scholarly journals Implementation of Data Mining Technique for Performance of WFH and WFO Agents Using the K-Means Method Case Study Study of PT. Infomedia Telkom Consumer Profiling Services

2021 ◽  
Vol 3 (2) ◽  
pp. 117-125
Author(s):  
Jaja Jaja ◽  
Nandi Priatna ◽  
Tazkia Salsabila Ardan
Keyword(s):  
Data Mining ◽  
Call Center ◽  
Data Mining Technique ◽  
Working Mechanism ◽  
Mining Technique ◽  
Significant Difference ◽  
Work At Home ◽  
Consumer Profiling ◽  
At Home

Outbound Call Center PT. Infomedia, consumer profiling service PT. Telkom during the pandemic period divided its agents into 80% WFH agents (Work at Home) and 20% agents WFO (Work from Office). For the division of the working mechanism, it is necessary to measure its performance. In the discussion of this paper, we will discuss the measurement with the application of data mining using the K-Means method, so it is hoped that it will provide an overview, how the cluster of each WFH or WFO agent in terms of performance. The results of this discussion indicate that there is a significant difference between the performance of WFH and WFO Agents.

scholarly journals The analysis of agricultural data with regression data mining technique

2015 ◽  
Vol 37 ◽  
pp. 102 ◽  
Author(s):  
Hooman Fetanat ◽  
Leila Mortazavifarr ◽  
Narsis Zarshenas
Keyword(s):  
Data Mining ◽  
Process Model ◽  
Relational Databases ◽  
Ornamental Plants ◽  
Regression Technique ◽  
Data Mining Technique ◽  
Independent Variables ◽  
Mining Technique ◽  
Analytical Tools

Data mining is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue, cuts costs, or both. Data mining software is one of a number of analytical tools for analyzing data. Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases. This paper discusses data mining technique such as regression and clustering which is a process model for analyzing data and describes the support that SPSS provides for this model. SPSS-based analysis and application construction process is illustrated through a case study in the agricultural domain-ornamental plants. Cluster analysis or clustering was used is the task of assigning a set of objects into groups so that the objects in the same cluster are more similar to each other than to those in other clusters. In this survey clustering technique divides growth factors into several independent categories. Also, regression technique which was used includes many techniques for modeling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables. More specifically, regression analysis helps one understand how the typical value of the dependent variable changes when any one of the independent variables is varied, while the other independent variables are held fixed. In this research, analyzed data with regression technique showed the effect of chlorophyll content on the number of flowers.

Data Mining as Support for Customer Relationship Management: A Case Study

2014 ◽  
Vol 13 (11) ◽  
pp. 5113-5120
Author(s):  
José Gonalo Dos Santos
Keyword(s):  
Data Mining ◽  
Information System ◽  
Customer Relationship Management ◽  
Relationship Management ◽  
Customer Relationship ◽  
Data Mining Technique ◽  
Mining Technique ◽  
Association Rules Discovery ◽  
Data Mining Application

This article describes the data mining application to CRM - Customer Relationship Management. The article starts with an introduction showing the importance of the CRM strategy for the company, after it’s introduced the theoretical about CRM, Knowledge Discovery Database and its stages, with emphasis to the mining stage and concludes with presentation of a case study and the conclusions. For the case study it was developed a prototype of an information system of a bookstore, it was implemented, beyond the conventional functions, the association rules discovery algorithm. The implementation of the data mining technique allowed to the system supply support so that the user knows better the client, becoming possible the application of the strategy of CRM.

scholarly journals A FUZZY ASSOCIATIVE CLASSIFICATION APPROACH FOR RECOMMENDER SYSTEMS

2012 ◽  
Vol 20 (04) ◽  
pp. 579-617 ◽  
Author(s):  
JOEL PINHO LUCAS ◽  
ANNE LAURENT ◽  
MARÍA N. MORENO ◽  
MAGUELONNE TEISSEIRE
Keyword(s):  
Data Mining ◽  
Recommender Systems ◽  
Real Data ◽  
Associative Classification ◽  
Data Mining Technique ◽  
Classification Approach ◽  
Mining Technique ◽  
Joint Method ◽  
Hybrid Methodology

Despite the existence of different methods, including data mining techniques, available to be used in recommender systems, such systems still contain numerous limitations. They are in a constant need for personalization in order to make effective suggestions and to provide valuable information of items available. A way to reach such personalization is by means of an alternative data mining technique called classification based on association, which uses association rules in a prediction perspective. In this work we propose a hybrid methodology for recommender systems, which uses collaborative filtering and content-based approaches in a joint method taking advantage from the strengths of both approaches. Moreover, we also employ fuzzy logic to enhance recommendations' quality and effectiveness. In order to analyze the behavior of the techniques used in our methodology, we accomplished a case study using real data gathered from two recommender systems. Results revealed that such techniques can be applied effectively in recommender systems, minimizing the effects typical drawbacks they present.

scholarly journals Validated data mining technique: a case study on pressure-field digital MEMS microphone calibration

2018 ◽  
Vol 1065 ◽  
pp. 072028 ◽  
Author(s):  
G D’Emilia ◽  
A Gaspari ◽  
E Natale ◽  
N Montali ◽  
A Prato ◽  
...  
Keyword(s):  
Data Mining ◽  
Pressure Field ◽  
Data Mining Technique ◽  
Mining Technique ◽  
Mems Microphone

scholarly journals O REGISTRO DE MARCA DOS EXPORTADORES DE AÇAÍ NO PARÁ

2021 ◽  
Vol 9 (211) ◽  
pp. 1-27
Author(s):  
SHEILA DE SOUZA CORREA DE MELO ◽  
ALEXANDRA DE SOUZA CORREA DE MELO
Keyword(s):  
Data Mining ◽  
Public Administration ◽  
Business Plan ◽  
Data Mining Technique ◽  
Industrial Property ◽  
The Public ◽  
Mining Technique ◽  
Using Data ◽  
Educational Campaigns

This research focuses on the registration of trademarks made by açaí exporting companies in the State of Pará with the National Institute of Industrial Property (INPI). The research was methodologically oriented as a case study and was performed using data mining technique in official databases such as INPI e-marcas and DataScience Brasil. The results obtained in the research point to the low percentage of protection of intangible assets of the brand type by this group of companies and the result shows all the distinctive signs used by companies in their products and/or services. Our indication is that brand registration is included in the companies' business plan as a priority for better positioning of their products and/or services and that there is an incentive from the public administration of Pará through educational campaigns regarding the importance of brand registration.

scholarly journals USE OF ASSOCIATION RULES TO PERFORM THE MINING OF A MARKETING DATABASE COMERCIAL

2021 ◽  
Vol 9 (4) ◽  
pp. 142-152
Author(s):  
Priscilla Leão de Lima ◽  
Richardyson Nobrega da Fonseca ◽  
Rilmar Pereira Gomes ◽  
David Barbosa de Alencar
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
Organizational Management ◽  
Apriori Algorithm ◽  
Data Mining Technique ◽  
Mining Technique

Currently, companies seek to find methods to analyze their customer behaviors and profiles. From this, a case study was carried out in a drugstore, in which the data mining technique and the Apriori algorithm were applied, for a better understanding. of your sales. First, a bibliographic survey on data mining and its tasks was carried out. Soon the sales made and their respective products were examined. Finally, marketing standards were presented according to the data analyzed, in order to assist the organizational management and marketing of the examined company.

Citizen Lifetime Value in E-Government

2011 ◽  
Vol 2 (3) ◽  
pp. 26-41
Author(s):  
B. Nikkhahan ◽  
M. J. Tarokh
Keyword(s):  
Data Mining ◽  
Cost Reduction ◽  
Data Mining Technique ◽  
Online Services ◽  
Mining Technique ◽  
Past Behavior ◽  
Customer Lifetime ◽  
Lifetime Value ◽  
The Government

Customer Lifetime Value (CLV) is one of the most important measures of valuing the customers in private sector. CLV calculates customer contribution in the profits of organization. In this paper Citizen Lifetime Value (CzLV) is introduced to measure the financial value of citizens for the government. CzLV evaluates citizen contribution in cost reduction of the organization. This measure can be calculated based on past behavior of citizens in using the service and cost reduction of using online services rather than offline ones. Logistic regression is employed as a data mining technique to predict future use of online services by citizens. A service of Tehran.ir called “137,” one of the most important portals of Iran’s E-government, is considered as a case study. CzLV for the citizens of this service is calculated and four citizen segments are specified. Then each segment is evaluated based on different characteristic of citizens, and suitable strategies are presented to build more financial values for the organization.

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