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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Ilmiah FIFO JURNAL MEDIA INFORMATIKA BUDIDARMA SINTECH (Science and Information Technology) Journal Abdimasku : Jurnal Pengabdian Masyarakat Journal of Intelligent Software Systems
Bagas Triaji
Universitas Teknologi Digital Indonesia, Yogyakarta
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Health Professions Industrial & Manufacturing Engineering Social Sciences

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Journal : Journal of Intelligent Software Systems

 1 
Query Execution Performance Analysis of Column-Oriented Database in Dashboard Bagas Triaji; Widyastuti Andriyani; Totok Suprawoto; Muhammad Agung Nugroho; Rikie Kartadie
Journal of Intelligent Software Systems Vol 1, No 2 (2022): Desember
Publisher : LPPM UTDI (d.h STMIK AKAKOM) Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (649.54 KB) | DOI: 10.26798/jiss.v1i2.768

Abstract

In making reports or dashboards from operational data, problems often occur in the query process with low speed in responding to an output, causing the server to experience overload. This condition often occurs in companies or higher education organizations in managing academic data. This condition can be improved by optimizing the database server by integrating relational databases with column-oriented databases to speed up query responses and save development costs. Based on the experiments that had been carried out, column-oriented has succeeded in optimizing with a significant difference in query execution time and the server does not crash.
Building a Knowledge Graph on Video Transcript Text Data Bagas Triaji; Widyastuti Andriyani; Bambang Purnomosidi DP; Faizal Makhrus
Journal of Intelligent Software Systems Vol 1, No 1 (2022): July
Publisher : LPPM UTDI (d.h STMIK AKAKOM) Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (802.045 KB) | DOI: 10.26798/jiss.v1i1.585

Abstract

Youtube is a video platform which not only provides entertainment but also education in which knowledge can be dug based on video transcripts. The results of this knowledge can be formed as a knowledge graph to build a knowledge base that saves storage space. Moreover, it can be used for other purposes such as recommendation systems and search engines. Prosen built a knowledge graph using NLP to extract the text by identifying the subject-verb-object (SVO) and stored in the graph database. The construction of a knowledge graph on a Youtube video transcript was successfully carried out. However, there are still obstacles in the process of extracting text using NLP which is less optimal so it is possible that there is still a lot of knowledge that has failed to be obtained.
Co-Authors Andriyani, Widyastuti Asyahri Hadi Nasyuha Azanuddin Azanuddin Bambang Purnomosidi Dwi Putranto Cucut Hariz Pratomo Faizal Makhrus Ibnu Rusydi Ita Mariami Laksana, Herdian Aji Leswanto, Tomi Nugroho, Muhammad Agung Rifai, Muhammad Arif Rikie Kartadie Subagyo, Aloysius Agus Totok Suprawoto Widyastuti Andriyani Yohanni Syahra