2021 9th International Conference on Information and Communication Technology (ICoICT)最新文献_第6页

Simulation Of Jellyfish Topology Link Failure Handling Using Floyd Warshall and Johnson Algorithm in Software Defined Network Architecture 软件定义网络体系结构中基于Floyd Warshall和Johnson算法的水母拓扑链路故障处理仿真

2021 9th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2021-08-03 DOI: 10.1109/ICoICT52021.2021.9527523

M. A. Nugroho, A. Rakhmatsyah

引用次数: 0

Analysis of Records Management Maturity Level for Data Collection of Network Assets in Indonesian Telecommunication Industry 印尼电信业网络资产数据采集记录管理成熟度分析

2021 9th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2021-08-03 DOI: 10.1109/ICoICT52021.2021.9527525

Rizky A C Eka Putri, A. Hidayanto

{"title":"Analysis of Records Management Maturity Level for Data Collection of Network Assets in Indonesian Telecommunication Industry","authors":"Rizky A C Eka Putri, A. Hidayanto","doi":"10.1109/ICoICT52021.2021.9527525","DOIUrl":"https://doi.org/10.1109/ICoICT52021.2021.9527525","url":null,"abstract":"PT.XYZ is a state-owned company in telecommunications and information technology. In developing its business, PT.XYZ has served more than 2.200 corporate customers and 22.760 retail customers by having a lot of network assets. The large number of network assets owned means that the company must be able to carry out good data collection to find out information on the distribution and capacity of assets that are still available. The most common problems encountered at PT.XYZ is about data records management of network assets. PT.XYZ already has a system for data collection of network assets, but it’s still not running well. This occurs because there are no procedures and clarity of accountability related to records management, so there were many data collection processes that were still manually. Based on the problem, the purpose of this study is to conduct an assessment of records management level at PT.XYZ and provide recommendations to increase the level. The assessment process and recommendations will be based on ARMA GARP Framework. This was chosen because it’s a comprehensive approach that widely used in managing the information assets of companies or organizations. The results of maturity level assessment of this study are at level 2 for accountability, transparency, compliance, availability, retention, and also level 1 for integrity, protection, and disposition. These results also indicate that the company needs to improve several processes in the GAPR Principles of Integrity, Protection, and Disposition because there is a large gap between the current level and the expected target level.","PeriodicalId":191671,"journal":{"name":"2021 9th International Conference on Information and Communication Technology (ICoICT)","volume":"162 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133950737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Raw Paper Material Stock Forecasting with Long Short-Term Memory 基于长短期记忆的原纸原料库存预测

2021 9th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2021-08-03 DOI: 10.1109/ICoICT52021.2021.9527528

Febry Kurniawan, D. Herwindiati, Manatap Dolok Lauro

{"title":"Raw Paper Material Stock Forecasting with Long Short-Term Memory","authors":"Febry Kurniawan, D. Herwindiati, Manatap Dolok Lauro","doi":"10.1109/ICoICT52021.2021.9527528","DOIUrl":"https://doi.org/10.1109/ICoICT52021.2021.9527528","url":null,"abstract":"The manufacturing business is one of the businesses in Indonesia that continues to show its development from year to year. Like a manufacturing business in general, one of the important efforts made in the printing business is the supply of raw paper materials to produce finished goods. The purpose of this research is making a forecasting of the raw paper material for printing company on 7 different types of 269 historical data with weekly intervals from January 2015 to February 2020 before the Covid19 pandemic season. Forecasting is done using the Long Short Term Memory method with Python language. The model architecture for training and testing is carried out using vanilla LSTM with single input, hidden and output layer with the configuration of 64 neurons in the hidden layer, 150 epoch, 12 batch size and Adam Optimizer (lr = 0.0001) which was repeated 10 times for best result. The test results show the best window size length in the model for each paper raw material differently from 4 to 16. All models was successfully forecasting the test data with an average MAPE of the overall forecast of 21.48%.","PeriodicalId":191671,"journal":{"name":"2021 9th International Conference on Information and Communication Technology (ICoICT)","volume":"147 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133522710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Enhanced AlexNet with Super-Resolution for Low-Resolution Face Recognition 增强AlexNet与超分辨率低分辨率人脸识别

2021 9th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2021-08-03 DOI: 10.1109/ICoICT52021.2021.9527433

Jin Chyuan Tan, K. Lim, C. Lee

{"title":"Enhanced AlexNet with Super-Resolution for Low-Resolution Face Recognition","authors":"Jin Chyuan Tan, K. Lim, C. Lee","doi":"10.1109/ICoICT52021.2021.9527433","DOIUrl":"https://doi.org/10.1109/ICoICT52021.2021.9527433","url":null,"abstract":"With the advancement in deep learning, high-resolution face recognition has achieved outstanding performance that makes it widely adopted in many real-world applications. Face recognition plays a vital role in visual surveillance systems. However, the images captured by the security cameras are at low resolution causing the performance of the low-resolution face recognition relatively inferior. In view of this, we propose an enhanced AlexNet with Super-Resolution and Data Augmentation (SRDA-AlexNet) for low-resolution face recognition. Firstly, image super-resolution improves the quality of the low-resolution images to high-resolution images. Subsequently, data augmentation is applied to generate variations of the images for larger data size. An enhanced AlexNet with batch normalization and dropout regularization is then used for feature extraction. The batch normalization aims to reduce the internal covariate shift by normalizing the input distributions of the mini-batches. Apart from that, the dropout regularization improves the generalization capability and alleviates the overfitting of the model. The extracted features are then classified using k-Nearest Neighbors method for low-resolution face recognition. Empirical results demonstrate that the proposed SRDA-AlexNet outshines the methods in comparison.","PeriodicalId":191671,"journal":{"name":"2021 9th International Conference on Information and Communication Technology (ICoICT)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116112977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Distributed Phylogenetic Tree Processing on Biology Sequences Using Mapreduce 基于Mapreduce的生物序列分布式系统发育树处理

2021 9th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2021-08-03 DOI: 10.1109/ICoICT52021.2021.9527475

Renaning Karutami Susilo, Setyorini, S. Karimah

引用次数: 0

Contributing Clinical Attributes to COVID-19 Mortality in Jakarta: Machine Learning Study 为雅加达COVID-19死亡率贡献临床属性:机器学习研究

2021 9th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2021-08-03 DOI: 10.1109/ICoICT52021.2021.9527428

M. E. Aminanto, B. I. Nasution, Andi Sulasikin, Y. Nugraha, J. Kanggrawan, A. Suherman

{"title":"Contributing Clinical Attributes to COVID-19 Mortality in Jakarta: Machine Learning Study","authors":"M. E. Aminanto, B. I. Nasution, Andi Sulasikin, Y. Nugraha, J. Kanggrawan, A. Suherman","doi":"10.1109/ICoICT52021.2021.9527428","DOIUrl":"https://doi.org/10.1109/ICoICT52021.2021.9527428","url":null,"abstract":"Since December 2019, we have lived in a pandemic era of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Medical records of COVID-19 patients have been reported and analyzed worldwide. The Health Agency of Jakarta, Indonesia, collected clinical symptoms, demographics, travel history, and mortality information from March 2020 up to now. Despite massive research on COVID-19 patients’ data, the significant clinical symptoms that lead to COVID-19 mortality in Jakarta have not been well described to the best of the authors’ knowledge. We extracted the COVID-19 records in Jakarta and compared them between patients who were discharged and deceased. This paper examines each clinical symptom’s importance to mortality using machine learning techniques, namely weighted Artificial Neural Network, Decision Tree, and Random Forest. We observed that Pneumonia, Shortness of Breath, Malaise, Hypertension, Fever, and Runny Nose are the top six significant clinical symptoms that lead to deaths in Jakarta. We suggest medical experts become more cautious with these symptoms. Also, in medical facilities, these symptoms can be used as prescreening before entering the facilities.","PeriodicalId":191671,"journal":{"name":"2021 9th International Conference on Information and Communication Technology (ICoICT)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122103404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Flexible Multi-Layer Condura Fabric Ultra Wide-Band Antenna For Telemedicine Application 用于远程医疗的柔性多层孔硬织物超宽带天线

2021 9th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2021-08-03 DOI: 10.1109/ICoICT52021.2021.9527521

Y. Rahayu, Tasya Kirana

引用次数: 1

Multi-Target Regression Using Convolutional Neural Network-Random Forests (CNN-RF) For Early Earthquake Warning System 基于卷积神经网络随机森林(CNN-RF)的多目标回归地震预警系统

2021 9th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2021-08-03 DOI: 10.1109/ICoICT52021.2021.9527461

Benaldy Yuga Adhaityar, D. Sahara, C. Pratama, A. Wibowo, L. Heliani

{"title":"Multi-Target Regression Using Convolutional Neural Network-Random Forests (CNN-RF) For Early Earthquake Warning System","authors":"Benaldy Yuga Adhaityar, D. Sahara, C. Pratama, A. Wibowo, L. Heliani","doi":"10.1109/ICoICT52021.2021.9527461","DOIUrl":"https://doi.org/10.1109/ICoICT52021.2021.9527461","url":null,"abstract":"Indonesia occupies a very active tectonic zone because the world's three large plates and nine other smaller plates meet each other in Indonesian territory and form a complex plate meeting path. East Java Province is part of the Sundanese arc, which has a relatively high level of seismicity and has a complex geological system resulting from the Indo-Australian plate. Therefore, a system that can provide earthquake early warning (EEW) is needed to reduce casualties. In this paper, we determine the epicenter and magnitude of the earthquake using the Multi-Target Regression Convolutional Neural Network-Random Forest (CNN-RF). This model uses Multi-Target Regression Convolutional Neural Network (CNN) as feature extraction and Multi-Target Regression Random Forest (RF) for multi-target regression. Earthquakes in East Java in 2009-2017 are used to train and validate the proposed model. Based on the experiment, the lowest error obtained from the Multi-Target Regression CNN-RF model is 16.3 km for longitude, 36.4 km for latitude, and 0.3095 for magnitude.","PeriodicalId":191671,"journal":{"name":"2021 9th International Conference on Information and Communication Technology (ICoICT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122015036","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Implementation of Hidden Markov Model (HMM) to Predict Financial Market Regime 隐马尔可夫模型(HMM)在金融市场机制预测中的应用

2021 9th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2021-08-03 DOI: 10.1109/ICoICT52021.2021.9527459

Irma Palupi, Bambang Ari Wahyudi, Agung Perdana Putra

{"title":"Implementation of Hidden Markov Model (HMM) to Predict Financial Market Regime","authors":"Irma Palupi, Bambang Ari Wahyudi, Agung Perdana Putra","doi":"10.1109/ICoICT52021.2021.9527459","DOIUrl":"https://doi.org/10.1109/ICoICT52021.2021.9527459","url":null,"abstract":"This work performs how to implement the concept of Hidden Markov Model (HMM) to find financial market trend for given only the observed state obtained from the stock price. The considered market trend is set as a hidden state, that in the financial technical analysis known as Bearish, Bullish, and Sideway, which are important for decision making of stock trading in order to recognize the good moment to sell, to buy or to just hold the shares. In order to obtain the most likely sequence of hidden states through HMM, which is computationally can be a dynamic programming problem, we explain how the Viterbi algorithm work for the case in this study. To get the stock price prediction as observation states, the ARIMA model is used based on experimental trial of fitting model, then use the result as a predicted observed states that be the input to predict the market trend using HMM for the short period of future time. Several interesting results of hidden market trend and its study are also provided, including the accuracy, precision, recall and the consistency of the model to the given data set.","PeriodicalId":191671,"journal":{"name":"2021 9th International Conference on Information and Communication Technology (ICoICT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124978776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Relaxation Oscillator Using Closed-loop Dual Comparator for Biomedical Applications 使用闭环双比较器的弛豫振荡器用于生物医学应用

2021 9th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2021-08-03 DOI: 10.1109/ICoICT52021.2021.9527517

Theodora Valerie, D. Garinto, Prapto Nugroho, A. Syahriar, Eka Samsul Ma'arif

{"title":"Relaxation Oscillator Using Closed-loop Dual Comparator for Biomedical Applications","authors":"Theodora Valerie, D. Garinto, Prapto Nugroho, A. Syahriar, Eka Samsul Ma'arif","doi":"10.1109/ICoICT52021.2021.9527517","DOIUrl":"https://doi.org/10.1109/ICoICT52021.2021.9527517","url":null,"abstract":"People's rising concerns about health have fueled research into high-performance biomedical devices and circuits, such as sensors and implantable systems on a chip. It is important for these biomedical devices to operate at the same low frequency to treat certain organs and diseases. Thus, the clock generator needs to be able to provide low frequency clock pulses with minimal size and high reliability. These constraints elevate power consumption and production cost within the circuit design to key parameters. One promising candidate is relaxation oscillator which has good on-chip compatibility, and superior frequency stability. This paper proposes a novel relaxation oscillator using closed-loop dual comparator. A frequency in the band of 50Hz to 2.5kHz can be generated by replacing the value of resistors and capacitor in all possible combinations. The simulation and experimental result confirm that closed-loop dual comparator-based relaxation oscillator provides low frequency with lower cost and more simplicity due to fewer components.","PeriodicalId":191671,"journal":{"name":"2021 9th International Conference on Information and Communication Technology (ICoICT)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127423562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0