Pattern Recognition on Vehicle Number Plates Using a Fast Match Algorithm

Computer Vision was the fast developing apps in the world, it is make people make a lot of new algorithm. Before we can use in out app, we need to test the algorithm to make sure how effective and optimal the algorithm to solve every case we given. A lot of traffic system has implemented computer vision, they need fast and can work in every condition, because every vehicle who pass needs to be recognized. In this research Fast Match algorithm was chosen because they can solve some test and make a lot of image have a similarity with the template. It makes accuracy of the data can be achieved with this algorithm. For example on of the sample was have a SAD point for 0.5 and Overlap Error for 0.5 and can run in standard computer just for a couple second. It makes the template and the original image has a little similarity.

Classification of Bird Based on Face Types Using Gray Level Co-Occurrence Matrix (GLCM) Feature Extraction Based on the k-Nearest Neighbor (K-NN) Algorithm

Indonesia is one of the countries with a large number of fauna wealth. Various types of fauna that exist are scattered throughout Indonesia. One type of fauna that is owned is a type of bird animal. Birds are often bred as pets because of their characteristic facial voice and body features. In this study, using the Gray Level Co-Occurrence Matrix (GLCM) based on the k-Nearest Neighbor (K-NN) algorithm. The data used in this study were 66 images which were divided into two, namely 55 training data and 11 testing data. The calculation of the feature value used in this study is based on the value of the GLCM feature extraction such as: contrast, correlation, energy, homogeneity and entropy which will later be calculated using the k-Nearest Neighbor (K-NN) algorithm and Eucliden Distance. From the results of the classification process using k-Nearest Neighbor (K-NN), it is found that the highest accuracy results lie at the value of K = 1 and at an degree of 0 ° of 54.54%.

A File Encoding Using A Combination of Advanced Encryption Standard, Cipher Block Chaining and Stream Cipher In Telkom Region 4 Semarang

The increase in significant advances in information technology greatly provides comfort and convenience in managing data. This convenience is what makes people who are not responsible for using it as a crime such as hacking, cracking, phishing, and so on. In Telkom Region 4 Semarang, there is a container where there are important company data such as customer data. Customer data is very important and the contents of the data must be kept confidential. The company has experienced significant losses due to information leakage due to negligence in the last 5 years. For this reason, data security is necessary so that data is safe and is not misused. This study applies the Advance Encryption Standard algorithm - Cipher Block Chaining (AES-CBC) and Stream cipher in order to secure data so as to reduce the risk of data theft by telecom subscribers. Based on the average avalanche effect value of AES-CBC and a stream cipher of 49.34%, this shows that the AES-CBC and Stream Cipher encrypted files are difficult to crack so that data confidentiality is well maintained.

Securitary Text on Images with RC-128 Bit Synthric Key Encryption

The main purpose of using cryptography is to provide the following four basic information security services. One of the purposes of cryptography is secrecy. Confidentiality is the fundamental security service provided by cryptography. This is a security service that stores information from unauthorized persons. Confidentiality can be achieved through a variety of ways ranging from physical security to the use of mathematical algorithms for data encryption. Vernam cipher is a stream cipher where the original data or plain with 8x8 block operation. Experimental results prove that RC4 can perform encryption and decryption with a fast execution process. In this study used a processor with 8GB of RAM. The encryption result of the text used yields the average encryption time and decryption average of 2 second.

E-Report System to Help Monitor Student Academic Progress Using Forward Chaining for Grade Promotion According to Student Development Level

The COVID-19 pandemic that has occurred in the world and Indonesia is one of the affected countries. To limit the rate of transmission of COVID-19, the Ministry of Education issued regulations relating to online schools. With this online school, both parents and teachers need media to be able to monitor students' academic progress as long as online schools are implemented. Therefore, we need a system that can assist teachers and parents in monitoring students' academic progress. In this study, an e-report was designed by incorporating the components of students' academic aspect and students' character aspect. This system is supported by a decision support system using forward chaining to determine the feasibility of a grade increase according to the level of development of the student. The output of this system is student grade reports, advice given to parents and grade promotion decisions based on academic and character aspect.

Designing The Concepts - Framework & The Maturity Level Of Smart Pondok Pesantren (Islamic Boarding Schools)

- The development of information technology and significant progress is happening today, where changes need to face increasingly high global competition. Islamic boarding schools are the centre of change, where boarding schools must develop four important factors: human resource development, information technology, culture and e-spirituality. This article is about developing smart city 3.0 and 5.0, where the resulting framework and methods can apply to Islamic boarding schools. Our research object is Islamic boarding schools, and in this place, we do community service. This article's results are the framework and the maturity level of smart Islamic boarding schools, where there are three indicators (people-culture, technology-business, implementation-global goals) and three important levels (stage 1-the foundation, stage 2-good foundation, stage 3- great foundation), which are the basis for developing a smart islamic boarding school. Moreover, this article is version 1.0, which in its development will extend to the application. An application Si-PenO (Online registration information system) completed at the Askhabul Kahfi Islamic boarding school as proof of applying the concept we created in this article. This change is needed to face globalization, and change is a good thing if it does systematically. Furthermore, this article will continue to develop in versions 2.0 and 3.0 and applications that we will implement in Islamic boarding schools.

CNN for Image Identification of Hiragana Based on Pattern Recognition using CNN

Hiragana is one of the letters in Japanese. In this study, CNN (Convolutional Neural Network) method used as identication method, while he preprocessing used thresholding. Then carry out the normalization stage and the filtering stage to remove noise in the image. At the training stage use maxpooling and danse methods as a liaison in the training process, wherea in testing stage using the Adam Optimizer method. Here, we use 1000 images from 50 hiragana characters with a ratio of 950: 50, 950 as training data and 50 data as testing data. Our experiment yield accuracy in 95%.

Improvement of Accuracy and Handling of Missing Value Data in the Naive Bayes Kernel Algorithm

The lost impact on the research process, can be serious in classifying results leading to biased parameter estimates, statistical information, decreased quality, increased standard error, and weak generalization of the findings. In this paper, we discuss the problems that exist in one of the algorithms, namely the Naive Bayes Kernel algorithm. The Naive Bayes kernel algorithm has the disadvantage of not being able to process data with the mission value. Therefore, in order to process missing value data, there is one method that we propose to overcome, namely using the mean imputation method. The data we use is public data from UCI, namely the HCV (Hepatisis C Virus) dataset. The input method used to correct the missing data so that it can be filled with the average value of the existing data. Before the imputation process means, the dataset uses yahoo bootstrap first. The data that has been corrected using the mean imputation method has just been processed using the Naive Bayes Kernel Algorithm. From the results of the research tests that have been carried out, it can be obtained an accuracy value of 96.05% and the speed of the data computing process with 1 second.

A Video Quality Testing : Review of Human Visual Aspect

Various types of video player applications have been widely used by the community. The emergence of the latest version and a variety of features make people need to make a choice to use a video player application with a good visual level. The type of video that is often played is a file with an MP4 extension. This file type is not heavy but is usually intended for long file durations such as movies. In this paper, we will use a dataset in the form of a movie file with an MP4 extension. The video player applications used include VLC, Quick time, Potplayer, KMPLayer, Media Player Classic (MPC), DivX Player, ACG Player, Kodi, MediaMonkey. Through various empirical calculations, such as Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), Structutral Similarity Index Measurement (SSIM), Threshold F-ratio, Visual Signal to Noise Ratio (VSNR), Visual Quality Metric (VQM), and Multiscale - Structutral Similarity Index Measurement (MS-SSIM) has analyzed the visual capabilities of each video player application. Experimental results prove that the KMPlayer application gets the best visual results compared to other selected applications.

Dies Process Performance Improvement Maintenance With e-DMIS Based on Iot Technology

Improvement between departments within the company requires a mutually supportive system so that cooperation occurs between interrelated departments. This requires effort and commitment that needs to be supported by related share holders so that the occurrence of lost time during the production process can be minimized so that the planned time runs effectively and efficiently in increasing productivity. The difficulty in supervising and controlling the production process is the reason for knowing the abnormality in the process of replacing the dies and controlling the process of replacing printing equipment or dies for the Stamping process still using a manual system and the process recording system still using paper that is prone to loss and is engineered irresponsibly . The method used to create an electronic Dies replacement monitoring system by collecting problem data, comparing manual systems with several experiments and testing tools, using IoT in the form of PLC, HDMI as a tool for online communication. The DIMS monitoring system can be used to monitor and provide initial information when there is a request for the Dies replacement process so that replacement requests and needs in the process can be carried out immediately because they can be detected early.