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Manajemen Mutu Pendidikan

Dalam mempertahankan dan meningkatkan mutu pendidikan dibutuhkan manajemen mutu pendidikan. Manajemen mutu adalah suatu sistem untuk membantu satuan pendidikan. Manajemen mutu merupakan kegiatan perencanaan, pelaksanaan, pengendalian dan pengawasan semua aktivitas kerja yang harus diselesaikan untuk mempertahankan mutu yang diinginkan. Dengan demikan, lembaga-lembaga pendidikan perlu mengembangkan sistem-sistem mutunya agar dapat membuktikan kepada publik bahwa mereka dapat memberikan layanan yang bermutu baik terkait dimensi layanan produk dan terutama terkait dimensi layanan jasanya. Pembahasan dalam buku ini adalah: Bab 1 Konsep Dasar Manajemen Mutu Pendidikan Bab 2 Hakikat Mutu Pendidikan Bab 3 Sejarah dan Tokoh Pemikir Mutu Bab 4 Penerapan Manajemen Mutu Terpadu dalam Pendidikan Bab 5 Penjaminan Mutu Internal Bab 6 Penjaminan Mutu Ektsternal Bab 7 Strategi Pengembangan Sistem Penjaminan Mutu Pendidikan Buku ini menyajikan pembahasan seputar manajemen mutu pendidikan. Adapun hal yang penulis bahas meliputi konsep dasar manajemen mutu pendidikan, hakikat mutu pendidikan, sejarah dan tokoh pemikir mutu, manajemen mutu pendidikan, penjaminan mutu internal, penjaminan mutu eksternal, akreditasi untuk penjaminan mutu eksternal, dan strategi pengembangan sistem penjaminan mutu pendidikan.

Dalam mempertahankan dan meningkatkan mutu pendidikan dibutuhkan manajemen mutu pendidikan. Manajemen mutu adalah suatu sistem untuk membantu satuan pendidikan.

Big Data Imperatives

Enterprise ‘Big Data’ Warehouse, ‘BI’ Implementations and Analytics

Big Data Imperatives, focuses on resolving the key questions on everyone's mind: Which data matters? Do you have enough data volume to justify the usage? How you want to process this amount of data? How long do you really need to keep it active for your analysis, marketing, and BI applications? Big data is emerging from the realm of one-off projects to mainstream business adoption; however, the real value of big data is not in the overwhelming size of it, but more in its effective use. Big Data Imperatives describes the complementary nature of traditional data warehouses and big-data analytics platforms and how they feed each other. This book aims to bring the big data and analytics realms together with a greater focus on architectures that leverage the scale and power of big data and the ability to integrate and apply analytics principles to data which earlier was not accessible. This book can also be used as a handbook for practitioners; helping them on methodology,technical architecture, analytics techniques and best practices. At the same time, this book intends to hold the interest of those new to big data and analytics by giving them a deep insight into the realm of big data.

At the same time, this book intends to hold the interest of those new to big data and analytics by giving them a deep insight into the realm of big data.

The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy

SPIoT-2021 Volume 1

This book presents the proceedings of the 2020 2nd International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2021), online conference, on 30 October 2021. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field.

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