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"The cloud is an outstanding platform to deal with functionally equivalent services which are exponentially increasing day-by-day. The selection of services to meet the client requirements is a subtle task. The services can be selected by ranking all the candidate services using their network and non-network Quality-of-Service (QoS) parameters, which is formulated as a NP hard optimization problem. In this paper, we proposed a linear discriminant analysis (LDA) based a four level matching model for service selection based on QoS parameters, which includes description matching of a service, matchmaking phase, LDA-based QoS matching and ranking. The LDA-service selection agent is deployed on each cloud to classify services into classes and rank the services based on the aggregate QoS value of each service. Finally, the test results show the efficiency in service selection with minimal discovery overhead, significant reduction in the computation time and the number of candidate services to be considered."

"The cloud is an outstandingplatform to deal with functionally equivalent services which are exponentiallyincreasing day-by-day. The selection of servicesto meet the client requirements is a subtle task. The services can be selected byranking all the candidate services using their network and non-network Quality-of-Service (QoS) parameters, which is formulated as a NP hard optimization problem. In this paper, weproposed a linear discriminant analysis (LDA) based a four level matching model for service selection based on QoS parameters,which includes description matching of a service, matchmaking phase, LDA-based QoS matching and ranking. The LDA-serviceselection agent is deployed on each cloud to classify services into classes andrank the services based on the aggregate QoS value of each service. Finally,the test results show the efficiency in service selection with minimaldiscovery overhead, significant reduction in the computation time and thenumber of candidate services to be considered."

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Pada karya tulis ini dijelaskan sebuah proses broadcasting menggunakan solusi aplikasi-aplikasi open-source dan implementasi low-cost cloud services yang fleksibel. Solusi infrastruktur live broadcasting secara komersial memiliki keterbatasan seperti cost mulai dari biaya perangkat belum lagi perangkat tersebut dapat bersifat proprietary. Konten diproses encode dengan standar H.264 yang ditransmisikan dengan protokol RTMP/HLS sebagai fungsi playback delivery hingga ke perangkat viewer. Dijelaskan juga proses capture dari konten yang diinginkan hingga menjadi media standar H.264 dengan encoder H.264. Dijelaskan pula unsur-unsur dari H.264 seperti konfigurasi Profil H.264 dan Level serta metrik lain seperti bitrate dan keyframe interval. Konten H.264 tersebut akan ditransmisikan dengan protokol RTMP/HLS dengan implementasi server RTMP/HLS menggunakan beberapa solusi cloud service. Lalu dengan menggunakan video player framework untuk mendukung playback pada berbagai macam viewer device. Open Broadcasting Software (OBS) digunakan sebagai implementasi encoder H.264 seperti X264 dan NVENC. Untuk implementasi server RTMP/HLS digunakan Simple-RTMP-Server (SRS) pada Google Cloud Platform atau dapat digunakan layanan live streaming cloud service dari Twitch.tv sebagai fungsi server RTMP/HLS. Konten pada server RTMP/HLS dapat ditonton dengan implementasi berbagai playback framework seperti VLC Media Player dan HTML5 HLS.JS. Berbagai solusi yang telah dibuat cukup stabil dengan standar deviasi dibawah 8% untuk usage seperti CPU, RAM dan GPU pada Host dan Server. Serta kestabilan bitrate dengan standar deviasi sekecil 400kbps dari Host serta Server. 

 

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This paper describes a live broadcasting solution with open-source applications and low-cost cloud services. Commercial live broadcasting solutions have several drawbacks in cost and flexibility. Cost of proprietary hardware and software in a confined environment. Paper also describes the process capturing, content organizing and processing with H.264 encoder. Content will be encoded in H.264 standard which transmitted with RTMP/HLS protocol for playback delivery. H.264 also has detailed configuration such as H.264 Profiles and Levels alongside other metrics such as bitrate and keyframe interval. The H.264 encoded content will be transmitted with RTMP/HLS protocol which implemented in a RTMP/HLS server from a cloud service. A video player framework will be used to support playback over a lot of devices. Open Broadcasting Software (OBS) used to implement H.264 encoders such as X264 and NVENC. RTMP/HLS server implemented with Simple-RTMP-Server (SRS) on Google Cloud Platform, or a live streaming cloud service from Twitch.tv can be used instead as a RTMP/HLS server and delivery. Content from RTMP/HLS server can be played with several implementation of a playback framework such as VLC Media Player or HTML5 HLS.JS. Solutions made have a standard deviation under 8% for CPU, RAM and GPU usage in the Host and Server. Bitrate stability is also present with standard deviation as low as 400kbps in the Host and Server. 

 

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"Bahasa isyarat merupakan bahasa yang mengutamakan komunikasi visual, pengguna bahasa ini menggunakan orientasi, bentuk, dan gerakan tangan, lengan, tubuh, serta ekspresi wajah untuk mengungkapkan pikiran mereka. Para tunawicara menggunakan bahasa isyarat untuk mengatasi keterbatasan mereka dalam berkomunikasi. Namun, berkomunikasi menggunakan bahasa isyarat seringkali menyulitkan dan membatasi komunikasi dengan orang lain khususnya orang normal yang umumnya tidak memahami bahasa isyarat. Untuk mengatasi hal ini, diperlukan upaya penerjemahan bahasa isyarat tersebut menjadi bahasa yang umum atau mudah dipahami oleh lawan bicara."

"Perkembangan teknologi informasi saat ini sudah mengalami kemajuan yang sangat pesat dalam jangka waktu yang cukup singkat, hal itu memicu pengembangan aplikasi yang memanfaatkan sistem cloud computingkarena mampu mengefisiensikan pengeluaran biaya dan sumber daya yang digunakan untuk aplikasi. Pada penelitian ini dilakukan pengujian performansi pada SIMPLE-O yang diterapkan pada cloud computing. Dari hasil dua pengujian performansi SIMPLE-O didapatkan bahwa untuk pengujian dengan metode GET yaitu pada saat pengguna hanya mengakses halaman utama dari aplikasi, performansi SIMPLE-O pada layanan cloud computing lebih baik dibandingkan dengan shared hosting, dimana cloud computing mengalami error sebesar 1,70 % dari 6000 request yang terkirim dengan response time rata-rata sebesar 32,62 s. Sementara shared hosting mengalami error sebesar 18,04 % dari 6000 request yang terkirim dengan response time rata-rata sebesar 36,27 s. Namun untuk pengujian dengan metode POST yaitu pada saat aplikasi SIMPLE-O melakukan proses penilaian otomatis terhadap jawaban yang dikirimkan, performansi SIMPLE-O pada layanan cloud computing sedikit lebih buruk dbandingkan dengan shared hosting, dimana cloud computing mengalami error sebesar 1,60 % dari 1000 request yang terkirim dengan response time rata-rata sebesar 63,95 s. Sedangkan shared hosting mengalami error sebesar 0,30 % dari 1000 request yang terkirim dengan response time rata-rata sebesar 52,67 s.

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The development of information technology have progress very rapidly in a relatively short period of time, it triggers the development of applications that take advantage of cloud computing systems because have more efficient cost and resource for application.From the results of two performance testing SIMPLE-O, for the testing with GET method it was found that when the user only access the main page of the application, the performance of SIMPLE-O in cloud computing services is better than shared hosting, where cloud computing has an error by 1.70% from the 6000 request that sent with average response time in 32,62 s. While shared hosting has an error by 18.04% from the 6000 request that sent with average response time in 36,27 s. However, for testing with POST method, that when the application SIMPLE-O doing aautomatic process to assessment the exam’s answer from the user, the performance of SIMPLE-O in cloud computing services slightly worse than shared hosting, where cloud computing which has an error by 1.60% from 1000 request that sent with average response time in 63,95 s. While shared hosting has an error by 0.30% from 1000 request that sent with average response time in 52,67 s."

"ABSTRAKSistem Call Center adalah bentuk penerapan Customer Relationship Management yang dapat meningkatkan hubungan Perusahaan dengan Pelanggan. Namun untuk membangun Sistem ini diperlukan biaya yang tinggi. Sistem Call Numbering menggunakan Platform Cloud merupakan bentuk penerapan Cloud Computing yang berfungsi menyerupai Call Center dan memerlukan biaya yang terjangkau. Dengan dibangunnya Sistem Call Numbering menggunakan Platform Cloud untuk Perusahaan Menengah Kebawah, maka hubungan dengan Pelanggan akan semakin terbina dengan baik. Karya ilmiah ini mengusulkan Pengembangan Aplikasi dan Analisis Bisnis Call Numbering berbasis Cloud. Pembangunan Sistem dilakukan menggunakan platform Web Hosting, Database Mangement System, dan Interactive Voice Response didalam Cloud dengan output berupa Aplikasi Web. Sedangkan Analisis Sistem menggunakan Tools Strategi “Samudra Biru”. Sistem Call Numbering menggunakan Platform Cloud yang telah dibangun memenuhi syarat kelayakan setelah diuji kualitasnya dengan menggunakan metode Pengambilan Data melalui Angket. Kemudian Sistem dianalisis mengunakan Tools Strategi “Samudra Biru” yang terdiri Analisis Kerangka Kerja Empat Langkah, Analisis Hapuskan-Kurangi-Tingkatkan-Ciptakan, Analisis Strategi Kanvas, Analisis Pemetaan Pioneer-Migrator-Setler, Analisis Rangkaian Strategi “Samudra Biru”, dan Analisis Tiga Tingkatan Konsumen. Hasil analisis menggunakan Tools Strategi “Samudra Biru” menyimpulkan bahwa Sistem Call Numbering menggunakan Platform Cloud memiliki keunggulan efisiensi biaya, peningkatan mobilitas, dan jaminan keamanan yang lebih baik dibandingkan dengan Sistem Call Center, Sistem ini juga dapat bertransformasi menjadi Call Numbering Mobile dan siap untuk dikomersialkan.

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ABSTRACTCall Center System is a Customer Relationship Management application form which can increase the Company's relationship with the customer. However, this system is necessary to build a high cost. Call Numbering system using Platform Cloud Cloud Computing is a form of application that functions like a call center and an affordable cost. By Call Numbering System built using Cloud Platform for Midsize Company Move Down, then the relationship with the customer will be nurtured well. This paper proposes Application Development and Business Analysis Cloud based Call Numbering. System development is done using the platform Web Hosting, Database Mangement System, and Interactive Voice Response in the Cloud with output in the form of Web Applications. While the use of System Analysis Tools Strategy "Blue Ocean". Call Numbering system using Cloud platform that has been built to meet eligibility requirements after quality tested using the method of data collection through questionnaire. Then analyzed using the System Tools Strategy "Blue Ocean" which consisted Four Steps Framework Analysis, Analysis Eliminate-Reduce-Raise-Create, Canvas Strategy Analysis, Analysis Mapping Pioneer-Migrator-Setler, Analysis of Strategies series "Blue Ocean", and Analysis of Three Consumer level. The analysis using the Tools Strategy "Blue Ocean" concluded that the Call Numbering System using Cloud Platform has the advantage of cost efficiency, improved mobility, and security better than the Call Center System, this system can also be transformed into Call Mobile Numbering and ready for commercialization."