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All Journal International Journal of Electrical and Computer Engineering TELKOMNIKA (Telecommunication Computing Electronics and Control) Indonesian Journal of Electrical Engineering and Computer Science
Mustafa Man
Universiti Malaysia Terengganu
Computer Science & IT Electrical & Electronics Engineering

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Journal : TELKOMNIKA (Telecommunication Computing Electronics and Control)

 1 
Formal Specification for Spatial Information Databases Integration Framework (SIDIF) Mustafa Man; Julaily Aida Jusuh; Mohd Shafry Mohd Rahim; Mohammad Zaidi Zakaria
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 9, No 1: April 2011
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v9i1.672

Abstract

This paper discusses the formal validation for spatial information databases integration framework (SIDIF). A SIDIF database is a large, organized body of persistent data, usually associated with computerized software designed to update, query, and retrieve components of the data stored within the system. One of the common difficulties faced by the developer is in designing a robust database system. Even so, in order to solve this matter, developers have to focus their efforts on the formal specifications. The formal specification is supposed to reduce the overall development time. Formal specifications can be used to provide an unambiguous and precise supplement to natural language descriptions. Besides, it can be rigorously validated and verified leading to the early detection of specification errors. Consequently, to validate this problem formally, we specify the SIDIF database framework using Z language and prove by using Z/EVES theorem proven tool. By using this kind of tools, it may help to reduce time, energy and mistake compared to manual theorem proving which can be error task and tedious.
WEIDJ: Development of a new algorithm for semi-structured web data extraction Ily Amalina Ahmad Sabri; Mustafa Man
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 1: February 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i1.16205

Abstract

In the era of industrial digitalization, people are increasingly investing in solutions that allow their process for data collection, data analysis and performance improvement. In this paper, advancing web scale knowledge extraction and alignment by integrating few sources by exploring different methods of aggregation and attention is considered in order focusing on image information. The main aim of data extraction with regards to semi-structured data is to retrieve beneficial information from the web. The data from web also known as deep web is retrievable but it requires request through form submission because it cannot be performed by any search engines. As the HTML documents start to grow larger, it has been found that the process of data extraction has been plagued with lengthy processing time. In this research work, we propose an improved model namely wrapper extraction of image using document object model (DOM) and JavaScript object notation data (JSON) (WEIDJ) in response to the promising results of mining in a higher volume of image from a various type of format. To observe the efficiency of WEIDJ, we compare the performance of data extraction by different level of page extraction with VIBS, MDR, DEPTA and VIDE. It has yielded the best results in Precision with 100, Recall with 97.93103 and F-measure with 98.9547.
i-Eclat: performance enhancement of eclat via incremental approach in frequent itemset mining Wan Aezwani Wan Abu Bakar; Mustafa Man; Mahadi Man; Zailani Abdullah
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 1: February 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i1.13497

Abstract

One example of the state-of-the-art vertical rule mining technique is called equivalence class transformation (Eclat) algorithm. Neither horizontal nor vertical data format, both are still suffering from the huge memory consumption. In response to the promising results of mining in a higher volume of data from a vertical format, and taking consideration of dynamic transaction of data in a database, the research proposes a performance enhancement of Eclat algorithm that relies on incremental approach called an Incremental-Eclat (i-Eclat) algorithm. Motivated from the fast intersection in Eclat, this algorithm of performance enhancement adopts via my structured query language (MySQL) database management system (DBMS) as its platform. It serves as the association rule mining database engine in testing benchmark frequent itemset mining (FIMI) datasets from online repository. The MySQL DBMS is chosen in order to reduce the preprocessing stages of datasets. The experimental results indicate that the proposed algorithm outperforms the traditional Eclat with 17% both in chess and T10I4D100K, 69% in mushroom, 5% and 8% in pumsb_star and retail datasets. Thus, among five (5) dense and sparse datasets, the average performance of i-Eclat is concluded to be 23% better than Eclat.
Co-Authors Amir Hussain Ily Amalina Ahmad Sabri Julaily Aida Jusoh Julaily Aida Jusuh Julalily Aida Jusoh Mahadi Man Masita Masila Abd Jalil Mohammad Zaidi Zakaria Mohd Hafizuddin Ibrahim Mohd Shafry Mohd Rahim Rozniza Ali Syarilla Iryani Ahmad Saany Usman Haruna Wan Aezwani Wan Abu Bakar Zailani Abdullah