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presentasi powerpoint menarik tentang data warehouse, data mining, data mart, OLAP
 
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ini adalah presentasi powerpoint tentang data warehouse data mining data mart dan OLAP JANGAN LUPA SUBSCRIBE YAHH !! :D https://youtu.be/_zrUi2PlyW8
Views: 381 Shala Azzahra
Types of Data: Nominal, Ordinal, Interval/Ratio - Statistics Help
 
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The kind of graph and analysis we can do with specific data is related to the type of data it is. In this video we explain the different levels of data, with examples. Subtitles in English and Spanish.
Views: 746292 Dr Nic's Maths and Stats
Introduction to data mining and architecture  in hindi
 
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Sample Notes : https://drive.google.com/file/d/19xmuQO1cprKqqbIVKcd7_-hILxF9yfx6/view?usp=sharing for notes fill the form : https://goo.gl/forms/C7EcSPmfOGleVOOA3 For full course:https://goo.gl/bYbuZ2 More videos coming soon so Subscribe karke rakho  :  https://goo.gl/85HQGm for full notes   please fill the form for notes :https://goo.gl/forms/MJD1mAOaTzyag64P2 For full hand made  notes of data warehouse and data mining  its only 200rs payment options is PAYTM :7038604912 once we get payment notification we will mail you the notes on your email id contact us at :[email protected] For full course :https://goo.gl/Y1UcLd Topic wise: Introduction to Datawarehouse:https://goo.gl/7BnSFo Meta data in 5 mins :https://goo.gl/7aectS Datamart in datawarehouse :https://goo.gl/rzE7SJ Architecture of datawarehouse:https://goo.gl/DngTu7 how to draw star schema slowflake schema and fact constelation:https://goo.gl/94HsDT what is Olap operation :https://goo.gl/RYQEuN OLAP vs OLTP:https://goo.gl/hYL2kd decision tree with solved example:https://goo.gl/nNTFJ3 K mean clustering algorithm:https://goo.gl/9gGGu5 Introduction to data mining and architecture:https://goo.gl/8dUADv Naive bayes classifier:https://goo.gl/jVUNyc Apriori Algorithm:https://goo.gl/eY6Kbx Agglomerative clustering algorithmn:https://goo.gl/8ktMss KDD in data mining :https://goo.gl/K2vvuJ ETL process:https://goo.gl/bKnac9 FP TREE Algorithm:https://goo.gl/W24ZRF Decision tree:https://goo.gl/o3xHgo more videos coming soon so channel ko subscribe karke rakho
Views: 136762 Last moment tuitions
Metode Kuantitatif Bisnis : Decision Tree
 
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Video ini adalah tutorial materi metode kuantitatif yaitu decision tree untuk memenuhi tugas besar metode kuantitatif semester 3 Anggota Kelompok : -Nurvi Apriana Yusuf (1401154215) -Shabrina Khairunissa Wardana (1401154481) -M Izudin Karimi (1401154257) -Jericho Haganta S (1401152285) Editor : Hanif Arroyisy
Views: 592 Nurvi Apriana
Data Mining  Association Rule - Basic Concepts
 
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short introduction on Association Rule with definition & Example, are explained. Association rules are if/then statements used to find relationship between unrelated data in information repository or relational database. Parts of Association rule is explained with 2 measurements support and confidence. types of association rule such as single dimensional Association Rule,Multi dimensional Association rules and Hybrid Association rules are explained with Examples. Names of Association rule algorithm and fields where association rule is used is also mentioned.
Tanagra Data Mining
 
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an "open source project" as every researcher can access to the source code, and add his own algorithms, as far as he agrees and conforms to the software distribution license.
Views: 13504 Emmanuel Felipe
What is Data Mining?
 
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NJIT School of Management professor Stephan P Kudyba describes what data mining is and how it is being used in the business world.
Views: 357133 YouTube NJIT
Database adalah
 
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Views: 201 admin admin
Crystal Widjaja - Pemanfaatan Big Data di dalam Bisnis GO-JEK | BukaTalks
 
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Subscribe: http://bl.id/subs-bukalapak Crystal Widjaja (SVP Business Intelligence GO-JEK) sharing mengenai penggunaan dan manfaat big data dalam mengembangkan bisnis dalam acara BukaTalks. Crystal berbagi pengalamannya tersebut selama 2 tahun bekerja di GO-JEK. Yuk, mari belajar dan menemukan berbagai insight bersama Crystal Widjaja GOJEK dengan menonton video ini. -------------------------------------------------------------------------------------------------------- Video #BukaTalks lainnya: https://www.youtube.com/watch?v=YfCUBLzDG04&list=PLzMtIVEHDtNqirMVMEh63Or3g3nkMRbkr Website: https://www.bukalapak.com/ Download Aplikasi Bukalapak di sini iOS: https://itunes.apple.com/id/app/bukalapak-jual-beli-online/id1003169137?l=id Google Play: https://play.google.com/store/apps/details?id=com.bukalapak.android Like / Follow Social Media Bukalapak: Facebook - https://www.facebook.com/Bukalapak Twitter - https://www.twitter.com/Bukalapak Instagram - https://instagram.com/bukalapak Google Plus - https://plus.google.com/+bukalapakdotcom Forum Komunitas - https://komunitas.bukalapak.com Stack Overflow - https://stackoverflow.com/jobs/companies/bukalapak LinkedIn - https://www.linkedin.com/company/pt-bukalapak-com
Views: 140985 Bukalapak
How SVM (Support Vector Machine) algorithm works
 
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In this video I explain how SVM (Support Vector Machine) algorithm works to classify a linearly separable binary data set. The original presentation is available at http://prezi.com/jdtqiauncqww/?utm_campaign=share&utm_medium=copy&rc=ex0share
Views: 453357 Thales Sehn Körting
What is Text Mining?
 
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An introduction to the basics of text and data mining. To learn more about text mining, view the video "How does Text Mining Work?" here: https://youtu.be/xxqrIZyKKuk
Views: 40463 Elsevier
Big Data PPT
 
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PPT on “Big Data” is data whose scale, diversity and complexity require new architecture, techniques, algorithms, and analytics to manage it and extract value and hidden knowledge from it… Visit: https://www.topicsforseminar.com to Download the Big Data PPT
Views: 31189 Topics For Seminar
skripsi regresi linier berganda part#1
 
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memahami dengan mudah tentang alat analisis regresi linier berganda dalam skripsi.
Views: 3714 Andri Wisnu 33
Weka Data Mining Tutorial for First Time & Beginner Users
 
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23-minute beginner-friendly introduction to data mining with WEKA. Examples of algorithms to get you started with WEKA: logistic regression, decision tree, neural network and support vector machine. Update 7/20/2018: I put data files in .ARFF here http://pastebin.com/Ea55rc3j and in .CSV here http://pastebin.com/4sG90tTu Sorry uploading the data file took so long...it was on an old laptop.
Views: 415684 Brandon Weinberg
bigdata ppt
 
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Views: 4035 whatsapp
Presentasi Proyek Akhir Data Mining - P1: PEP marketing analysis
 
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Presentasi Proyek Akhir Data Mining - P1: PEP marketing analysis "Analisis Pemasaran PEP dengan Association Rules Mining" June 2015 Fakultas Ilmu Komputer - Universitas Indonesia Oleh : Kelompok 2 1. Dalilah Ghaisani – 1206208385 2. Dhika Ayu Agustin Cahyani – 1206239844 3. Kamila Dini Nabilati – 1206208391 4. Nefri Suswita – 1206208353 5. Tyas Kusuma Handayani – 1206208214 deskripsi masalah "Project P1: PEP marketing analysis pada topik “Market Basket Analysis via Associate Rule Mining”. Permasalahan yang akan dianalisis adalah permasalahan analisis pemasaran PEP (Personal Equality Plan Marketing). Departemen pemasaran dari suatu perusahaan keuangan akan mempromosikan produk terbarunya yaitu PEP ke customer mereka. Manajer perusahaan tersebut ingin memodelkan tipe-tipe konsumennya sehingga dapat diketahui tipe konsumen seperti apa yang menggunakan PEP.
Views: 409 Dalilah Ghaisani
Veri Madenciliği(Excel İşlemleri)-Bölüm 1
 
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Veri Madenciliği, Veri Madenciliği(Excel İşlemleri), Veri Madenciliği(Excel İşlemleri)-Bölüm 1 TAGS veri madenciliği yöntemleri, veri madenciliği nedir, microsoft excell, makro nedir, makrolarla excell dersleri, mining data, mining, datamining, what is data, data mining pdf, data mining techniques, data analysis, mineria, mineria de datos, data warehouse, data warehousing, database, data mining algorithm, data mining ppt, database mining, data mining software, big data, clustering, data mining tools, google data mining, classification, big data mining, smite, datamining smite, smite data mining, coursera, smite reddit, smite patch notes, smite wiki,0 gw2 data mining, big data analytics, bigdata, big data mining, big data, slideshare, kaggle, data scientist, hadoop,0 data mining meaning, jurnal data mining, python data mining, data mining adalah, nptel, python, data mining pdf TAGS https://www.kodkolik.net/
Presentasi Tugas Fakultas Teknologi Informasi UNISBANK Semarang (2016)
 
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video ini merupakan tugas presentasi matakuliah Data Warehouse Dan Data Mining tentang mencari frequent item set menggunakan algoritma apriori pada Tabel FoodMart atauAdventureWorks dan membuat kaidah asosiasi pada Tabel FoodMart atau AdventureWorks. Note : yang kita buat adalah tabel AdventureWorks .
Views: 276 fahmailmasifa 475
Data Science vs Big Data vs Data Analytics | Simplilearn
 
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Data is everywhere. In fact, the amount of digital data that exists is growing at a rapid rate, doubling every two years, and changing the way we live. According to IBM, 2.5 billion gigabytes (GB) of data was generated every day in 2012. An article by Forbes states that Data is growing faster than ever before and by the year 2020, about 1.7 megabytes of new information will be created every second for every human being on the planet. Which makes it extremely important to at least know the basics of the field. After all, here is where our future lies. In this video, we will differentiate between the Data Science, Big Data, and Data Analytics, based on what it is, where it is used, the skills you need to become a professional in the field, and the salary prospects in each field. For more updates on courses and tips follow us on: - Facebook : https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn Get the android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 131681 Simplilearn
Symmetric Key and Public Key Encryption
 
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Modern day encryption is performed in two different ways. Check out http://YouTube.com/ITFreeTraining or http://itfreetraining.com for more of our always free training videos. Using the same key or using a pair of keys called the public and private keys. This video looks at how these systems work and how they can be used together to perform encryption. Download the PDF handout http://itfreetraining.com/Handouts/Ce... Encryption Types Encryption is the process of scrambling data so it cannot be read without a decryption key. Encryption prevents data being read by a 3rd party if it is intercepted by a 3rd party. The two encryption methods that are used today are symmetric and public key encryption. Symmetric Key Symmetric key encryption uses the same key to encrypt data as decrypt data. This is generally quite fast when compared with public key encryption. In order to protect the data, the key needs to be secured. If a 3rd party was able to gain access to the key, they could decrypt any data that was encrypt with that data. For this reason, a secure channel is required to transfer the key if you need to transfer data between two points. For example, if you encrypted data on a CD and mail it to another party, the key must also be transferred to the second party so that they can decrypt the data. This is often done using e-mail or the telephone. In a lot of cases, sending the data using one method and the key using another method is enough to protect the data as an attacker would need to get both in order to decrypt the data. Public Key Encryption This method of encryption uses two keys. One key is used to encrypt data and the other key is used to decrypt data. The advantage of this is that the public key can be downloaded by anyone. Anyone with the public key can encrypt data that can only be decrypted using a private key. This means the public key does not need to be secured. The private key does need to be keep in a safe place. The advantage of using such a system is the private key is not required by the other party to perform encryption. Since the private key does not need to be transferred to the second party there is no risk of the private key being intercepted by a 3rd party. Public Key encryption is slower when compared with symmetric key so it is not always suitable for every application. The math used is complex but to put it simply it uses the modulus or remainder operator. For example, if you wanted to solve X mod 5 = 2, the possible solutions would be 2, 7, 12 and so on. The private key provides additional information which allows the problem to be solved easily. The math is more complex and uses much larger numbers than this but basically public and private key encryption rely on the modulus operator to work. Combing The Two There are two reasons you want to combine the two. The first is that often communication will be broken into two steps. Key exchange and data exchange. For key exchange, to protect the key used in data exchange it is often encrypted using public key encryption. Although slower than symmetric key encryption, this method ensures the key cannot accessed by a 3rd party while being transferred. Since the key has been transferred using a secure channel, a symmetric key can be used for data exchange. In some cases, data exchange may be done using public key encryption. If this is the case, often the data exchange will be done using a small key size to reduce the processing time. The second reason that both may be used is when a symmetric key is used and the key needs to be provided to multiple users. For example, if you are using encryption file system (EFS) this allows multiple users to access the same file, which includes recovery users. In order to make this possible, multiple copies of the same key are stored in the file and protected from being read by encrypting it with the public key of each user that requires access. References "Public-key cryptography" http://en.wikipedia.org/wiki/Public-k... "Encryption" http://en.wikipedia.org/wiki/Encryption
Views: 417984 itfreetraining
How SOM (Self Organizing Maps) algorithm works
 
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In this video I describe how the self organizing maps algorithm works, how the neurons converge in the attribute space to the data. It is important to state that I used a very simple map with only two neurons, and I didn't show the connection between the neurons to simplify the video.
Views: 121411 Thales Sehn Körting
KONSEP DASAR DATABASE by Annisa Mutia Arva_6W_04
 
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Database ( Basis Data ) Merupakan Kumpulan dari suatu data yang tersimpan dan saling berhubungan satu sama lain tersimpan dalam suatu komputer dan digunakan perangkat lunak untuk memanipulasinya. Konsep dasar penyimpanan data yaitu: Entity, adalah suatu yang dipakai untuk menyimpan informasi. Contohnya karyawan, persediaan, dan rekening pelanggan. Setiap entity memiliki atribut. Atributes, adalah elemen data yang merupakan bagan dari entity. Contohnya: alamat pelanggan, nama pelanggan, batas kredit, dan lain-lain. Character, adalah huruf atau angka. Data value, adalah kombinasi karakter (huruf dan angka) yang memiliki makna. Contoh:kotak pos 2001 (data value), alamat (atribut) perusahaan ABC (entity) Field , yaitu kumpulan elemen data terkecil yang disimpan dalam sebuah spasi (ruang fisik). Record, adalah sejumlah field yang dikelompokan dan membentuk sebuah satuan data, yang sekaligus menguraikan atribut khusus dari sebuah entity . file, adalah sekumpulan record yang sejenis. Contoh seluruh record piutang pelanggan dikumpulkan dalam satu tempat yang disebut file piutang dagang, database, adalah kumpulan file-file yang membentuk satuan data yang besar. Dengan dikumpulkannya data e perusahaan ke dalam database, maka koordinasi data menjadi lebih mudah sehingga proses pembaruan (updating) dan akses data menjadi lebih lancar.
Views: 88 W St
Pengenalan Data Warehouse
 
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Materi data warehouse arsitektur untuk mengenali arsitektur data warehouse, implementasi, OLAP, dan mengenali data multidimensi. penyusun : Ahzan mustofa 105410033, dan Wahyu Qurniawan 105410189.
Views: 894 Ahzan Mustofa
Tugas SIG Presentasi Review Jurnal
 
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presentasi ini adalah review jurnal
Views: 2349 muhammad zakariya
Random Forest - Fun and Easy Machine Learning
 
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Random Forest - Fun and Easy Machine Learning https://www.udemy.com/machine-learning-fun-and-easy-using-python-and-keras/?couponCode=YOUTUBE_ML Hey Guys, and welcome to another Fun and Easy Machine Learning Algorithm on Random Forests. Random forest algorithm is a one of the most popular and most powerful supervised Machine Learning algorithm in Machine Learning that is capable of performing both regression and classification tasks. As the name suggest, this algorithm creates the forest with a number of decision trees. In general, the more trees in the forest the more robust the prediction. In the same way in the random forest classifier, the higher the number of trees in the forest gives the high accuracy results. To model multiple decision trees to create the forest you are not going to use the same method of constructing the decision with information gain or gini index approach, amongst other algorithms. If you are not aware of the concepts of decision tree classifier, Please check out my lecture here on Decision Tree CART for Machine learning. You will need to know how the decision tree classifier works before you can learn the working nature of the random forest algorithm. To learn more on Augmented Reality, IoT, Machine Learning FPGAs, Arduinos, PCB Design and Image Processing then Check out http://www.arduinostartups.com/ Please like and Subscribe for more videos :)
Views: 129774 Augmented Startups
Introduction to the KNIME data mining system (tutorial)
 
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Tutorial regarding how to build a workflow in the KNIME data mining and predictive analytics system. For more information or to download KNIME, please visit: http://www.knime.org/ Brought to you by Rapid Progress Marketing and Modeling, LLC (RPM Squared) http://www.RPMSquared.com/
Views: 38323 Predictive Analytics
Presentasi Marketing Plan CMO IBis
 
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Ibis pro 54 adalah Program kepemilikan mobil dengan Hak Guna Pakai Untuk mendapatkan mobil baru dengan HGP hanya perlu membayar 54% OTR HGP bisa diperpanjang 2 kali (3 tahun HGP) dengan membayar 10% dari nilai depsoit awal atau 5,4% OTR Jika setelah 1 tahun atau 2 tahun atau 3 tahun mobil dikembalikan maka uang deposit dikembalikan ke anggota dengan potongan 10% dari nilai deposit Metode HGP ini sangat menguntungkan karena ; 1. Harga mobil sangat murah, hanya bayar 54% 2. Nilai penyusutan saat diual kembali sangat kecil hanya 5.4% OTR, bandingkan dengan pembelian cara konvensional mobil baru yang sudah dipakai 1 tahun ika diual kembali maka nilainya akan turun 20% ~ 30% dari harga beli OTR 3. Sangat cocok digunakan untuk perusahaan baik untuk operasional ataupun rental Keuntungan CMO (Chief Executives Officer) 1. Bonus perkembangan jaringan 2. Bonus penualan mobil Rp. 2,5 juta ditambah 5% OTR atau motor Rp. 250.000,- ditambah 5% OTR Info selengkapnya http://www.komunitas.asia Pin 525281ce Call/sms/wa 087781742832
Views: 3374 pakde qiuce
Anomaly Detection: Algorithms, Explanations, Applications
 
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Anomaly detection is important for data cleaning, cybersecurity, and robust AI systems. This talk will review recent work in our group on (a) benchmarking existing algorithms, (b) developing a theoretical understanding of their behavior, (c) explaining anomaly "alarms" to a data analyst, and (d) interactively re-ranking candidate anomalies in response to analyst feedback. Then the talk will describe two applications: (a) detecting and diagnosing sensor failures in weather networks and (b) open category detection in supervised learning. See more at https://www.microsoft.com/en-us/research/video/anomaly-detection-algorithms-explanations-applications/
Views: 5936 Microsoft Research
Video simulasi aplikasi WP
 
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ini adalah video simulasi aplikasi pemilihan sepeda motor sport menggunakan metode WP
Views: 838 Viya Miyya
DATA WAREHOUSING (GUDANG DATA)
 
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Data warehouse adalah suatu konsep dan kombinasi teknologi yang memfasilitasi organisasi untuk mengelola dan memeliharadata historis yang diperoleh dari sistem atau aplikasi operasional [Ferdiana, 2008]. Pemakaian teknologi data warehouse hampir dibutuhkan oleh semua organisasi, tidak terkecuali Perpustakaan.
Views: 307 viralin aja
More Data Mining with Weka (5.1: Simple neural networks)
 
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More Data Mining with Weka: online course from the University of Waikato Class 5 - Lesson 1: Simple neural networks http://weka.waikato.ac.nz/ Slides (PDF): http://goo.gl/rDuMqu https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 21027 WekaMOOC
Data Mining with Weka (3.6: Nearest neighbor)
 
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Data Mining with Weka: online course from the University of Waikato Class 3 - Lesson 6: Nearest neighbor http://weka.waikato.ac.nz/ Slides (PDF): https://goo.gl/YjZnrh https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 40946 WekaMOOC
Veri Madenciliği Nedir?
 
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Veri Madenciliği, Veri Madenciliği Dersleri, Veri Madenciliği Nedir?, Veri Madenciliği Eğitim Seti, Excel-Weka İlişkisi TAGS veri madenciliği yöntemleri, veri madenciliği nedir, microsoft excell, makro nedir, makrolarla excell dersleri, mining data, mining, datamining, what is data, data mining pdf, data mining techniques, data analysis, mineria, mineria de datos, data warehouse, data warehousing, database, data mining algorithm, data mining ppt, database mining, data mining software, big data, clustering, data mining tools, google data mining, classification, big data mining, smite, datamining smite, smite data mining, coursera, smite reddit, smite patch notes, smite wiki,0 gw2 data mining, big data analytics, bigdata, big data mining, big data, slideshare, kaggle, data scientist, hadoop,0 data mining meaning, jurnal data mining, python data mining, data mining adalah, nptel, python, data mining pdf TAGS http://kodkolik.net/
Decision Tree (CART) - Machine Learning Fun and Easy
 
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Decision Tree (CART) - Machine Learning Fun and Easy https://www.udemy.com/machine-learning-fun-and-easy-using-python-and-keras/?couponCode=YOUTUBE_ML Decision tree is a type of supervised learning algorithm (having a pre-defined target variable) that is mostly used in classification problems. A tree has many analogies in real life, and turns out that it has influenced a wide area of machine learning, covering both classification and regression (CART). So a decision tree is a flow-chart-like structure, where each internal node denotes a test on an attribute, each branch represents the outcome of a test, and each leaf (or terminal) node holds a class label. The topmost node in a tree is the root node. To learn more on Augmented Reality, IoT, Machine Learning FPGAs, Arduinos, PCB Design and Image Processing then Check out http://www.arduinostartups.com/ Please like and Subscribe for more videos :) -------------------------------------------------- Support us on Patreon http://bit.ly/PatreonArduinoStartups --------------------------------------------------
Views: 77103 Augmented Startups
Pra Klinik Proposal Penelitian Dosen Perguruan Tinggi Raharja
 
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Untuk meningkatkan minat dosen STMIK Raharja dan AMIK Raharja Informatika menulis proposal penelitian, diselenggarakan Pra Klinik Proposal Penelitian bagi Dosen bertempat di Aula Serbaguna Perguruan Tinggi Raharja (2/2/2017). Yang menjadi Pemateri Pra Klinik Proposal ini adalah staff ahli pimpinan, Dr. Ir. Sunar Abdul Wahid, MS, juga salah satu dosen peneliti dari Universitas Borobudur. Beliau menjelaskan tentang pengalamannya selama ini dalam memperoleh dana penelitian dari berbagai instansi seperti dari Balitbang Deptan, Departemen Lingkungan Hidup, dan terakhir yang diperolehnya beberapa waktu lalu yaitu dari Ristekdikti melalui Skema PPT (Penelitian Produk Terapan) dengan tema Sistem Pakar bersama tim peneliti lintas Bidang Keilmuan seperti Bidang Pertanian, Bidang Komputer dan Bidang Kedokteran. Hibah Pengabdian Kepada Masyarakat yang diperolehnya pada tahun ini Ipteks bagi Kewirausahaan (IbK). Selain itu, beliau menjelaskan tentang pentingnya dosen melakukan penelitian, menjelaskan skema penelitian yang dapat diikuti oleh dosen sesuai dengan jabatan fungsional dosen, output penelitian berbasis luaran dan TKT (tingkat kesiapan teknologi), serta pelaporan keuangan penelitian. Menurut beliau bahwa penulis proposal itu sangat mudah kalau sudah terbiasa dan hanya cukup 20 lembar saja, satu malam pun pasti jadi kalau memiliki niat untuk menulis, papar beliau. Disampaikan pula teknik penulisan proposal dan diakhiri dengan tanya jawab. Tindaklanjut dari Pra Klinik Proposal ini diharapkan dosen memiliki semangat dalam menyusun proposal penelitian sesuai dengan Panduan Penelitian Edisi X. Bagi dosen yang sudah memiliki proposal, selanjutnya akan dilakukan review melalui Workshop Klinik Proposal Penelitian ini dibedah langsung oleh Bapak Sunar. Adapun kegiatan Klinik Proposal Penelitian akan diadakan beberapa minggu kedepan, sehingga diakhir Februari 2017 seluruh dosen sudah siap mengunggah proposalnya ke dalam Simlitabmas yang tentunya dibantu secara teknis oleh REC sebagai Divisi Penelitian dan Pengabdian Masyarakat di Perguruan Tinggi Raharja. Melalui kegiatan Pra Klinik Proposal ini diharapkan bertambahnya minat dosen dalam menghasilkan proposal penelitian untuk pendanaan DIKTI dan tentunya memiliki potensi untuk lolos review.
Views: 449 LLDD Channel
Big Data - Pengantar Teknologi Informasi #WBA  #Seamolec #kelompok3
 
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Big data adalah himpunan data yang tidak dapat di olah oleh sistem komputer atau perangkat lunak biasa karena sangat unik Terima kasih kepada para pembimbing seamolec para peserta dan teman sekalian
Views: 274 Azzam Fathi
Pengimplementasian ETL dan OLAP pada Retail Sales (Drama)
 
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FE-BIDW 2014 Nama : Siti Rohani Ayundari 5211100062 Muhammad Nashief 5211100130 Adimas Indra 5211100131 Krishna Wacana 5211100141 Hafizh Pahlevie 5211000172 Revy Febri A 5211100119 Carissa Cindy 5211100181 Mayangsekar A 5211100189
Views: 93 rohani ayundari
Weka Tutorial 06: Discretization (Data Preprocessing)
 
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An important feature of Weka is Discretization where you group your feature values into a defined set of interval values. Experiments showed that algorithms like Naive Bayes works well with discretized feature values
Views: 54025 Rushdi Shams
PROFIL SATU DATA INDONESIA
 
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Satu Data adalah sebuah inisiatif pemerintah Indonesia untuk mendorong pengambilan kebijakan berdasarkan data. Untuk mewujudkan hal tersebut, maka diperlukan pemenuhan atas data pemerintah yang akurat, terbuka, dan interoprable. Satu Data memiliki tiga prinsip utama yaitu, satu standar data, satu metadata baku, dan satu portal data. Dengan demikian, pemanfaatan data pemerintah tidak hanya terbatas pada penggunaan secara internal antar instansi, tetapi juga sebagai bentuk pemenuhan kebutuhan data publik bagi masyarakat. Melalui inisiatif Satu Data, Kantor Staf Presiden (KSP) bersama Kementerian Perencanaan Pembangunan Nasional (PPN) / Bappenas serta didukung oleh Badan Pusat Statistik (BPS) dan Badan Informasi Geospasial (BIG) berupaya penuh untuk melakukan pembenahan atas data pemerintah Indonesia. Satu Data menggunakan prinsip data terbuka dalam merilis data. Data tersedia dalam format terbuka yang mudah digunakan kembali, dengan tujuan untuk meningkatkan transparansi dan akuntabilitas pemerintah, serta untuk meningkatkan partisipasi masyarakat dalam mengawal pembangunan. Data.go.id adalah portal resmi Satu Data Indonesia sebagai wujud operasionalisasi rilis dan pemanfaatan data terbuka, yang tidak terbatas pada kementerian, lembaga, atau pemerintah daerah saja, namun juga semua instansi lain yang menghasilkan data terkait Indonesia. • Website : http://www.data.go.id • E-mail : [email protected] • Sosial Media : Facebook : https://www.facebook.com/datagoid/ Instagram : http://www.instagram.com/data.go.id Twitter : http://www.twitter.com/datagoid
Views: 246 Satu Data Indonesia
Weka Yazılımını Yakından Tanıyalım
 
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Weka, Weka Programı, Weka Programı Tanıtımı, Weka Yazılımını Yakından Tanıyalım TAGS veri madenciliği yöntemleri, veri madenciliği nedir, microsoft excell, makro nedir, makrolarla excell dersleri, mining data, mining, datamining, what is data, data mining pdf, data mining techniques, data analysis, mineria, mineria de datos, data warehouse, data warehousing, database, data mining algorithm, data mining ppt, database mining, data mining software, big data, clustering, data mining tools, google data mining, classification, big data mining, smite, datamining smite, smite data mining, coursera, smite reddit, smite patch notes, smite wiki,0 gw2 data mining, big data analytics, bigdata, big data mining, big data, slideshare, kaggle, data scientist, hadoop,0 data mining meaning, jurnal data mining, python data mining, data mining adalah, nptel, python, data mining pdf TAGS https://www.kodkolik.net/
WEKA - Birliktelik Analizi
 
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Weka, Weka Analiz, WEKA - Birliktelik Analizi TAGS veri madenciliği yöntemleri, veri madenciliği nedir, microsoft excell, makro nedir, makrolarla excell dersleri, mining data, mining, datamining, what is data, data mining pdf, data mining techniques, data analysis, mineria, mineria de datos, data warehouse, data warehousing, database, data mining algorithm, data mining ppt, database mining, data mining software, big data, clustering, data mining tools, google data mining, classification, big data mining, smite, datamining smite, smite data mining, coursera, smite reddit, smite patch notes, smite wiki,0 gw2 data mining, big data analytics, bigdata, big data mining, big data, slideshare, kaggle, data scientist, hadoop,0 data mining meaning, jurnal data mining, python data mining, data mining adalah, nptel, python, data mining pdf TAGS https://www.kodkolik.net/ Weka, makine öğrenimi amacıyla Waikato Üniversitesinde geliştirilmiş ve "Waikato Environment for Knowledge Analysis" kelimelerinin baş harflerinden oluşmuş yazılımın ismidir. Günümüzde yaygın kullanımı olan çoğu makine öğrenimi algoritmalarını ve metotlarını içermektedir. Java dilinde geliştirilmiş olması ve kütüphanelerinin .jar dosyaları halinde geliyor olması sayesinde, Java dilinde yazılan projelere kolayce entegre edilebilmesi kullanımını daha da yaygınlaştırmıştır Yazılım, GNU Genel Kamu Lisansı ile dağıtılmaktadır. Weka, tamamen modüler bir tasarıma sahip olup, içerdiği özelliklerle veri kümeleri üzerinde görselleştirme, veri analizi, iş zekası uygulamaları, veri madenciliği gibi işlemler yapabilmektedir. Weka yazılımı, kendisine özgü olarak bir .arff uzantısı desteği ile gelmektedir. Ancak Weka yazılımının içerisinde CSV dosyalarını da ARFF formatına çevirmeye yarayan araçlar mevcuttur. Temel olarak aşağıdaki 3 Veri Madenciliği işlemi Weka ile yapılabilir: Sınıflandırma (Classification) Bölütleme (Clustering) İlişkilendirme (Association) Ayrıca yukarıdaki işlemlere ilave olarak, veri kümeleri üzerinde ön ve son işlemler yapılabilir Veri Ön işleme (Data Pre-Processing) Görselleme (Visualization) Son olarak Weka Kütüphanesi'nde veri kümelerini içeren dosyalar üzerinde çalışan çok sayıda hazır fonksiyon bulunmaktadır. Machine Learning Group at the University of Waikato Project Software Book Publications People Related Weka 3: Data Mining Software in Java Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes. Found only on the islands of New Zealand, the Weka is a flightless bird with an inquisitive nature. The name is pronounced like this, and the bird sounds like this. Weka is open source software issued under the GNU General Public License. We have put together several free online courses that teach machine learning and data mining using Weka. Check out the website for the courses for details on when and how to enrol. The videos for the courses are available on Youtube. Yes, it is possible to apply Weka to big data!
5W 1H DATA WAREHOUSE, EGA CLAUDIA I A , RIZKI WIDY
 
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"5W 1H DATA WAREHOUSE, EGA CLAUDIA I A 135150401111122, RIZKI WIDYA PRIYANGGA 135150401111153 ,FILKOM UNIVERSITAS BRAWIJAYA" Pembuatan video ini adalah untuk memenuhi tugas Data Maining & Data Warehouse (DMDW) yang di berikan oleh Asisten Praktikum guna menambah nilai pada praktikum matakuliah DMDW. Semoga video ini dapat memenuhi syarat dari penilaian kategori video yang sudah di tentukan. Amin Terima Kasih, silahkan like jika video ini menginspirasi anda semua. :D
An Introduction to Linear Regression Analysis
 
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Tutorial introducing the idea of linear regression analysis and the least square method. Typically used in a statistics class. Playlist on Linear Regression http://www.youtube.com/course?list=ECF596A4043DBEAE9C Like us on: http://www.facebook.com/PartyMoreStudyLess Created by David Longstreet, Professor of the Universe, MyBookSucks http://www.linkedin.com/in/davidlongstreet
Views: 587999 statisticsfun
DATABASE MENAJEMEN SISTEM
 
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Data merupakan fakta atau nilai (value) yang tercatat atau merepresentasikan deskripsi dari suatu obyek. Data yang merupakan fakta yang tercatat dan selanjutnya dilakukan pengolahan (proses) menjadi bentuk yang berguna atau bermanfaat bagi pemakainya akan membentuk apa yang disebut informasi. secara konsep basis data atau database adalah kumpulan dari data-data yang membentuk suatu berkas (file) yang saling berhubungan (relation) dengan tata cara yang tertentu untuk membentuk data baru atau informasi. Atau Basis data (database) merupakan kumpulan dari data yang saling berhubungan (relasi) antara satu dengan lainnya yang diorganisasikan berdasarkan skema atau struktur tertentu
Views: 16 MASDIDI CHANNEL
IMPLEMENTASI DATA WAREHOUSE PADA RUMAH SAKIT
 
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FE02 5211100003_5211100069_5211100071_5211100087 5211100090_5211100094_5211100138_5211100166
Views: 635 Dyah Retnani
Machine Learning - Kelompok 6 : Support Vector Machine (SVM) Ilmu Komputer 2014 Unhas
 
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Tugas kelompok Mata Kuliah Pembelajaran Mesin
Views: 385 Matt Hammet
Pengolahan Data Regresi Berganda dengan Software SPSS dan Cara Manual #4
 
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Video pengolahan data regresi berganda dengan software SPSS dan cara manual ini dibuat oleh mahasiswa-mahasiswi Prodi Pendidikan Matematika semester 2 angkatan 2016 dari Universitas Kristen Indonesia, yang beranggotakan Lucky Clinton Retify, Cipto Hardiansyah, Gita Meylisa Yolanda, dan Novia Angela Natawidjaja. . Analisis regresi linier berganda adalah hubungan secara linear antara dua atau lebih variabel independen (X1, X2,….Xn) dengan variabel dependen (Y), serta software SPSS adalah aplikasi untuk melakukan analisis statistik. SPSS merupakan singkatan dari Statistical Package for the Social Sciences. Sedangkan yang dimaksud dengan cara manual ialah menghitung data dengan berbagai rumus.
Views: 310 Matematika UKI
Box Plots
 
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Use this lesson and activity free at http://www.brainingcamp.com/resources/math/. Learn that Box and Whisker Plots are graphs that show the distribution of data along a number line. See how to construct box plots by ordering a data set to find the median of the set of data, median of the upper and lower quartiles, and upper and lower extremes. Draw a Box and Whisker plot and learn how to use box plots to solve a real world problem. See how to construct box plots if there are no middle values
Views: 644549 Brainingcamp
Veri Madenciliği(Excel -  Karışık Örnekler)
 
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Veri Madenciliği, Veri Madenciliği Dersleri, Veri Madenciliği Eğitim Seti, Veri Madenciliği Dersleri Serisi, Veri Madenciliği(Excel - Karışık Örnekler) TAGS veri madenciliği yöntemleri, veri madenciliği nedir, microsoft excell, makro nedir, makrolarla excell dersleri, mining data, mining, datamining, what is data, data mining pdf, data mining techniques, data analysis, mineria, mineria de datos, data warehouse, data warehousing, database, data mining algorithm, data mining ppt, database mining, data mining software, big data, clustering, data mining tools, google data mining, classification, big data mining, smite, datamining smite, smite data mining, coursera, smite reddit, smite patch notes, smite wiki,0 gw2 data mining, big data analytics, bigdata, big data mining, big data, slideshare, kaggle, data scientist, hadoop,0 data mining meaning, jurnal data mining, python data mining, data mining adalah, nptel, python, data mining pdf TAGS http://kodkolik.net/ Machine Learning Group at the University of Waikato Project Software Book Publications People Related Weka 3: Data Mining Software in Java Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes. Found only on the islands of New Zealand, the Weka is a flightless bird with an inquisitive nature. The name is pronounced like this, and the bird sounds like this. Weka is open source software issued under the GNU General Public License. We have put together several free online courses that teach machine learning and data mining using Weka. Check out the website for the courses for details on when and how to enrol. The videos for the courses are available on Youtube. Yes, it is possible to apply Weka to big data!