Tugas PTI HI UP 2018

AI has 2 categories namely weak or strong. Weak AI also known as narrow AI. Weak AI is an AI system designed and trained for certain tasks. Weak AI can be a virtual personal assistant, like Apple Siri, Amazon’s Alexa, and Google Home. While strong AI, also known as general artificial intelligence, is an AI system with general human cognitive abilities. When a special task is presented, a strong AI system can find its own solution without human intervention. S trong AI acts more like a brain. It does not classify, but uses clustering and association to process data. In short, it means there isn’t a set answer to your keywords.  Beside that, an assistant professor of integrative biology and computer science engineering at Michigan State University, Arend Hintze, categorizes AI into 4 types, ranging from existing AI systems to AI systems that are still in design. The categories are as follows: Reactive machine. An example is Deep Blue, the IBM chess program that defeated Garr...

Artificial intelligence is the simulation of human intelligence process by machines, especially computer systems. Its shaping many industries even when its new compared to other technologies and becomes the important part of our daily life. These process include learning ( the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions) and self correction. Artificial intelligence is the simulation of human intelligence process by machines, especially computer systems. Its shaping many industries even when its new compared to other technologies and becomes the important part of our daily life. These process include learning ( the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions) and self correction. Every technology has its advantages and disadvantages but advantages always outweigh disadvantages for the technology to surv...

So what is image analysis? Basically image analysis is a program for identifying subject from the image, it can identyfying color, shape, and etc. This technology still being developed to get the closer result like human eyes. This day the image analysis technology is very important for computer, so the computer can easly recognize something by an image and get new information from the similar data. Image analysis basically just like reading a barcode. So by only submit the image to the application you can get all the result that you want, you can get all the information, all the similar image, and etc. Image analysis also teach a computer to see, how? Just like the way we see something, a computer use computer vision and image recognition. But not with the eyes but with the processing part. AI powered by image recognition uses computer vision to make sense of input recieved. Google image search is an example. But what the different between image analysis and image recognition? ...

Artificial Neural Network  is a computational model based on the structure and functions of biological neural networks. Information that flows through the network affects the  a neural network changes or learns, based on that input and output. So the point is  to create a computational system that could solve problems like a human brain. The Neural Networks was founded by  Warren McCulloch and Walter Pitts in 1943. Then it was upgraded with AI (Artificial Intelligence) in 1975 by Kunijiko Fukushima called Artificial Neural Network (ANN) .   Warren McCulloch and Walter Pitts Today  Neural Networks are important in information age, because help society to solve complex problems in real life condition. They can learn from model the relationships between inputs and outputs that are nonlinear and complex; make generalizations and inferences; reveal hidden relationships, patterns and predictions (such as financial time series data) and varianc...

Artificial Intelligence is a branch of computer science that aims to create intelligent machines. It has become an essential part of the technology industry. Research associated with artificial intelligence is highly technical and specialized. Artificial intelligence is a very broad term that includes things from Apple’s Siri and Amazon’s Alexa, to, more recently, more complex things like autonomous vehicles and robotics with the ability to interact and adjust appropriately to their environment in order to complete small tasks. It is growing in importance every year, with new forms and uses constantly being dreamt up and brought to life.   Even though artificial intelligence may have  positive  outcomes and negative outcomes. The positive outcomes is, first, increased production and indirectly lowered costs have already been witnessed in factories and production lines. Artificial intelligence is also being pursued to replace humans in dangerous situations...

Big data itself is an extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions. Big data is also a term that describes the large volume of data – both structured and unstructured – that inundates a business on a day-to-day basis. By using big data, various organization can generate actionable insights that enable them to drive their business forward. Data sets grow rapidly, because they are gathered by numerous devices such as mobile phone, cameras, microphones, wireless sensor networks, etc.  Big data also have various sources. I’ve put together the main five sources of big data and explain them one by one in short explanation. Media Media is number one and most popular source of big data, since media can provide valuable insights. Media is also the fastest way for businesses to get in depth overview of their target audience. Media includes social media and an...

Big Data: Big Data Technologies Have a Challenges? B usiness people are now looking for more data for good reasons that support digital commerce. However, turning that large data set into actionable insights is still difficult. Organizations seeking solutions to the challenges of great data will be better positioned to get the economic benefits of the fruits of digital innovation. One of the reasons big data is so underutilized is because big data and big data technologies also present many challenges. the following are the biggest challenges in managing big data technologies: Data Management Still Difficult The big idea behind big data analysis is quite clear, finding interesting patterns placed in the amount of data, pattern-gathering patterns and applying various models to provide the best solution. However, this should be very difficult to understand. For starters, collecting data from several different sources remains difficult and requires data-based ETL skills. Cleanin...

RFM Analysis For Successful Customer Segmentation Analysis RFM in Big Data RFM (Recency, Frequency, Monetary) analysis is a proven marketing model for behavior based customer segmentation. It groups customers based on their transaction history – how recently, how often and how much did they buy. RFM helps divide customers into various categories or clusters to identify customers who are more likely to respond to promotions and also for future personalization services. RFM analysis evaluates which customers are of highest and lowest value to an organization based on purchase recency, frequency, and monetary value, in order to reasonably predict which customers are more likely to make purchases again in the future. What are Recency, Frequency and Monetary? ·         Recency      : How much time has elapsed since a customer’s last activity or transaction with the brand. ·     ...