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Automatic Backup System for Virtualization Environment Winarno, Idris; Sani, Muzaki Nurus
EMITTER International Journal of Engineering Technology Vol 2, No 1 (2014)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (10037.285 KB)

Abstract

Virtualization is a technology lately much discussed and considered as the proper way to cut costs in the construction of a data center. One example of the implementation of virtualization technologies is to using VMware. Another tools for virtualization are Xen and OpenVZ, but VMware is more flexible than Xen or OpenVZ because VMware can run a variety of operating systems. Although it has the advantage, virtualization technology also has a vital weakness, virtualization technologies could be analogous by putting all the eggs in a basket. This means that if the master server problem, all systems inside the virtual machine can not be used. However, it can be anticipated by provide backup facilities that run continually and automatically. VMware itself has had an application to backup/replicate virtual machines. However, that application is not free yet.This research has been design and creates a web-based software forbacking up virtual machines on VMware. So it made easier for users and admins to perform periodic backups of virtual machines. From the test results has been done, it can be seen that used disk type thin or zeroed thick make process backup faster, system can’t work well when virtual machine has snapshot, scheduling system and restoring system has worked well, physical ability data storage influence system.Keywords: Virtual machine, virtualization, Vmware, Backup, Data Center.
Automatic Representative News Generation using On-Line Clustering Sigita, Marlisa; Barakbah, Ali Ridho; Kusumaningtyas, Entin Martiana; Winarno, Idris
EMITTER International Journal of Engineering Technology Vol 1, No 1 (2013)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (8313.353 KB)

Abstract

The increasing number of online news provider has produced large volume of news every day. The large volume can bring drawback in consuming information efficiently because some news contain similar contents but they have different titles that may appear. This paper presents a new system for automatically generating representative news using on-line clustering. The system allows the clustering to be dynamic with the features of centroid update and new cluster creation. Text mining is implemented to extract the news contents. The representative news is obtained from the closest distance to each centroid that calculated using Euclidean distance. For experimental study, we implement our system to 460 news in Bahasa Indonesia. The experiment performed 70.9% of precision ratio. The error is mainly caused by imprecise results from keyword extraction that generates only one or two keywords for an article. The distribution of centroid’s keywords also affects the clustering results.Keywords: News Representation, On-line Clustering, Keyword Aggregation, Text Mining.
Automatic Backup System for Virtualization Environment Winarno, Idris; Sani, Muzaki Nurus
EMITTER International Journal of Engineering Technology Vol 2, No 1 (2014)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (10037.285 KB) | DOI: 10.24003/emitter.v2i1.20

Abstract

Virtualization is a technology lately much discussed and considered as the proper way to cut costs in the construction of a data center. One example of the implementation of virtualization technologies is to using VMware. Another tools for virtualization are Xen and OpenVZ, but VMware is more flexible than Xen or OpenVZ because VMware can run a variety of operating systems. Although it has the advantage, virtualization technology also has a vital weakness, virtualization technologies could be analogous by putting all the eggs in a basket. This means that if the master server problem, all systems inside the virtual machine can not be used. However, it can be anticipated by provide backup facilities that run continually and automatically. VMware itself has had an application to backup/replicate virtual machines. However, that application is not free yet.This research has been design and creates a web-based software forbacking up virtual machines on VMware. So it made easier for users and admins to perform periodic backups of virtual machines. From the test results has been done, it can be seen that used disk type thin or zeroed thick make process backup faster, system can’t work well when virtual machine has snapshot, scheduling system and restoring system has worked well, physical ability data storage influence system.Keywords: Virtual machine, virtualization, Vmware, Backup, Data Center.
Automatic Representative News Generation using On-Line Clustering Sigita, Marlisa; Barakbah, Ali Ridho; Kusumaningtyas, Entin Martiana; Winarno, Idris
EMITTER International Journal of Engineering Technology Vol 1, No 1 (2013)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (8313.353 KB) | DOI: 10.24003/emitter.v1i1.11

Abstract

The increasing number of online news provider has produced large volume of news every day. The large volume can bring drawback in consuming information efficiently because some news contain similar contents but they have different titles that may appear. This paper presents a new system for automatically generating representative news using on-line clustering. The system allows the clustering to be dynamic with the features of centroid update and new cluster creation. Text mining is implemented to extract the news contents. The representative news is obtained from the closest distance to each centroid that calculated using Euclidean distance. For experimental study, we implement our system to 460 news in Bahasa Indonesia. The experiment performed 70.9% of precision ratio. The error is mainly caused by imprecise results from keyword extraction that generates only one or two keywords for an article. The distribution of centroid’s keywords also affects the clustering results.Keywords: News Representation, On-line Clustering, Keyword Aggregation, Text Mining.
Indonesian Online News Extraction and Clustering Using Evolving Clustering Muhammad Alfian; Ali Ridho Barakbah; Idris Winarno
JOIV : International Journal on Informatics Visualization Vol 5, No 3 (2021)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.3.537

Abstract

43,000 online media outlets in Indonesia publish at least one to two stories every hour. The amount of information exceeds human processing capacity, resulting in several impacts for humans, such as confusion and psychological pressure. This study proposes the Evolving Clustering method that continually adapts existing model knowledge in the real, ever-evolving environment without re-clustering the data. This study also proposes feature extraction with vector space-based stemming features to improve Indonesian language stemming. The application of the system consists of seven stages, (1) Data Acquisition, (2) Data Pipeline, (3) Keyword Feature Extraction, (4) Data Aggregation, (5) Predefined Cluster using Automatic Clustering algorithm, (6) Evolving Clustering, and (7) News Clustering Result. The experimental results show that Automatic Clustering generated 388 clusters as predefined clusters from 3.000 news. One of them is the unknown cluster. Evolving clustering runs for two days to cluster the news by streaming, resulting in a total of 611 clusters. Evolving clustering goes well, both updating models and adding models. The performance of the Evolving Clustering algorithm is quite good, as evidenced by the cluster accuracy value of 88%. However, some clusters are not right. It should be re-evaluated in the keyword feature extraction process to extract the appropriate features for grouping. In the future, this method can be developed further by adding other functions, updating and adding to the model, and evaluating.
Desain Antar Muka Platform Reselient Untuk Manajemen Bencana Idris Winarno; Wiratmoko Yuwono; Tri Harsono
PROSIDING CSGTEIS 2013 CSGTEIS 2013
Publisher : PROSIDING CSGTEIS 2013

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Abstrak - Salah satu sistem informasi kebencanaanyang ada saat ini adalah Sahana.Sahana memilikiketerbatasan dalam integrasi dengan aplikasi pendukungkebencanaan yang dikembangkan olehpihaklain. Hal initerjadi karena tidak adanya platform standar yangmemiliki protokol yang terbuka untuk dapatdimanfaatkan oleh pengembang aplikasi atau sistem.Olehkarena itu dibutuhkan sebuah sistem informasikebencanaan yang bersifat universal dimana memilikiprotokol yang dapat dimanfaatkan oleh pengembang agaraplikasi yang dibuat dapat diintegrasikan secara langsungterhadap sistem informasi kebencanaan dengan diawalidengan pembuatan desain antar muka dari sisteminformasi tersebut.Penelitian ini membuat desain antarmuka yang bersifat universal dimana fitur-fiturnya lebihlengkap dari Sahana. Secara garis besar desain antarmuka antara Sahana dan Sistem informasi kebencanaanhampir sama tetapi pada sistem informasi kebencanaanterdapat tambahan beberapa fitur yaitu ManejemenTrackingdengan penggunaan UI Boostrap didalampembangunannya.Kata Kunci : Sistem Informasi, Bencana Alam, platform,antar muka
Automatic Representative News Generation using On-Line Clustering Marlisa Sigita; Ali Ridho Barakbah; Entin Martiana Kusumaningtyas; Idris Winarno
EMITTER International Journal of Engineering Technology Vol 1 No 1 (2013)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (8313.353 KB) | DOI: 10.24003/emitter.v1i1.11

Abstract

The increasing number of online news provider has produced large volume of news every day. The large volume can bring drawback in consuming information efficiently because some news contain similar contents but they have different titles that may appear. This paper presents a new system for automatically generating representative news using on-line clustering. The system allows the clustering to be dynamic with the features of centroid update and new cluster creation. Text mining is implemented to extract the news contents. The representative news is obtained from the closest distance to each centroid that calculated using Euclidean distance. For experimental study, we implement our system to 460 news in Bahasa Indonesia. The experiment performed 70.9% of precision ratio. The error is mainly caused by imprecise results from keyword extraction that generates only one or two keywords for an article. The distribution of centroid’s keywords also affects the clustering results.Keywords: News Representation, On-line Clustering, Keyword Aggregation, Text Mining.
Automatic Backup System for Virtualization Environment Idris Winarno; Muzaki Nurus Sani
EMITTER International Journal of Engineering Technology Vol 2 No 1 (2014)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (10037.285 KB) | DOI: 10.24003/emitter.v2i1.20

Abstract

Virtualization is a technology lately much discussed and considered as the proper way to cut costs in the construction of a data center. One example of the implementation of virtualization technologies is to using VMware. Another tools for virtualization are Xen and OpenVZ, but VMware is more flexible than Xen or OpenVZ because VMware can run a variety of operating systems. Although it has the advantage, virtualization technology also has a vital weakness, virtualization technologies could be analogous by putting all the eggs in a basket. This means that if the master server problem, all systems inside the virtual machine can not be used. However, it can be anticipated by provide backup facilities that run continually and automatically. VMware itself has had an application to backup/replicate virtual machines. However, that application is not free yet.This research has been design and creates a web-based software forbacking up virtual machines on VMware. So it made easier for users and admins to perform periodic backups of virtual machines. From the test results has been done, it can be seen that used disk type thin or zeroed thick make process backup faster, system can’t work well when virtual machine has snapshot, scheduling system and restoring system has worked well, physical ability data storage influence system.Keywords: Virtual machine, virtualization, Vmware, Backup, Data Center.
Towards a Resilient Server with an external VMI in the Virtualization Environment Agus Priyo Utomo; Idris Winarno; Iwan Syarif
EMITTER International Journal of Engineering Technology Vol 8 No 1 (2020)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v8i1.468

Abstract

Currently, cloud computing technology is implemented by many industries in the world. This technology is very promising due to many companies only need to provide relatively smaller capital for their IT infrastructure. Virtualization is the core of cloud computing technology. Virtualization allows one physical machine to runs multiple operating systems. As a result, they do not need a lot of physical infrastructures (servers). However, the existence of virtualization could not guarantee that system failures in the guest operating system can be avoided. In this paper, we discuss the monitoring of hangs in the guest operating system in a virtualized environment without installing a monitoring agent in the guest operating system. There are a number of forensic applications that are useful for analyzing memory, CPU, and I/O, and one of it is called as LibVMI. Drakvuf, black-box binary analysis system, utilizes LibVMI to secure the guest OS. We use the LibVMI library through Drakvuf plugins to monitor processes running on the guest operating system. Therefore, we create a new plugin to Drakvuf to detect Hangs on the guest operating system running on the Xen Hypervisor. The experiment reveals that our application is able to monitor the guest operating system in real-time. However, Extended Page Table (EPT) violations occur during the monitoring process. Consequently, we need to activate the altp2m feature on Xen Hypervisor to by minimizing EPT violations.
Student Behavior Analysis to Predict Learning Styles Based Felder Silverman Model Using Ensemble Tree Method Yunia Ikawati; M. Udin Harun Al Rasyid; Idris Winarno
EMITTER International Journal of Engineering Technology Vol 9 No 1 (2021)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v9i1.590

Abstract

Learning styles are very important to know so that students can learn effectively. By understanding the learning style, students will learn about their needs in the learning process. One of the famous learning management systems is called Moodle. Moodle can catch student experiences and behaviors while learning and store all student activities in the Moodle Log. There is a fundamental issue in e-learning where not all students have the same degree of comprehension. Therefore, in some cases of learning in E-Learning, students tend to leave the classroom and lack activeness in the classroom. In order to solve these problems, we have to know students' preferences in the learning process by understanding each student's learning style. To find out the appropriate student learning style, it is necessary to analyze student behavior based on the frequency of visits when accessing Moodle E-learning and fill out the Index Learning Style (ILS) questionnaire. The Felder Silverman model's learning style classifies it into four dimensions: Input, Processing, Perception, and Understanding. We propose a learning style prediction model using the Ensemble Tree method, namely Bagging and Boosting-Gradient Boosted Tree. Afterwards, we evaluate the classification results using Stratified Cross Validation and measure the performance using accuracy. The results showed that the Ensemble Tree method's classification efficiency has higher accuracy than a single tree classification model.