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Journal of Information Technology and Computer Science

jitecs
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Published by Universitas Brawijaya

ISSN : 25409433 EISSN : 25409824 DOI : -

Core Subject : Science, Engineering,

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

The Journal of Information Technology and Computer Science (JITeCS) is a peer-reviewed open access journal published by Faculty of Computer Science, Universitas Brawijaya (UB), Indonesia. The journal is an archival journal serving the scientist and engineer involved in all aspects of information technology, computer science, computer engineering, information systems, software engineering and education of information technology. JITeCS publishes original research findings and high quality scientific articles that present cutting-edge approaches including methods, techniques, tools, implementations and applications.

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Articles 10 Documents

Search results for , issue "Vol. 6 No. 2: August 2021" : 10 Documents clear

Virtual Machine Customization Using Resource Using Prediction for Efficient Utilization of Resources in IaaS Public Clouds Derdus Kenga; Vincent Omwenga; Patrick Ogao
Journal of Information Technology and Computer Science Vol. 6 No. 2: August 2021
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

The main cause of energy wastage in cloud data centres is the low level of server utilization. Low server utilization is a consequence of allocating more resources than required for running applications. For instance, in Infrastructure as a Service (IaaS) public clouds, cloud service providers (CSPs) deliver computing resources in the form of virtual machines (VMs) templates, which the cloud users have to choose from. More often, inexperienced cloud users tend to choose bigger VMs than their application requirements. To address the problem of inefficient resources utilization, the existing approaches focus on VM allocation and migration, which only leads to physical machine (PM) level optimization. Other approaches use horizontal auto-scaling, which is not a visible solution in the case of IaaS public cloud. In this paper, we propose an approach of customizing user VMâ€™s size to match the resources requirements of their application workloads based on an analysis of real backend traces collected from a VM in a production data centre. In this approach, a VM is given fixed size resources that match applications workload demands and any demand that exceeds the fixed resource allocation is predicted and handled through vertical VM auto-scaling. In this approach, energy consumption by PMs is reduced through efficient resource utilization. Experimental results obtained from a simulation on CloudSim Plus using GWA-T-13 Materna real backend traces shows that data center energy consumption can be reduced via efficient resource utilization

Study and Analysis of Network Topology Performance Using Wireless Distribution System Technology Mohammad Faried Rahmat; Erfan Rohadi; Indrazno Siradjuddin; Farif Chrissandy
Journal of Information Technology and Computer Science Vol. 6 No. 2: August 2021
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

The use of wireless networks has become a trend at this time. However, this can cause several problems in the use of this technology. One of the problems arising from this technology is the limited signal coverage in a certain place. To solve these problems, WDS technology is an alternative solution that can be done. WDS technology will be applied to each room. In this study, QOS analysis will be used to evaluate throughput performance and response time. The test scenario is performed with 1000 users (simulated) for seven days, four sampling times considering working hours and outside working hours. The analysis results show that with WDS technology, the resulting performance tends to be more stable with a throughput value of 500 KBps and a max response time of 5.5 ms.

Utilizing of the Trello API Within the Development of a Monitoring Information System Recording of Project Activities Using a Website-Based Kanban System (Case Study : Electrical Project of PT. XYZ) Rayhan Alya Chaerul; Widhy Hayuhardhika Nugraha Putra; Buce Trias Hanggara
Journal of Information Technology and Computer Science Vol. 6 No. 2: August 2021
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

One of the units of the company which is engaged in electricity handles many electrical large projects. The current condition of recording project activities that is still done manually and is not centralized has become difficulties in searching for data when needed. Job targets that also cannot be monitored create difficulties in management. Therefore, an effective and efficient monitoring information system for recording project activities is required so as to facilitate the management of monitoring data projects and data retrieval. The system development process using the prototyping method is implemented on a website basis by utilizing the Kanban system in managing work items. The Trello API is used to retrieve project data along with the use of the Kanban system in Trello to maintain data security which can only be managed by the project manager. System development is carried out through the stages of problem identification, literature study, needs analysis, design with Unified Modeling Language, and implementation using Laravel as a framework. Functional testing of the system with Blackbox testing gets 100% indicating the system is in accordance with the requirements specifications. Usability testing using the System Usability Scale gets a value of 84 in the acceptable system category. Responsive testing is conducted with the results of the interface meets various screen sizes and orientations. The compatibility testing implementation shows the system works well with various browsers.

Evaluation of TF-IDF Algorithm Weighting Scheme in The Qur'an Translation Clustering with K-Means Algorithm M Didik R Wahyudi
Journal of Information Technology and Computer Science Vol. 6 No. 2: August 2021
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

The Al-Quran translation index issued by the Ministry of Religion can be used in text mining to search for similar patterns of Al-Quran translation. This study performs sentence grouping using the K-Means Clustering algorithm and three weighting scheme models of the TF-IDF algorithm to get the best performance of the Tf-IDF algorithm. From the three models of the TF-IDF algorithm weighting scheme, the highest percentage results were obtained in the traditional TF-IDF weighting scheme, namely 62.16% with an average percentage of 36.12% and a standard deviation of 12.77%. The smallest results are shown in the TF-IDF 1 normalization weighting scheme, namely 48.65% with an average percentage of 25.65% and a standard deviation of 10.16%. The smallest standard deviation results in a normalized 2 TF-IDF weighting of 8.27% with an average percentage of 28.15% and the largest percentage weighting of 48.65% which is the same as the normalized TF-IDF 1 weighting.

Website Visitors Forecasting using Recurrent Neural Network Method Putu Bagus Arya; Wayan Firdaus Mahmudy; Achmad Basuki
Journal of Information Technology and Computer Science Vol. 6 No. 2: August 2021
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Abstract. The number of visitors and content accessed by users on a site shows the performance of the site. Therefore, forecasting needs to be done to find out how many users a website will come. This study applies the Long Short Term Memory method which is a development of the Recurrent Neural Network method. Long Short Term Memory has the advantage that there is an architecture of remembering and forgetting the output to be processed back into the input. In addition, the ability of another Long Short Term Memory is to be able to maintain errors that occur when doing backpropagation so that it does not allow errors to increase. The comparison method used in this study is Backpropagation. Neural Network method that is often used in various fields. The testing using new visitor data and first time visitors from 2018 to 2019 with vulnerable time per month. The computational experiment prove that the Long Short Term Memory produces better result in term of the mean square error (MSE) comparable to those achieved by Backpropagation Neural Network method.

A Rapid Review of Image Captioning Adriyendi Adriyendi
Journal of Information Technology and Computer Science Vol. 6 No. 2: August 2021
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Image captioning is an automatic process for generating text based on the content observed in an image. We do review, create framework, and build application model. We review image captioning into 4 categories based on input model, process model, output model, and lingual image caption. Input model is based on criteria caption, method, and dataset. Process model is based on type of learning, encoder-decoder, image extractor, and metric evaluation. Output model based on architecture, features extraction, feature aping, model, and number of caption. Lingual image caption based on language model with 2 groups: bilingual image caption and cross-language image caption. We also design framework with 3 framework model. Furthermore, we also build application with 3 application models. We also provide research opinions on trends and future research that can be developed with image caption generation. Image captioning can be further developed on computer vision versusÂ human vision.

Interactive Design of 3D -Tactile Map for Visual Impairment people Muhammad Arif; Fatwa Ramdani; Agung Setia Budi
Journal of Information Technology and Computer Science Vol. 6 No. 2: August 2021
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

on maps. In general, the map can only be used by users who are can see visually and blind people have difficulty reading the map because there is no map for the visual impairment in 3D. This map has the advantage of being printable so that it is easy to understand and use for blind users. Amid the development of the map, the authors developed a 3D interactive map design that can accommodate the needs of blind users. This development is generated from DSM data through aerial surveys using drones altered to produce a smoother surface so that it can be reconstructed into a 3D design and analysis of the level of texture density and the level of conformity to the real or original shape and reconstruction using aims to improve and model. Shape to fit the 3-dimensional printing process. The voice module is installed using the RFID Tag identification that is embedded in the 3D map and the RFID Reader in the user's hand, with voice data processing. This innovation that has been developed has the advantage of having a 3-dimensional shape that can be felt, texture, shape, and height equipped with braille-shaped markings that are specially made using Riglet for easy reading and sound as a support to improve the blind's people spatial understanding and spatial literacy.

A Literature Review of Knowledge Tracing for Student Modeling : Research Trends, Models, Datasets, and Challenges Ebedia Hilda Am; Indriana Hidayah; Sri Suning Kusumawardani
Journal of Information Technology and Computer Science Vol. 6 No. 2: August 2021
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Modeling students' knowledge is a fundamental part of online learning platforms. Knowledge tracing is an application of student modeling which renowned for its ability to trace students' knowledge. Knowledge tracing ability can be used in online learning platforms for predicting learning performance and providing adaptive learning. Due to the wide uses of knowledge tracing in student modeling, this study aims to understand the state-of-the-art and future research of knowledge tracing. This study focused on reviewing 24 studies published between 2017 to the third quarter of 2021 in four digital databases. The selected studies have been filtered using inclusion and exclusion criteria. Several previous studies have shown that there are two approaches used in knowledge tracing, including probabilistic and deep learning. Bayesian Knowledge Tracing model is the most widely used in the probabilistic approach, while the Deep Knowledge Tracing model is the most popular model in the deep learning approach. Meanwhile, ASSISTments 2009–2010 is the most frequently tested dataset for probabilistic and deep learning approaches. In the future, additional studies are required to explore several models which have been developed previously. Therefore this study provides direction for future research of each existing approach.

Sentiment Visualization of Covid-19 Vaccine Based On Naive Bayes Analysis Nabilah Putri Aprilia; Dian Pratiwi; Anung Barlianto Ariwibowo
Journal of Information Technology and Computer Science Vol. 6 No. 2: August 2021
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

COVID-19 is one of the topics that is being discussed intensively. The virus which was declared a global pandemic on March 11 by WHO caused around 2.09 million Indonesians to be infected with the COVID-19 virus. To overcome this, the government carried out a vaccination program. The data taken for this study is public opinion about the COVID-19 vaccine written on Twitter. The number of opinions written on Twitter requires classification according to the sentiments they have, whether they tend to be negative opinions or positive opinions using lexicon-based The idea of this research is to classify the covid vaccination dataset using the naive Bayes classifier method and visualization using word cloud. Crawling to obtain the dataset from Twitter, text pre-processing and labelling to determine the positive and negative classes, TFIDF feature extraction, data splitting with a percentage of 80% for train data and 20% for data testing, and finally classification using nave Bayes are the stages in this research The system's sentiment analysis research yielded significant results, the accuracy value is 73.1%, the precision value is 73% and the recall value is 83%.

Development of an Intelligent Smart Home Automation System Raphael Akinyede
Journal of Information Technology and Computer Science Vol. 6 No. 2: August 2021
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Generally speaking, security has been a major concern in every nook and cranny of our nation -Nigeria. Recently, cases of vandalisation, stolen vehicles, and related issues have been on the increase. The security personnel has done lots of work to curb this menace but most of their actions have not yielded the expected results. Therefore, there is need to use technology to create a safer society. Such technology will use GSM and camera for detections. The technology is not going to replace the security personnel and usage of appliances such as gates, and doors locks, electric wires, etc, but it will be used as an alternative method for prevention/detection. Based on this background, a digital light-dependent resistor (LDR) sensor coupled with a microcontroller, relay, camera, and GSM technology was used to develop a smart home security system for automatic detection. The LDR sensor converts the light intensity to a digital format for the microcontroller to control the security lights automatically by using the relay as a switch. The passive infrared motion sensor perceives human movement and converts it to digital format for the microcontroller to trigger the GSM module and alert the user for live streaming of what is happening on the mobile app by establishing a connection between the camera and android smart device. The capturing and videoing are done on the mobile android device.

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