital

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

Found 2 Documents
Search

Data Integration Approaches for AI-Ready Data Architecture: A Comparative Review of Relational Databases, Data Warehouses, and Knowledge Graphs Kodrat Mahatma; Mamok Andri Senubekti; Binastya Anggara Sekti
Jurnal Teknologi Informatika dan Komputer Vol. 12 No. 1 (2026): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v12i1.3447

Abstract

The rapid development of Artificial Intelligence (AI)-based systems has increased demand for integrated data architectures that support operational, analytical, and semantic data management. Organizations currently utilize relational databases, Data Warehouses, and Knowledge Graphs to support data integration in modern AI environments. However, previous studies generally discuss these approaches separately and rarely provide an integrated perspective regarding their roles within AI-ready architectures. This article conducts a comparative literature review of Relational Databases, Data Warehouses, and Knowledge Graphs as data integration approaches for AI-based systems. The study applies a conceptual literature review approach by analyzing scientific publications related to data integration, data warehouses, the semantic web, and knowledge graphs. The findings indicate that Relational Databases mainly support operational layers, Data Warehouses support analytical layers, while Knowledge Graphs provide semantic representation and contextual reasoning capabilities for modern AI systems. This article proposes a three-layer data integration perspective consisting of operational, analytical, and semantic layers as a conceptual framework for AI-ready data architectures.
Perancangan Aplikasi Penilaian Untuk Otomasi Rekapitulasi Nilai Berbasis Desktop SMP Bina Harapan Bangsa Saskia Aulia Rachman; Robby Rohman Sukarya; Kodrat Mahatma
Jurnal Nasional Komputasi dan Teknologi Informasi Vol. 9 No. 4 (2026): Agustus, 2026
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/ps0xq149

Abstract

Abstrak - Proses penilaian hasil belajar siswa di SMP Bina Harapan Bangsa saat ini masih dilakukan secara semi manual menggunakan lembar kerja spreadsheet, sehingga menimbulkan risiko kesalahan input nilai, inkonsistensi format rekapitulasi, duplikasi data, serta keterlambatan penyusunan laporan akademik akibat proses pengecekan berulang. Penelitian ini bertujuan untuk merancang dan mengimplementasikan aplikasi penilaian siswa berbasis desktop guna mengotomasi proses pengolahan dan rekapitulasi nilai agar lebih efektif dan efisien. Metode pengembangan sistem yang digunakan adalah Rapid Application Development (RAD) yang meliputi tahapan perencanaan kebutuhan, perancangan bersama pengguna, konstruksi, dan implementasi. Aplikasi ini dibangun menggunakan bahasa pemrograman Python dengan pustaka Tkinter sebagai antarmuka pengguna serta basis data lokal berbasis format CSV untuk kemudahan pengelolaan data secara offline. Hasil penelitian melalui pengujian Black Box Testing menunjukkan bahwa seluruh fungsi utama seperti kalkulasi nilai otomatis dan fitur ekspor berjalan sesuai spesifikasi. Hasil evaluasi User Acceptance Testing (UAT) juga menyimpulkan bahwa aplikasi layak digunakan karena mampu mempercepat proses rekapitulasi nilai, meminimalkan kesalahan manusia, serta membantu guru dalam penyusunan laporan akademik secara sistematis. Kata kunci : Aplikasi Penilaian; Aplikasi Desktop; Python Tkinter; RAD; Abstract - The student learning assessment process at SMP Bina Harapan Bangsa is currently still conducted in a semi-manual manner using spreadsheet worksheets, which raises risks of data entry errors, inconsistent recapitulation formats, data duplication, and delays in preparing academic reports due to repeated data verification. This study aims to design and implement a desktop-based student assessment application to automate the processing and recapitulation of student scores in order to improve effectiveness and efficiency. The system development method used is Rapid Application Development (RAD), which includes requirement planning, user design, construction, and implementation stages. The application is built using the Python programming language with the Tkinter library as the user interface and a local database based on the CSV format for ease of offline data management. The research results through Black Box Testing indicate that all primary functions, such as automatic score calculation and export features, run according to specifications. The User Acceptance Testing (UAT) evaluation concludes that the application is feasible for implementation as it accelerates the score recapitulation process, minimizes human error, and assists teachers in preparing academic reports systematically. Keywords : Assessment Application; Desktop Application; Python Tkinter; RAD;