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"Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that's so clouded in hype? This insightful book, based on Columbia University's Introduction to Data Science class, tells you what you need to know. In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use"

"This book constitutes selected papers from the 14th European, Mediterranean, and Middle Eastern Conference, EMCIS 2017, held in Coimbra, Portugal, in September 2017. EMCIS is focusing on approaches that facilitate the identification of innovative research of significant relevance to the IS discipline following sound research methodologies that lead to results of measurable impact. The 37 full and 16 short papers presented in this volume were carefully reviewed and selected from a total of 106 submissions. They are organized in sections on big data and Semantic Web; digital services, social media and digital collaboration; e-government; healthcare information systems; information systems security and information privacy protection; IT governance; and management and organizational issues in information systems."

"This book constitutes the refereed proceedings of the 4th International Conference on Soft Computing, Intelligent Systems, and Information Technology, ICSIIT 2015, held in Bali, Indonesia, in March 2015"

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Penelitian ini bertujuan untuk mengidentifikasi perilaku belanja konsumen, menentukan segmentasi konsumen dan mengidentifikasi konsumen berdasarkan wilayah konsumen Bukku.id. Penelitian ini menggunakan data transaksi pada periode 1 September 2017 hingga 17 September 2018. Data diolah dengan analisis Recency, Frequency, Monetary (RFM) dan clustering untuk membentuk segmentasi konsumen. Selanjutnya, analisis pareto diberlakukan dalam menentukan penerbit dan penulis yang layak diprioritaskan untuk memaksimalkan hasil/return dengan meminimalkan usaha/effort. Pemetaan terhadap lokasi konsumen untuk pareto penulis ditentukan agar memberikan pemahaman untuk perbaikan promosi dan strategi pemasaran offline.

Hasil dari penelitian ini menunjukkan adanya tiga jenis profil konsumen yang berbeda berdasarkan analisis RFM dan clustering. Profil konsumen yang dipetakan terhadap penerbit dan penulis akan memberikan perusahaan keuntungan dalam memprioritisasi usaha dalam mengembangkan pola treatment terhadap penerbit dan penulis. Pengembangan offline marketing juga dapat dibangun karena mengetahui analisis lokasi konsumen yang ada.

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The purpose of this research is to identify customer purchase behavior, form customer segmentation, and identify customer address of Bukku.id. this research uses customer purchase data of Bukku.co.id in the period 1 September 2017 – 17 September 2018. RFM method and clustering are used to identify customer segmentation. Then, pareto analysis results which publishers and authors need to be concerned for prioritizing effort in order to gain maximum benefit. Customer address or location has been mapped based on priority authors to determine promotion and offline marketing strategy.

The results of this research show three customer cluster based on RFM and clustering analysis. Each cluster has different characteristic and it can determine which strategy suit to approach their customers. Customer profile based on authors and publisher could also benefit the company to prioritize any treatments relate to them. Better offline marketing strategy can be developed by knowing location analysis

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"ABSTRAK

Semakin strategisnya peran Direktorat Jenderal Bea dan Cukai (DJBC) Kementerian Keuangan Republik Indonesia dalam memfasilitasi perdagangan internasional membuat DJBC harus terus berinovasi dengan memanfaatkan teknologi mutakhir. DJBC dituntut untuk memberikan pelayanan yang efisien dan melakukan pengawasan yang efektif yang merujuk pada praktik-praktik terbaik dalam kepabeanan internasional. Implementasi Big Data pada DJBC bertujuan untuk mendapatkan manfaat dari data yang telah dikumpulkan agar dapat dianalisis untuk mendukung pengambilan keputusan. Konsep Smart Customs and Excise mengusung Big Data sebagai inti dari semua sistem dan proses bisnis pada DJBC, namun sampai dengan saat ini penerapan Big Data masih bersifat proof of concept. Penerapan teknologi baru tanpa adanya arah pengembangan yang jelas memiliki risiko kegagalan, untuk itu diperlukan evaluasi penerapan Big Data di DJBC. Pengukuran tingkat kematangan Big Data dapat digunakan sebagai langkah awal untuk menilai situasi yang sebenarnya dari sebuah organisasi, memperoleh dan memprioritaskan langkah-langkah perbaikan dan kemudian mengontrol setiap tahap pelaksanaannya. Hasil pengukuran kematangan Big Data dapat dijadikan sebagai acuan untuk merumuskan saran dan rekomendasi bagi DJBC untuk mencapai tingkat kematangan yang lebih tinggi. Pengukuran dilakukan menggunakan framework TDWI Big Data Maturity Model untuk mengevaluasi implementasi Big Data pada DJBC. Pengumpulan data dilakukan melalui wawancara pertanyaan tertutup, kemudian diolah menggunakan assessment tools. Hasil evaluasi menunjukkan bahwa tingkat kematangan Big Data pada DJBC ada pada tingkat 3 (Early Adoption) dari skala 1 - 5. Hasil penelitian memberikan rekomendasi pada tiap dimensi untuk dapat meningkatkan tingkat kematangan ke tingkat 4 (Corporate Adoption) dengan prioritas perubahan mulai dimensi organisasi, analitis, manajemen data, infrastruktur, dan tata kelola.

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ABSTRACT

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The more strategic role of the Directorate General of Customs and Excise (DGCE) of the Ministry of Finance of Republic of Indonesia in facilitating international trade has made DGCE to continue to innovate by utilizing the latest technology. DGCE is required to provide efficient services and conduct effective supervision that refers to international customs organization best practices. Implementation of Big Data on DGCE aims to get the benefits of the data that has been collected so that it can be analyzed to support decision making. The Smart Customs and Excise concept brings Big Data as the core of all systems and business processes in DGCE, but until now the implementation of Big Data is still proof of concept. Implementation of new technology without the direction of development that clearly defined has the risk of failure, therefore an evaluation is needed regarding the implementation of Big Data on DGCE. Measuring the maturity level of Big Data can be used as a first step to assess the actual situation of an organization, obtain and prioritize corrective steps and then control each stage of its implementation. The measurement results can be used as a reference to formulate suggestions and recommendations for DGCE to reach a higher maturity level. Measurements were made using the TDWI Big Data Maturity Model framework to evaluate the implementation of Big Data on DGCE. Data collection is done through closed question interviews, then processed using assessment tools. The evaluation results indicate that the maturity level of Big Data on DGCE is at phase 3 (Early Adoption) of scale 1 to 5. The results of the study provide recommendations on each dimension to be able to increase the maturity level to phase 4 (Corporate Adoption) with priority changes starting from the organizational dimension, analytics, data management, infrastructure, and governance.

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"Build deep learning applications, such as computer vision, speech recognition, and chatbots, using frameworks such as TensorFlow and Keras. This book helps you to ramp up your practical know-how in a short period of time and focuses you on the domain, models, and algorithms required for deep learning applications. Deep Learning with Applications Using Python covers topics such as chatbots, natural language processing, and face and object recognition. The goal is to equip you with the concepts, techniques, and algorithm implementations needed to create programs capable of performing deep learning. This book covers intermediate and advanced levels of deep learning, including convolutional neural networks, recurrent neural networks, and multilayer perceptrons. It also discusses popular APIs such as IBM Watson, Microsoft Azure, and scikit-learn. You will: Work with various deep learning frameworks such as TensorFlow, Keras, and scikit-learn. Build face recognition and face detection capabilities Create speech-to-text and text-to-speech functionality Make chatbots using deep learning. "

"Enterprise Resource Planning (ERP), Supply Chain Management(SCM), Customer Relationship Management (CRM), Business Intelligence (BI)and Big Data Analytics (BDA) are business related tasks and processes, which aresupported by standardized software solutions. This requires business orientedthinking and acting from IT specialists and data scientists. It is a good idea to letstudents experience this directly from the business perspective, for example asexecutives of a virtual company in a serious gaming environment."