Iwan Tri Riyadi Yanto
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View article: High Accuracy Data Classification and Feature Selection for Incomplete Information Systems Using Extended Limited Tolerance Relation and Conditional Entropy Approach
High Accuracy Data Classification and Feature Selection for Incomplete Information Systems Using Extended Limited Tolerance Relation and Conditional Entropy Approach Open
Data classification and feature/attribute selection approaches play important role in enabling organizations to extract meaningful insights from vast and complex datasets. Besides, the accuracy and processing time are two parameters of int…
View article: Depression Detection on Mandarin Text through Bert Model
Depression Detection on Mandarin Text through Bert Model Open
Depression is currently one of the most prevalent mental disorders and its incidence has been rising significantly in Malaysia amid the Covid-19 pandemic. While previous studies have demonstrated the potential of artificial intelligence te…
View article: Fuzzy Soft Set Clustering for Categorical Data
Fuzzy Soft Set Clustering for Categorical Data Open
Categorical data clustering is difficult because categorical data lacks natural order and can comprise groups of data only related to specific dimensions. Conventional clustering, such as k-means, cannot be openly used to categorical data.…
View article: Soft Set Parametric-based Data Clustering for Building Data Set
Soft Set Parametric-based Data Clustering for Building Data Set Open
Identifying buildings for safety purposes is critical to anticipate unforeseen scenarios during a disaster. Rapid Visual Screening (RVS) is one of the procedures that can be used to determine a building's hazardous structure. The growing n…
View article: Data Clustering for Identification of Building Conditions Using Hybrid Multivariate Multinominal Distribution Soft Set (MMDS) Method
Data Clustering for Identification of Building Conditions Using Hybrid Multivariate Multinominal Distribution Soft Set (MMDS) Method Open
Identifying building conditions for user safety is an urgent matter, especially in earthquake-prone areas. Clustering buildings according to their conditions in the categories of danger, vulnerable, normal, and safe is important informatio…
View article: Fast Building Identification Using Fuzzy Soft Set Based on Rapid Visual Building (RVS)
Fast Building Identification Using Fuzzy Soft Set Based on Rapid Visual Building (RVS) Open
Building damage can be caused by disasters such as earthquakes, landslides, etc. To minimize the fatality, the identification of buildings is needed to know the condition of buildings and whether the construction of buildings is able to en…
View article: Soft Set Multivariate Distribution for Categorical Data Clustering
Soft Set Multivariate Distribution for Categorical Data Clustering Open
Clustering is the process of breaking down a huge dataset into smaller groups. It has been used in some field studies including pattern recognition, segmentation, and statistics with remarkable success. Clustering is a technique for dividi…
View article: Fast Clustering Environment Impact using Multi Soft Set Based on Multivariate Distribution
Fast Clustering Environment Impact using Multi Soft Set Based on Multivariate Distribution Open
Every development activity is always related to human or community aspects. This can also lead to changes in the characteristics of the community. The community's increasing awareness and critical attitude need to be accommodated to avoid …
View article: Similarity measure fuzzy soft set for phishing detection
Similarity measure fuzzy soft set for phishing detection Open
Phishing is a serious web security problem, and the internet fraud technique involves mirroring genuine websites to trick online users into stealing their sensitive information and taking out their personal information, such as bank accoun…
View article: A Framework of Mutual Information Kullback-Leibler Divergence based for Clustering Categorical Data
A Framework of Mutual Information Kullback-Leibler Divergence based for Clustering Categorical Data Open
Clustering is a process of grouping a set of objects into multiple clusters, so that the collection of similar objects will be grouped into the same cluster and dissimilar objects will be grouped into other clusters. Fuzzy k-means Algorith…
View article: Generalized Normalized Euclidean Distance Based Fuzzy Soft Set Similarity for Data Classification
Generalized Normalized Euclidean Distance Based Fuzzy Soft Set Similarity for Data Classification Open
Classification is one of the data mining processes used to predict predetermined target classes with data learning accurately. This study discusses data
\nclassification using a fuzzy soft set method to predict target classes accurately.
\…
View article: Laying Chicken Algorithm (LCA) Based For Clustering
Laying Chicken Algorithm (LCA) Based For Clustering Open
Numerous research and related applications of fuzzy clustering are still interesting and important. In this paper, Fuzzy C-Means (FCM) and Laying Chicken Algorithm (LCA) were modified to improve local optimum of Fuzzy Clustering presented …
View article: A Relative Tolerance Relation of Rough Set in Incomplete Information
A Relative Tolerance Relation of Rough Set in Incomplete Information Open
University is an educational institution that has objectives to increase student retention and also to make sure students graduate on time.Student learning performance can be predicted using data mining techniques e.g. the application of f…
View article: Soft Set Theory Based Decision Support System for Mining Electronic Government Dataset
Soft Set Theory Based Decision Support System for Mining Electronic Government Dataset Open
Electronic government (e-gov) is applied to support performance and create more efficient and effective public services. Grouping data in soft-set theory can be considered as a decision-making technique for determining the maturity level o…
View article: Variable precision rough set model for attribute selection on environment impact dataset
Variable precision rough set model for attribute selection on environment impact dataset Open
The investigation of environment impact have important role to development of a city. The application of the artificial intelligence in form of computational models can be used to analyze the data. One of them is rough set theory. The util…
View article: A Comparative Analysis of Rough Sets for Incomplete Information System in Student Dataset
A Comparative Analysis of Rough Sets for Incomplete Information System in Student Dataset Open
Rough set theory is a mathematical model for dealing with the vague, imprecise, and uncertain knowledge that has been successfully used to handle incomplete information system. Since we know that in fact, in the real-world problems, it is …
View article: A Soft Set-based Co-occurrence for Clustering Web User Transactions
A Soft Set-based Co-occurrence for Clustering Web User Transactions Open
Grouping web transactions into some clusters are essential to gain a better understanding the behavior of the users, which e-commerce companies widely use this grouping process. Therefore, clustering web transaction is important even thoug…
View article: An Application of Rough Set Theory for Clustering Performance Expectancy of Indonesian e-Government Dataset
An Application of Rough Set Theory for Clustering Performance Expectancy of Indonesian e-Government Dataset Open
Performance expectancy has been studied as an important factor which influences e-government. Therefore, grouping of e-government users involving performance expectancy factor is still challenging. Computational model can be explored as an…
View article: A Framework of Clustering Based on Chicken Swarm Optimization
A Framework of Clustering Based on Chicken Swarm Optimization Open
Chicken Swarm Optimization (CSO) algorithm which is one of the most recently introduced optimization algorithms, simulates the intelligent foraging behaviour of chicken swarm. Data clustering is used in many disciplines and applications. I…
View article: Histogram Thresholding for Automatic Color Segmentation Based on k-means Clustering
Histogram Thresholding for Automatic Color Segmentation Based on k-means Clustering Open
Color segmentation method has been proposed and developed by many researchers, however it still become a challenging topic on how to automatically segment color image based on color information. This research proposes a method to estimate …
View article: Clustering Based on Classification Quality (CCQ)
Clustering Based on Classification Quality (CCQ) Open
Clustering a set of objects into homogeneous classes is a fundamental operation in data mining. Categorical data clustering based on rough set theory has been an active research area in the field of machine learning. However, pure rough se…
View article: Application of Wavelet De-noising Filters in Mammogram Images Classification Using Fuzzy Soft Set
Application of Wavelet De-noising Filters in Mammogram Images Classification Using Fuzzy Soft Set Open
Recent advances in the field of image processing have revealed that the level of noise in mammogram images highly affect the images quality and classification performance of the classifiers. Whilst, numerous data mining techniques have bee…
View article: Ringed Seal Search for Global Optimization via a Sensitive Search Model
Ringed Seal Search for Global Optimization via a Sensitive Search Model Open
The efficiency of a metaheuristic algorithm for global optimization is based on its ability to search and find the global optimum. However, a good search often requires to be balanced between exploration and exploitation of the search spac…
View article: Alternative Technique reducing complexity of Maximum Attribute Relation
Alternative Technique reducing complexity of Maximum Attribute Relation Open
Clustering refers to the method grouping the large data into the smaller groups based on the similarity measure. Clustering techniques have been applied on numerical, categorical and mix data. One of the categorical data clustering techniq…
View article: Alternative Technique reducing complexity of Maximum Attribute Relation
Alternative Technique reducing complexity of Maximum Attribute Relation Open
Clustering refers to the method grouping the large data into the smaller groups based on the similarity measure. Clustering techniques have been applied on numerical, categorical and mix data. One of the categorical data clustering techniq…
View article: Automatic differentiation based for particle swarm optimization Steepest descent direction
Automatic differentiation based for particle swarm optimization Steepest descent direction Open
Particle swam optimization (PSO) is one of the most effective optimization methods to find the global optimum point. In other hand, the descent direction (DD) is the gradient based method that has the local search capability. The combinati…