The Decision Tree Algorithm is an algorithm that has its main advantages compared to other algorithms, the decision tree algorithm is a classification algorithm that is commonly used. The Decision Tree C5.0 algorithm has ...

The search for the shortest path is the search for a path in a weighted graph that minimizes the sum of the weights of the edges forming the path. Determining the shortest path also really needs a path availability analysis ...

Self-organizing Maps is one of the methods in Artificial Neural Networks are able to learn on their own and are often used for pattern recognition or image .. The most decisive in the learning process Self Organizing ...

The similarity calculation is a basic function which is used by a wide range of infotn1ation processing applications such as searching for clustering and classification. There are different types of relationships can be ...

On agricultural area in particular on oil palm agronomy, agribusinesses increasing effort oil palm plant be still experience interference. Main interference that often been faced is its low problem quality and oil palm ...

The problems on a company or institution is often contrained on decision makers. Computer science concept come with supporting computer - based decision making (Computer Based Decision Support System). In many decision ...

Knowledge of computer vision technology is advancing and in line with the need for a system that is controlled continuously, causing research in the field of computer vision will continue to be made. The need for vehicle ...

Cryptography as a field of science that focuses on data and network security is one of the fields of science that demands innovation, as well as creativity both in the implementation, development, and creation of new ...

The ANFIS algorithm is a technique in data mining that can be used for the data classification process. The ANFIS algorithm still has weaknesses, especially in determining the initial parameters for the network training ...

As a novel and efficient ensemble learning algorithm, XGBoost has been widely applied due to its multiple advantages, but its classification effect in cases of data imbalance is often not ideal. Because of it, efforts ...