2019 3rd International Conference on Informatics and Computational Sciences (ICICoS)最新文献_第5页

Ensembles of Convolutional Neural Networks for Skin Lesion Dermoscopy Images Classification 基于卷积神经网络的皮肤病变皮肤镜图像分类

2019 3rd International Conference on Informatics and Computational Sciences (ICICoS) Pub Date : 2019-10-01 DOI: 10.1109/ICICoS48119.2019.8982484

Muhammad Ammarul Hilmy, P. S. Sasongko

引用次数: 5

Normal and Murmur Heart Sound Classification Using Linear Predictive Coding and k-Nearest Neighbor Methods 基于线性预测编码和k近邻方法的正常心音和杂音分类

2019 3rd International Conference on Informatics and Computational Sciences (ICICoS) Pub Date : 2019-10-01 DOI: 10.1109/ICICoS48119.2019.8982393

A. Sofwan, Imam Santoso, Himawan Pradipta, M. Arfan, Ajub Ajulian Zahra M

{"title":"Normal and Murmur Heart Sound Classification Using Linear Predictive Coding and k-Nearest Neighbor Methods","authors":"A. Sofwan, Imam Santoso, Himawan Pradipta, M. Arfan, Ajub Ajulian Zahra M","doi":"10.1109/ICICoS48119.2019.8982393","DOIUrl":"https://doi.org/10.1109/ICICoS48119.2019.8982393","url":null,"abstract":"Heart rate sounds have a special pattern that is in accordance with a person's heart condition. An abnormal heart will cause a distinctive sound called a murmur. Murmurs caused by various things that indicate a person's condition. Through a Phonocardiogram (PCG), it can be seen a person's heart rate signal wave. Normal heartbeat and murmurs have a distinctive pattern, so that through this pattern it can be detected a person's heart defects. This study will make a classification program that will sense normal heart sounds and murmurs. This program uses feature extraction methods using LPC (Linear Predictive Coding) and classification using k-NN (k-Nearest Neighbor) to identify these 2 heart conditions. The data that will be used as a database consists of samples of normal heart rate sounds and murmurs, and also data obtained from the heart rate detection device in the. wav, mono format. The system for detecting heart abnormalities consists of three main parts, namely: recording heart rate sounds, feature extraction using LPC with order 10, and feature lines using k-NN with 3 types of distances and variations of k. From the results of testing with these types of distance, the obtained average accuracy value of Chebyshev, City Block, and Euclidean are 96.67, 91.67, and 93.33 percent, respectively. In addition, the value of k equal 3 is the most optimal value of k with an average level of 96.67 percent.","PeriodicalId":105407,"journal":{"name":"2019 3rd International Conference on Informatics and Computational Sciences (ICICoS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126897927","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 Key Role of Ontology Alignment and Enrichment Methodologies for Aligning and Enriching Dwipa Ontology with the Weather Concept on the Tourism Domain 本体对齐与充实方法在Dwipa本体与旅游领域天气概念对齐与充实中的关键作用

2019 3rd International Conference on Informatics and Computational Sciences (ICICoS) Pub Date : 2019-10-01 DOI: 10.1109/ICICoS48119.2019.8982437

G. P. Kuntarto, Yossy Alrin, I. Gunawan

{"title":"The Key Role of Ontology Alignment and Enrichment Methodologies for Aligning and Enriching Dwipa Ontology with the Weather Concept on the Tourism Domain","authors":"G. P. Kuntarto, Yossy Alrin, I. Gunawan","doi":"10.1109/ICICoS48119.2019.8982437","DOIUrl":"https://doi.org/10.1109/ICICoS48119.2019.8982437","url":null,"abstract":"The Dwipa Ontology III is a one of many sources of knowledge about the tourism domain in Indonesia. It stores information and its relations mainly about accommodation, attraction, activity, and amenity. However, this particular ontology is lack to present information about weather which highly needed by tourists during traveling to the tourism destinations. Firstly, this research aims to align two sources of weather ontologies: the weather ontology and the weather ontology for smart city in order to create a new concept of weather ontology. This new weather ontology concept is generated by measuring its linguistic similarity. Secondly, this research focus on enriching the concept of initial ontology named the Dwipa Ontology III with the concept generated by ontology alignment approaches. The ontology alignment method has been successfully mapped two weather ontologies into a new concept of weather that consist of 14 literal data: WeatherCondition, WeatherReport, dewPointAtmospere, unit, gustingWind, Celsius, Humidity, AtmosperePressure, Speed, Temperature, Interval, hasDate, hasSpeedValue, and hasUnit. This new concept has been enriched to the Dwipa Ontology III by adding one new concept/ class named weatherReport that consist of four sub classes: Unit, Interval, WeatherCondition and Temperature and a total of 255 instances. This latest version of aligned and enriched ontology is given name as Dwipa Ontology III+.","PeriodicalId":105407,"journal":{"name":"2019 3rd International Conference on Informatics and Computational Sciences (ICICoS)","volume":"761 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122995033","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

Improved Line Operator for Retinal Blood Vessel Segmentation 改进的线算子用于视网膜血管分割

2019 3rd International Conference on Informatics and Computational Sciences (ICICoS) Pub Date : 2019-10-01 DOI: 10.1109/ICICoS48119.2019.8982512

R. Wihandika

引用次数: 0

Twitter Sentiment Analysis About Public Opinion on 4G Smartfren Network Services Using Convolutional Neural Network 基于卷积神经网络的4G smartfriend网络服务舆情推特情绪分析

2019 3rd International Conference on Informatics and Computational Sciences (ICICoS) Pub Date : 2019-10-01 DOI: 10.1109/ICICoS48119.2019.8982429

Muhammad Radifan Aldiansyah, P. S. Sasongko

{"title":"Twitter Sentiment Analysis About Public Opinion on 4G Smartfren Network Services Using Convolutional Neural Network","authors":"Muhammad Radifan Aldiansyah, P. S. Sasongko","doi":"10.1109/ICICoS48119.2019.8982429","DOIUrl":"https://doi.org/10.1109/ICICoS48119.2019.8982429","url":null,"abstract":"Sentiment Analysis was a process for identifying whether a source of text contains certain opinions, emotions, and polarity. Twitter Sentiment Analysis was a process for identifying sentiment and polarity on tweet. Twitter Sentiment Analysis provided a way for did survey about public sentiment to product, or particular even through collections of tweet. Main problem in sentiment identifying was how to determine classification model that gave high accuracy to classifying sentiment of tweet. One of the method for classifying sentiment of tweet was Deep Learning. Convolutional Neural Network (CNN) was special type of architecture from Deep Learning that its architecture had convolution layer. Convolution layer was important for extract relevant feature from text for classifying sentiment. The objective of this research was for found out the best CNN model for classifying sentiment of tweet. By using a dataset of tweets about public opinion on the Smartfren 4G network service, we searched the best CNN model using 6 combination parameters, that is the computational eficiency method, window size, and dimension of word embedding for parameters in Word2Vec Skip-gram model, then activation function in convolution layer, dropout rate, and pool size in pooling layer for parameters in CNN. The test is done using 10-fold cross validation for each search for the best parameter value and produced the best CNN model with an accuracy value of 88,21%.","PeriodicalId":105407,"journal":{"name":"2019 3rd International Conference on Informatics and Computational Sciences (ICICoS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134599984","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

Real-Time Human Detection and Tracking Using Two Sequential Frames for Advanced Driver Assistance System 基于两帧序列的高级驾驶员辅助系统实时人体检测与跟踪

2019 3rd International Conference on Informatics and Computational Sciences (ICICoS) Pub Date : 2019-10-01 DOI: 10.1109/ICICoS48119.2019.8982396

A. Mulyanto, Rohmat Indra Borman, Purwono Prasetyawan, W. Jatmiko, P. Mursanto

{"title":"Real-Time Human Detection and Tracking Using Two Sequential Frames for Advanced Driver Assistance System","authors":"A. Mulyanto, Rohmat Indra Borman, Purwono Prasetyawan, W. Jatmiko, P. Mursanto","doi":"10.1109/ICICoS48119.2019.8982396","DOIUrl":"https://doi.org/10.1109/ICICoS48119.2019.8982396","url":null,"abstract":"Real-time human detecting and tracking is an important task in Advanced Driver Assistance System (ADAS) especialy in providing an information about situation in front of vehicle. Deep Convolutional Neural Networks (CNN) is one algorithm that is widely applied to classify and detect objects. CNN has shown an impressive performance. However, the high computation of Deep CNN makes the algorithm difficult to be applied to the real ADAS system. Since 2014, the One-stage Detector approach such as SSD and YOLO began to be applied on devices with low computation. In this experiment, we present a real-time system for the detection and the tracking of humans (pedestrians, cyclists, and riders) for the ADAS system implemented in Raspberry Pi 3 Model B Plus. The object detection approach in this study applies the SSD framework, and the tracking human movements approach is done by calculating the movement of midpoint coordinates from bounding box objects from two sequenced frames. The result shows the realtime human detection and tracking on Raspberry Pi 3 B devices with input frame with a height 300 and a width 300 runs at 0.8 FPS with 77.6 percent processor consumption and 70.3 percent memory. Therefore, the use of Raspberry Pi 3 B Plus for human detection and tracking in ADAS systems is not suitable for the vehicle speeds above 50 Km per hour when runs at 0.8 FPS. Then the tracking system based on the coordinate movement of the midpoint bounding box has a problem when there is a bounding box overlapping or slicing each other","PeriodicalId":105407,"journal":{"name":"2019 3rd International Conference on Informatics and Computational Sciences (ICICoS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133379998","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

An Energy-Aware Computation Offloading Framework for a Mobile Crowdsensing Cluster Using DMIPS Approach 基于DMIPS方法的移动众感集群能量感知计算卸载框架

2019 3rd International Conference on Informatics and Computational Sciences (ICICoS) Pub Date : 2019-10-01 DOI: 10.1109/ICICoS48119.2019.8982480

Fuad Dary Rosyadi, W. Wibisono, T. Ahmad, R. Ijtihadie, Ary Mazharuddin Shidiqqi

{"title":"An Energy-Aware Computation Offloading Framework for a Mobile Crowdsensing Cluster Using DMIPS Approach","authors":"Fuad Dary Rosyadi, W. Wibisono, T. Ahmad, R. Ijtihadie, Ary Mazharuddin Shidiqqi","doi":"10.1109/ICICoS48119.2019.8982480","DOIUrl":"https://doi.org/10.1109/ICICoS48119.2019.8982480","url":null,"abstract":"The proliferation of the Internet of Things (IoT) devices for systems development has highlighted requirements for the devices to be able to perform various types of computations and services. They include basic computation applications that perform the simple computation to more complex and cumbersome load computation tasks. Since IoT devices are designed to be powered by battery. It has limitation in energy. This issue become one of the main challenges need to be dealt with in IoT -based application developments. Computation offloading where heavy tasks can be sent to the cloud server is one of promising technique to address this issue. However, sending large computational jobs along with the data to the cloud server not always give better results in term of energy consumptions. This paper proposes an approach to build energy-efficient computation offloading framework for an IoT-based mobile crowdsensing cluster based on the DMIPS approach. The experiments were conducted using real IoT devices and the results show that the smart offloading approach can reduce the energy consumption of the devices in performing high computation tasks compared to the full local or offloading executions.","PeriodicalId":105407,"journal":{"name":"2019 3rd International Conference on Informatics and Computational Sciences (ICICoS)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122782728","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

Fuzzy Semantic-Based String Similarity Experiments to Detect Plagiarism in Indonesian Documents 基于模糊语义的字符串相似度实验检测印尼语文献中的抄袭

2019 3rd International Conference on Informatics and Computational Sciences (ICICoS) Pub Date : 2019-10-01 DOI: 10.1109/ICICoS48119.2019.8982501

Chonan Firda Odayakana Umareta, Siti Mariyah

{"title":"Fuzzy Semantic-Based String Similarity Experiments to Detect Plagiarism in Indonesian Documents","authors":"Chonan Firda Odayakana Umareta, Siti Mariyah","doi":"10.1109/ICICoS48119.2019.8982501","DOIUrl":"https://doi.org/10.1109/ICICoS48119.2019.8982501","url":null,"abstract":"Plagiarism is a topic of concern in the world of education. One way to overcome plagiarism is to make comparisons between documents. Due to a large number of documents, extrinsic plagiarism detection frameworks are needed to make comparisons of documents in large numbers. On the other hand, there is intelligent plagiarism in which plagiarists try to hide their actions by one of them is replacing words with semantics. Therefore, this study applies an extrinsic plagiarism detection system with a Fuzzy Semantic-Based String Similarity method which is divided into three stages, namely Preprocessing, Heuristic Retrieval (HR), and Detailed Analysis (DA). In the preprocessing stage, the removal of irrelevant characters, the division of text based on sentences, stemming, tokenization, and the elimination of stopwords were performed. The search for pairs of candidate documents in the HR stage used fingerprints and Jaccard similarity. DA stage applied fuzzy semantic based-similarity. Experiments were carried out by comparing the level of document similarity between Jaccard similarity in the HR stage and fuzzy semantic-based similarity in the DA stage because both were able to produce a level of document similarity. The results show that fuzzy semantic-based similarity is better than Jaccard similarity because it can detect semantic similarities in the form of synonyms.","PeriodicalId":105407,"journal":{"name":"2019 3rd International Conference on Informatics and Computational Sciences (ICICoS)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125181007","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

Cataract Detection Using Single Layer Perceptron Based on Smartphone 基于智能手机的单层感知器白内障检测

2019 3rd International Conference on Informatics and Computational Sciences (ICICoS) Pub Date : 2019-10-01 DOI: 10.1109/ICICoS48119.2019.8982445

R. Sigit, E. Triyana, M. Rochmad

引用次数: 14

Rating Prediction on Movie Recommendation System: Collaborative Filtering Algorithm (CFA) vs. Dissymetrical Percentage Collaborative Filtering Algorithm (DSPCFA) 电影推荐系统的评分预测:协同过滤算法(CFA)与非对称百分比协同过滤算法(DSPCFA)

2019 3rd International Conference on Informatics and Computational Sciences (ICICoS) Pub Date : 2019-10-01 DOI: 10.1109/ICICoS48119.2019.8982385

J. Purnomo, S. Endah

{"title":"Rating Prediction on Movie Recommendation System: Collaborative Filtering Algorithm (CFA) vs. Dissymetrical Percentage Collaborative Filtering Algorithm (DSPCFA)","authors":"J. Purnomo, S. Endah","doi":"10.1109/ICICoS48119.2019.8982385","DOIUrl":"https://doi.org/10.1109/ICICoS48119.2019.8982385","url":null,"abstract":"Recommendation system is one of many solutions for getting information rapidly from the many data available and one of its applications is the movie recommendation system. Movie recommendation system filters information then recommends movies based on rating preferences or user information. One of the most widely used algorithms is the user based collaborative filtering algorithm (CFA) to predict movie ratings which will be recommended based on similarity between target user and other users regardless of common items or the number of movies that have been rated by both. One different approach of the CFA algorithm is a dissymmetrical percentage collaborative filtering algorithm (DSPCFA) that involves common items as a consideration of measuring similarity. This study also uses two similarity measurement methods, namely the pearson correlation similarity method and the cosine similarity method as a comparison to determine the characteristics of each measurement method. The experiment results show that the DSPCFA algorithm produces a lower error value than the CFA algorithm with an error decrease of about 5% for the RMSE evaluation method (Root-mean Squared Error) and an error decrease of about 7% using the MAE (Mean Absolute Error) evaluation method. While measurement method tested shows that the pearson correlation similarity method produces a lower error value than the cosine similarity method.","PeriodicalId":105407,"journal":{"name":"2019 3rd International Conference on Informatics and Computational Sciences (ICICoS)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127101406","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: 8