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"Time series big data dynamically changes the size, and, unfortunately, it may be difficult to curate the enormous amount of data due to the processing capacity and storage size. This big data allows researcher to iterate on the model millions of times over. To execute a regression on several billion rows of data on a distributed network, the resource capacity regarding large volumes of data and its distributed environment must be considered. Algorithms must be real-time based data awareness. Moreover, analyzing big data sources requires the data to be pre-processed rather than immediately collected and analyzed. This pre-processing approach for the big data sources helps minimize the amount of collected data by extracting insights. It analyzes big data quicker and is cost-effective for storage space. Hence, in this research, an approximation method for analyzing regression problems in a big data stream with parallelism is proposed. The partitioning method for huge data stream helps reduce the computing time and required space, and the speed-up can improve the processing time. The performance evaluation of concurrent regression model is first executed by massive online analysis (MOA) simulation. Then, to validate the approximation method, the results performed by our proposed method are compared to those results collected from the simulation. The comparisons show evenly between the two methods."

"Dengan adanya big data dan pengolahan data, perusahaan mampu meningkatkan efek kompetitifnya sehingga menciptakan kekuatan pasar di pasar bersangkutan dengan peningkatan layanannya yang berpotensi menciptakan entry to barrier. Hal ini terbukti dengan kasus Facebook yang menyalahgunakan dominasinya dengan penggunaan big data dan melanggar Sec. 19(1) dari GWB dengan persyaratan layanannya kepada pengguna. Hal ini membuat urgensi kebijakan persaingan di Indonesia untuk mengatur lebih lanjut hal tersebut dengan potensi dalam proses merger Gojek dan Tokopedia dapat mengakibatkan akumulasi data dan selanjutnya diproses untuk efek kompetitif dan berpotensi mengakibatkan hambatan masuk pasar. Makalah penelitian ini bertujuan untuk menganalisis penggunaan big data untuk perusahaan digital dalam perilaku penyalahgunaan dominasi menurut Hukum Persaingan Indonesia berdasarkan kasus perbandingan Facebook di Jerman dan GoTo di Indonesia. Metode penelitian yang digunakan adalah yuridis normatif yang dilakukan dengan pendekatan peraturan perundang-undangan, pendekatan konseptual, dan pendekatan kasus. Pasal 25 Undang-Undang Nomor 5 Tahun 1999 telah mengatur tentang penyalahgunaan kekuasaan secara umum, sehingga perlu dilakukan analisis lebih lanjut agar dapat diterapkan dalam penggunaan big data.

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With the existence of big data and data processing, companies are able to raise its competitive effects and therefore create market power in relevant market with the improvement of its services which potentially create entry to barriers. This is proven with the Facebook case constituted to abuse its dominance with big data usage and breached Sec. 19(1) of GWB with its terms of service to the users. This create an urgency for competition policy in Indonesia to further regulate the matter with the potential in merger process of Gojek and Tokopedia could result in accumulation of data and further to be processed for competitive effects and potentially resulting barriers to market entry. This research paper aims to analyse the usage of big data for digital companies in abuse of dominance conduct according to Indonesian Competition Law based on comparison cases of Facebook in Germany as well as GoTo in Indonesia. The research method that is used is juridical normative which is done with laws and regulations approach, conceptual approach, and cases approach. Article 25 of Law No. 5 of 1999 have regulated abuse of dominance matter in general, hence it needs a further analysis to be applicable in big data usage. "

"Selama pandemi ini, para pemangku kepentingan pariwisata dan perhotelan di Indonesia harus menyesuaikan strategi mereka untuk bertahan hidup. Meskipun sebagian besar penduduk Indonesia aktif dan konsumtif di Internet, mereka membutuhkan dorongan motivasi seperti keterlibatan untuk mengeluarkan uang demi mendapatkan waktu bersantai. Penelitian ini menganalisis aktivitas pemasaran media sosial, menganalisis customer engagement yang terjadi, dan mengkaji pengaruh social media marketing (SMM) terhadap customer engagement hotel mewah saat terjadi pandemi dengan memanfaatkan big data. Dalam menganalisis SMM dan customer engagement, peneliti memanfaatkan data real time dari akun media sosial hotel kemudian menggunakan natural language processing (NLP) serta pelabelan data untuk mengolahnya. Analisis pengaruh menggunakan regresi data panel dari hasil analisis sebelumnya. Hasil yang didapatkan adalah gambaran SMM terkait dengan dimensi hiburan, terkini, interaksi, kustomisasi, serta aktivitas engagement pada media sosial. Dimensi hiburan dan terkini terwakili dengan 17 kata yang telah diuji keabsahannya. Dimensi interaksi meningkat pada akhir tahun 2020, sedangkan dimensi kustomisasi tidak banyak digunakan oleh pihak hotel. Customer engagement juga meningkat pada akhir tahun 2020. Diketahui bahwa penggambaran pengaruh yang dimiliki SMM terhadap customer engagement sesuai dengan model random-effect. Customer engagement yang terjadi di masa pandemi tidak hanya dipengaruhi oleh dimensi hiburan, terkini, interaksi, dan customisasi. Para pemasar dan pelaku bisnis perhotelan bisa mendapatkan perspektif baru tentang cara mengatasi SMM dan peningkatan engagement di Instagram selama pandemi ini. Berdasarkan studi sebelumnya yang telah dilakukan pada merek mewah, studi ini akan lebih bermanfaat bagi stakeholders pariwisata dan perhotelan.

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During this pandemic, stakeholders of tourism and hospitality in Indonesia have to adjust their strategy to survive. Even though most Indonesia users are active and consumptive on the Internet, they need motivational drives such as an engagement to spend money for leisure. This research will examine the impact of social media marketing (SMM) on customer engagement in luxury hotels during the pandemic situations by utilizing the real time benefits of big data. Firstly, formed panel data of SMM and customer engagement. Researchers scripted real time data from social media accounts of the hotels then use natural processing language (NLP) and automated text analysis to processed the data. Then, for the impact analysis, researchers utilized a panel data regression from the transformed data panel. The results were describing the SMM related to four dimensions which are entertainment, trendiness, interaction, customization, and also the engagement activities. The results discovered that the random-effect model was suitable to determine the influence of SMM on customer engagement. During the pandemic, customer engagement was influenced by other unobservable variables besides entertainment, trendiness, customization, and interaction dimension. The marketer and hoteliers can get new perspectives about overcoming SMM on Instagram during this pandemic. Based on the previous study that has been done in luxury brands, this study will be more useful for tourism and hospitality stakeholders. "

"This book introduces the concept of smart city as the potential solution to the challenges created by urbanization. The Internet of Things (IoT) offers novel features with minimum human intervention in smart cities. This book describes different components of Internet of Things (IoT) for smart cities including sensor technologies, communication technologies, big data analytics and security."