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"Tahun 2011 merupakan era baru teknologi komputasi awan (Cloud Computing). Teknologi komputasin awan adalah solusi teknologi informasi dan komunikasi yang memberikan kesempatan kepada konumdn untuk dapat menyewa layanan teknologi dari penyedia (provider). Penyedia memberikan jasa pengelolaan infrastruktur, platform, dan aplikasi jasa teknologi informaao sehingga mudahkan konsumen tanpa harus berinvestasi. Hanya saja, ketika media baik media masaa dan media online menyebarluaskan informasi tentang teknologi komputasi awan, yang terjadi adalah penggunaan istilah-istilah teknologi yang beradanpada level pakar (expert sphere) yang sulit dimengerti oleh masyarakat luas. Dengan menggunakan model Arnold Pacey yang menjelaskan adanya dua lapian :pakar (expert sphere) dan penggunan(user spehere) dalam pemanfaatan teknologi, penelitian ini memperlihatkannadanya kecenderungan penggunaannbahasa dan tulisan wartawan yang tidak seimbang.

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In the 2011 is new er cloud computing. Cloud computing technology is solution of information and communication tehnology which gave opportunity to consumer to rent technology service from provider. Provider give service infrastructure management, platform, and information tehnology service until facilitate consumer without investment. It is just, both mass media and media online expandn information about cloud computing technology, that happened is using of tehnology term in expert spehere level were difficulted by society. By using Arnold Pacey model define two layer :expert sphere and user spehere in utilization technology, this study view existencen tend of language using and journalist writing were unbalance."

"This book is an outcome of the second national conference on Communication, Cloud and Big Data (CCB) held during November 10-11, 2016 at Sikkim Manipal Institute of Technology. The nineteen chapters of the book are some of the accepted papers of CCB 2016. These chapters have undergone review process and then subsequent series of improvements. The book contains chapters on various aspects of communication, computation, cloud and big data. Routing in wireless sensor networks, modulation techniques, spectrum hole sensing in cognitive radio networks, antenna design, network security, Quality of Service issues in routing, medium access control protocol for Internet of Things, and TCP performance over different routing protocols used in mobile ad-hoc networks are some of the topics discussed in different chapters of this book which fall under the domain of communication.Moreover, there are chapters in this book discussing topics like applications of geographic information systems, use of radar for road safety, image segmentation and digital media processing, web content management system, human computer interaction, and natural language processing in the context of Bodo language. These chapters may fall under broader domain of computation.Issues like robot navigation exploring cloud technology, and application of big data analytics in higher education are also discussed in two different chapters. These chapters fall under the domains of cloud and big data, respectively."

"This book is an outcome of the second national conference on Communication, Cloud and Big Data (CCB) held during November 10-11, 2016 at Sikkim Manipal Institute of Technology. The nineteen chapters of the book are some of the accepted papers of CCB 2016. These chapters have undergone review process and then subsequent series of improvements. The book contains chapters on various aspects of communication, computation, cloud and big data. Routing in wireless sensor networks, modulation techniques, spectrum hole sensing in cognitive radio networks, antenna design, network security, Quality of Service issues in routing, medium access control protocol for Internet of Things, and TCP performance over different routing protocols used in mobile ad-hoc networks are some of the topics discussed in different chapters of this book which fall under the domain of communication.Moreover, there are chapters in this book discussing topics like applications of geographic information systems, use of radar for road safety, image segmentation and digital media processing, web content management system, human computer interaction, and natural language processing in the context of Bodo language. These chapters may fall under broader domain of computation.Issues like robot navigation exploring cloud technology, and application of big data analytics in higher education are also discussed in two different chapters. These chapters fall under the domains of cloud and big data, respectively."

"Dalam era revolusi industri 4.0, integrasi teknologi menjadi kunci untuk meningkatkan produktivitas di sektor manufaktur. Dalam konteks ini, penggunaan Cloud Computing, Internet of Things (IoT), dan Machine Learning (ML) memainkan peran penting. IoT dan Cloud Computing digunakan untuk mengelola proses pengumpulan dan pengolahan data, terutama dari sensor mesin. Data ini kemudian dapat digunakan untuk pelatihan model ML, khususnya dalam kasus Predictive Maintenance. Predictive Maintenance bertujuan untuk memprediksi kapan suatu mesin memerlukan perawatan. Dalam penelitian sebelumnya, pendekatan masalah hanya memilih satu metode (klasifikasi atau regresi). Oleh karena itu, penelitian ini menciptakan metode Predictive Maintenance yang menggabungkan keduanya. Model yang dikembangkan menggunakan dua jenis pendekatan: Random Forest Tree untuk klasifikasi dan LSTM (Long Short-Term Memory) dengan Fully Connected layer untuk prediksi. Hasil pengujian menunjukkan bahwa model yang menggunakan LSTM untuk klasifikasi dan regresi mencapai akurasi 100%. Diikuti dengan hasil recall, precission, dan F-1 score yang mencapai 1.00. Oleh karena itu, LSTM dapat dianggap sebagai algoritma terbaik untuk Predictive Maintenance dalam industri manufaktur.

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In the era of the 4th industrial revolution, technology integration is key to improving productivity in the manufacturing sector. In this context, the use of Cloud Computing, Internet of Things (IoT), and Machine Learning (ML) plays a crucial role. IoT and Cloud Computing are used to manage the process of data collection and processing, especially from machine sensors. This data can then be used for ML model training, particularly in the case of Predictive Maintenance. Predictive Maintenance aims to predict when a machine requires maintenance. In previous research, the problem approach often involved choosing only one method (classification or regression). Therefore, this study created a Predictive Maintenance method that combines both approaches. The developed model uses two types of approaches: Random Forest Tree for classification and LSTM (Long Short-Term Memory) with a Fully Connected layer for prediction. Test results show that the model using LSTM for both classification and regression achieves 100% accuracy. Additionally, the recall, precision, and F-1 score results also reach 1.00. Therefore, LSTM can be considered the best algorithm for Predictive Maintenance in the manufacturing industry."

"Skripsi ini berisi mengenai konsep dasar, perancangan dan implementasi enkripsi data dengan RSA yang diterapkan pada private cloud Infrastucture as a Service (IaaS). Tujuan dari skripsi ini menganalisa keamanan pengiriman data dan waktu dari implementasi kriptografi RSA pada sistem Eucalyptus private cloud. Pengiriman data pada sistem virtualisasi private cloud membutuhkan enkripsi untuk mengantisipasi serangan dari man-in-the-middle sehingga penyerang tidak mengetahui isi data dengan mudah. Hasil penelitian menunjukkan bahwa waktu eksekusi program RSA dipengaruhi oleh ukuran data dan nilai kunci RSA yang dibangkitkan. Peningkatan ukuran data akan mempengaruhi peningkatan waktu eksekusi program RSA. Peningkatan waktu eksekusi untuk format .txt sebesar 31,44%, untuk format .doc sebesar 24,83% dan untuk format .pdf sebesar 24,85%. Nilai d untuk kunci privat RSA yang besar akan sangat mempengaruhi waktu eksekusi karena membutuhkan waktu dekripsi yang lebih lama. Sedangkan nilai e yang besar untuk kunci publik RSA tidak terlalu signifikan mempengaruhi waktu enkripsi menjadi lebih lama namun tetap berkontribusi terhadap waktu eksekusi RSA. Keamanan pengiriman data pada sistem private cloud dibutuhkan terutama dengan RSA 2048 bit dan sistem padding, namun pada skripsi ini hanya digunakan enkripsi plain RSA.

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This thesis contains about fundamental concept, the design and the implementation of data encryption using RSA which is applied on private cloud Infrastucture as a Service (IaaS). The purposes of this thesis are to analyze the the data transfer security and the time of RSA cryptography appliance on Eucalyptus private cloud system. Secret data transfer on private cloud virtualization requires encryption in order to anticipated the attack from man-in-the-middle so that the attacker won?t know the contents of data easily.

The result of this research prove that RSA execution time influented by the size of data and the value of the generated RSA keys. Data size increment will influence the execution times of RSA. The increment time for .txt is 31,44%, increment time for .doc is 24,83%, and increment time for .pdf is 24,85%. Large values of d for RSA private key greatly affect the execution time because need a longer decryption time.

However, the large value of e for public keys isn?t influence the encryption time significantly but still contributes the execution time. The security of data transfer on private cloud system is needed especially using RSA 2048 bit and padding system appliance,however this thesis only implement plain RSA encryption."

"Keberadaan data center pada sistem cloud computing sangat besar artinya. Data center yang terletak pada lapisan IaaS pada sistem cloud berisi komponen fisik yang meliputi komponen komputasi seperti server dan switch dan komponen non komputasi seperti sistem pendingin dan pengaturan suhu. Seiring dengan meningkatnya jumlah pengguna data center, maka konsumsi daya listrik pada data center akan meningkat. Telah diusulkan skema penghematan energi pada data center yakni skema DVFS dan DNS. Pada penelitian ini telah disimulasikan menggunakan GreenCloud, yang merupakan ekstensi dari NS2, kepada tiga macam arsitektur data center yakni two-tier, three-tier dan three-tier high-speed dengan jenis workload adalah High Performance Computing HPC. Penerapan skema penghematan meliputi skema DVFS dan DNS saja serta DVFS dan DNS sekaligus. Dari hasil yang diperoleh menunjukkan bahwa penerapan skema DNS menunjukkan hasil terbaik karena berhasil melakukan penghematan rata-rata sebesar 63,42% pada server dan hampir 100% pada switch.

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The existence of a data center in the cloud computing system was huge. Data center is located on the IaaS layer cloud systems containing physical component includes computing components such as servers and switches and non-computing components such as cooling systems and temperature regulation. Along with the increasing number of users of data center, then the electric power consumption in the data center will increase. Energy conservation schemes have been proposed in the data center is DNS and DVFS.

In this study has been simulated using GreenCloud, which is an extension of NS2, the three kinds of data center architecture these are two-tier, three-tier and three-tier high-speed with the type of data center workloads is HPC High Performance Computing. The applications of the savings schemes include schemes DVFS only, DNS only and both DVFS and DNS. From the results obtained indicate that the application of the DNS control scheme is the best because it managed to save an average of 63.42% on the server and almost 100% on the switch for all data center architecture."

"Teknologi Cloud Computing merupakan tren teknologi informasi saat ini yang memanfaatkan jaringan internet untuk penyediaan akses ke berbagai layanan TI. Teknologi ini diprediksikan akan semakin berkembang karena layanan cloud menawarkan berbagai keunggulan seperti efektivitas biaya, fleksibilitas layanan, kemudahan akses, kecepatan proses komputasi dan lain-lain. Terdapat juga faktor-faktor yang menjadi penghambat untuk adopsi cloud seperti faktor keamanan dan privasi data, lambatnya akses internet, proses migrasi yang rumit, dan lain-lain. Berbagai faktor tersebut menjadi pertimbangan organisasi untuk melihat benefit yang diperoleh jika adopsi layanan cloud dilakukan. Karya akhir ini akan mengidentifikasikan prioritas dari faktor-faktor seperti efektifitas biaya, efektivifitas keamanan, kebutuhan organisasi, koneksi internet, reliabilitas, dan kepercayaan terhadap provider dalam kaitan dengan adopsi layanan cloud computing di organisasi, serta identifikasi model layanan cloud computing yang paling sesuai untuk organisasi.Penelitian ini mengumpulkan data dari organisasi dengan metode survey. Organisasi dipilih dengan cara purposive sampling dengan menyebarkan kuesioner yang diisi oleh staf yang kompeten/ahli dengan masalah cloud computing atau bertanggungjawab terhadap infrastruktur TI di organisasi. Data primer yang dikumpulkan selanjutnya diolah dengan metode Analytic Hierarchy Process. Hasilnya adalah bahwa urutan prioritas dari faktor-faktor yang berpengaruh dalam adopsi layanan cloud computing di organisasi adalah faktor keandalan/reliability (0.237), faktor keamanan/security (0.224) dan faktor koneksi internet (0.175). Untuk model layanan cloud yang paling sesuai untuk organisasi, urutannya adalah layanan Infrastruktur (0.557), layanan Aplikasi (0.246) dan layanan Platform (0.196).

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Cloud Computing technology is a recent information technology trends that utilize the Internet connections to provide access to a range of IT services. This technology is expected to further evolve as cloud services offer many advantages such as cost effectiveness, service flexibility, ease of access, swift computing process, etc. There are also some factors listed as an obstacle in cloud computing adoption such as security concern, data privacy, slow internet access, migration process, etc. These various factors will be considered by organization to analyze the benefits obtained if cloud service adoption is performed. This thesis will identify the priority of factors such as cost effectiveness, security effectiveness, organization needs, internet connection, reliability, and trust in cloud provider in influencing cloud service adoption in organizations and also identifying cloud service model that most suited with organizations.

This study collects data from organizations using survey methods. Organizations selected by purposive sampling in which questionnaires filled out by competent staff or cloud computing experts in organization or staff that responsible for IT infrastructure. Primary data collected then processed using Analytic Hierarchy Process. This resulting prioritization of factors that influencing adoption of cloud services in the organization which are : Reliability factor (0.237), Security factor (0.224) and Internet connection factor (0.175). In determining cloud service model that suited with organization needs, the priority order are : Infrastructure services (0.557), Application services (0.246) and Platform services (0.196)."

"Bank Perkreditan Rakyat (BPR) sebagai salah satu pemain terbesar dalam bisnis keuangan mikro di Indonesia telah meningkatkan penggunaan Sistem Informasi/Teknologi Informasi (SI/TI) untuk mendukung bisnis mereka. Namun, hanya sedikit dari mereka yang menyadari isu-isu seputar investasi TI. Ada kekhawatiran tentang tidak tersedianya sumber daya yang cukup untuk membeli, memelihara, dan mengamankan SI/TI mereka sendiri. Di sisi lain, investasi yang besar diperlukan dan akhirnya menjadi momok bagi BPR yang paling menerapkan SI/TI untuk mendukung pengembangan bisnis mereka. Penelitian ini menganalisis nilai ekonomi dari penerapan komputasi awan di BPR. Analisis dilakukan, pertama dengan mengidentifikasi dan mengukur relevansi manfaat SI/TI menggunakan Ranti?s IS/IT Generic Business Values dan kedua dengan menempatkan nilai-nilai yang diukur atau manfaat pada metode Economic Value Added (EVA), untuk melakukan analisis keuangan. Komputasi awan mampu memberikan solusi bagi masalah yang dihadapi oleh BPR seperti dapat dilihat dari nilai EVA positif. Oleh karena itu, komputasi awan merupakan pendekatan yang berharga bagi BPR untuk bergerak maju. Resiko investasi SI/TI dapat ditransfer ke penyedia komputasi awan, dengan kata lain, tidak ada waktu untuk berpikir tentang teknologi usang sebelum Return of Investment (ROI) tercapai.

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AbstractBank Perkreditan Rakyat (BPR) as one of the biggest players in Indonesia?s microfinance business has increased their use of Information Systems/Information Technology (IS/IT) to support their business. However, only few of them are aware of issues around IT investment. There are concerns about the unavailability of sufficient resource to purchase, maintain, and secure their own IS/IT. On the other hand, a large investment is needed and it eventually becomes the scourge for most rural banks to apply IS/IT to support their business development. This research analyzes the economic value of implementing cloud computing in BPR. Analysis is done, firstly by identifying and quantifying the relevant IS/IT benefits using Ranti?s IS/IT Generic Business Values and, secondly by putting the quantified values or benefits into Economic Value Added (EVA) method to do the financial analysis. Cloud computing is able to provide solutions for problems faced by BPR as can be seen from the positive EVA value. Hence, the cloud computing is a valuable approach for BPR to move forward. IS/IT investment risk can be transferred to cloud computing providers, in other words, there is no time to think about outdated technology before Return of Investment (ROI) is achieved."

"Penelitian ini bertujuan untuk mengembangkan kerangka kesesuaian suatu institusi pemerintah di Indonesia dalam mengadopsi cloud computing. Pengembangan kerangka tersebut dibagi menjadi dua yaitu: 1) kerangka untuk menentukan perlu tidaknya sebuah organisasi mengadopsi cloud, dan 2) kerangka untuk menentukan tipe cloud deployment yang sesuai. Kerangka pertama dikembangkan dengan memodifikasi model Misra Mondal yang dilakukan dengan melakukan wawancara dengan pakar di bidang adopsi cloud untuk institusi pemerintah. Kerangka kedua dikembangkan dengan menggunakan gabungan antara BCOR, Entropi dan TOPSIS, yang validasi modelnya dilakukan dengan mengirimkan kuesioner kepada pelaku TI di pemerintahan. Selain itu, sebuah studi juga dilakukan ke Dinas Komunikasi dan Informatika kota Depok untuk menguji aplikasi dari kerangka yang sudah dikembangkan.Hasil studi kasus yang dilakukan di Dinas Kominfo kota Depok menunjukkan institusi ini sudah cocok jika melakukan adopsi cloud computing. Selain itu, hasil dari penelitian pengembangan kerangka tipe cloud deployment menunjukkan bahwa faktor yang paling dianggap penting oleh pelaku TI di pemerintah adalah keamanan data. Dan juga, tipe deployment yang paling sesuai diimplementasikan di sana adalah private cloud.

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The purpose of this study is to develop framework of Indonesian government institutions' suitability in adopting cloud technology. The proposed framework comprises the following: 1) a framework for determining an organization necessity to adopt the cloud, and 2) a framework for determining the appropriate type of cloud deployment. The first framework was developed by modifying the Misra Mondal?s model, which was done by conducting interviews with experts in the areas of cloud adoption for government institutions. The second framework was developed using a combination of BCOR, Entropy and TOPSIS, in which the validation of the model was done by distributing questionnaires to the IT specialist in government institution. In addition, a study was also conducted to department of Communication and Information in Depok city to test the application of the framework that has been developed.

The results of a case study conducted in the department of Communication and Information in Depok City showed this institution is highly suitable to adopt cloud computing. In addition, the result of this study indicates that the factors considered important by most IT specialist in government institution is data protection. Moreover, private cloud is considered as the most appropriate cloud deployment model to be implemented."