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All Journal CommIT (Communication & Information Technology) Jurnal Mantik
Iskandar Fitri
Nasional University
Computer Science & IT Economics, Econometrics & Finance Languange, Linguistic, Communication & Media

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Information Technology Service Management with Cloud Computing Approach to Improve Administration System and Online Learning Performance Wilianto Wilianto; Iskandar Fitri
CommIT (Communication and Information Technology) Journal Vol. 9 No. 2 (2015): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v9i2.1655

Abstract

This work discusses the development of information technology service management using cloud computing approach to improve the performance of administration system and online learning at STMIK IBBI Medan, Indonesia. The network topology is modeled and simulated for system administration and online learning. The same network topology is developed in cloud computing using Amazon AWS architecture. The model is designed and modeled using Riverbed Academic Edition Modeler to obtain values of the parameters: delay, load, CPU utilization, and throughput. The simu- lation results are the following. For network topology 1, without cloud computing, the average delay is 54  ms, load 110 000 bits/s, CPU utilization 1.1%, and throughput 440  bits/s.  With  cloud  computing,  the  average  delay  is 45 ms,  load  2 800  bits/s,  CPU  utilization  0.03%,  and throughput 540 bits/s. For network topology 2, without cloud computing, the average delay is 39  ms, load 3 500 bits/s, CPU utilization 0.02%, and throughput database server 1 400 bits/s. With cloud computing, the average delay is 26 ms, load 5 400 bits/s, CPU utilization email server 0.0001%, FTP server 0.001%, HTTP server 0.0002%, throughput email server 85 bits/s, FTP    server 100 bits/sec, and HTTP server 95  bits/s.  Thus,  the  delay, the load, and the CPU utilization decrease; but,  the throughput increases. Information technology service management with cloud computing approach has better performance.
DATA CLUSTER MAPPING OF GLOBAL COVID-19 PANDEMIC BASED ON GEO-LOCATION: DATA CLUSTER MAPPING OF GLOBAL COVID-19 PANDEMIC BASED ON GEO-LOCATION Iskandar Fitri; Muchamad Refly Asmar; Albar Rabhasy
Jurnal Mantik Vol. 4 No. 1 (2020): May: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1121.186 KB)

Abstract

The spread of the covid-19 virus pandemic is very fast, where was start of the virus spreading from Wuhan City, Hubei Province, China and suddenly spread out widely to almost around the word. According that kind of pandemic phenomena, this research was conducted to make clustering based on data of latitude and longitude due global spreading of Covid-19 use DBSCAN (Density-Based Spatial Clustering Of Applications With Noise) and K-Means to find a level accurate and suitable in calculating for this pandemic case as the alternative choices for condition analyse in decision making purpose. The algorithm had developed calculate based on characterization from geolocation of the country which is to determine the number quality of cluster use Silhoutte Coefficient and Elbow Methods. Therefore, from calculated results can be analyse similarity of covid-19 spreading pattern refer to clustering in each province or country. From data testing show that DBSCAN method separate the data of noise points with eps=22 and minimum pts=4, and for K-Means method with k = 3. After calculation by use the two methods, finally, can visualize the mapping cluster continent of Asia, Europe and Africa with showing the pattern of increasing covid19 cases that can began controlled. The other result show cluster for continent of north and South America have increased significant and the Australian Continent cluster gets the lowest case and can controlled.
Co-Authors Albar Rabhasy Muchamad Refly Asmar Wilianto Wilianto