scholarly journals Application of K-Means Algorithm to Mapping Poverty Outline by Province in India

2020 ◽  
Vol 8 (6) ◽  
pp. 1045-1049
Keyword(s):  
Data Mining ◽  
Poverty Line ◽  
Line Number ◽  
Process Data ◽  
Class Label ◽  
Data Utilization ◽  
Data Similarity ◽  
New Information ◽  
The World ◽  
Mining Methods

India has a second largest population and seventh largest country in the world, the UN data in 2018 recorded that there were 1,368,681,134 more people scattered throughout the Indian provinces. In addition, India also has a variety of social problems, one of which is poverty. The poverty line number in Indonesia needs to be improved. Data utilization techniques become new information called data mining. One of the most popular data mining methods is clustering using the k-means algorithm. K-means can process data without being notified in advance of the class label. This study will produce three provincial groups according to very low, low and sufficient income figures. Data processing of poverty line numbers in India using the k-means algorithm to get the results of the Davies Bouldin index of 0.271. These results are considered well enough because the closer the results obtained with zeros, the better the data similarity between members of the cluster.

scholarly journals Market Basket Analysis for Determination of Consumer Behavior at XYZ Stores Using R Programming

2021 ◽  
Vol 3 (2) ◽  
pp. 0210206
Author(s):  
Kelik Sussolaikah
Keyword(s):  
Data Mining ◽  
Consumer Behavior ◽  
Market Basket Analysis ◽  
Process Data ◽  
Market Basket ◽  
Data Mining Techniques ◽  
Programming Tool ◽  
The World ◽  
R Programming

Data mining is one of the fields of science in the world of informatics which has an important role, especially with regard to data. There are many algorithms and methods that can be used to process data. The paper this time the author tries to conduct research on consumer behavior by using one of the data mining techniques, namely market basket analysis. This research uses the R Programming tool, where it is hoped that the research can be carried out effectively and efficiently. Based on the research conducted, it is known that there has been a significant purchase of several items that have been described as a plot. The tendency of consumers to buy several items followed by other items can be a consideration for arranging the layout of goods on the sales shelf or arranging product stock in a supermarket.

Knowledge Discovery with Artificial Neural Networks

2011 ◽  
pp. 669-673
Author(s):  
Juan R. Rabuñal Dopico ◽  
Daniel Rivero Cebrian ◽  
Julián Dorado de la Calle ◽  
Nieves Pedreira Souto
Keyword(s):  
Data Mining ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Knowledge Discovery ◽  
Powerful Technique ◽  
Complex Problems ◽  
New Information ◽  
Wide Range ◽  
The World ◽  
Artificial Neural

The world of Data Mining (Cios, Pedrycz & Swiniarrski, 1998) is in constant expansion. New information is obtained from databases thanks to a wide range of techniques, which are all applicable to a determined set of domains and count with a series of advantages and inconveniences. The Artificial Neural Networks (ANNs) technique (Haykin, 1999; McCulloch & Pitts, 1943; Orchad, 1993) allows us to resolve complex problems in many disciplines (classification, clustering, regression, etc.), and presents a series of advantages that convert it into a very powerful technique that is easily adapted to any environment. The main inconvenience of ANNs, however, is that they can not explain what they learn and what reasoning was followed to obtain the outputs. This implies that they can not be used in many environments in which this reasoning is essential.

Visual Data Mining in Physiotherapy Using Self-Organizing Maps

2012 ◽  
pp. 187-194 ◽  
Author(s):  
Yasser Alakhdar ◽  
José M. Martínez-Martínez ◽  
Josep Guimerà-Tomás ◽  
Pablo Escandell-Montero ◽  
Josep Benitez ◽  
...  
Keyword(s):  
Data Mining ◽  
Cruciate Ligament ◽  
Visual Data ◽  
Visual Data Mining ◽  
Process Data ◽  
Self Organizing Maps ◽  
Clinical Specialist ◽  
Post Surgery ◽  
Mining Methods ◽  
Anterior Cruciate

The basis of all clinical science developments is the analysis of the data obtained from a particular problem. In recent decades, however, the capacity of computers to process data has been increasing exponentially, which has created the possibility of applying more powerful methods of data analysis. Among these methods, the multidimensional visual data mining methods are outstanding. These methods show all the variables of one particular problem on the whole allowing to the clinical specialist to extract his own conclusions. In this chapter, a neural approximation to this kind of data mining is shown by means of the valuation analysis of the knee in athletes in the pre- and post-surgery of the anterior cruciate ligament, studying variables of force and measurements at different distances of the knee.

scholarly journals Website evaluation using opinion mining

2018 ◽  
Vol 7 (2.7) ◽  
pp. 51
Author(s):  
T V.R. Sai ◽  
SK Haaris ◽  
S Sridevi
Keyword(s):  
Data Mining ◽  
Opinion Mining ◽  
User Feedback ◽  
The Internet ◽  
Website Evaluation ◽  
The World ◽  
Frame Work ◽  
Mining Methods ◽  
Feedback Data

In this project we used opinion mining methods to evaluate various websites present on the internet. We also analyzed the approaches, tools, and dataset used by Scholars with their accuracy and we used this technology for evaluation of a website. Opinion mining is used in various scenarios around the world. But it is hardly used in websites evaluation which we are implementing with this project, as now a day’s, websites we regularly use are spamming with advertisements and unusable content. This paper proposed a frame work of evaluating a website using the user feedback on the website collected on our website. That collected feedback data is processed using a data mining software that is rapid miner. 

scholarly journals PENERAPAN DATA MINING DENGAN ALGORITMA C4.5 UNTUK KALKULASI DATA DALAM AL-QUR’AN TERJEMAHAN

2019 ◽  
Vol 6 (2) ◽  
pp. 152
Author(s):  
Asmira Mira Rusli
Keyword(s):  
Data Mining ◽  
Decision Trees ◽  
The World ◽  
C4.5 Algorithm ◽  
Mining Methods

<p><em>Al-Qur'an was delivered by Prophet Muhammad SAW to mankind to become a guide in life in the world, which has 30 Juz, 114 suras and 6,236 verses. In the Qur'an there are many words that are repeated in a surah on a particular topic. To find out the number of repetitions of the word, an application of data calculations is built in the Al-Qur'an translation that can facilitate the calculation of words. So that users can quickly find out the number of words that repeat and how accurate the data is. This application is made with C4.5 algorithm, one of the data mining methods. Using the C4.5 algorithm is expected to be able to solve the problem of search and calculation in the translation of the Qur'an. The advantages of the C4.5 algorithm are producing decision trees that can be easily interpreted, as well as acceptable and efficient levels of accuracy. In this case the accuracy of the C4.5 algorithm reaches 80%.</em></p><p><em><strong>Keywords</strong></em><em>: </em><em>al-quran, data mining, algoritma </em>C4.5</p><p><em>Al-Qur’an </em><em>disampaikan oleh Nabi Muhammad SAW kepada umat manusia untuk dijadikan pedoman dalam kehidupan di dunia, yang </em><em>mempunyai 30 Juz, 114 surah dan 6</em><em>.</em><em>236 ayat. Dalam Al-Qur’an </em><em>terdapat banyak kata yang berulang dalam suatu surah mengenai topik tertentu. Untuk mengetahui jumlah perulangan kata tersebut, maka dibangun sebuah aplikasi kalkulasi data dalam Al-Qur’an terjemahan yang dapat mempermudah pengkalkulasian kata. Sehingga pengguna bisa dengan cepat mengetahui jumlah kata yang berulang serta seberapa akuratnya data tersebut. Aplikasi ini dibuat dengan algoritma C4.5 salah satu metode data mining. Dengan menggunakan algoritma C4.5 diharapkan mampu menyelesaikan masalah pencarian dan pengkalkulasian dalam terjemahan Al-Qur’an. </em><em>Kelebihan </em><em>dari </em><em>algoritma C4.5 </em><em>yaitu </em><em>menghasilkan pohon keputusan yang </em><em>dapat dengan </em><em>mudah diinterprestasikan, </em><em>serta </em><em>tingkat akurasi yang dapat diterima dan efisien. </em><em>Dalamm kasus ini tingkat akurasi Algoritma C4.5 mencapai 80%</em><em>.</em></p><p><em><strong>Kata kunci</strong></em><em>: </em><em>al-quran, data mining, algoritma </em>C4.5</p>

Visual Data Mining in Physiotherapy Using Self-Organizing Maps

Data Mining ◽  
2013 ◽  
pp. 650-657 ◽  
Author(s):  
Yasser Alakhdar ◽  
José M. Martínez-Martínez ◽  
Josep Guimerà-Tomás ◽  
Pablo Escandell-Montero ◽  
Josep Benitez ◽  
...  
Keyword(s):  
Data Mining ◽  
Cruciate Ligament ◽  
Visual Data ◽  
Visual Data Mining ◽  
Process Data ◽  
Self Organizing Maps ◽  
Clinical Specialist ◽  
Post Surgery ◽  
Mining Methods ◽  
Anterior Cruciate

The basis of all clinical science developments is the analysis of the data obtained from a particular problem. In recent decades, however, the capacity of computers to process data has been increasing exponentially, which has created the possibility of applying more powerful methods of data analysis. Among these methods, the multidimensional visual data mining methods are outstanding. These methods show all the variables of one particular problem on the whole allowing to the clinical specialist to extract his own conclusions. In this chapter, a neural approximation to this kind of data mining is shown by means of the valuation analysis of the knee in athletes in the pre- and post-surgery of the anterior cruciate ligament, studying variables of force and measurements at different distances of the knee.

Analysis of Heart Disorder by Using Machine Learning Methods and Data Mining Techniques

2021 ◽  
pp. 212-221
Author(s):  
Sarangam Kodati ◽  
Jeeva Selvaraj
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Support Vector Machine ◽  
Heart Disease ◽  
Heart Diseases ◽  
Support Vector ◽  
Primary Reason ◽  
The World ◽  
Mining Methods ◽  
Using Data

Data mining is the most famous knowledge extraction approach for knowledge discovery from data (KDD). Machine learning is used to enable a program to analyze data, recognize correlations, and make usage on insights to solve issues and/or enrich data and because of prediction. The chapter highlights the need for more research within the usage of robust data mining methods in imitation of help healthcare specialists between the diagnosis regarding heart diseases and other debilitating disease conditions. Heart disease is the primary reason of death of people in the world. Nearly 47% of death is caused by heart disease. The authors use algorithms including random forest, naïve Bayes, support vector machine to analyze heart disease. Accuracy on the prediction stage is high when using a greater number of attributes. The goal is to function predictive evaluation using data mining, using data mining to analyze heart disease, and show which methods are effective and efficient.

scholarly journals Research of Chronic Kidney Disease based on Data Mining Techniques

2019 ◽  
Vol 8 (2S11) ◽  
pp. 115-120
Keyword(s):  
Data Mining ◽  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Information Mining ◽  
Data Mining Techniques ◽  
Medical Issues ◽  
The World ◽  
Mining Methods ◽  
The Given ◽  
Low Pay

Kidney disease is one of the real general medical issues these days. Ceaseless ailments prompt to horribleness and mortality in India and furthermore in the low pay and center nation. The interminable infections on record is 60% of death all through the around the world. 80% of unending malady passing overall additionally happen in low and center pay nations. In India, most likely the quantity of passing is because of the ceaseless ailment observed to be 5.21 million in 2008 and is by all accounts brought to 7.63 million up in 2020 roughly 66.7%. Information mining is the procedure of extraction is the concealed data from the given expansive dataset. Different information mining strategies, for example, bunching, characterization, affiliation investigation, relapse, outline, time arrangement examination and succession investigation were utilized to anticipate kidney maladies. The strategies that were presented so far had minor downsides in the nature of pre handling or at some other stages. In this paper, the different information mining methods are reviewed to foresee kidney sicknesses and real issues are quickly clarified

THE MODEL FOR THE ANALYSIS OF PHARMACOEPIDEMIOLOGICAL DATA BASED ON DATA MINING METHODS

2017 ◽  
Vol 19 (10) ◽  
pp. 289-298
Author(s):  
I.M. Burykin ◽  
◽  
G.N. Aleeva ◽  
R.Kh. Khafizianova ◽  
◽  
...  
Keyword(s):  
Data Mining ◽  
Mining Methods
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