Article Per Year (5 Year)
p-Index From 2019 - 2024
0.23
P-Index
This Author published in this journals
All Journal Data Science: Journal of Computing and Applied Informatics Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal Rekayasa elektrika
Amalia Amalia
Universitas Sumatera Utara
Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Public Health

Published : 4 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Data Science: Journal of Computing and Applied Informatics

 1 
Improving Data Collection on Article Clustering by Using Distributed Focused Crawler Dani Gunawan; Amalia Amalia; Atras Najwan
Data Science: Journal of Computing and Applied Informatics Vol. 1 No. 1 (2017): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (435.726 KB) | DOI: 10.32734/jocai.v1.i1-82

Abstract

Collecting or harvesting data from the Internet is often done by using web crawler. General web crawler is developed to be more focus on certain topic. The type of this web crawler called focused crawler. To improve the datacollection performance, creating focused crawler is not enough as the focused crawler makes efficient usage of network bandwidth and storage capacity. This research proposes a distributed focused crawler in order to improve the web crawler performance which also efficient in network bandwidth and storage capacity. This distributed focused crawler implements crawling scheduling, site ordering to determine URL queue, and focused crawler by using Naïve Bayes. This research also tests the web crawling performance by conducting multithreaded, then observe the CPU and memory utilization. The conclusion is the web crawling performance will be decrease when too many threads are used. As the consequences, the CPU and memory utilization will be very high, meanwhile performance of the distributed focused crawler will be low.
Co-Authors Abiyulail Alatas Abus Atras Najwan Dani Gunawan Fahmi Fahmi Lubis, Tasnim Maya Silvi Lydia Miftahul Huda Muhammad Dafitra Nurul Adilla Alatas Abus Raisya Aulia Lubis Siti Dara Fadilla