2019 4th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE)最新文献

A Novel Approach to Resource Starvation Attacks on Message Queuing Telemetry Transport Brokers 消息队列遥测传输代理资源饥渴攻击的一种新方法

2019 4th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE) Pub Date : 2019-11-01 DOI: 10.1109/ICITISEE48480.2019.9003770

R. Paz, Aiden Sehovic, David M. Cook, L. Armstrong

引用次数: 1

Social Network Users Switching Platforms Behaviour: A Proposal for Research Explorations using a Mixed Method Approach 社交网络用户切换平台行为:使用混合方法的研究探索建议

2019 4th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE) Pub Date : 2019-11-01 DOI: 10.1109/ICITISEE48480.2019.9003951

Timothy McBush Hiele, A. E. Widjaja, C. Haryani

引用次数: 0

ICITISEE 2019 Organizing Committee icitissee 2019组委会

2019 4th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE) Pub Date : 2019-11-01 DOI: 10.1109/icitisee48480.2019.9003726

引用次数: 0

Performance Comparison of Blackman, Bartlett, Hanning, and Kaiser Window for Radar Digital Signal Processing Blackman, Bartlett, Hanning和Kaiser窗口在雷达数字信号处理中的性能比较

2019 4th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE) Pub Date : 2019-11-01 DOI: 10.1109/ICITISEE48480.2019.9003791

Sulistyaningsih, P. Putranto, Taufiq qurrachman, W. Desvasari, P. Daud, Y. N. Wijayanto, D. Mahmudin, D. Kurniadi, A. N. Rahman, S. Hardiati, A. Setiawan, F. Darwis, E. J. Pristianto

引用次数: 7

Mobile Business Intelligence Assistant (m-BELA) for Higher Education Executives 移动商务智能助理(m-BELA)为高等教育主管

2019 4th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE) Pub Date : 2019-11-01 DOI: 10.1109/ICITISEE48480.2019.9003950

M. I. Afandi, E. D. Wahyuni, S. Mukaromah

{"title":"Mobile Business Intelligence Assistant (m-BELA) for Higher Education Executives","authors":"M. I. Afandi, E. D. Wahyuni, S. Mukaromah","doi":"10.1109/ICITISEE48480.2019.9003950","DOIUrl":"https://doi.org/10.1109/ICITISEE48480.2019.9003950","url":null,"abstract":"In the era of Industrial Revolution 4.0 marked by the use of information technology, the Internet in particular, university executives, as well as executives in companies, are often in such a situation which forces them to conduct business intelligence activities ranging from simply accessing data and information to analyzing them to support their decision making whenever and wherever they are. Typically, university executives are able to access data and information not only from their university databases through their web applications but also from other data sources using internet browser installed on their laptops or mobile devices. However, information access model using web application tends to be rigid where the order of menu, layout, and user-interface provided are static which forces the user to memorize or search for the right place to find the data and information needed. Certainly, this model cannot keep up with the dynamic information needs. This study produces a mobile-based application named m-BELA which functions like a human personal assistant equipped with pre-defined data, information, and knowledge who is able to interpret user’s voice command and then responds appropriately by following conversation or providing data and information relevant to the command. This new solution offers a competitive advantage since the user does not need to load a browser, open the web application, and then search for the menu and UI which provide information needed.","PeriodicalId":380472,"journal":{"name":"2019 4th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129474083","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

Integration of K-Means Clustering and Naïve Bayes Classification Algorithms for Smart AC Monitoring and Control in WSAN

2019 4th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE) Pub Date : 2019-11-01 DOI: 10.1109/ICITISEE48480.2019.9003927

Ryan Putranda Kristianto, Banu Santoso, Marti Widya Sari

{"title":"Integration of K-Means Clustering and Naïve Bayes Classification Algorithms for Smart AC Monitoring and Control in WSAN","authors":"Ryan Putranda Kristianto, Banu Santoso, Marti Widya Sari","doi":"10.1109/ICITISEE48480.2019.9003927","DOIUrl":"https://doi.org/10.1109/ICITISEE48480.2019.9003927","url":null,"abstract":"There is still a lot of excessive use of lamps, televisions, air conditioners (AC) and other electronic goods, resulting in a surge in electricity bills charged by electricity users due to neglect and waste of electrical energy. Based on these problems a system that is needed not only to monitor but also to control electrical equipment remotely so that electricity consumption can be controlled. Wireless Sensor and Actuator Network (WSAN) technology can monitor the physical condition of the environment which is widely applied in intelligent environments. WSAN is placed at certain regional points that will be observed the physical condition of the environment, each WSAN can use several sensors and actuators which will later be sent to the server via a wireless connection. In this research, we will test by making Smart AC (Air Conditioner) where at every point where there is AC will be installed WSAN. Data from several sensors generated from WSAN will be sent to the server to be observed and processed using intelligent computing and machine learning (K-Means and Naïve Bayes) so that the AC can turn on and off according to the physical conditions in the place. We evaluate our model too by using Confusion Matrix and obtain the score for accuracy 90%, precision 83%, recall 100% and error rate 10%, So our model can be called good model.","PeriodicalId":380472,"journal":{"name":"2019 4th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126896887","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: 9

Animal metamorphosis learning media using android Based augmented reality technology 基于android的增强现实技术的动物变形学习媒体

2019 4th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE) Pub Date : 2019-11-01 DOI: 10.1109/ICITISEE48480.2019.9003765

Agus Purwanto, M. P. Kurniawan, A. Rahman

引用次数: 0

Indonesian Part of Speech Tagging Using Hidden Markov Model – Ngram & Viterbi 印尼语词性标注的隐马尔可夫模型- Ngram & Viterbi

2019 4th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE) Pub Date : 2019-11-01 DOI: 10.1109/ICITISEE48480.2019.9003989

D. E. Cahyani, Mtchael Juan Vindiyanto

{"title":"Indonesian Part of Speech Tagging Using Hidden Markov Model – Ngram & Viterbi","authors":"D. E. Cahyani, Mtchael Juan Vindiyanto","doi":"10.1109/ICITISEE48480.2019.9003989","DOIUrl":"https://doi.org/10.1109/ICITISEE48480.2019.9003989","url":null,"abstract":"Part of Speech (POS) Tagging is a process of labelling word classes on sentences. One of the POS Tagging problems is some words that spelt the same but have a different POS Tag depending on the context of the sentence (ambiguity). The approach to solving this problem is using the Hidden Markov Model (HMM) Ngram Algorithm and the Viterbi Algorithm. This study discusses the development of a system for Indonesian POS Tagging using the HMM N-gram algorithm (Bigram and Trigram) and the Viterbi algorithm and compares the result between the HMM Bigram and HMM trigram. An Indonesian language corpus that has been manually labeled called Indonesian Manually Tagged Corpus is used as the knowledge for the system. Then the corpus is processed using the HMM N-gram algorithm to get the rules. Furthermore, process the data with Viterbi algorithm using the previous formed rules to determine the POS tag with the highest probability. The highest accuracy results is 77.56% using the HMM Bigram - Viterbi Algorithm. While the HMM Trigram– Viterbi algorithm has the highest accuracy of 61.67%. The result shows that the system can solve the problem of tag ambiguity with HMM Ngram – Viterbi algorithm and the accuracy of HMM Bigram is better than the HMM Trigram.","PeriodicalId":380472,"journal":{"name":"2019 4th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114066576","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: 6

The Mapping of Lighting Intensity from the Light Distribution on LED and CFL Lamps 从LED和节能灯的光分布映射照明强度

2019 4th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE) Pub Date : 2019-11-01 DOI: 10.1109/ICITISEE48480.2019.9004004

Herlina, Randa Adriano, R. Setiabudy

{"title":"The Mapping of Lighting Intensity from the Light Distribution on LED and CFL Lamps","authors":"Herlina, Randa Adriano, R. Setiabudy","doi":"10.1109/ICITISEE48480.2019.9004004","DOIUrl":"https://doi.org/10.1109/ICITISEE48480.2019.9004004","url":null,"abstract":"Electricity is an essential need for humans, specifically for the lighting function. Lighting is needed to aid humans visually perceive objects in areas that require lighting, both at night and during the day. At this day, there are two type of lamps that are extensively employed, paticularly the type of Light-Emitting Diode (LED) and Compact Fluorescent Lamp (CFL). The adoption of lights in an area takes a lot of energy, so it is particularly crucial to choose the appropriate type of lamp that is adequate to perform effectively and efficiently. To determine the light distribution of the two types of lights, it is crucial to investigate the distribution of light. The investigation was carried out by the direct measurement technique on 6 and 8 watt LED lamps, as well as on CFL lamps 11 and 14 watt using luxmeter in an area projecting 3×4 meters. The analysis range is varied in several horizontal and vertical points. From the assessment results it was noticed that the LED and CFL lamps the value of the light intensity reduces if the horizontal and vertical distance of the measurement point are far from the lamp. The ends of the light distribution mapping discovered that the light distribution on the LED lights is better indeed and brighter at each point. This is because all the electrons recombine with holes. Whereas in the CFL lamp there has been a filament heating and ionization between the electrons with argon gas and mercury vapor which generates another energy which is relatively large heat energy.","PeriodicalId":380472,"journal":{"name":"2019 4th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127611852","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

Machine Learning Classifiers for Autism Spectrum Disorder: A Review 自闭症谱系障碍的机器学习分类器:综述

2019 4th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE) Pub Date : 2019-11-01 DOI: 10.1109/ICITISEE48480.2019.9003807

Dadang Eman, A. Emanuel

引用次数: 12