2017 International Seminar on Intelligent Technology and Its Applications (ISITIA)最新文献_第4页

Ink bleed-through binarization of Javanese handwritten ancient document using local adaptive threshold based on local class width 基于局部类宽度的局部自适应阈值的爪哇手写体古文档墨水溢出二值化

2017 International Seminar on Intelligent Technology and Its Applications (ISITIA) Pub Date : 2017-08-01 DOI: 10.1109/ISITIA.2017.8124097

Yogi Dwi Mahandi, Eko Mulyanto Yuniamo, Y. Suprapto, Endang Purwaningsih

引用次数: 2

Analysis of contaminant effect on ceramic & polymer insulator surface under artificial environmental condition 人工环境条件下污染物对陶瓷和聚合物绝缘子表面的影响分析

2017 International Seminar on Intelligent Technology and Its Applications (ISITIA) Pub Date : 2017-08-01 DOI: 10.1109/ISITIA.2017.8124073

D. Fahmi, I. M. Y. Negara, Anisa Kusumaningrum, Dirman Hariono Santosa

引用次数: 2

A prototype of monitoring precision agriculture system based on WSN 基于无线传感器网络的精准农业监测系统原型

2017 International Seminar on Intelligent Technology and Its Applications (ISITIA) Pub Date : 2017-08-01 DOI: 10.1109/ISITIA.2017.8124103

N. Fahmi, Samsul Huda, E. Prayitno, M. A. Rasyid, M. Roziqin, M. U. Pamenang

引用次数: 20

Predicting daily consumer price index using support vector regression method based cloud computing 基于云计算的支持向量回归方法预测每日消费者物价指数

2017 International Seminar on Intelligent Technology and Its Applications (ISITIA) Pub Date : 2017-08-01 DOI: 10.1109/ISITIA.2017.8124101

S. M. S. Nugroho, Intan Ari Budiastuti, M. Hariadi

{"title":"Predicting daily consumer price index using support vector regression method based cloud computing","authors":"S. M. S. Nugroho, Intan Ari Budiastuti, M. Hariadi","doi":"10.1109/ISITIA.2017.8124101","DOIUrl":"https://doi.org/10.1109/ISITIA.2017.8124101","url":null,"abstract":"Severe inflation can cause a country's economic downturn. Therefore, inflation needs to be controlled. One of inflation control conducted by the government is predicting and calculating inflation using CPI indicators on a monthly. Prediction with monthly frequency, could be too late, because inflation has been a few days and it is not known quickly. With the development of internet technology today, various data sources related to inflation easily obtained in real-time. This data can be used for daily CPI prediction. Daily predictions allow policy makers to make better policies. CPI prediction using daily data will face challenges. The growing variants and data volumes need good computing systems. Cloud computing can be used to solve the problem. This is a preliminary research in developing daily CPI prediction model using big data and cloud computing. Here we focus on developing a daily CPI prediction model using the Support Vector Regression (SVR) method in a cloud computing. For better accuracy, we compared the kernel functions of SVR and tuning SVR parameters using the grid search and Random Search method. In addition, we compared SVR with the Random Forest method. These daily CPI predictions are simulated into cloud computing environments. From this simulation we show computation time and accuration comparisons needed if run on personal computers with cloud computing. The results showed that SVR using RBF kernel has less mse value 0.3454 in monthly prediction and 0.0095 in daily predictions. And Random Forest result is slightly different than SVR — RBF, mse value 0.0171 in daily prediction. Experiment show that running CPI prediction have less time, for 1644 data need takes 522s than PC takes 837s.","PeriodicalId":308504,"journal":{"name":"2017 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130938748","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

Cogging torque reduction by modifying stator teeth and permanent magnet shape on a surface mounted PMSG 通过修改定子齿和永磁体形状在表面安装的PMSG上的齿槽转矩减少

2017 International Seminar on Intelligent Technology and Its Applications (ISITIA) Pub Date : 2017-08-01 DOI: 10.1109/ISITIA.2017.8124085

Herlina, R. Setiabudy, A. Rahardjo

引用次数: 15

Network management models to anticipate the problem of international Internet traffic in Indonesia 预测印尼国际互联网流量问题的网络管理模型

2017 International Seminar on Intelligent Technology and Its Applications (ISITIA) Pub Date : 2017-08-01 DOI: 10.1109/ISITIA.2017.8124047

Bagus Riyowiyoso, M. Suryanegara

{"title":"Network management models to anticipate the problem of international Internet traffic in Indonesia","authors":"Bagus Riyowiyoso, M. Suryanegara","doi":"10.1109/ISITIA.2017.8124047","DOIUrl":"https://doi.org/10.1109/ISITIA.2017.8124047","url":null,"abstract":"The number of Internet users in Indonesia in 2020 will increase up to 136.2 million users, while the Internet traffic will increase up to 2.1 Exabyte per month. However, 88% of internet traffic goes to international link and only 12% of traffic goes to domestic server. The problem is that the current capacity of Indonesian international links is only 20 Gbps, while the the required capacity is predicted to be 30 Gbps in year 2020. Therefore, we need a model to attain an efficient use of international bandwidth connection. This research aims to propose the three network management model in Indonesia, on the basis of cached server implementation. The models are derived by varying number of cached server, rack co-location, power supply, and capacity of international and domestic connectivity. The data is taken by conducting experimental test on an Indonesian leading telecommunications company. The result shows that the models can provide international bandwidth saving as much as 33.7%. Concerning the parameters of latency and hop count, the hybrid-cached server with 3 regional nodes has become the recommended model.","PeriodicalId":308504,"journal":{"name":"2017 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115672415","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

Sentiment analysis of public complaints using lexical resources between Indonesian sentiment lexicon and Sentiwordnet 利用印尼语情感词典和Sentiwordnet的词汇资源对公众投诉进行情感分析

2017 International Seminar on Intelligent Technology and Its Applications (ISITIA) Pub Date : 2017-08-01 DOI: 10.1109/ISITIA.2017.8124100

M. Lailiyah, S. Sumpeno, I. Purnama

{"title":"Sentiment analysis of public complaints using lexical resources between Indonesian sentiment lexicon and Sentiwordnet","authors":"M. Lailiyah, S. Sumpeno, I. Purnama","doi":"10.1109/ISITIA.2017.8124100","DOIUrl":"https://doi.org/10.1109/ISITIA.2017.8124100","url":null,"abstract":"Public complaints were one of the kinds of public participation and awareness to public service implementation. Information from public complaints can be used by the government to improve public satisfaction. In addition, the government can obtain public sentiment from public complaints either on media social or the official government site. Many kinds of research on sentiment analysis have been done, either used statistical method approach, semantic method approach or both. Statistical method approach was widely used. While semantic method approach being the hot topic recently. On semantic method approach, lexical resource was an important component to classily sentiment on text. Namely Sentiwordnet and Indonesian sentiment lexicon. Currently, Indonesian lexical resources for sentiment analysis has grown. But the lexicon doesn't have polarity score that can be measure emotion on text like Sentiwordnet. Sentiwordnet has been widely used on research in English. In this research, we apply Sentiwordnet to classify sentiment on Indonesian public complaints with accuracy 47% either on media Twitter and 56.85% on the official government website's data. Furthermore, we compare it with Indonesian sentiment lexical and get the accuracy 65.4% on media Twitter and 81.4% on the of Ticial government website","PeriodicalId":308504,"journal":{"name":"2017 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"343 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121608609","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: 18

Core-cutting topology effects of single phase 1-KVA transformer on inrush current 单相1kva变压器割心拓扑对涌流的影响

2017 International Seminar on Intelligent Technology and Its Applications (ISITIA) Pub Date : 2017-08-01 DOI: 10.1109/ISITIA.2017.8124070

Arief Budi Ksatria, I. M. Y. Negara, D. Riawan, D. A. Asfani, D. Fahmi

引用次数: 1

High performance asynchronous bit-level parallel interface for board-to-board inter processor communication 用于板对板处理器间通信的高性能异步位级并行接口

2017 International Seminar on Intelligent Technology and Its Applications (ISITIA) Pub Date : 2017-08-01 DOI: 10.1109/ISITIA.2017.8124112

Faizal Arya Samman, Thagiat Ahzan Adp, F. Nugraha

引用次数: 0

Affective human pose classification from optical motion capture 基于光学动作捕捉的情感人体姿势分类

2017 International Seminar on Intelligent Technology and Its Applications (ISITIA) Pub Date : 2017-08-01 DOI: 10.1109/ISITIA.2017.8124095

Muhtadin, S. Sumpeno, Aang Pamuji Dyaksa

{"title":"Affective human pose classification from optical motion capture","authors":"Muhtadin, S. Sumpeno, Aang Pamuji Dyaksa","doi":"10.1109/ISITIA.2017.8124095","DOIUrl":"https://doi.org/10.1109/ISITIA.2017.8124095","url":null,"abstract":"In the animation movie production, there is a common tool namely motion capture (mocap) to capture the motion of actors. Using this technology, reconstruction of actors motion is being mapped to drive 3D character in the animation. In the reconstruction process of human motion, there were some significant parameters that affect the quality of the result such as subtle motion and high precision reconstruction. In order to get the best result, it requires some configurations such as camera disposition, camera configuration, and marker arrangement that should be placed in the proper position. Furthermore, after the capturing process, the result needs to be repaired due to misplaced or unable to define some markers. The result of this research is a Human Motion Database (HMDB), consist of poses which express basic emotion based on database from The Bodily Expressive Action Stimulus Test (BEAST). Basic emotions are anger, fear, happiness and sadness. The database result evaluated by conducting classification and validation of the data affective poses. Pose data is represented by rotation value of each joint in the skeleton. This value classified using machine learning to predict each pose to emotion classes. Classification result of the affective pose has the highest accuration score was fear class. Respectively the accuracy of class fear, anger, happiness and sadness are 96.87%, 95.62%, 94.37%, and 94.37%/","PeriodicalId":308504,"journal":{"name":"2017 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134360718","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: 4