Hasil Pencarian  ::  Simpan CSV :: Kembali

"What's wrong with targeted advertising in political campaigns? Are echo chambers a matter of genuine concern? How does data collection impact on trust in society? As decision-making becomes increasingly automated, how can decision-makers be held to account? This collection consider potential solutions to these challenges."

"Perkembangan teknologi informasi dan internet dalam berbagai sektor kehidupan menyebabkan terjadinya peningkatan pertumbuhan data di dunia. Pertumbuhan data yang berjumlah besar ini memunculkan istilah baru yaitu Big Data. Karakteristik yang membedakan Big Data dengan data konvensional biasa adalah bahwa Big Data memiliki karakteristik volume, velocity, variety, value, dan veracity. Kehadiran Big Data dimanfaatkan oleh berbagai pihak melalui Big Data Analytics, contohnya Pelaku Usaha untuk meningkatkan kegiatan usahanya dalam hal memberikan insight yang lebih luas dan dalam. Namun potensi yang diberikan oleh Big Data ini juga memiliki risiko penggunaan yaitu pelanggaran privasi dan data pribadi seseorang. Risiko ini tercermin dari kasus penyalahgunaan data pribadi Pengguna Facebook oleh Cambridge Analytica yang berkaitan dengan 87 juta data Pengguna. Oleh karena itu perlu diketahui ketentuan perlindungan privasi dan data pribadi di Indonesia dan yang diatur dalam General Data Protection Regulation (GDPR) dan diaplikasikan dalam Big Data Analytics, serta penyelesaian kasus Cambridge Analytica-Facebook. Penelitian ini menggunakan metode yuridis normatif yang bersumber dari studi kepustakaan. Dalam Penelitian ini ditemukan bahwa perlindungan privasi dan data pribadi di Indonesia masih bersifat parsial dan sektoral berbeda dengan GDPR yang telah mengatur secara khusus dalam satu ketentuan. Big Data Analytics juga memiliki beberapa implikasi dengan prinsip perlindungan privasi dan data pribadi yang berlaku. Indonesia disarankan untuk segera mengesahkan ketentuan perlindungan privasi dan data pribadi khusus yang sampai saat ini masih berupa rancangan undang-undang.

---

The development of information technology and the internet in various sectors of life has led to an increase in data growth in the world. This huge amount of data growth gave rise to a new term, Big Data. The characteristic that distinguishes Big Data from conventional data is that Big Data has the characteristic of volume, velocity, variety, value, and veracity. The presence of Big Data is utilized by various parties through Big Data Analytics, for example for Corporation to incurease their business activities in terms of providing broader and deeper insight. But this potential provided by Big Data also comes with risks, which is violation of one's privacy and personal data. One of the most scandalous case of abuse of personal data is Cambridge Analytica-Facebook relating to 87 millions user data. Therefor it is necessary to know the provisions of privacy and personal data protection in Indonesia and which are regulated in the General Data Protection (GDPR) and how it applied in Big Data Analytics, as well as the settlement of the Cambridge Analytica-Facebook case. This study uses normative juridical methods sourced from library studies. In this study, it was found that the protection of privacy and personal data in Indonesia is still partial and sectoral which is different from GDPR that has specifically regulated in one bill. Big Data Analytics also has several implications with applicable privacy and personal data protection principles. Indonesia is advised to immediately ratify the provisions on protection of privacy and personal data which is now is still in the form of a RUU."

"In today’s fast growing digital world, the web, mobile, social networks and other digital platforms are producing enormous amounts of data that hold intelligence and valuable information. Correctly used it has the power to create sustainable value in different forms for businesses. The commonly used term for this data is Big Data, which includes structured, unstructured and hybrid structured data. However, Big Data is of limited value unless insightful information can be extracted from the sources of data.The solution is Big Data analytics, and how managers and executives can capture value from this vast resource of information and insights. This book develops a simple framework and a non-technical approach to help the reader understand, digest and analyze data, and produce meaningful analytics to make informed decisions. It will support value creation within businesses, from customer care to product innovation, from sales and marketing to operational performance.The authors provide multiple case studies on global industries and business units, chapter summaries and discussion questions for the reader to consider and explore. Big Data for Managers also presents small cases and challenges for the reader to work on – making this a thorough and practical guide for students and managers."

"This book highlights the state of the art and recent advances in Big Data clustering methods and their innovative applications in contemporary AI-driven systems. The book chapters discuss Deep Learning for Clustering, Blockchain data clustering, Cybersecurity applications such as insider threat detection, scalable distributed clustering methods for massive volumes of data; clustering Big Data Streams such as streams generated by the confluence of Internet of Things, digital and mobile health, human-robot interaction, and social networks; Spark-based Big Data clustering using Particle Swarm Optimization; and Tensor-based clustering for Web graphs, sensor streams, and social networks. The chapters in the book include a balanced coverage of big data clustering theory, methods, tools, frameworks, applications, representation, visualization, and clustering validation. "

"Saat ini kompetisi di industri telekomunikasi semakin ketat. Perusahaan telekomunikasi yang dapat tetap menghasilkan banyak keuntungan yaitu perusahaan yang mampu menarik dan mempertahankan pelanggan di pasar yang sangat kompetitif dan semakin jenuh. Hal ini menyebabkan perubahan strategi banyak perusahaan telekomunikasi dari strategi 'growth '(ekspansi) menjadi 'value added services'. Oleh karena itu, program mempertahankan pelanggan ('customer retention') saat ini menjadi bagian penting dari strategi perusahaan telekomunikasi. Program tersebut diharapkan dapat menekan 'churn' 'rate 'atau tingkat perpindahan pelanggan ke layanan/produk yang disediakan oleh perusahaan kompetitor. Program mempertahankan pelanggan ('customer retention') tersebut tentunya juga diimplementasikan oleh PT Telekomunikasi Indonesia, Tbk (Telkom) sebagai perusahaan telekomunikasi terbesar di Indonesia. Program tersebut diterapkan pada berbagai produk Telkom, salah satunya Indihome yang merupakan 'home services' berbasis 'subscriber' berupa layanan internet, telepon, dan TV interaktif. Melalui kajian ini, penulis akan menganalisa penyebab 'churn' pelanggan potensial produk Indihome tersebut, sehingga Telkom dapat meminimalisir angka 'churn' dengan melakukan program 'customer retention' melalui 'caring' yang tepat. Mengingat ukuran 'database' pelanggan Indihome yang sangat besar, penulis akan menganalisis data pelanggan tersebut menggunakan metoda 'Big Data Analytics'. 'Big Data' merupakan salah satu metode pengelolaan data yang sangat besar dengan pemetaan dan 'processing' data. Melalui berbagai bentuk 'output', implementasi 'big data' pada perusahaan akan memberikan 'value' yang lebih baik dalam pengambilan keputusan berbasis data.

---

Nowadays, telecommunication industry is very competitive. Telecommunication companies that can make a lot of profit is the one who can attract and retain customers in this highly competitive and increasingly saturated market. This causes change of the strategy of telecommunication companies from growth strategy toward value added services. Therefore, customer retention program is becoming very important in telecommunication companies strategy. This program hopefully can reduce churn rate or loss of potential customers due to the shift of customers to other similar products.

Customer retention program also implemented by PT Telekomunikasi Indonesia, Tbk (Telkom) as the leading telecommunication company in Indonesia. Customer retention program implemented for many Telkom products, including Indihome, a home services based on subscriber which provide internet, phone, and interactive TV. Through this study, the authors will analyze the cause of churn potential customers Indihome product, so that Telkom can minimize the churn number by doing customer retention program through the efficient caring.

Given by huge customer database the author will analyze using Big Data analytics method. Big Data is one method in data management that contain huge data, by mapping and data processing. Through various forms of output, big data implementation on the organization will provide better value in data-based decision making."

"Informasi telah menjadi komoditas berharga yang membawa pada perubahan pada kehidupan manusia. Salah satu perubahan adalah bagaimana manusia memperoleh informasi tersebut dari kepingan data yang sangat banyak. Kepingan data yang banyak tersebut merupakan big data membutuhkan tempat untuk disimpan di organisasi dan di analisa. Perpustakaan memiliki sejarah panjang sebagai tempat penyimpanan, pengorganisasian dan analisa informasi. Artikel ini berusaha memberikan gambaran umum tentang big data dan pengaruhnya terhadap dunia perpustakaan. Big data membawa pengaruh besar dalam dunia perpustakaan khususnya pada aspek layanan perpustakaan, kompetensi pustakawan."

"ABSTRAKRevolusi digital telah meluncurkan era baru pemberdayaan dan keterlibatan manusia di seluruh bisnis, masyarakat, dan dalam setiap aspek kehidupan kita. Big data akan menjadi sumber nilai dan inovasi ekonomi baru. Pengaruh big data mewakili tiga pergeseran dalam cara kami menganalisis informasi yang mengubah cara untuk memahami dan mengatur masyarakat. Makalah ini akan memeriksa seberapa besar big data dapat digunakan dalam membantu usaha kecil dan menengah UKM untuk tumbuh dan menyelidiki seberapa besar data telah berkontribusi untuk membantu UKM dan perusahaan baru dalam bersaing dengan perusahaan yang lebih besar dan lebih mapan. Menurut definisi, usaha kecil dan menengah UKM adalah non-subsidiari, perusahaan independen yang mempekerjakan lebih sedikit dari jumlah karyawan yang diberikan OECD 2001 . UKM dalam konteks ini termasuk toko individu di platform besar seperti Tokopedia, Bukalapak, dll atau usaha kecil yang menjual langsung ke pelanggan.

---

The digital revolution has launched a new era of human empowerment and engagement across business, society and in every aspect of our lives. Big data will be the source of a new economic value and innovation. Big data rsquo;s ascendency represents three shifts in the way we analyze information that transform how we understand and organize society. This paper will examine how big data can be used in helping small and medium enterprises SMEs to grow and investigate how big data have contributed to help SMEs and startups in competing with bigger and more established companies. By definition, small and medium-sized enterprises SMEs are non-subsidiary, independent firms which employ fewer than a given number of employees OECD 2001 . SME in this context includes individual stores on big platforms such as Tokopedia, Bukalapak, etc or small businesses that sell directly to customers."

"Data warehousing in the age of the big data will help you and your organization make the most of unstructured data with your existing data warehouse.As big data continues to revolutionize how we use data, it doesn't have to create more confusion. Expert author Krish Krishnan helps you make sense of how big data fits into the world of data warehousing in clear and concise detail. The book is presented in three distinct parts. Part 1 discusses big data, its technologies and use cases from early adopters. Part 2 addresses data warehousing, its shortcomings, and new architecture options, workloads, and integration techniques for Big Data and the data warehouse. Part 3 deals with data governance, data visualization, information life-cycle management, data scientists, and implementing a big data–ready data warehouse. Extensive appendixes include case studies from vendor implementations and a special segment on how we can build a healthcare information factory."