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%.
Diabetes is one of the top three killers in Indonesia. According to the 2014 sample enrollment survey, the number of people with diabetes is increasing year by year. This is because the diagnosis of the disease is delayed. Also unhealthy lifestyle. In an era of fast and efficient technological advancement, this is a very good thing for advancement in various fields. More and more fields of knowledge are developing, one of which is expert systems. An expert system is a software or computer program that matches the ability of an expert, meaning that it can match humans with special abilities that ordinary people cannot solve. Expert systems aim to solve specific problems, such as in fields such as medicine, education, etc. This expert system takes as inputs several variables consisting of transient blood sugar (GDS), fasting blood sugar (GDP), frequent hunger, thirst, weight loss, and urine (BAK), the method used by the author is Fuzzy Tsukamoto. This Tsukamoto method states that every result of IF-Then must be described as a fuzzy set with an immutable or monotonic membership function, and uses PHP for programming. The results obtained in the study conducted by the authors were in the form of an expert system that detects diabetes and obtains results with 94% accuracy.
Penggunaan masker mengakibatkan wajah seseorang sulit dikenali oleh sistem keamanan pada saat penggunaan fitur Face Recognition. Deteksi penggunaan masker akan berguna bagi satgas Covid-19 yang memantau masyarakat untuk selalu patuh dalam aturan penggunaan masker. Dalam penelitian ini, deteksi penggunaan masker pada wajah menggunakan Metode Principal Component Analysis (PCA) dan K-Nearest Neighbor (KNN). Data yang digunakan berupa citra wajah yang menggunakan masker dan tidak bermasker. Kemudian dilakukan tahap prepocessing dengan melakukan cropping, penghapusan latar belakang citra, segmentasi dengan menggunakan metode thresholding, ekstraksi ciri dan terakhir mengklasifikasinya menggunakan KNN. Berdasarkan hasil pengujian sistem, didapatkan akurasi sebesar 90% dengan jumlah citra sebanyak 180 citra latih dan 20 citra uji.
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.
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.
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