ONTODB : Aplikasi untuk Transformasi Ontologi OWL ke Basis Data Relasi SQL

Rus, Amalia Mabrina Masbar; Othman, Zulaiha Ali

doi:10.24815/jda.v2i1.13094

Cited by 2 publications

(2 citation statements)

References 3 publications

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“…3. Document, can be a collection of web pages, electronic books, or other digital documents that being entered and organized to the database [11].…”

Section: Introductionmentioning

confidence: 99%

Web-Based Information Search System Development Using a Semantic Network

Samodra

Wijayati

Rosyidah

et al. 2021

KSS

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Finding information from a large collection of documents is a complicated task; therefore, we need a method called an information retrieval system. Several models that have been used in information retrieval systems include the Vector Space Model (VSM), DICE Similarity, Latent Semantic Indexing (LSI), Generalized Vector Space Model (GVSM), and semantic-based information retrieval systems. The purpose of this study was to develop a semantic network-based search system that will find information based on keywords and the semantic relationship of keywords provided by users. This cannot be done by most search systems that only work based on keyword matching or similarities. The Waterfall development model was used, which divides the development stages into five steps, namely: (1) requirements analysis and definition; (2) system and software design; (3) implementation and unit testing; (4) integration and system testing; and (5) operation and maintenance. The developed system/application was tested by trying to find information based on various combinations of keywords provided by the user. The results showed that the system can find information that matches the keyword, and other relevant information based on the semantic relationships of these keywords. Keywords: information retrieval, search system, semantic network, web-based application

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“…3. Document, can be a collection of web pages, electronic books, or other digital documents that being entered and organized to the database [11].…”

Section: Introductionmentioning

confidence: 99%

Web-Based Information Search System Development Using a Semantic Network

Samodra

Wijayati

Rosyidah

et al. 2021

KSS

View full text Add to dashboard Cite

show abstract

“…Beberapa penelitian memanfaatkan ontology karena dapat membantu dalam merepresentasikan data menjadi informasi yang sesuai ke dalam data warehouse, mampu merepresentasikan kebutuhan bisnis selama proses perancangan, dan memiliki kemampuan penalaran untuk memfasilitasi tugas perancangan. Ontologi adalah salah satu solusi untuk standarisasi penamaan tabel dan field dalam basis data sehingga basis data yang dihasilkan akan memiliki penamaan yang sama dan dapat memudahkan pertukaran data (Rus & Othman, 2019). Teknologi web semantik seperti ontologi dapat digunakan untuk membantu merepresentasikan data menjadi informasi yang koheren yang dapat dimasukkan ke dalam Data Warehouse (Thenmozhi, 2013).…”

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Transformasi Ontologi ke Model Dimensional

Togatorop

Simanjuntak²,

Nababan³

et al. 2022

JTIIK

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Data warehouse adalah salah satu komponen penting untuk analisis bisnis yang efektif. Salah satu model pada data warehouse adalah dimensional model yang banyak digunakan karena performa permrosesan yang lebih cepat dari model lain. Dua faktor utama pada perancangan dimensional model adalah adalah sumber data dan kebutuhan bisnis.Salah satu sumber data yang banyak digunakan adalah ontologi karena mampu merepresentasikan data menjadi informasi yang koheren yang dapat dimasukkan ke dalam Data Warehouse. Dalam penelitian ini dihasilkan sebuah tools berbasis ontologi yang digunakan untuk secara otomatis mendapatkan dimensional model untuk data warehouse dari sumber data dan kebutuhan bisnis. Tahapan yang dilakukan mengidentifikasi semua informasi pada file ontology yang dimasukkan pengguna, kemudian daftar dimensi dan fact dihasilkan berdasarkan aturan perancangan dimensional model. Pembuatan fact tabel dan dimensi tabel dirancang berdasarkan rule perancangan dimensional model yang diperkenalkan oleh Kimball. Setelah tabel fact dan dimensidiidentifikasi, maka tabel fact dan dimensi tersebut diubah ke dalam bentuk kueri yang dapat dieksekusi pada MySQL. Penelitian ini berhasil menghasilkan dimensional model dari sumber data ontology. AbstractThe data warehouse is one of the essential components for effective business analysis. One of the models in the data warehouse is the dimensional model that is widely used because the processing performance is faster than other models. The two main factors in designing a dimensional model are data sources and business requirements. One of the most widely used data sources is ontology because it is able to represent data into coherent information that can be entered into the Data Warehouse. In this research, an ontology-based tool is produced which is used to automatically obtain dimensional models for the data warehouse from data sources and business needs. The step taken identifies all the information in the ontology file entered by the user, then a list of dimensions and facts is generated based on the design rules for the dimensional model. The creation of fact tables and dimension tables are designed based on the dimensional model design rules introduced by Kimball. After the fact and dimension tables are identified, the fact and dimension tables are converted into queries that can be executed in MySQL. This study succeeded in producing dimensional models from the ontology data source.

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ONTODB : Aplikasi untuk Transformasi Ontologi OWL ke Basis Data Relasi SQL

Cited by 2 publications

References 3 publications

Web-Based Information Search System Development Using a Semantic Network

Web-Based Information Search System Development Using a Semantic Network

Transformasi Ontologi ke Model Dimensional

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