2021 13th International Conference on Information & Communication Technology and System (ICTS)最新文献

{"title":"Checking Wrong Decision and Wrong Pattern by Using A Graph-based Method","authors":"K. R. Sungkono, Erina Oktavia Putri, Habibatul Azkiyah, R. Sarno","doi":"10.1109/ICTS52701.2021.9608229","DOIUrl":"https://doi.org/10.1109/ICTS52701.2021.9608229","url":null,"abstract":"Companies in the world have been considered fraud as a crucial problem. The fraud can be caused by many things, including data manipulation and anomalies in business processes or standard operational procedures (SOP). Anomalies have several types; two of them are a wrong decision and a wrong pattern. A wrong decision, which is not in accordance with the standard list in SOP, occurs as a result of making wrong decisions. On the other hand, the wrong sequence of activities is called a wrong pattern. For detecting those two anomalies, this paper proposed a graph-based method. The graph-based method creates rules for detecting a wrong pattern by measuring the similarity between traces of SOP and the process and checks the attributes of activities to detect a wrong decision. The evaluation uses an event log of the credit application process in a bank. Based on the evaluation, the proposed graph-based method gains 100% for the accuracy value in checking wrong pattern and wrong decision.","PeriodicalId":6738,"journal":{"name":"2021 13th International Conference on Information & Communication Technology and System (ICTS)","volume":"27 1","pages":"184-189"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77045177","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}

{"title":"Analysis of Image Steganography using Wavelet and Cosine Transforms","authors":"Aulia Teaku Nururrahmah, T. Ahmad","doi":"10.1109/ICTS52701.2021.9609062","DOIUrl":"https://doi.org/10.1109/ICTS52701.2021.9609062","url":null,"abstract":"In this cyber era, protecting data has been a must, one of which is performed by implementing data hiding methods or steganography. It is a technique of hiding data or messages into a media cover, which can be an audio, image, or video file. This paper examines two transformed-based steganography, implementing DCT (Discrete Cosine Transform) and DWT (Discrete Wavelet Transform) to two types of cover images, general and medical. The purpose of this research is to analyze the performance of the embedding process using the low, middle, and low-middle frequency components of the DC coefficient and embed the payload bits into Low-Low (LL), Low-High (LH), High-Low (HL), High-High (HH) of the DWT bands. The experimental results show that, in general, the DCT method has better PSNR (Peak Signal to Noise Ratio) and payload capacity than DWT. Meanwhile, the combined low and middle frequency in the DCT method has a greater PSNR than other components in this transformation, which is 51.6751. Whereas in the DWT technique, LH and HL frequency components show better PSNR values than other DWT band components, which are 43.6939 and 43.5576, respectively.","PeriodicalId":6738,"journal":{"name":"2021 13th International Conference on Information & Communication Technology and System (ICTS)","volume":"2016 1","pages":"40-45"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86652396","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}

{"title":"Pedagogical Importance of Learner Interface in Web-Based e-Learning Content","authors":"S. D. S. de S Sirisuriya, L. Ranathunge, S. Karunanayake, N. A. Abdullah","doi":"10.1109/ICTS52701.2021.9608258","DOIUrl":"https://doi.org/10.1109/ICTS52701.2021.9608258","url":null,"abstract":"e-Learning has been revolutionizing education system based on the concept of learning occurring at any time and any place. Today the whole world adopts their life to the concept called “new normal” due to COVID-19 pandemic. When applying the new normal idea to the education system, online education is more important than ever. At present, online learning is applicable not only to learn academic work but also it helps to learn extracurricular activities for students as well as conducting training sessions for employees. With no face-to-face instructions, e-Learning provides a safe and effective alternative to classroom learning. Therefore, carefully designed and attractive content is the success of an e-Learning program that can keep the audience focused and interested. Hence, evaluating the web-based e-Learning content is necessary. The evaluation process usually consists of pedagogical evaluation and content evaluation. This research study is mainly focused on automating the pedagogical evaluation component. In automating the pedagogical evaluation, identifying inconsistencies is the biggest challenge faced by pedagogical experts in the current manual reviewing process, because different institutions use different checklists to pedagogically evaluate their e-Learning content. Developing a calibrated checklist to be used in the pedagogical evaluation process is the solution. This calibrated checklist was devised based on studying existing checklists, followed by creating a questionnaire, and a survey conducted with pedagogical experts to identify the essential review factors considered in the pedagogical evaluation process. Analyzed survey results identified that, “Learner interface of the course” was the most important review factor. A simple and user-friendly interface is a key component in enhancing the quality of online courses. This paper focused on giving comparative clarification about factors considered under ‘Learner Interface’ in the web-based e-Learning content.","PeriodicalId":6738,"journal":{"name":"2021 13th International Conference on Information & Communication Technology and System (ICTS)","volume":"1 1","pages":"101-105"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91525567","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}

{"title":"A Novel Approach on Conducting Reviewer Recommendations Based on Conflict of Interest","authors":"Adi Setyo Nugroho, Aizul Faiz Iswafaza, R. Anggraini, R. Sarno","doi":"10.1109/ICTS52701.2021.9609054","DOIUrl":"https://doi.org/10.1109/ICTS52701.2021.9609054","url":null,"abstract":"the reviewer's recommendation in accordance with the field of research is crucial where this is directly proportional to the results of the review on the research. In finding suitable reviewers, conflicts of interest (COI) are often found. In this paper, we propose an approach to reviewer recommendations with topic extraction and author extraction to prevent COI. First, we separate the process into 2, namely to do topic extraction using Latent Dirichlet Allocation (LDA), and also to do author extraction using Cosine Similarity. The next step is to combine the two results to rank the 10 recommended authors. The experimental results show that our approach has succeeded in getting 10 recommended reviewers to avoid COI.","PeriodicalId":6738,"journal":{"name":"2021 13th International Conference on Information & Communication Technology and System (ICTS)","volume":"5 1","pages":"195-200"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90199310","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}

{"title":"Activity Design Using Innovation Profiling in Appreciative Learning Serious Game of Indonesian Pronunciation","authors":"Hanny Haryanto, Aripin, I. Gamayanto","doi":"10.1109/ICTS52701.2021.9608559","DOIUrl":"https://doi.org/10.1109/ICTS52701.2021.9608559","url":null,"abstract":"Activity is one of the main elements for shaping the experience in serious game, that could enhance the player understanding on the learning material. However, lack of concept or framework to design the activity could resulted in poor experience. In previous research, Appreciative Learning has been used to design the activities in serious game. In this study, we use Innovation Profiling as a framework to develop activities in Design Stage of Appreciative Learning. Design stage in Appreciative Learning consists of activities to produce innovation. Therefore, the Innovation Profiling could provide the detailed concept for the activities in this stage. Innovation profiling has four types of innovation, that are open innovation, blind innovation, hidden innovation and unknown innovation. It divided into seven important parts: imitating, seeing, understanding, trying, changing, understanding, solution, integration and creative. Realistic visual speech synthesis is used as the player avatar to interact with the game and serve as main education tool of Indonesian pronunciation. Results show that the activity could enhance the player experience and motivation to learn Indonesian pronunciation.","PeriodicalId":6738,"journal":{"name":"2021 13th International Conference on Information & Communication Technology and System (ICTS)","volume":"278 1","pages":"24-28"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76893346","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}

{"title":"Bilingual Question Answering System Using Bidirectional Encoder Representations from Transformers and Best Matching Method","authors":"D. A. Navastara, Ihdiannaja, A. Arifin","doi":"10.1109/ICTS52701.2021.9608905","DOIUrl":"https://doi.org/10.1109/ICTS52701.2021.9608905","url":null,"abstract":"Question answering (QA) system is built to answer asked queries based on an unstructured collection of documents in natural language. The implementation of the QA system makes QA more efficient because the system can answer similar questions automatically. However, similarity queries based on questions or answers alone fail to retrieve documents relevant to the query in some cases because the word choice used in the query is different from the word choice in the QA database even though the context is the same. The same context can be seen from the list of references used by a QA. Therefore, it is necessary to measure the similarity of the query that does not only take into account the question and answer but also the reference. In this paper, we propose to build a bilingual QA system that answers Indonesian questions based on the combination of query similarities among question, answer, and external reference in Arabic using Bidirectional Encoder Representation from Transformers (BERT) and Best Matching (BM25) method. The similarity between query and reference are able to help to recognize a QA that uses reference with similar context. Based on the experimental result, the combination parameter of query-Question followed by query-Answer achieves the highest evaluation score with the Mean Average Precision (MAP) score of 0.988 and the Mean Reciprocal Rank (MRR) score of 1.000.","PeriodicalId":6738,"journal":{"name":"2021 13th International Conference on Information & Communication Technology and System (ICTS)","volume":"114 1","pages":"360-364"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80795589","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}

{"title":"Evaluating The Preliminary Models to Identify Fake News on COVID-19 Tweets","authors":"Ayu Mutiara Sari, Nurul Fajrin Ariyani, A. Ahmadiyah","doi":"10.1109/ICTS52701.2021.9607996","DOIUrl":"https://doi.org/10.1109/ICTS52701.2021.9607996","url":null,"abstract":"The spread propagation of fake news about COVID-19 can make it distressing to handle the pandemic situation. Identifying the fake and real news on social media needs to be done as quickly as possible to prevent chaos in the community and hampering the handling of COVID-19. In this study, we conducted some experiments to get a model that works well for classifying information into fake or real news using tweet data. We implemented two different ways to represent data to train machine learning classifier models, syntactic-based using Bag-of-Words and TF-IDF, and semantic-based using Word2Vec and FastText. We evaluated each model produced by the training process using two types of testing data. The results show that The Linear Support Vector Machine model using TF-IDF obtained the best F1-Score value in both testing data. The model obtained F1-Score 92.21% in Testing Data 1 and 93.33% in Testing Data 2.","PeriodicalId":6738,"journal":{"name":"2021 13th International Conference on Information & Communication Technology and System (ICTS)","volume":"75 1","pages":"336-341"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82025676","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}

{"title":"SER: Speech Emotion Recognition Application Based on Extreme Learning Machine","authors":"Ainurrochman, Irfanur Ilham Febriansyah, Umi Laili Yuhana","doi":"10.1109/ICTS52701.2021.9609016","DOIUrl":"https://doi.org/10.1109/ICTS52701.2021.9609016","url":null,"abstract":"Nowadays, device control is commonly using the human body feature or voice recognition technology. To expand the functionality of voice recognition, plenty of researchers have developed speech emotion recognition. By recognizing sound emotions, a system can provide better and beneficial decision-making output. This paper describes the development of an application that is able to recognize speech emotions using Extreme Learning Machine (ELM). We use the dataset from Toronto Emotional Speech Set (TESS). The dataset contains 2800 data points (audio files) in total and has high quality audio that focused on female voices to ensure the reliability of the data. The Speech Emotion Recognition application was design as web-based application that used Golang and Python which built with Extreme Learning Machine and Random Forest to recognize speech emotions. As a result, the functionality test shows that the application was able to satisfy 6 out of 6 requirements, and the accuracy test shows an accuracy value of 100% by identifying 70 out of 70 test data.","PeriodicalId":6738,"journal":{"name":"2021 13th International Conference on Information & Communication Technology and System (ICTS)","volume":"183 1","pages":"179-183"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91527580","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}

{"title":"Discontinuity Preserving Optical Flow Based on Anisotropic Operator","authors":"Muzammil Khan, Pushpendra Kumar","doi":"10.1109/ICTS52701.2021.9608188","DOIUrl":"https://doi.org/10.1109/ICTS52701.2021.9608188","url":null,"abstract":"Variational models are more popular approaches in the estimation of optical flow between two image frames and yield the most accurate flow fields. More fidelity terms in the variational model makes the estimation robust. This paper proposed an anisotropic operator which is designed using the greatest integer and an exponential function to estimate average flow velocity. This will help to preserve discontinuity in the optical flow and provides a significant smooth flow over a uniform region. The design of this operator is motivated from an isotropic operator that is based on the intensity differences of the pixels. This is employed in the controlling of flow propagation. The validation of the accuracy and robustness of our algorithm is provided in terms of qualitative and quantitative results on a variety of spectrum datasets.","PeriodicalId":6738,"journal":{"name":"2021 13th International Conference on Information & Communication Technology and System (ICTS)","volume":"51 1","pages":"306-311"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73586430","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}

{"title":"Ensemble Methods Classifier Comparison for Anomaly Based Intrusion Detection System on CIDDS-002 Dataset","authors":"Ainurrochman, A. Nugroho, Raditia Wahyuwidayat, Santi Tiodora Sianturi, Muhamad Fauzi, M. Ramadhan, B. Pratomo, A. M. Shiddiqi","doi":"10.1109/ICTS52701.2021.9608714","DOIUrl":"https://doi.org/10.1109/ICTS52701.2021.9608714","url":null,"abstract":"With the rapid development of information technology, the network has been everywhere. This technology has brought a lot of convenience to people, but there are also some security problems. To solve these problems, many methods have been proposed, among which is intrusion detection. A lot of research has been done to find the most effective Intrusion Detection Systems. In term of detecting novel attacks, Anomaly-Based Intrusion Detection Systems has better significance than Misuse-Based Intrusion Detection Systems. The research on the datasets being used for training and testing purposes in the detection model is as important as the model. Better dataset quality can improve intrusion detection model results. This research presents the statistical analysis of labeled flow-based CIDDS-002 dataset using ensemble methods classifier. The analysis is done concerning some prominent evaluation metrics used for evaluating Intrusion Detection Systems including Detection Rate, Accuracy, and False Positive Rate. As a result, the accuracy of the Bagging (Decision Tree) is 99.71% and Bagging (Gaussian Naïve Bayes) is 67.57%.","PeriodicalId":6738,"journal":{"name":"2021 13th International Conference on Information & Communication Technology and System (ICTS)","volume":"1 1","pages":"62-67"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82077470","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}