Desain dan Implementasi Digital Rights Management pada Media Streaming dengan Menggunakan Algoritma Kriptografi XOR

ABSTRAKSI: Dalam dunia kriptografi, konten digital termasuk salah satu jenis pesan. Konten digital yang berupa visual maupun audio yang berbayar sudah banyak dibajak oleh pihakpihak yang menginginkan konten tersebut menjadi sebuah konten yang gratis. Banyak recording company atau production house yang mengalami kerugian yang cukup besar dikarenakan oleh pembajakan yang dilakukan pihak-pihak yang tidak bertanggung jawab. Kriptografi itu sendiri adalah ilmu atau seni untuk untuk menjaga keamanan pesan. Kriptografi akan mengenkripsi konten digital tersebut ketika server mengirimkan pesan, kemudian akan mendekripsikannya ketika pesan tersebut sampai ke client. Hal ini dilakukan untuk menghindari dari pihak yang ingin membajak atau mengetahui isi pesan tersebut. Digital rights management atau sering juga disebut DRM adalah salah satu upaya untuk menghentikan pembajakan. DRM dapat berperan untuk memberikan pilihan untuk melakukan pengontrolan dalam penggunaan hak cipta dari sebuah konten digital. Apabila DRM dipadukan dengan ilmu kriptografi, konten digital akan susah dibajak. Pada tugas akhir ini diimplementasikan DRM yang dipadukan dengan ilmu kriptografi pada konten digital yang berfungsi sebagai sistem keamanan pada proses pengiriman dan penerimaan pesan. DRM pada penelitian ini digunakan untuk mengamankan konten digital yang bersifat streaming. Adapun parameter evaluasi hasil implementasi adalah bandwitdh usage dan error rate. Serial key dan authentification key dirancang untuk membangun sistem kerja DRM. Kedua key ini memberikan kemampuan kepada sebuah server untuk mengenali jenis client yang menggunakan fasilitas yang diberikan oleh server tersebut. Fasilitas yang diberikan kepada setiap tipe client akan berbeda sesuai dengan tipe client itu sendiri.Kata Kunci : Cryptography, Digital Rights Management, Media Streaming.ABSTRACT: In the world of cryptography, digital contents can be defined as a form of message. Digital video and audio contents has became object of piracy for certain parties who willing to make the paid contents to be free. Many record companies or production houses suffer significant loss from their pirated contents done by irresponsible people. Cryptography itself defined as knowledge or art of securing a data and messages. Through cryptography, we can encrypt digital content when the server start to send message, then it will be decrypted as soon as it reached the client. This system has been done to avoid people to see the information of message. Digital Right Management or DRM is one of effort to stop the piracy. DRM has role to give choices to control the use of copyright of certain digital content. If the DRM has combined with cryptography principals, piracy would be much harder to be done. In this final assignment, DRM would be implemented as combination for cryptography toward digital content which functioned as security system within the distribution process of the digital content itself. DRM in this assignment will be used for secure the streaming digital contents. Evaluation parameter of the implementation result would be bandwidth usage and error rate. Serial key and authentification key were made to build DRM system. Both of these key have ability to a server for knowing the type of client which is using the facilities from server. Facilities for clients will different for each type of client.Keyword: Cryptography, Digital Rights Management, Media Streamin

Analysis Simple Additive Weighting And Genetic Algorithm For Traffic Management System

Bandung Tourism is currently developing rapidly, where every year the number of tourist attractions has increased. The convenience provided by today's technology such as Google Maps is still lacking in helping tourists. Until now, software that is useful for determining the route by selecting tourist attractions is still small. The problem of tourists in making a tour include traffic jams, distances and tourist attractions to be visited. Application development to help find the best route is very much needed by tourists. The best route search optimization can be done using Genetic Algorithms. Genetic Algorithms are often used in determining the route because based on previous research it produces optimal results. Weighting for a path can be done using the Simple Additive Weighting Algorithm. In this study optimization of route selection is done in the hope that it can provide solutions to tourists in route selection

Traffic Flow Prediction Using SUMO Application with K-Nearest Neighbor (KNN) Method

In Indonesia, the density of traffic flow occurs at the time of leaving and returning to work, long holidays or national holidays such as the end of the year (New Year). This annual routine activity is mostly carried out especially in big cities in Indonesia such as Bandung. Because Bandung is a city that has a lot of tourism, Bandung is therefore always the center of visitors to enjoy weekends or long holidays. So from this problem, we want to create a traffic prediction application that can help to solve congestion problems that have become an annual routine. The several types of vehicles used in the prediction are private cars, motorcycles, taxis, public transportation, large buses, mini buses, and mini trucks. Research conducted using the K-Nearest Neighbor method is a prediction of short-term traffic flow on Jl. Riau Bandung. The input used in making predictions is historical data on the number of vehicles going on Jl. Riau Bandung. The output generated from the use of the K-Nearest Neighbor method is the level of the jam class that runs on Jl. Riau Bandung in 2018 used a simulation on the SUMO (Simulation of Urban Mobility) application. The resulting performance of KNN with k = 3 has an accuracy of 99.21%, k = 5 has an accuracy of 99.60%, and k = 7 has an accuracy rate of 99.21% on 90% training data and 10% testing data

Secure E-voting System by Utilizing Homomorphic Properties of the Encryption Algorithm

The use of cryptography in the e-voting system to secure data is a must to ensure the authenticity of the data. In contrast to common encryption algorithms, homomorphic encryption algorithms had unique properties that can perform mathematical operations against ciphertext. This paper proposed the use of the Paillier and Okamoto-Uchiyama algorithms as two homomorphic encryption algorithms that have the additional properties so that it can calculate the results of voting data that has been encrypted without having to be decrypted first. The main purpose is to avoid manipulation and data falsification during vote tallying process by comparing the advantages and disadvantages of each algorithm

Selection of Bandung City Travel Route Using The FLOYD-WARSHALL Algorithm

The rapid development of information and technology, the city of Bandung tourism has also increased. However, tourists who visit the city of Bandung have problems in a limited time when visiting Bandung tourist attractions. Traffic congestion, distance and the number of tourist destinations to be a problem in tourists travel. The optimal route selection is the solution to the problem. Congestion and distance data are processed using the Simple Additive Weighting (SAW) method. Route selection uses the Floyd-Warshall Algorithm. In this study, the selection of the best route gets the smallest weight with a value of 5.127 from the Algorithm process. Based on testing, from two to five tourist attractions get an average calculation time of 3 to 5 seconds. This application is expected to provide optimal solutions for tourists in the selection of tourist travel routes

Perbandingan Metode Clustering Menggunakan Metode Single Linkage dan K - Means pada Pengelompokan Dokumen

Penyebaran berita saat ini semakin tersebar  luas semenjak perkembangan dunia internet yang semakin pesat. Perkembangan dunia internet membuat berita yang  tersebar semakin beragam dan berjumlah  sangat besar. Pembaca berita akan kesulitan untuk memperoleh berita yang diinginkan  jika berita tersebut tidak terkelompok dengan baik. Dan jika harus dikelompokkan secara manual membutuhkan waktu yang sangat lama. Oleh sebab itu, Clustering menjadi solusi untuk mengatasi masalah tersebut. Clustering akan  mengelompokkan dokumen berita berdasarkan  tingkat kemiripan dari dokumen tersebut. Metode Single Linkage merupakan metode pengelompokan hierarchical clustering. Metode Single Linkage mengelompokkan dokumen didasarkan pada jarak terdekat antar dokumen. Komputasi Single Linkage merupakan komputasi yang mahal dan kompleks.  Sedangkan metode K-means merupakan metode pengelompokan partitioned clustering. Metode K-means mengelompokkan dokumen didasarkan pada jarak terdekat dengan centroid-nya. K-Means merupakan  metode pengelompokan yang sederhana dan dapat digunakan dengan mudah. Tetapi pada jenis data tertentu, K-means tidak dapat memberikan segementasi data dengan baik, sehingga kelompok yang terbentuk tidak murni data yang sama. Metode pengujian yang digunakan untuk mengukur kualitas cluster adalah Silhouette Coefficient dan Purity. Berdasarkan hasil pengujian yang dilakukan, dapat disimpulkan, bahwa metode Single Linkage memiliki performansi yang lebih baik dibandingkan dengan metode K-means. Nilai silhouette coefficient Single Linkage selalu lebih unggul dibandingkan dengan  K-Means. Pertambahan jumlah dokumen membuat nilai silhouette coefficient single linkage semakin kecil sedangkan K-means terkadang menghasilkan nilai yang negatif. Untuk nilai purity, Single Linkage selalu bernilai 1 sedangkan K-Means tidak pernah bernilai 1. Hasil pertambahan jumlah cluster dan jumlah dokumen memberikan pengaruh terhadap nilai silhouette coefficient dan purity. Hal ini berarti single linkage selalu menghasilkan dokumen yang sama, sedangkan K-means masih bercampur dengan dokumen yang lain

Implementasi Digital Rights Management pada Media-Streaming Sebagai Pelindung Data Digital

Pembajakan pada konten digital saat ini sudah menyebabkan kerugian pada beberapa perusahaan recording company atau production house. Digital Rights Management (DRM) merupakan salah satu upaya untuk menghentikan pembajakan. DRM dapat berperan untuk memberikan pilihan untuk mengkontrol dalam penggunaan hak cipta dari sebuah konten digital. Pada system ini, DRM diintegrasikan dengan algoritma kriptografi untuk mengamankan pesan khususnya dalam pengiriman dan penerimaan data streaming. Sistem serial key dan authentication key dirancang untuk membangun system kerja DRM. Kedua kunci ini memberikan kemampuan kepada sebuah server untuk mengenali jenis client yang menggunakan fasilitas yang diberikan oleh server. Fasilitas yang diberikan kepada setiap tipe client berbeda sesuai dengan tipe client itu sendiri. Sistem DRM dapat dibentuk dengan menerapkan system yang dihasilkan dalam penelitian ini yang membutuhkan dua kunci tambahan sebagai media verifikasi client. Pemilahan jenis pengguna dan data berdasarkan kunci serial dan kunci autentikasi dapat berjalan 100% berdasarkan pengujian fungsional. Jumlah frame maksimum yang dapat diacak dalam sistem ini adalah 2070 frame. Hasil kemiripan dari hasil pengembalian data acak didapatkan dengan menyebarkan kuisioner dan mendapatkan nilai 2,59 dari skala 4 yang berarti hasil pengembalian data dapat dikatakan mirip

Pedestrian Detection System using YOLOv5 for Advanced Driver Assistance System (ADAS)

The technology in transportation is continuously developing due to reaching the self-driving vehicle. The need of detecting the situation around vehicles is a must to prevent accidents. It is not only limited to the conventional vehicle in which accident commonly happens, but also to the autonomous vehicle. In this paper, we proposed a detection system for recognizing pedestrians using a camera and minicomputer. The approach of pedestrian detection is applied using object detection method (YOLOv5) which is based on the Convolutional Neural Network. The model that we proposed in this paper is trained using numerous epochs to find the optimum training configuration for detecting pedestrians. The lowest value of object and bounding box loss is found when it is trained using 2000 epochs, but it needs at least 3 hours to build the model. Meanwhile, the optimum model’s configuration is trained using 1000 epochs which has the biggest object (1.49 points) and moderate bounding box (1.5 points) loss reduction compared to the other number of epochs. This proposed system is implemented using Raspberry Pi4 and a monocular camera and it is only able to detect objects for 0.9 frames for each second. As further development, an advanced computing device is needed due to reach real-time pedestrian detection.  The technology in transportation is continuously developing due to reaching the self-driving vehicle. The need of detecting the situation around vehicles is a must to prevent accidents. It is not only limited to the conventional vehicle in which accident commonly happens, but also to the autonomous vehicle. In this paper, we proposed a detection system for recognizing pedestrians using a camera and minicomputer. The approach of pedestrian detection is applied using object detection method (YOLOv5) which is based on the Convolutional Neural Network. The model that we proposed in this paper is trained using numerous epochs to find the optimum training configuration for detecting pedestrians. The lowest value of object and bounding box loss is found when it is trained using 2000 epochs, but it needs at least 3 hours to build the model. Meanwhile, the optimum model’s configuration is trained using 1000 epochs which has the biggest object (1.49 points) and moderate bounding box (1.5 points) loss reduction compared to the other number of epochs. This proposed system is implemented using Raspberry Pi4 and a monocular camera and it is only able to detect objects for 0.9 frames for each second. As further development, an advanced computing device is needed due to reach real-time pedestrian detection

Personalized Route Recommendation Using F-AHP-Express

The route recommendation system helps the driver find the best route between origin and destination. A recommendation system often suggests its decision without considering some criteria. This paper proposes a multicriteria decision-making method, namely Fuzzy—Analytic Hierarchy Process—Express (F-AHP-Express) for recommending a personal travel route from several alternative routes. It is calculated based on the driving preferences of a driver and road conditions for each road segment. We compare the F-AHP-Express to others; Fuzzy—Analytic Hierarchy Process (F-AHP) and Fuzzy—Analytic Hierarchy Process—Technique for Others Preference by Similarity to Ideal Solution (F-AHP-TOPSIS), for its recommendation results, time processing, agility, and complexity. Our experiments show that F-AHP-Express could deliver similar recommendation results compared to other methods, and it is additionally the fastest method. F-AHP-Express is 45% and 23% faster than F-AHP and F-AHP-TOPSIS, respectively. F-AHP-Express not only has the fastest time processing among the others but also has the least judgments in agility testing. It needs 37.5% and 16.67% fewer judgments from F-AHP and F-AHP-TOPSIS, respectively. Moreover, AHP-Express has a complexity of O(n), meanwhile, the others have O(n2) for their complexity. Thus, the results show that F-AHP-Express is the best method for recommending a personal route