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Aplikasi Pengenalan Kosakata Bahasa Inggris "My Picture Dictionary" untuk Anak Sekolah Dasar Berbasis Android Yesmaya, Violitta; Wongso, Rini; Swandyka, Imam; Zeavani, Muhammad Niko; Safrizal, Noverdi
Teknik dan Ilmu Komputer Vol. 3 No. 11 Juli-September 2014
Publisher : Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar

One of the technological advances in computer technology is the widespread phenomenon of mobile devices. Nowadays, many children often spend their time by playing games in mobile devices thereby reducing time to study. This makes children prefer playing than studyng. In fact, the development of mobile device technology can actually be used by parents to provide guidance in its use because mobile device is considered effective as a medium of education for children. Therefore, this research is develiped which is used to design the English vocabulary recognition application "My Picture Dictionary" by providing interactive information to general users of Android. Methodology in designing this application is by using the methods of analysis and design. The result of this design is the application running ÃÂ on a mobile device, with Android as the operating system. With this application, children are expected to be able to understand more about English while playing (interactive) in this application.ÃÂ Keywords: mobile devices, English, Android

Perancangan Sistem Informasi Penjualan dan Persediaan pada PT Selatan Jaya Prima Perkasa Surja, Stephanie; Wongso, Rini
ComTech: Computer, Mathematics and Engineering Applications Vol 4, No 2 (2013): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v4i2.2497

This study aims to analyze the organization needs in sales and stock company process that related with the current business process at PT Selatan Jaya Prima Perkasa. The result will be used for developing an integrated system that can be the solution for the company needs in running their sales and to control theirinventory stock status as the main business of the company. The analyzed result in the company needs will be documented using unified modeling language. This information system is expected to simplify ease the company’s activitis in sales process and inventory stock control. This system will also minimize the data lost and human error usually caused by manual process of transactional data storage.

Eve: An Automated Question Answering System for Events Information Christanno, Ivan; Priscilla, Priscilla; Maulana, Jody Johansyah; Suhartono, Derwin; Wongso, Rini
ComTech: Computer, Mathematics and Engineering Applications Vol 8, No 1 (2017): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v8i1.3781

The objective of this research was to create a closed-domain of automated question answering system specifically for events called Eve. Automated Question Answering System (QAS) is a system that accepts question input in the form of natural language. The question will be processed through modules to finally return the most appropriate answer to the corresponding question instead of returning a full document as an output. Thescope of the events was those which were organized by Students Association of Computer Science (HIMTI) in Bina Nusantara University. It consisted of 3 main modules namely query processing, information retrieval, and information extraction. Meanwhile, the approaches used in this system included question classification, document indexing, named entity recognition and others. For the results, the system can answer 63 questions for word matching technique, and 32 questions for word similarity technique out of 94 questions correctly.

Question Categorization using Lexical Feature in Opini.id Saputra, Christian Eka; Suhartono, Derwin; Wongso, Rini
ComTech: Computer, Mathematics and Engineering Applications Vol 8, No 4 (2017): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v8i4.4026

This research aimed to categorize questions posted in Opini.id. N-gram and Bag of Concept (BOC) were used as the lexical features. Those were combined with Naïve Bayes, Support Vector Machine (SVM), and J48 Tree as the classification method. The experiments were done by using data from online media portal to categorize questions posted by user. Based on the experiments, the best accuracy is 96,5%. It is obtained by using the combination of Bigram Trigram Keyword (BTK) features with J48 Tree as classifier. Meanwhile, the combination of Unigram Bigram (UB) and Unigram Bigram Keyword (UBK) with attribute selection in WEKA achieves the accuracy of 95,94% by using SVM as the classifier.

Complaint Analysis in Indonesian Language Using WPKE and RAKE Algorithm Rini Wongso; Novita Hanafiah; Jaka Hartanto; Alexander Kevin; Charles Sutanto; Fiona Kesuma
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

Social media provides convenience in communicating and can present two-way communication that allows companies to interact with their customer. Companies can use information obtained from social media to analyze how the communities respond to their services or products. The biggest challenge in processing information in social media like Twitter, is the unstructured sentences which could lead to incorrect text processing. However, this information is very important for companies’ survival. In this research, we proposed a method to extract keywords from tweets in Indonesian language, WPKE. We compared it with RAKE, an algorithm that is language independent and usually used for keyword extraction. Finally, we develop a method to do clustering to groups the topics of complaints with data set obtained from Twitter using the “komplain” hashtag. Our method can obtain the accuracy of 72.92% while RAKE can only obtain 35.42%.

Summarizing Text for Indonesian Language by Using Latent Dirichlet Allocation and Genetic Algorithm Silvia .; Pitri Rukmana; Vivi Regina Aprilia; Derwin Suhartono; Rini Wongso; Meiliana .
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 1: EECSI 2014
Publisher : IAES Indonesia Section

The number of documents progressively increases especially for the electronic one. This degrades effectivity and efficiency in managing them. Therefore, it is a must to manage the documents. Automatic text summarization is able to solve by producing text document summaries. The goal of the research is to produce a tool to summarize documents in Bahasa: Indonesian Language. It is aimed to satisfy the user’s need of relevant and consistent summaries. The algorithm is based on sentence features scoring by using Latent Dirichlet Allocation and Genetic Algorithm for determining sentence feature weights. It is evaluated by calculating summarization speed, precision, recall, F-measure, and some subjective evaluations. Extractive summaries from the original text documents can represent important information from a single document in Bahasa with faster summarization speed compared to manual process. Best F-measure value is 0,556926 (with precision of 0.53448 and recall of 0.58134) and summary ratio of 30%.

Perancangan Sistem Informasi Penjualan dan Persediaan pada PT Selatan Jaya Prima Perkasa Stephanie Surja; Rini Wongso
ComTech: Computer, Mathematics and Engineering Applications Vol. 4 No. 2 (2013): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v4i2.2497

This study aims to analyze the organization needs in sales and stock company process that related with the current business process at PT Selatan Jaya Prima Perkasa. The result will be used for developing an integrated system that can be the solution for the company needs in running their sales and to control theirinventory stock status as the main business of the company. The analyzed result in the company needs will be documented using unified modeling language. This information system is expected to simplify ease the company’s activitis in sales process and inventory stock control. This system will also minimize the data lost and human error usually caused by manual process of transactional data storage.

Eve: An Automated Question Answering System for Events Information Ivan Christanno; Priscilla Priscilla; Jody Johansyah Maulana; Derwin Suhartono; Rini Wongso
ComTech: Computer, Mathematics and Engineering Applications Vol. 8 No. 1 (2017): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v8i1.3781

The objective of this research was to create a closed-domain of automated question answering system specifically for events called Eve. Automated Question Answering System (QAS) is a system that accepts question input in the form of natural language. The question will be processed through modules to finally return the most appropriate answer to the corresponding question instead of returning a full document as an output. Thescope of the events was those which were organized by Students Association of Computer Science (HIMTI) in Bina Nusantara University. It consisted of 3 main modules namely query processing, information retrieval, and information extraction. Meanwhile, the approaches used in this system included question classification, document indexing, named entity recognition and others. For the results, the system can answer 63 questions for word matching technique, and 32 questions for word similarity technique out of 94 questions correctly.

Question Categorization using Lexical Feature in Opini.id Christian Eka Saputra; Derwin Suhartono; Rini Wongso
ComTech: Computer, Mathematics and Engineering Applications Vol. 8 No. 4 (2017): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v8i4.4026

This research aimed to categorize questions posted in Opini.id. N-gram and Bag of Concept (BOC) were used as the lexical features. Those were combined with Naïve Bayes, Support Vector Machine (SVM), and J48 Tree as the classification method. The experiments were done by using data from online media portal to categorize questions posted by user. Based on the experiments, the best accuracy is 96,5%. It is obtained by using the combination of Bigram Trigram Keyword (BTK) features with J48 Tree as classifier. Meanwhile, the combination of Unigram Bigram (UB) and Unigram Bigram Keyword (UBK) with attribute selection in WEKA achieves the accuracy of 95,94% by using SVM as the classifier.

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