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"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."

"Cloud computing adalah teknologi baru hasil pengembangan dari sistem berbasis Internet dengan sumber daya komputasi dalam skala besar yang disediakan melalui Internet untuk pengguna. Aplikasi multimedia pada cloud membutuhkan Quality of Service (QoS) seperti bandwidth, delay, dan lain-lain. Penyediaan QoS merupakan tantangan pada multimedia cloud computing. Penelitian ini mengusulkan sistem QoS MEC, sebuah sistem QoS cloud computing dengan kombinasi teknologi Hadoop dan metode Load Balancing berbasis Eucalyptus untuk aplikasi multimedia. Hadoop merupakan platform yang bersifat open source digunakan untuk data berukuran besar yang diproses secara terdistribusi dan paralel. Load balancing merupakan metode untuk membagi beban kerja server. Hasil pengujian menunjukkan bahwa terjadi percepatan response time dan peningkatan throughput, terbesar terjadi pada saat jumlah koneksi per detik 5000. Persentase percepatan response time video ukuran 58,4 MB, adalah 20,42 %; video ukuran 137 MB, adalah 21,36%; video ukuran 249 MB, adalah 21,51%. Persentase peningkatan throughput video ukuran 58,4 MB, adalah 12,52%; video ukuran 137 MB, adalah 13,39%; video ukuran 249 MB, adalah 14,09%.

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Cloud computing is a new technology development results of Internet-based systems with computing resources on a large scale are provided via the Internet to the user. Multimedia application in the cloud requires Quality of Service (QoS) such as bandwidth, delay, and others. Provision of QoS is a challenge on a multimedia cloud computing.

This research proposed a QoS MEC system, a QoS cloud computing system with technology combination of Hadoop and Load Balancing method based Eucalyptus for multimedia applications. Hadoop is an open source platform which is used for large data that is distributed and processed in parallel. Load balancing is a method to divide the workload of the server.

The test results show that there is accelerated response time and increased throughput and largest occurred when the number of simultaneous access is 5000. Percentage of acceleration response time for video size of 58.4 MB is 20.42%; video size of 137 MB is 21,36%; and video size of 249 MB is 21,51%. The increased percentage of throughput for video size of 58.4 MB is 12,52%; video size of 137 MB is 13,39%; and video size of 249 MB is 14,09%."

"Data kehadiran adalah data yang penting baik di lingkup sekolah, universitas, maupun perkantoran untuk karyawan. Presensi yang berupa tandatangan dapat dipalsukan oleh siapa saja dan kapan saja. Sehingga dibutuhkan sebuah perangkat yang dapat mempermudah proses absensi sekaligus mendeteksi keterlambatan siswa/pegawai sebelum memasuki ruangan. Skripsi ini mengembangkan Smart Presence System berbasis Face Recognition dengan machine learning yang dirancang dengan komputasi pada awan (Cloud Computing) dan komputasi pada sebuah node/titik (Fog Computing). Skripsi ini melakukan perbandingan performa Smart Presence System yang dibangun dengan Cloud Computing menggunakan layanan AWS Face Rekognition dan Fog Computing yang ditulis menggunakan bahasa Python dengan library OpenCV yang menggunakan perangkat Raspberry Pi sebagai titik komputasi. Penulis telah melakukan pengujian perbandingan waktu komputasi, penggunaan memori, serta penggunaan biaya antara Cloud Computing dan Fog Computing. Pengujian waktu komputasi dilakukan dengan menggeser router/titik uji sejauh 3 meter, 5 meter dan 7 meter dari sensor kamera. Pengujian waktu komputasi pada Cloud Computing didpat sebesar 11.02 detik, 2.99 detik dan 3.02 detik dengan total penggunaan memori sebesar 0.0042 MB dan total biaya yang diperlukan untuk membangun rancangan Cloud Computing sebesar Rp2.819.516 dalam penggunaan 12 bulan. Dan rata-rata waktu untuk komputasi pada fog sebesar 0.723 detik, 0.99 detik, 1.94 detik dengan total penggunaan memori sebesar 540MB dan total biaya untuk membangun rancangan ini sebesar Rp2.220.00 dalam penggunaan 12 bulan.

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Attendance document is an important thing in schools, universities, and offices for employees. Attendance is usually done by giving a signature on a piece of paper, and it can be forged by anyone. In school, attendance is usually done manually by the teacher and it takes time. So we need a device that can simplify the attendance process and can not be forged. This thesis has developed a Smart Presence System with machine learing designed with Cloud Computing and Fog Computing. This Thesis compared the performance of The Smart Presence System that built with Cloud Computing using AWS Rekognition and Fog Computing that built in Raspberry pi and written in python and library Opencv. The author has tested the comparison of Cloud Computing and Fog Computing in Computing Time, Memory usage and Cost. Computing time testing is done by shifting the router/test point as far as 3 meters, 5 meters, and 7 meters. The computing time on Cloud Computing were 11.02s, 2.99s, and 3.02s with total memory usage of 0.0042MB and the total cost is Rp.2.819.516 in 12 months of use. And The computing time on Fog Computing were o.72s, 0.99s, and 1.94s with the total memory usage of 540MB and the total cost to build this architecture is Rp2.220.000 in 12 months of use."

""The first chapter gives an overview of cloud computing at a level accessible to a lay person. To motivate the reasons for a paradigm shift in the way we compute and store information, we introduce the concept of network-centric computing and network-centric content. A brief discussion of peer-to-peer systems, a first step in the shift from local to remote data storage and processing follows. The chapter continues with a discussion of technological advances that have made cloud computing possible and of the economical reasons why this new paradigm is attractive for many users and applications. Then we take a closer look at the cloud computing delivery models, Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). SaaS gives the users capability to use applications supplied by the service provider but allows no control of the platform or the infrastructure. PaaS gives the capability to deploy consumer-created or acquired applications using programming languages and tools supported by the provider. IaaS allows the user to deploy and run arbitrary software, which can include operating systems and applications. The new paradigm raises ethical questions and has significant vulnerabilities each dissected in separate sections. Finally, the chapter presents the major challenges faced by this new paradigm. The chapter concludes with a overview of the literature and with a historic perspective"--"

""Key Features: Explains how to make design choices and tradeoffs to consider when building applications to run in a virtual cloud environment; Test and experiment with a live cloud system on the Aneka platform; Real-world case studies include scientific, business, and energy-efficiency considerations; Download examples and instructor support materials on the book's companion page.Cloud computing is a technological advancement that focuses on the way in which we design computing systems, develop applications, and leverage existing services for building software. It is based on the concept of dynamic provisioning, which is applied not only to services, but also to compute capability, storage, networking, and IT (Information Technology) infrastructure in general. Resources are made available through the Internet and offered on a pay-per-use basis from Cloud computing vendors. Today, anyone with a credit card can subscribe to Cloud services and deploy and configure servers for an application in hours, growing and shrinking the infrastructure serving its application according to the demand, and paying only for the time these resources have been used"--"

"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."

"As part of the Syngress basics series, The basics of cloud computing provides readers with an overview of the cloud and how to implement cloud computing in their organizations. Cloud computing continues to grow in popularity, and while many people hear the term and use it in conversation, many are confused by it or unaware of what it really means. This book helps readers understand what the cloud is and how to work with it, even if it isn’t a part of their day-to-day responsibility.Authors Derrick Rountree and Ileana Castrillo explains the concepts of cloud computing in practical terms, helping readers understand how to leverage cloud services and provide value to their businesses through moving information to the cloud. The book will be presented as an introduction to the cloud, and reference will be made in the introduction to other Syngress cloud titles for readers who want to delve more deeply into the topic."

"ABSTRAKPemanfaatan Teknologi Informasi dalam sebuah organisasi merupakan sebuah alat penting dalam mencapai tujuan bisnis organisasi tersebut. Salah satu teknologi yang dapat mencapai tujuan tersebut adalah cloud computing, yang memungkinkan layanan dapat diakses dari mana saja secara nyaman. Cloud computing juga dapat memungkinkan akses terhadap layanan jaringan bersama dari suatu sumber daya komputasi yang telah dikonfigurasi.Penelitian ini bertujuan untuk mengidentifikasi kesesuaian Kementerian Luar Negeri RI dalam mengadopsi cloud computing dengan menggunakan pemodelan Misra Mondal Model dan menentukan tipe cloud deployment yang tepat menggunakan pendekatan AHP (Analytic Hierarchy Process) serta kriteria yang ditentukan berdasarkan analisa BCOR (Benefit, Cost, Opportunity, Risk). Dalam penelitian ini dilakukan wawancara, penyebaran kuesioner dan juga studi literatur untuk metode pengumpulan datanya.Hasil dari penelitian ini yaitu organisasi Kementerian Luar Negeri berada di range yang dapat dimungkinkan untuk mengadopsi teknologi cloud. Sedangkan hasil penelitian untuk tipe deployment yang paling sesuai di Kementerian Luar Negeri adalah tipe deployment private cloud.

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ABSTRACTThe use of information technology in an organization is an important tool to achieve the business goals of the organization. One of the technology that can be used for that purpose is cloud computing which enable some services could comfortably accessed anywhere. Cloud computing also enabling access to the shared network in some computing resource that have been configured.The purpose of this research are to identify the suitability of cloud computing adoption by using Misra Mondal model and to select the most suitable cloud deployment type by using AHP (Analytic Hierarchy Process) and the specified criteria by using BCOR (Benefit, Cost, Opportunity, Risk) Analysis. On this research, the data collection method are interviews, questionnaires, and also study the literature.The results from this research is that Ministry of Foreign Affairs on the range which cloud computing technology could be possible to adopt. While the other results of this research in the Ministry of Foreign Affairs for the most appropriate type of cloud deployment type is private cloud type."