Teknologi Aplikatif

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Teknologi Aplikatif Courses

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kunci sukses integrasi industry 4.0 driver & enabler. Bagaimana implementasi industri 4.0 terhadap teknologi seperti AI, CLou..

  • 500000 800000
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What you will learn
  • Introduction to Industry 4.0 Driver and Enabler
  • Various Industry Revolution
  • Digitalization and Networked Economy
  • Opportunity and Challenge of Industry 4.0
  • Important Aspect of Industry 4.0
  • Introduction to Smart Manufacturing
  • Introduction to Smart Maintenance
  • Condition Monitoring
  • Introduction to typical Industry 4.0 technology ( AI, Cloud Computing, Cyber Physical System, Additive manufacturing, Bi...

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Building information modeling (BIM) is an intelligent 3D model-based process that gives architecture, engineering, and constr..

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What you will learn
  • 1. Take-off for Architectural & Structural
  • 2. Take-off for Reinforcement Bar
  • 3. Combination 2D and 3D drawing
  • 4. Cost Management

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Structural Equation Modeling (SEM) and Its Application for Life and Social Science

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What you will learn
  • 1. Memahami konsep Statistika dasar yang terkait SEM
  • 2. Memahami variabel yang digunakan dalam SEM
  • 3. Materi singkat Confirmatory Factor Analysis, Path Analysis, dan Structural Equation Modeling
  • 4. Contoh Aplikasi CFA
  • 5. Contoh Aplikasi Path Analysis
  • 6. Contoh Aplikasi SEM

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Tak seperti printer biasa, printer 3D mampu menghasilkan produk berbentuk tiga dimensi yang dapat dimanfaatkan dalam berbagai..

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What you will learn
  • 1. Introduction: a) Background Information b) Rapid Prototyping, 3D Print, Type, & Software c) Scheme of 3D Printing
  • 2. Applications a) Demonstration Scheme of 3D Printing b) Tutorial 3D Software c) Advantages of 3D print & It's Appli...

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SPSS (Statistical Program for Social Science) merupakan software aplikasi statistik yang populer karena SPSS dapat membantu p..

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What you will learn
  • 1. Pengantar teknik analisis data
  • 2. Input data, transfer data, entry data, dan cleaning data
  • 3. Statistik deskriptif untuk data numeric (mean, median, standar deviasi, varians, percentile, dll) dan data kategorik...
  • 4. Penyajian data (box plot, bar diagram, pie, histogram, dll)
  • 5. Uji Validitas dan reliabilitas data
  • 6. Uji beda (2 kelompok independen, 2 kelompok berpasangan, 3 kelompok independen atau lebih)
  • 7. Regresi sederhana dan berganda
  • 8. Asumsi klasik (normalitas, autokorelasi, multikolinearitas, heteroskedastisitas)