IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
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Bidirectional Long Short Term Memory Method and Word2vec Extraction Approach for Hate Speech Detection
Get PDFCurrently, the discussion about hate speech in Indonesia is warm, primarily through social media. Hate speech is communication that disparages a person or group based on characteristics such as (race, ethnicity, gender, citizenship, religion and organization). Twitter is one of the social media that someone uses to express their feelings and opinions through tweets, including tweets that contain expressions of hatred because Twitter has a significant influence on the success or destruction of one's image.This study aims to detect hate speech or not hate Indonesian speech tweets by using the Bidirectional Long Short Term Memory method and the word2vec feature extraction method with Continuous bag-of-word (CBOW) architecture. For testing the BiLSTM purpose with the calculation of the value of accuracy, precision, recall, and F-measure.The use of word2vec and the Bidirectional Long Short Term Memory method with CBOW architecture, with epoch 10, learning rate 0.001 and the number of neurons 200 on the hidden layer, produce an accuracy rate of 94.66%, with each precision value of 99.08%, recall 93, 74% and F-measure 96.29%. In contrast, the Bidirectional Long Short Term Memory with three layers has an accuracy of 96.93%. The addition of one layer to BiLSTM increased by 2.27%
Resource Modification On Multicore Server With Kernel Bypass
Get PDFTechnology develops very fast marked by many innovations both from hardware and software. Multicore servers with a growing number of cores require efficient software. Kernel and Hardware used to handle various operational needs have some limitations. This limitation is due to the high level of complexity especially in handling as a server such as single socket discriptor, single IRQ and lack of pooling so that it requires some modifications. The Kernel Bypass is one of the methods to overcome the deficiencies of the kernel. Modifications on this server are a combination increase throughput and decrease server latency. Modifications at the driver level with hashing rx signal and multiple receives modification with multiple ip receivers, multiple thread receivers and multiple port listener used to increase throughput. Modifications using pooling principles at either the kernel level or the program level are used to decrease the latency. This combination of modifications makes the server more reliable with an average throughput increase of 250.44% and a decrease in latency 65.83%
An Expert System of Chicken Disease Diagnosis by Using Dempster Shafer Method
Get PDF Chicken is an animal that can provide many benefits for human life, meat and eggs can be used as food to fulfill the needs of human food, the excrement can be made fertilizer, and frequently its be used as a farm animal. Although it can provide many benefits, but for chicken farmers, the maintenance of chicken meet some obstacles that must be faced such as disease, poor environmental sanitation, and the production of eggs are declining. From some of the obstacles that have been mentioned, the most frequently encountered are animals infected with the disease. Based on the results of interviews that have been done to some chicken farmers, it can be said that the knowledge of chicken farmers against chicken disease and its handling is still very lacking. But the number of experts who understand and know about the type of chicken disease and the way of handling is limited, then it takes an expert system that can simulate knowledge and understanding of experts to overcome the problem. Based on the study of the libraries, the method suitable for use in the expert system is the Dempster shafer method by processing the value of belief in a disease. Dempster shafer method is a method used to calculate uncertainty due to the addition or reduction of new facts that will change the existing rules. Based on tests in 40 cases using an expert system applying the Dempster Shafer method, obtained the percentage of diagnostic compatibility result given by experts and system is 95%
Dataset Splitting Techniques Comparison For Face Classification on CCTV Images
Get PDFThe performance of classification models in machine learning algorithms is influenced by many factors, one of which is dataset splitting method. To avoid overfitting, it is important to apply a suitable dataset splitting strategy. This study presents comparison of four dataset splitting techniques, namely Random Sub-sampling Validation (RSV), k-Fold Cross Validation (k-FCV), Bootstrap Validation (BV) and Moralis Lima Martin Validation (MLMV). This comparison is done in face classification on CCTV images using Convolutional Neural Network (CNN) algorithm and Support Vector Machine (SVM) algorithm. This study is also applied in two image datasets. The results of the comparison are reviewed by using model accuracy in training set, validation set and test set, also bias and variance of the model. The experiment shows that k-FCV technique has more stable performance and provide high accuracy on training set as well as good generalizations on validation set and test set. Meanwhile, data splitting using MLMV technique has lower performance than the other three techniques since it yields lower accuracy. This technique also shows higher bias and variance values and it builds overfitting models, especially when it is applied on validation set
Twitter’s User Opinion About Master and Doctoral Degrees: A Model of Sentiment Comparison
Get PDFThis paper examines the opinion of student candidate about their plan to study further to master degree (S2) and doctoral degree (S3). There is lack of approach in finding public opinion about the interest of student candidate in continuing study to higher level such as master degree or doctoral degree. Through this paper, the Twitter’s user opinions are extracted using certain data mining technique to find out three sentiment types (negative, neutral, and positive) by taking the most dominant type of emotions (i.e., anger, anticipation, love, fear, joy, sadness, surprise, trust). The dataset is divided into two groups of Twitter’s users. Both datasets represent group A those opinion is about continuing study further to master degree versus group B whose continuing to doctoral degree. The groups are then divided into three types of sentiment statements about master degree versus doctoral degree. The first group is their sentiment about continuing study further to master degree with the result: (a) 109 negative tweets, 1683 neutral tweets and 131 positive tweets. For the second group (e.g., student’s sentiments about continuing to doctoral degree), it has results: (a) 421 negative tweets, 7666 neutral tweets and 1805 positive tweets. The data are tested to give accuracy value of 85%. The result of this sentiment analysis is useful as a reference for universities to understand the development of sentiments (opinion) from Twitter’s users and help the institutions to improve their reputation and qualit
Combination of AHP Method and VIKOR Method For Assesing Sunday School Teacher
Get PDFThe performance appraisal of Sunday school teacher in the Imanuel Lurang congregation aims to measure and distinguish the quality of performance achieved by Sunday school teacher and decide various policies such as giving rewards to every Sunday school teacher with the best performance, and for Sunday school teacher who have poor performance scores will be given a guiding, approach, etc. The number of criteria in determining the quality of Sunday school teacher is not an easy thing to do by manual. Then it is essential that a computerized performance appraisal-based performance app can speed up the process of progressing to be more effective and efficient. This research develops decision support systems (DSS) that is dynamic using the PHP programming language, by combining the AHP method that has been refined by the VIKOR method. The AHP method is used in determining the weight of each criterion, and the VIKOR method is used for the ranking process. Test results indicate that the system can provide a sequence of alternative Sunday school teacher that will be used as recommendations for decision makers to determine which Sunday school teachers are quality and not qualified
Determination of Temporal Association Rules Pattern Using Apriori Algorithm
Get PDFA supermarket must have good business plan in order to meet customer desires. One way that can be done to meet customer desires is to find out the pattern of shopping purchases resulting from processing sales transaction data. Data processing produces information related to the function of the association between items of goods temporarily. Association rules functions in data mining.Association rule is one of the data mining techniques used to find patterns in combination of transaction data. Apriori algorithm can be used to find association rules. Apriori algorithm is used to find frequent itemset candidates who meet the support count. Frequent itemset that meets the support count is then processed using the temporal association rules method. The function of temporal association rules is as a time limitation in displaying the results of frequent itemsets and association rules. This study aims to produce rules from transaction data, apriori algorithm is used to form temporal association rules. The final results of this research are strong rules, they are rules that always appear in 3 years at certain time intervals with limitation on support and confidence, so that the rules can be used for business plan layout recommendations in Maharani Supermarket Demak
Optimizing Virtual Resources Management Using Docker on Cloud Applications
Get PDFThis study aims to optimize servers with low utility levels on hardware using container virtualization techniques from Docker. This study's primary focus is to maximize the work of the CPU, RAM, and Hard Drive. The application of virtualization techniques is to create many containers as each of the containers is for the application to run a cloud storage system with the CaaS service infrastructure concept (Container as a Service). Containers on infrastructure will interact with other containers using configuration commands at Docker to form an infrastructure service such as CaaS in general. Testing of hardware carried out by running five Nextcloud cloud storage applications and five MariaDB database applications running in Docker containers and tested by random testing using a multimedia dataset. Random testing with datasets includes uploading and downloading datasets simultaneously and CPU monitoring under load, RAM, and Disk hardware resources. The testing will be done using Docker stats, HTOP, and Cockpit monitoring tools to determine the hardware capabilities when processing multimedia datasets
The Strategy of Enhancing Employee Reward Using TOPSIS Method as a Decision Support System
Get PDF Giving rewards for good performance and achievement of tasks needs to be done as a form of recognition and appreciation by the organization/institution to employees, as well as being part of the process of achieving organizational goals. This study aims to develop a Decision Support System that uses the Technique for Order of Preference by Similarity (TOPSIS) method with the PHP programming language to select reward recipients at University. The data used came from 2 groups, namely educational staff (lecturers) and non-educative staff (employees). Determination criteria applied to the educative group are 10 things, namely: tenure, DP3 value, the value on the percentage of work attendance, value on the percentage of teaching attendance, value on lecturer functional position, value on research implementation, the value on implementation of community service, value on the results of the questionnaire by students, the value of employment status, and the value of sanctions. There are 5 determinant criteria used in the non-educative group, namely: tenure, DP3 value, percentage of work attendance, the value of employment status, and value of sanctions. The results of this study are in the form of an information system program as a decision-making tool for the process of selecting reward recipient employees
P2P Communication among Computers and Smartphones Based on Bluetooth and Wi-Fi Direct Technologies
Get PDFAs result of the development of technology, most of modern computer and smartphones are Bluetooth and Wi-Fi direct wireless technologies enabled. While those wireless technologies come with the benefits of interconnecting devices without the need access point or central base station. However, computer and smartphones connected via Bluetooth based or via Wi-Fi Direct connection does not guarantee intercommunication or data transmission in meaningful way. Therefore, third party software is always needed to help for achieving data transmission. In this research an effort is done to design and develop P2P software applications and web based application by using C# and ASP.net MVC programming languages as features of Visual Studio 2017. Application would facilitate P2P communication of interconnected devices via the same channel. Built software system has been tested based on functional testing method, and usability testing. The result from functional testing shows that P2P communication meets functional requirements while usability testing has an average score of 72.2% from System Usability Scale method. The results from SUS scores brands our proposed P2P communication system to be good and highly accepted