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INDONESIA
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING
Published by Universitas Medan Area
ISSN : 25496247     EISSN : 25496255     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Engineering
JURNAL TEKNIK INFORMATIKA, JITE (Journal of Informatics and Telecommunication Engineering) is a journal that contains articles / publications and research results of scientific work related to the field of science of Informatics Engineering such as Software Engineering, Database, Data Mining, Network, Telecommunication and Artificial Intelligence which published and managed by the Faculty of Informatics Engineering at the University of Medan Area .
Arjuna Subject : -
Articles 412 Documents
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Propagation Model for Mobile Communication 2100 Mhz in Tampan Pekanbaru City Ahmad Fandy; Mulyono; Fitri Amillia; Sutoyo Sutoyo
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 7 No. 1 (2023): Issues July 2023
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v7i1.9988

Abstract

Dalam merancang sebuah jaringan komunikasi hal yang harus diperhatikan adalah model propagasi yang digunakan harus sesuai dengan daerah yang akan dilakukan perancangan jaringan komunikasi. Sinyal mempunyai mekanisme tersendiri dari pemancar dan diterima oleh user, maka dibutuhkan model propagasi yang sesuai dengan karakteristik daerah. Seperti daerah Kota Pekanbaru tepatnya di Kecamatan Tampan. Penelitian ini bertujuan untuk menentukan model propagasi komunikasi bergerak 2100 MHz yang sesuai dengan karakteristik Kecamatan Tampan. Metode yang digunakan adalah drive test dibantu dengan aplikasi G-Net Track Pro. Berdasarkan perhitungan dan simulasi yang dilakukan di dapatkan persamaan model loss propagasi yaitu linear : Y = 1.1*x + 67, persamaan kuadratik : Y = -0.28*x2 + 1.9*x + 67, persamaan kubik : Y = -0.8*x3 + 3.3*x2 – 2*x+67.
Optimizing Blockchain Network Creation: Automation with Ansible on Private Blockchain Hyperledger Fabric Using Simplified RAFT Consensus Method Muhammad Rizal Supriadi Rizal; Roni Andarsyah; M. Yusril Helmi Setyawan
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 7 No. 1 (2023): Issues July 2023
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v7i1.10035

Abstract

In the rapidly evolving world of blockchain technology, efficient and reliable blockchain network creation poses a significant challenge. Manual processes in blockchain network setup often consume time, are prone to errors, and difficult to maintain. This research aims to optimize the creation of blockchain networks by leveraging Ansible automation tools on private blockchains using Hyperledger Fabric and implementing a simplified RAFT method. The approach involves configuring blockchain infrastructure with Ansible and integrating the simplified RAFT method into the private blockchain network. The test results demonstrate that the proposed approach significantly reduces the time required for blockchain network creation. In testing with a 92 Mbps internet connection, the time needed to create a blockchain network with 1 orderer and 1 peer with 44 connected channels, ready for transactions, was successfully reduced from 102.6 minutes to only 51.4 minutes. Moreover, the Ansible automation approach reduces the risk of errors and simplifies network maintenance. In conclusion, this research confirms the effectiveness of the proposed approach in optimizing the blockchain network creation process, reducing the required time, and enhancing efficiency and ease of maintenance. The proposed solution provides a valuable contribution to the development of efficient private blockchain infrastructure while minimizing errors and increasing flexibility.
Validation of the Haar Cascade Classification Method in Face Detection Muhammad Bahit; Nadia Putri Utami; Heru Kartika Candra; Yonal Supit; As’ary Ramadhan
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 7 No. 1 (2023): Issues July 2023
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v7i1.10040

Abstract

As technology develops, faces are used as a tool for human interaction with computers for security systems. Face detection technology can also provide convenience to users in various fields, especially security systems. However, there are problems regarding accuracy, complexity in the face recognition process so that many methods have been developed to increase the accuracy and complexity of the face detection process. This study aims to validate the haar cascade classification method in detecting faces from various shooting angles, with a distance of one meter from the camera and the respondent is free to make movements as well as various facial expressions and various lighting conditions that are different for each respondent. The results of this study found that the haar cascade classification method showed that the higher the epoch value, the lower the mean square error (MSE). This study also found that the haar cascade classification method has good accuracy for detecting faces from various angles, different lighting and different facial expressions with a maximum distance of one meter from the camera. This study provides recommendations for making face recognition applications using the haar cascade classification method because it can be used well for lighting effects, facial expressions and a maximum shooting distance of one meter.
E-Culture Design in Batubara District by Implementing Web-Based Crowdsourcing Methods Fauzia Mahyarani; Samsudin
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 7 No. 1 (2023): Issues July 2023
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v7i1.10067

Abstract

The development of technology today is very rapid and makes it easier for humans to access various information that they want to know by using technology in the form of the internet. E-Cultural is a cultural digitization system that utilizes internet technology to increase efficiency in the field of culture, especially in terms of documentation, dissemination of information as well as knowledge of elements of culture. At this time, web-based information regarding tourism and culture of Batubara Regency is not yet available, the public can only introduce it through social media such as Facebook, Instagram and other media. Lack of legal media at the Batu Bara District Youth, Sports and Culture Service and Tourism to promote tourism and culture in the Batubara District. This prompted the author to create a legal system so that the Batubara Regency Cultural Sports Youth Service can promote tourism and culture by involving the global community. Therefore, this research uses the crowdsourcing method, namely that there is unlimited involvement and regardless of background for everyone who wants to make a contribution, whether paid or free. In the system that I will create, the global community can play a role in updating data or information on the website as well as using the waterfall development method, namely analysis, design, implementation and testing. The results of the development of E-Culture in Batubara Regency using the crowdsourcing method have had a good impact, by making it easier for the local community to promote culture and tourism in their area
The Effect of Augmented Reality on Glasses Purchasing Decisions Using the Structural Equation Model Method Ilham Prabowo; M. Fakhriza; Muhammad Dedi Irawan
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 7 No. 1 (2023): Issues July 2023
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v7i1.10084

Abstract

Development of information technology in the business sector can be seen with many business people marketing the sale of their services or products by utilizing social media platforms and also e-commerce because it can make it easier for buyers to get the desired information anywhere and anytime. The optimization of social media and e-commerce has been implemented by Fifan Glasses Store to sell their products. Generally, buyers will try on the frames one by one until they decide to buy them. But, online buyers cannot try on the frames and can only see the frames based on the pictures in the catalog provided by Fifan Glasses Store. For this reason, an Android-based Augmented Reality eyeglass frame application will be built at Fifan Glasses Store. The purpose of building this application is to facilitate online buyers in trying on the frames that have been provided and minimize the occurrence of damage to eyeglass frames by prospective buyers. This research uses the Rapid Application Development (RAD) method in building the application and this research will also analyze the effect of the application of Augmented Reality glasses frames using the Structural Equation Model (SEM) method. The final results of the analysis of the effect of Augmented Reality on eyeglass frames by testing the outermodel, inner model, and hypothesis show that Augmented Reality has a positive effect on purchasing decisions for glasses at Fifan Glasses Store.
Implementation of the X-Means Algorithm on Unemployment Data in West Java N.PRIYA DHARSHINNI -; Gurbinder Singh; Riama D.Lumban Tobing; Aldwin Simamora; Johannes April Talihan Naibaho; BA Wijaya
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 7 No. 1 (2023): Issues July 2023
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v7i1.10109

Abstract

The unemployment rate is a serious issue in many countries, including Indonesia, with impacts that encompass psychological pressure, declining living standards, reduced national income, and diminished workforce quality. High unemployment rates can lead to poverty, resource wastage, and have implications for a country's economic growth. Additionally, inadequate workforce quality is a determining factor in unemployment rates. The objective of this study is to classify unemployment data, specifically in West Java Province, using the X-Means algorithm based on educational levels and districts/cities, in order to examine the fluctuations in unemployment. The research findings indicate fluctuations in the number of unemployed individuals in West Java Province from 2011 to 2022. The low unemployment rate in West Java Province experienced a 66.7% increase in 2014-2015, remained stable in 2017-2019, while the high unemployment rate decreased by 80% in 2014-2015, remained stable in 2017-2019, but increased by 20% in 2020-2022. Furthermore, Bogor Regency consistently recorded the highest unemployment rate in each cluster, with a total of 135,000 unemployed individuals in Bogor Regency in 2017-2019, while the education level with the highest unemployment rate was junior high school graduates
Machine Learning Model for Language Classification: Bag-of-words and Multilayer Perceptron Devi Hawana Lubis; Sawaluddin Sawaluddin; Ade Candra
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 7 No. 1 (2023): Issues July 2023
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v7i1.10114

Abstract

The availability of data today has become a great asset for research that is used for various purposes such as for machine learning. One of the basic machine learning methods for natural language processing is bag-of-words. The problem in this study is the difficulty in classifying texts because texts still have unstructured characteristics, so this study will apply a model to classify the language of texts. Texts will be placed in four categories, English, Indonesian, German and French. Research was conducted using Bag-of-words and Multilayer Perceptron to solve this supervised machine learning problem. The use of Bag-of-words to perform text representation for simple patterns, easy processing and good performance. On the other hand, a multilayer perceptron has the ability to study complex data patterns in the form of images, text or videos. This study will collect data using text mining techniques, namely crawling Twitter social media as many as 4000 data records. This study produces a model with an accuracy of 98 percent with a loss of 0.14 percent which shows good model performance in classifying languages based on text data.
Attribute Selection in Naive Bayes Algorithm Using Genetic Algorithms and Bagging for Prediction of Liver Disease Utami, Dwi Yuni; Nurlelah, Elah; Hikmah, Noer
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 4 No. 1 (2020): ---> EDISI JULI
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v4i1.3793

Abstract

Liver disease is an inflammatory disease of the liver and can cause the liver to be unable to function as usual and even cause death. According to WHO (World Health Organization) data, almost 1.2 million people per year, especially in Southeast Asia and Africa, have died from liver disease. The problem that usually occurs is the difficulty of recognizing liver disease early on, even when the disease has spread. This study aims to compare and evaluate Naive Bayes algorithm as a selected algorithm and Naive Bayes algorithm based on Genetic Algorithm (GA) and Bagging to find out which algorithm has a higher accuracy in predicting liver disease by processing a dataset taken from the UCI Machine Learning Repository database (GA). University of California Invene). From the results of testing by evaluating both the confusion matrix and the ROC curve, it was proven that the testing carried out by the Naive Bayes Optimization algorithm using Algortima Genetics and Bagging has a higher accuracy value than only using the Naive Bayes algorithm. The accuracy value for the Naive Bayes algorithm model is 66.66% and the accuracy value for the Naive Bayes model with attribute selection using Genetic Algorithms and Bagging is 72.02%. Based on this value, the difference in accuracy is 5.36%.Keywords: Liver Disease, Naïve Bayes, Genetic Agorithms, Bagging.
Analyzing Node Density Impact on End-to-End Delay and Throughput in Mobile Ad hoc Network Video Conferencing Services Kango, Riklan; Jamal, Nurwahidah; Ihsan
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 7 No. 2 (2024): Vol. 7 No. 2 (2024): Issues January 2024
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v7i2.9998

Abstract

Video conferencing services have gained significant popularity in recent years, enabling real-time communication and collaboration among individuals and groups. However, the performance of video conferencing systems over MANETs poses challenges of topology fluctuations and node density. This research paper aims to present an analysis of end-to-end delay and throughput in video conferencing over MANETs. The main objective is to identify the impact of node density in MANETs on video conferencing user experience. To conduct the study, an experimental setup of Zoom cloud meeting service was designed, consisting of a simulated MANET environment and a video conferencing application. End-to-end delay and throughput were measured via Wireshark software based on interconnected node scenarios and different configurations at densities of 2 and 4 nodes. The collected data was analyzed using appropriate statistical techniques to identify trends, patterns. The end-to-end delay analysis results revealed the impact of fluctuating network density conditions, on the overall delay experienced during the video conferencing session increased by 27%. While throughput analysis revealed a 65% decrease in data transfer capacity caused by higher packet loss factor in MANET. The integrated analysis explores the relationship between end-to-end delay and throughput, providing insight into optimization strategies. These findings can guide the design and implementation of more efficient and reliable video conferencing systems in mobile ad-hoc environments, In the face of fluctuations in node density, these findings can encourage the development of QoS mechanisms specifically designed for MANETs. These mechanisms can prioritize video packets and allocate network resources effectively, ensuring better user experience and overcoming resource constraints
Combination of Image Improvement on Segmentation Using a Convolutional Neural Network in Efforts to Detect Liver Disease Umilizah, Nia; Octavia, Pipin; Kesuma, Lucky Indra; Rayani, Ira; Suedarmin, Muhammad
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 7 No. 2 (2024): Vol. 7 No. 2 (2024): Issues January 2024
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v7i2.10221

Abstract

Liver disease is a disease caused by various factors such as the spread of viruses. Liver damage causes the ability to break down red blood cells to be disrupted. Detection of liver disease can be done using the segmentation. Segmentation is useful for separating an area of the liver in an image from other areas. Segmentation carried out manually requires experts and a long time, so automatic segmentation is needed. CNN can be used to perform automatic segmentation. One of the CNN architectures is the U-Net architecture. Segmentation requires quality images to improve recognition of image patterns, so image improvement is needed in the form of contrast enhancement. Contrast improvement was carried out by taking Green Channel images. Contrast enhancement was carried out using the Contrast Stretching and CLAHE methods. The image improvement results show MSE and SSIM values 66.1844 and 0.7088. Evaluation of the image improvements obtained provides significant changes. The improved image is used at the segmentation stage. Segmentation is carried out using the U-Net architecture. The segmentation results obtained performance evaluation values in the form of accuracy 99.6%, sensitivity 98.9%, and specificity 99.7%. This shows that the proposed method can detect liver disease in liver images well

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