Facial recognition is one of the most popular way to authenticate user into a system. This method is preferable considering the tendency of users for using the same password across multiple sites which made the user has already made his own account securities in vulnerable states. Using biometrics might supply solutions to solve this problem and facial recognition is one of the best biometric methods can be apply as a digital account security solution. This study to design a prototype system implementing facial recognition to verify users to measure how accurate these methods are. The method used here is Viola-Jones for face detection, Eigenface and Haar feature for face recognition from the OpenCV. The system was designed in Java. Based on the test results from the system designed, system can recognize user face with 100% accuracy if faces are shot in a well desirable condition. The system is able to recognize the user's face with various expressions including with or without glasses. However, the system has difficulty in recognizing user’s face in facing up, down, sideways position or blocked by accessories or body parts such as hands. After some experiment, it was proven that the system designed is accurate, reliable and safe enough to be implemented to digital authorization process.

In general, high school students view mathematics as a difficult and boring subject. In addition to students, teachers also have difficulty in conveying material for the introduction of majors for lectures. The lack of student interest in learning mathematics is a problem for every high school teacher. This happens if the teacher's ability to use conventional learning methods such as from textbooks and explanations from the teacher only. Therefore, it is necessary to strive in the process of learning mathematics to be more interesting, more interactive and fun. This issue also applies to science materials that require understanding. For this reason, teaching aids are needed that are used to stimulate students' responsiveness in studying material according to their scientific competence.  This service aims to apply knowledge and technology by conducting training in making and tutorials on mathematics learning media so that it can increase understanding and attract students' interest in learning and help improve the quality of teacher education and teaching at Husni Thamrin High School.

Beberapa citra digital membutuhkan privasi dan kerahasiaan, seperti citra medis, citra diagnosa medis jarak jauh, citra rahasia melalui komunikasi internet, atau citra rahasia kemiliteran. Salah satu cara untuk mengamankan informasi di dalam citra digital adalah dengan melakukan pengacakan (scrambling). Penelitian ini mengacak nilai piksel citra digital dengan mengubah nilai piksel dari sistem bilangan desimal menjadi bilangan basis empat (kuartener), kemudian mengurai (dekomposisi) keempat bit kuartener dan melakukan pengacakan terhadap keempat posisi bit berdasarkan pada bilangan acak yang dihasilkan oleh algoritma logistic mapping, kemudian bit hasil pengacakan digabungkan kembali (rekombinasi) untuk menghasilkan nilai piksel baru. Logistic mapping merupakan penghasil bilangan acak yang mampu menghasilkan deretan bilangan yang acak berdasarkan nilai kunci ???µ (3.569945 ???µ 4) dan nilai awal x0 (0 x0 1). Hasil penelitian ini dapat melakukan pengacakan terhadap citra digital dengan dekomposisi dan rekombinasi nilai piksel berdasarkan pada nilai acak yang dihasilkan oleh algoritma logistic mapping. Hasil pengujian menunjukkan bahwa pasangan kunci-1 (???µ1, x1) memiliki sensitivitas paling tinggi dalam mengacak citra, kemudian diikuti oleh pasangan kunci-2 (???µ2, x2), pasangan kunci-3 (???µ3, x3) dan pasangan kunci-4 (???µ4, x4).

Modern smartphone has been society’s lifestyle where every smartphone has a high quality digital camera with all the digital image processing feature. One of those features are face detection. Face detection is the most basic process of any face processing operations. Most digital images are stored in the form of RGB (Red, Green, Blue) data. In this research, detection of human face features is done by using different RGB values in digital images. After applying skin tone color segmentation on digital images, detection area will be optimized using human head properties by eliminating non-human face skin tone area. The experiment shows that the detection is mostly accurate for images but there is issue on low light face skin color captured by digital cameras. From the experiment of our model using 10 sample face images, face can be detected on 9 of them, while in 1 image, the face cannot be detected at all because of low light condition.

One of the main forms of information and entertainment presentation is in the form of on-demand audio content or often referred as podcast. The problem met is the difficulty of users to find podcasts that match their preferences among hundreds of thousands of podcasts that are now available on the internet. Besides the number of podcasts, the incompletion of podcasts metadata is one of the problems in developing a recommendation system in general.This system is designed by utilizing N-Gram and Term Frequency to generate queries from the title and description of a podcast which will then be used to find other podcasts that are similar by utilizing Cosine Similarity calculations. The testing phase is done through by testing the system using nDCG calculations to determine the relevance level of the recommendation results. From the results, the average value of the relevance level of podcast recommendations is 53.8% and the best average f1-score of the 10 best categories is 14%.