Pub Date : 2018-05-01DOI: 10.1109/ICOICT.2018.8528789
Diamun Fikri Solissa, M. Abdurohman
This paper proposes The High Availability Method using Heartbeat and DRBD on Hadoop Namenode Failover. Implementation of Hadoop as computing process framework and media storage needs to be supported by the availability in case of failure. Cluster system utilization in Hadoop with many Datanode is one of the strength points. Stored file will be replicated in distributed datanode as blocks that makes if one the datanode server fails, the other datanodes server still has duplicates blocks. The problem in hadoop system, there is just one Namenode which is the communicator between users and Datanodes. While Namenode goes down then users can't access files stored in Datanode. This proposed method accomplishes the Namenode failover process. The use of this method is very effective because it can accelerate downtime with automatic failover formed by Heartbeat and real-time mirroring formed by DRBD. The results indicate that the use of DRBD and Heartbeat may accelerate failover time of less than 10 seconds.
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Pub Date : 2018-05-01DOI: 10.1109/ICOICT.2018.8528755
Arga Putra Panatagama, Guntur Putra Pratama, Dwi Yoga Wibawa
Divorce rate in Indonesia is the highest in the Asia Pacific. Meanwhile, the effects of divorce and domestic violence are so bad for children, especially for teenagers. The children of the divorce will show more anxiety, depression, and antisocial behavior than the child of a normal family. On the other side, the most important thing for people who are depressed is the presence of people who are willing to listen to them patiently and to not to underestimate the problem. However, depressed people don't always find people who are willing to do so when they are depressed. Thus, an application to facilitate them to share their stories and problems is needed, it is called SocioEmpathy. Methodology to develop SocioEmpathy is literature study based on scientific journals and books on ICT, and unstructured interviews towards divorce victim and professional psychologist. The result is a SocioEmpathy application that has features: 1) Timeline, 2) Personal Chat, 3) Panic Button, 4) Mood Tracker, and 5) Psychologist Consultation. The conclusion of this research is SocioEmpathy is expected to become a solution for divorce victims to ease their depression. On the other hand, the SocioEmpathy app also increase experience for psychology students and psychologists involved in this application.
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Pub Date : 2018-05-01DOI: 10.1109/ICOICT.2018.8528762
S. Putra, M. Gunawan, Agung Suryatno
Tokenization is an important process used to break the text into parts of a word. N-gram model now is widely used in computational linguistics for predicting the next item in such a contiguous sequence of $mathbf{n}$ items from a particular sample of text. This paper focuses on the implementation of tokenization and n-gram model using RapidMiner to produce unigram and bigram word for indexing Indonesian Translation of the Quran (ITQ). This study uses ITQ data sets consisting of 114 documents. The methods are data extracting and preprocessing text including tokenization, stemming, stopword removal, transformation cases, and n-grams. The results of this study showed the model produces the 6794 and 60323 tokens combination unigram and bigram use for index ITQ. Significant the contribution of this study is to enhance the digital index of ITQ.
{"title":"Tokenization and N-Gram for Indexing Indonesian Translation of the Quran","authors":"S. Putra, M. Gunawan, Agung Suryatno","doi":"10.1109/ICOICT.2018.8528762","DOIUrl":"https://doi.org/10.1109/ICOICT.2018.8528762","url":null,"abstract":"Tokenization is an important process used to break the text into parts of a word. N-gram model now is widely used in computational linguistics for predicting the next item in such a contiguous sequence of $mathbf{n}$ items from a particular sample of text. This paper focuses on the implementation of tokenization and n-gram model using RapidMiner to produce unigram and bigram word for indexing Indonesian Translation of the Quran (ITQ). This study uses ITQ data sets consisting of 114 documents. The methods are data extracting and preprocessing text including tokenization, stemming, stopword removal, transformation cases, and n-grams. The results of this study showed the model produces the 6794 and 60323 tokens combination unigram and bigram use for index ITQ. Significant the contribution of this study is to enhance the digital index of ITQ.","PeriodicalId":266335,"journal":{"name":"2018 6th International Conference on Information and Communication Technology (ICoICT)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115218616","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}
Pub Date : 2018-03-28DOI: 10.1109/ICOICT.2018.8528805
Ismail Rusli, B. Trilaksono, W. Adiprawita
Inferring walls configuration of indoor environment could help robot “understand” the environment better. This allows the robot to execute a task that involves inter-room navigation, such as picking an object in the kitchen. In this paper, we present a method to inferring walls configuration from a moving RGB-D sensor. Our goal is to combine a simple wall configuration model and fast wall detection method in order to get a system that works online, is real-time, and does not need a Manhattan World assumption. We tested our preliminary work, i.e. wall detection and measurement from moving RGB-D sensor, with MIT Stata Center Dataset. The performance of our method is reported in terms of accuracy and speed of execution.
推断室内环境的墙体配置可以帮助机器人更好地“理解”环境。这使得机器人可以执行包括房间间导航的任务，比如在厨房里挑选一个物体。在本文中，我们提出了一种从移动的RGB-D传感器推断壁面结构的方法。我们的目标是结合一个简单的墙配置模型和快速的墙检测方法，以获得一个在线工作的系统，是实时的，不需要曼哈顿世界的假设。我们使用MIT Stata Center数据集测试了我们的初步工作，即移动RGB-D传感器的墙壁检测和测量。我们的方法在准确性和执行速度方面的性能得到了报道。
{"title":"Mapping Walls of Indoor Environment Using Moving RGB-D Sensor","authors":"Ismail Rusli, B. Trilaksono, W. Adiprawita","doi":"10.1109/ICOICT.2018.8528805","DOIUrl":"https://doi.org/10.1109/ICOICT.2018.8528805","url":null,"abstract":"Inferring walls configuration of indoor environment could help robot “understand” the environment better. This allows the robot to execute a task that involves inter-room navigation, such as picking an object in the kitchen. In this paper, we present a method to inferring walls configuration from a moving RGB-D sensor. Our goal is to combine a simple wall configuration model and fast wall detection method in order to get a system that works online, is real-time, and does not need a Manhattan World assumption. We tested our preliminary work, i.e. wall detection and measurement from moving RGB-D sensor, with MIT Stata Center Dataset. The performance of our method is reported in terms of accuracy and speed of execution.","PeriodicalId":266335,"journal":{"name":"2018 6th International Conference on Information and Communication Technology (ICoICT)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122862868","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}
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