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

{"title":"Systematic Analysis of Hateful Text Detection Using Machine Learning Classifiers","authors":"Tanzina Akter Tani, Tabassum Islam, Sayed Atique Newaz, N. Sultana","doi":"10.1109/ICTS52701.2021.9608010","DOIUrl":"https://doi.org/10.1109/ICTS52701.2021.9608010","url":null,"abstract":"In today's internet-based world, social media is one of the most popular platforms through which users can outburst their different types of feelings, emotions, frustration, anger, happiness etc. without having concern about distinguishes between moral and social values. These kinds of abusive or offensive texts cause social disturbances, crimes, and many unethical deeds. So, there is a huge necessity to distinguish these kinds of abusive texts/posts and remove them from social media. Different researchers have distinguished different text detection processes in their related work. In our proposed work, three classifiers have been used: Naïve Bayes (NB), Random Forest (RF), and Support Vector Machine (SVM) for detecting hateful text. Bag of Words (BoW) and TF-IDF feature extraction methods have been used to compare these three classifiers for both unigram and bigrams words. To balance hateful and clean content, the Twitter dataset has been under-sampled. Text preprocessing is essential for NLP to produce better and more accurate results which have been carried out in this work. In our result, Naive Bayes has provided the highest accuracy (89%) using the TF-IDF feature extraction model, whereas Random Forest has provided the most accuracy (88%) using Bag of words (BoW) in the case of unigram word. Overall, we got much better performance using unigram than using bigrams word. Finally, we made a number of principle contributions.","PeriodicalId":6738,"journal":{"name":"2021 13th International Conference on Information & Communication Technology and System (ICTS)","volume":"339 1","pages":"330-335"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80733948","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":"Graph Algorithm for Anomaly Prediction in East Java Student Admission System","authors":"Dwi Sunaryono, Annas Nuril Iman, D. Purwitasari, A. B. Raharjo","doi":"10.1109/ICTS52701.2021.9608565","DOIUrl":"https://doi.org/10.1109/ICTS52701.2021.9608565","url":null,"abstract":"Before the zoning policy, students or their parents tend to choose a recognized school with high educational quality despite its distance. New Student Admissions or Penerimaan Peserta Didik Baru (PPDB) is a school zoning enrollment system that aims to reduce the student travel distance. The online-based PPDB system requires home location input supplemented with legal documents as validation mechanism. However, falsifying home residence or enrollment fraud could not be identified by the PPDB system. This study examines the possible fraud cases from the PPDB enrollment ranks data. The ranks data forms a graph relationship between the registrant and the school. Every data contains a longitude-latitude point, and it is the main factor for accepting based on PPDB policy. The process is trying to analyze the connection between distance gap distribution derived from the ranks data, with the concurrent fraud cases. Because the distance gap distribution still has a missing value on several gap points, it is useful to use KDE (Kernel Density Estimation) to estimate those unknown values. KDE will result in estimated distance gap distribution. The distance gap distribution is affected by the residence location that is plotted on a geo map. When there's an uncommon location of some registrant it will create fluctuation on the distance gap distribution. The gap distribution value exceeds the estimated distance gap distribution from this situation and will be detected as an enrollment fraud. The process to detect enrollment fraud is handled with a graph algorithm. The graph algorithm traverses the graph data and gets ranked registrant from a school. The data are grouped every two meters and check whether its count does not exceed the estimated distance gap distribution. The graph algorithm builds over the PPDB system and tests several manipulated residence locations. It could detect those manipulated data and has a fast process since it only took less than one second.","PeriodicalId":6738,"journal":{"name":"2021 13th International Conference on Information & Communication Technology and System (ICTS)","volume":"104 1","pages":"252-257"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72817666","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":"Tracking Position of Airborne Target on SPx-Radar-Simulator Using Probabilistic Data Association Filter","authors":"M. Sahal, Zaidan Adenin Said, Rusdhianto Effendi Abdul Kadir, Z. Hidayat, Y. Bilfaqih, Abdullah Alkaff","doi":"10.1109/ICTS52701.2021.9608370","DOIUrl":"https://doi.org/10.1109/ICTS52701.2021.9608370","url":null,"abstract":"Radar has various functions, one of which is tracking the position of targets in the air. In tracking the target position, there are obstacles, namely the uncertainty of data associations. To overcome the uncertainty of data associations, the concept of data association can be used where one of the algorithms that use this concept is the Probabilistic Data Association Filter (PDAF). A single target position tracking system in the air will be tested on radar using the PDAF with our proposed maintenance track algorithm. The data used for testing comes from simulating two motions on the SPx-Radar-Simulator. False alarms originating from interference (clutter) will be generated in the environment around the simulated target. The test results of the target tracking system using the PDAF algorithm that has been designed can track targets well, maintain tracking conditions in an environment that has clutter, and maintain track on multitarget environments. The error between the original data and the prediction on the validated target has a relatively small value, although there is a relatively significant difference in the error of the altitude data when the motion has varying altitude conditions.","PeriodicalId":6738,"journal":{"name":"2021 13th International Conference on Information & Communication Technology and System (ICTS)","volume":"56 1","pages":"258-263"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76622298","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":"Hiding Messages in Audio using Modulus Operation and Simple Partition","authors":"I. B. Prayogi, T. Ahmad, Ntivuguruzwa Jean de La Croix, Pascal Maniriho","doi":"10.1109/ICTS52701.2021.9609028","DOIUrl":"https://doi.org/10.1109/ICTS52701.2021.9609028","url":null,"abstract":"Today's information technology tools allow people to share personal data and information through online media. Data security techniques are also developed to protect confidential messages that are only intended for certain parties, one of which is by embedding those data in a specific medium. The hiding method proposed in this study uses a simple partition to split the 16-bit audio cover file into two groups of the same length. The simple partition technique is applied to improve the quality of the resulting stego file. Furthermore, it is also developing an adaptive modulus operation calculation method, whose implementation on the difference of sample can increase the embedding capacity of the secret messages. The final result of the proposed method shows that all secret messages at the 700 kb payload file size can be successfully embedded, and the PSNR can be maintained up to 120.55 dB.","PeriodicalId":6738,"journal":{"name":"2021 13th International Conference on Information & Communication Technology and System (ICTS)","volume":"72 1","pages":"51-55"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73342980","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":"Dungeon's Room Generation Using Cellular Automata and Poisson Disk Sampling in Roguelike Game","authors":"Nur Muhammad Husnul Habib Yahya, Hadziq Fabroyir, D. Herumurti, Imam Kuswardayan, S. Arifiani","doi":"10.1109/ICTS52701.2021.9608037","DOIUrl":"https://doi.org/10.1109/ICTS52701.2021.9608037","url":null,"abstract":"Procedural Content Generation (PCG) allows game developers to create worlds in games easier compared with creating them manually. One of many PCG algorithms is Cellular Automata (CA). CA was used in this research together with Poisson Disk Sampling (PDS) to generate two-dimensional dungeons in a roguelike game. PDS was modified to adapt to a grid-based environment to increase computation's efficiency. Each room generated in the game was connected to each other. Together, all the rooms created a dungeon. The connections between the rooms were architected using Depth First Search (DFS) algorithm as commonly used in maze generation. The created dungeons became the world in the game. Players could explore the dungeons to conquer them and collect resources. Then, players could spend the resources to upgrade their character. According to the research evaluation, using only CA was not sufficient to generate dungeons with specific designs. Certain pipelines were demanded to adjust and to control the end results. The algorithm still run adequately fast, which was around 73 milliseconds, despite all the pipeline additions.","PeriodicalId":6738,"journal":{"name":"2021 13th International Conference on Information & Communication Technology and System (ICTS)","volume":"25 1","pages":"29-34"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74043900","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":"Generating Team Quality Formula to Predict Product Quality in Software Engineering Project of College Students","authors":"Umi Sa’adah, Maulidan Bagus Afridian Rasyid, S. Rochimah, Umi Laili Yuhana","doi":"10.1109/ICTS52701.2021.9607916","DOIUrl":"https://doi.org/10.1109/ICTS52701.2021.9607916","url":null,"abstract":"In the CHAOS report 2020 released by the Standish Group, “a good team” is an essential factor in determining the success of a project. Therefore, team quality assessment becomes significant for team management. Furthermore, it has believed that the quality of the product developed represents the quality of the development team. For this reason, it is necessary to measure the quality of the team at any point, so we can take mitigation steps to improve the quality. The study has two aims: (1) to build a team quality measurement model to prove that team quality positively correlates with product quality and (2) to produce a team quality formula to predict product quality. We conducted the study on ten teams with 57 students who attended the Software Development Workshop class. The students applied self-assessment to assess the quality of the team. In addition, software development practitioners carried out product quality assessments. The method used to obtain a relationship between the two is the Pearson correlation. We generated a team quality measurement formula using the Brute Force method. This study proves that the quality of the development team has a positive correlation with the quality of the product developed by 0.87. Meanwhile, the team quality formula can be used as a reference to predict the quality of the product developed","PeriodicalId":6738,"journal":{"name":"2021 13th International Conference on Information & Communication Technology and System (ICTS)","volume":"108 1","pages":"106-111"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79406066","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":"Sketch Generation From Real Object Images Using Generative Adversarial Network and Deep Reinforcement Learning","authors":"Shintya Rezky Rahmayanti, C. Fatichah, N. Suciati","doi":"10.1109/ICTS52701.2021.9608634","DOIUrl":"https://doi.org/10.1109/ICTS52701.2021.9608634","url":null,"abstract":"Technology in Robotics and machine learning have been applied in numerous fields including the arts. Paul The Robot is able to draw sketches from human faces using the conventional convolution filter method. Generative Adversarial Network (GAN) has been successful in generating synthetic images. Researches in sketch generation have been conducted either by using Recurrent Neural Network (RNN) or by using Deep Reinforcement Learning, with step-by-step stroke drawing. This research proposes a system to generate sketches from real object images using GAN dan Deep Reinforcement Learning. The training framework used is based on Doodle-SDQ (Doodle with Stroke Demonstration and Deep Q-Network) that combines supervised learning and reinforcement learning. Real object images are converted into contour images by GAN to be the reference images by the reinforcement learning agent to generate the sketch. The experiment is done by modifying pooling layers during the supervised learning stage and rare exploration scenarios during the reinforcement learning stage. The result of this research is a model that can reach an average total reward of 2558.98 with an average pixel error of 0.0489 using 200 as the maximum step in an average time of 3.29 seconds for the sketch generation.","PeriodicalId":6738,"journal":{"name":"2021 13th International Conference on Information & Communication Technology and System (ICTS)","volume":"114 1","pages":"134-139"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80463960","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":"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}