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"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.

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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."

"Ekonomi digital sekarang ini memiliki penggerak utama berupa data untuk pelaku usaha menjalankan usahanya Pokok permasalahan yang akan dibahas mengenai dampak yang akan timbbul akibat dari kepemilikan Big Data yang besar oleh pelaku usaha pada era ekonomi digital. Hal tersebut dikhawatirkan dapat memunculkan adanya potensi terjadinya praktik diskriminasi harga akibat kepemilikan Big Data tersebut. Penulisan ini memiliki tujuan untuk mengetahui lebih lanjut mengenai dampak dan potensi adanya diskriminasi harga akibat kepemilikan Big Data yang dilihat dari sudut pandang hukum persaingan usaha terlebih pada Undang-Undang Nomor 5 Tahun 1999. Penelitian yang akan dilakukan adalah penelitian hukum  normatif dengan mengkaji penerapan hukum pada Undang-Undang Nomor 5 Tahun 1999 tentang Larangan Praktik Monopoli dan Persaingan Usaha Tidak Sehat serta peraturan perundang-undangan terkait lainnya. Dampak yang timbul akibat kepeilikan Big Dataapabila dilihat dari hukum persaingan usaha dapat membantu pelaku usaha dalam mengembangkan usaha dan membuat iklim persaingan menjadi lebih baik. Namun disisi lain hal tersebut apabila diikuti oleh niat buruk dari pelaku usaha dapat mengakibatkan dampak yang menjatuhkan pelaku usaha pesaingnya. Salah satunya pelaku usaha dapat dengan lebih mudah menerapkan praktik diskriminasi harga kepada pembeli atau konsumennya. Dalam menetapkan harga yang berbeda kepada konsumen yang berbeda pelaku usaha memerlukan informasi yang akurat untuk mengetahui harga yang bersedia dibayarkan oleh konsumen. Oleh sebab itu peran Big Data yang dimiliki oleh pelaku usaha akan berpengaruh tehadap basis data yang menjadi sumber informasi bagi pelaku usaha. Kepemilikan Big Data memiliki sisi positif dan negatif untuk persaingan usaha tergantung kepada motif dari pelaku usaha itu sendiri apabila dilihat dari sisi hukum persaingan usaha yang ada. Hal tersebut harus dibuktikan lebih lanjut apakah hal tersebut dapat dikatakan sebagai tindakan pelanggaran terkait penerapan diskriminasi harga yang diatur.

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Today's digital economy has the main driver in the form of data for business actors to run their business. The main issues that will be discussed are the impacts that will arise as a result of large Big Data ownership by business actors in the digital economy era. It is feared that this could raise the potential for price discrimination practices due to Big Data ownership. This writing aims to find out more about the impact and potential for price discrimination due to ownership of Big Data from the point of view of business competition law, especially Law Number 5 of 1999. The research that will be carried out is normative legal research by examining the application of law to Law Number 5 of 1999 concerning Prohibition of Monopolistic Practices and Unfair Business Competition and other related laws and regulations. The impacts arising from the ownership of Big Data when viewed from the business competition law can assist business actors in developing their business and create a better competitive climate. But on the other hand, if this is followed by bad intentions from business actors, it can have an impact that brings down competing business actors. One of them is that business actors can more easily apply price discrimination practices to their buyers or consumers. In setting different prices to different consumers, business actors need accurate information to find out the price consumers are willing to pay. Therefore, the role of Big Data owned by business actors will affect the database which is a source of information for business actors. Ownership of Big Data has positive and negative sides for business competition depending on the motives of the business actors themselves when viewed from the existing business competition law. This must be further proven whether this can be said to be an act of violation related to the application of regulated price discrimination."

"Penelitian ini bertujuan untuk mengidentifikasi segmentasi RFM pada toko kosmetik online di Indonesia. Penelitian ini menggunakan analisis RFM (Recency, Frequency, dan Monetary) yang dilanjutkan dengan K-Means Clustering dengan menggunakan Hiearchical Clustering untuk mencari nilai k. Penelitian ini menggunakan data transaksi penjualan Makeupuccino sepanjang tahun 2017 untuk segmentasi RFM. Hasilnya menunjukkan bahwa jumlah segmentasi yang paling tepat untuk toko kosmetik online adalah 4, yang dibagi menjadi Platinum, Gold, Iron, dan Lead. Keempat segmentasi tersebut memiliki marketing objective dan program marketing yang berbeda.

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This research aims to identify RFM segmentation on makeup online store in Indonesia. This research uses RFM (Recency, Frequency, and Monetary) analysis and then uses K-Means Clustering with Hierarchical Clustering as the way to finds k values. This study uses transaction on Makeupuccino (one of makeup online store in Indonesia) during 2017 to get RFM segmentation. The result shows that the best RFM segmentation for makeup online store in Indonesia is 4, that divided into Platinum, Gold, Iron, and Lead. Each of segmentation has different marketing objective and marketing program."

"Penelitian ini bertujuan untuk menganalisis representasi kelas sosial dalam big data di Indonesia. Penelitian ini berargumen bahwa persoalan pengaplikasian big data terletak pada bias yang disebabkan tidak reprsentatifnya data yang diproduksi. Berdasarkan konteks struktural pada masyarakat Indonesia, dimana secara kuantitatif melalui analisis terhadap data Susenas 2016 menunjukan bahwa terdapat hubungan antara kelas sosial, konteks sosial desa-kota, dan konteks spasial terhadap akses internet dalam proses transformasi struktur sosial kedalam masyarakat jaringan yang berimplikasi terhadap produksi data. Dimana terdapat kecenderungan menghilangkan representasi kelas bawah di Indonesia.

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The research purposes are to study the social class representation of big data in Indonesia. This research argues that problems of big data are situated by bias in how the data are produced. Based on Indonesian socio structural context, analyzed quantitatively on Susenas 2016 data show that there is a linear statistical relationship from social class to internet access controlled by rural urban social context and spatial context. This relationship creating a significant impact on structural transformation toward network society, and how data are produced by the tendency of eliminating lower class in data generating process."

"An examination of the uses of data within a changing knowledge infrastructure, offering analysis and case studies from the sciences, social sciences, and humanities."Big Data" is on the covers of Science, Nature, the Economist, and Wired magazines, on the front pages of the Wall Street Journal and the New York Times. But despite the media hyperbole, as Christine Borgman points out in this examination of data and scholarly research, having the right data is usually better than having more data; little data can be just as valuable as big data. In many cases, there are no data -- because relevant data don't exist, cannot be found, or are not available. Moreover, data sharing is difficult, incentives to do so are minimal, and data practices vary widely across disciplines.Borgman, an often-cited authority on scholarly communication, argues that data have no value or meaning in isolation; they exist within a knowledge infrastructure -- an ecology of people, practices, technologies, institutions, material objects, and relationships. After laying out the premises of her investigation -- six "provocations" meant to inspire discussion about the uses of data in scholarship -- Borgman offers case studies of data practices in the sciences, the social sciences, and the humanities, and then considers the implications of her findings for scholarly practice and research policy. To manage and exploit data over the long term, Borgman argues, requires massive investment in knowledge infrastructures; at stake is the future of scholarship.--publisher."

"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."

"This book provides users with cutting edge methods and technologies in the area of big data and visual analytics, as well as an insight to the big data and data analytics research conducted by world-renowned researchers in this field. The authors present comprehensive educational resources on big data and visual analytics covering state-of-the art techniques on data analytics, data and information visualization, and visual analytics. Each chapter covers specific topics related to big data and data analytics as virtual data machine, security of big data, big data applications, high performance computing cluster, and big data implementation techniques. Every chapter includes a description of an unique contribution to the area of big data and visual analytics. This book is a valuable resource for researchers and professionals working in the area of big data, data analytics, and information visualization. Advanced-level students studying computer science will also find this book helpful as a secondary textbook or reference."

"ABSTRAKJakarta yang telah didukung oleh teknologi big data. Peran teknologi big data bagi perkembangan smart city sangat penting karena dapat menjadi dasar untuk menyusun perencanaan dan menentukan kebijakan pemerintah daerah. Pada tesis ini dibahas mengenai analisis implementasi teknologi big data di Pemerintah Provinsi DKI Jakarta dengan menggunakan metode gap analysis pada data-data hasil in-depth interview dan data pendukung lainnya. Berdasarkan hasil gap analysis diketahui bahwa implementasiteknologi big data di Jakarta Smart City masih memerlukan perbaikan dan pengembangan karena masih adanya kesenjangan pada elemen-elemen penelitian yaitu data, infrastruktur, pengelolaan, sumber daya manusia dan manfaat. Pada penelitian ini selanjutnya dirumuskan usulan perbaikan terhadap kesenjangan yang ditemukan dan menyusun urutan prioritas perbaikan dengan menggunakan metode capability, accessibility, readiness dan leverage (CARL).

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ABSTRACTThe Jakarta Smart City Unit is a work unit of the Jakarta Provincial Government in Indonesia with the main duty and function of implementing smart city, one of itsefforts using big data technology. The role of big data technology in the development of smart city is very important, because it can be the basis of the steps in determining the policies of the local government. This study discusses and analyses the implementation of big data technology in the Provincial Government of Jakarta by using gap analysis tool based on in-depth interview data and other supporting data. Based on the results of the gap analysis, it is known that the use of big data technology in Jakarta Smart City still needs improvement and development because there are still gaps in the research elements, namely data, infrastructure, governance, human resources and benefit. In this study the proposed improvements to the gaps that were found and formulated the priority order of improvement using the method of Capability, Accessibility, Readiness,and Leverage CARL."

"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."