International Journal of artificial intelligence research (IJAIR)
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The Implementation Analysis Of Lamport Scheme With Sha-256 On Mobile E-Office
No full textElectronic administration system is one of the best solutions in the current digital era, electronic-based systems are considered to make it easier for an organization to process data and can reduce the possibility of data loss due to human error or natural disasters. The current administrative data management application is called the Electronic Office (E-Office). The E-Office handles data for incoming mail, outgoing mail and mail disposition. There are frequent delays in receiving information and validating letter files that are still carried out using physical files, so the mobile e-office is a solution that can be used by an agency to make it easier for workers to access information more quickly and can be done anywhere. Data security is an important thing that needs to be considered in an electronic transaction, so this research will add data security to the mobile e-office using sha-256 and lamport schemes. We present data on the results of this mobile e-office test on mobile devices and virtual private servers (vps), the data is in the form of functional application performance testing results and records of processing time performed by mobile and vps devices. From this data an analysis will be carried out to determine the appropriateness of the devices that can be used in running a mobile e-office
Information systems Estimated demand for certified seed
Get PDFThe availability of certified seeds is a very important strategy to maintain food security. When farmers plant their farms with certified seeds, it can increase the production yields grown by farmers. To answer the availability of sources according to the needs of farmers or consumers, it is necessary to design an information system for forecasting the demand for certified seeds, with a methodology Rational Unified Process (RUP) so that this method can be useful to identify the system that is running and can describe the system to be built. Meanwhile, to produce an estimate of the demand for certified seeds, a linear regression approach will be used which will be included in the design of the system. The design of this system will produce a function to assist producer farmers in estimating certified seed production, assisting the availability of certified seed information for consumers, and assisting the PSBTPH Installation in the Subang Region in carrying out evaluation and monitoring
Distributed Denial Of Service (DDOS) Attack Detection On Zigbee Protocol Using Naive Bayes Algoritm
Get PDFDistributed Denial of Service or better known as DDoS is an attempted attack from several computer systems that target a server so that the amount of traffic becomes too high so that the server cannot handle the request. DDoS is usually done by using several computer systems that are used as sources of attacks. So they attack one server through several computers so that the amount of traffic can also be higher. A DDoS attack is like a traffic jam that prevents a driver from reaching their desired destination on time. According to data, 33% of businesses in the world have fallen victim to DDoS attacks. DDoS is hard to trace. Some types of DDoS attacks can be very powerful and even reach speeds of 1.35 Tbps. Additionally, DDoS attacks can cause losses of $ 40,000 per hour if they occur. ZigBee is a standard from IEEE 802.15.4 for data communication on personal consumer devices as well as for business scale. ZigBee is designed with low power consumption and works for low level personal networks. ZigBee devices are commonly used to control another device or as a wireless sensor. ZigBee has a feature which is able to manage its own network, or manage data exchange on the network [1]. Another advantage of ZigBee is that it requires low power, so it can be used as a wireless control device which only needs to be installed once, because only one battery can make ZigBee last up to a year. In addition, ZigBee also has a "mesh" network topology so that it can form a wider network and more reliable data. In the previous research of Muhammad Aziz, Rusydi Umar, Faizin Ridho (2019) based on the results of the analysis carried out that the attack information that has been detected by the IDS based on signatures needs to be reviewed for accuracy using classification with statistical calculations. Based on the analysis and testing carried out with the artificial neural network method, it was found that the accuracy was 95.2381%. The neural network method can be applied in the field of network forensics in determining accurate results and helping to strengthen evidence at trial. The Naïve Bayes model performed relatively poor overall and produced the lowest accuracy score of this study (45%) when trained with the CICDDoS2019 dataset [47]. For the same model, precision was 66% and recall was 54%, meaning that almost half the time, the model misses to identify threats.Â
Social Awareness and Safety Assistance of COVID-19 based on DLN face mask detection and AR Distancing
Get PDFThe outbreak of coronavirus disease (COVID-19) has forced major countries to apply strict policy toward society. People must wear a facemask and always keep their distance from each other's to avoid virus contamination. Government employ officers to monitor citizen and warn them if not wearing a face mask. The warning message also spread through SMS and social media to ensure people about safety and awareness. This paper aims to provide face mask detection using the Deep Learning Network(DLN) and warning system through video stream input from CCTV or images then analyzed. If people not wearing a mask are detected, they will alert them through the speaker and remind them about a penalty. AR distancing very useful to give position toward violator location based on the detected person in a certain area. The system is designed to work intelligently and automatically without human intervention. With the accuracy of 99% recognition, it's expected that the system can help the government to increase people awareness toward the safety of themselves and people around them
Prediction of Scholarship Recipients Using Hybrid Data Mining Method with Combination of K-Means and C4.5 Algorithms
Get PDFObtaining a scholarship is the desire of every student or student who studies, especially those who come from poor families. The scholarship can lighten the burden on parents who pay for these students and can streamline the lecture process. However, students do not know exactly what they have to do to get the scholarship. Aside from that, students naturally want to know what causes and conditions have the greatest impact on achievement. The objective of this research is how to predict which number of students among them are predicted to get a scholarship at the opening of the scholarship acceptance using the K-Means and C4.5 methods. Apart from that, the aim of this research is to discover how the K-Means algorithm conducts data clustering (clustering) of student data to determine if they will succeed or not, as well as how the C4.5 algorithm makes predictions against students who have been clustered together. The Rapid Miner program version 9.7.002 was used to process the data in this report. The results of this study were that out of 100 students, 32 students were not scholarship recipients and 68 students were scholarship recipients. Another result of this research is that out of 100 students it is predicted that 9 (9%) will receive scholarships and 91 (91%) will not receive scholarships
Prediction of SPT value based on CPT data and soil properties using ANN with and without normalization
No full textArtificial neural networks (ANN) are now widely used and are becoming popular among researchers, especially in the geotechnical field. In general, data normalization is carried out to make ANN whose range is in accordance with the activation function used. Other studies have tried to create an ANN without normalizing the data and ANN is considered capable of making predictions. In this study, a comparison of ANN with and without data normalization was carried out in predicting SPT values based on CPT data and soil physical properties on cohesive soils. The input data used in this study are the value of tip resistance, sleeve resistance, effective soil overburden pressure, liquid limit, plastic limit and percentage of sand, silt and clay. The results showed that the ANN was able to make predictions effectively both on networks with and without data normalization. In this study, it was found that the ANN without data normalization showed a smaller error value than the ANN with data normalization. In the network model without data normalization, RMSE values were 3.024, MAE 1.822, R2 0.952 on the training data and RMSE 2.163, MAE 1.233 and R2 0.976 on the test data. Whereas in the ANN with data normalization, the RMSE values were 3.441, MAE 2.318, R2 0.936 in the training data and RMSE 2.785, MAE 2.085 and R2 0.963 in the test data. ANN with normalization provides a simpler architecture, which only requires 1 hidden layer compared to ANN without normalization which requires 2 hidden layer architecture
Extractive Text Summarization of Student Essay Assignment Using Sentence Weight Features and Fuzzy C-Means
Get PDFOne of the main tasks of a lecturer is to give students an academic assessment in the learning process. The assessment process begins with reading or checking the answers of student assignments that contain a combination of very long sentences such as essay or report assignments. This certainly takes a lot of time to get the primary information contained therein. It is necessary to summarize the answers so that the lecturer does not need to read the whole document but is still able to take the essence of the response to the task. This study proposes the application of summarizing text documents of student essay assignments automatically using the Fuzzy C-Means method with the sentence weighting feature. The sentence weighting feature is used by selecting the sentence with the highest weight in one cluster, helping the system to get the primary information from a document quickly. The results of this study indicate that the system succeeds in summarizing text with an average evaluation of the values of precision, recall, accuracy, and F-measure of 0.52, 0.54, 0.70, and 0.52, respectively.One of the main tasks of a lecturer is to give students an academic assessment in the learning process. The assessment process begins with reading or checking the answers of student assignments that contain a combination of very long sentences such as essay or report assignments. This certainly takes a lot of time to get the primary information contained therein. It is necessary to summarize the answers so that the lecturer does not need to read the whole document but is still able to take the essence of the response to the task. This study proposes the application of summarizing text documents of student essay assignments automatically using the Fuzzy C-Means method with the sentence weighting feature. The sentence weighting feature is used by selecting the sentence with the highest weight in one cluster, helping the system to get the primary information from a document quickly. The results of this study indicate that the system succeeds in summarizing text with an average evaluation of the values of precision, recall, accuracy, and F-measure of 0.52, 0.54, 0.70, and 0.52, respectively
Data Warehouse Design With ETL Method (Extract, Transform, And Load) for Company Information Centre
Get PDFData Warehouse is a technology use to analyze, extract and evaluate data into information which produce knownledge in the form of analysis to provide an advice in decision making process. Designing a Data Warehouse using ETL (Extract, Transformation and Load) process serves as the collection of data from different data sources into a multitude of integrated data sets. By using snowflake scheme for the design of the data warehouse make data prepare well and ready for analyze on Data Warehouse. The result of  this reseach is to applied Data Warehouse that use to support company decision making progress make easier and has a good decision since its come from Data Warehous
Intelligent Traffic Monitoring Systems: Vehicle Type Classification Using Support Vector Machine
Get PDFIn the automation of vehicle traffic monitoring system, information about the type of vehicle, it is essential because used in the process of further analysis as management of traffic control lights. Currently, calculation of the number of vehicles is still done manually. Computer vision applied to traffic monitoring systems could present data more complete and update.In this study consists of three main stages, namely Classification, Feature Extraction, and Detection. At stage vehicle classification used multi-class SVM method to evaluate characteristics of the object into eight classes (LV-TK, LV-Mobil, LV-Mikrobis, MHV-TS, MHV-BS, HV-LB, HV- LT, MC). Features are obtained from the detection object, processed on the feature extraction stage to get features of geometry, HOG, and LBP in the detection stage of the vehicle used MOG method combined with HOG-SVM to get an object in the form of a moving vehicle and does not move. SVM had the advantage of detail and based statistical computing. Geometry, HOG, and LBP characterize complex and represents an object in the form of the gradient and local histogram.The test results demonstrate the accuracy of the calculation of the number of vehicles at the stage of vehicle detection is 92%, with the parameters HOG cellSize 4x4, 2x2 block size, the son of vehicle classification 9. The test results give the overall mean recognition rate 91,31 %, mean precision rate 77,32 %, and mean recall rate 75,66 %.Â
The Influence Of Information Technology And The Perception Of Usefulness On The Use Of E-Filing
Get PDFThis present study at identifying the influence of information technology toward the use of e-Filing and the influence of perception of usefulness toward the use of e-Filing. The research method used is descriptive and verification with quantitative approach. The data used is primary data, while data collection techniques used are field research and library research. The sample in this research are 34 individual taxpayers of Weat Java Provincial Secretariat Office. The analysis model used is SEM PLS. The results of this study show that information technology has an effect on the use of e-Filingand usability perception has an effect on the use of e-Filin