scholarly journals Problems of Data Collection for the Application of the Data Mining Methods in Analyzing Threshold Levels of Indicators of Economic Security

2018 ◽  
Vol 3 (2) ◽  
pp. 369 ◽  
Author(s):  
Zhukov A. N. ◽  
Leonov P.Y.
Keyword(s):  
Data Mining ◽  
Data Collection ◽  
Economic Security ◽  
Data Mining Algorithm ◽  
Threshold Values ◽  
Economic Stability ◽  
Time Intervals ◽  
Security Issues ◽  
Existing Problems ◽  
Collection Data

Determining threshold values of key economic security indices describing an economic situation in any country is an important stage in the assessment of the country’s economic stability. A research was undertaken to determine how this problem can be effectively solved with such Data Mining algorithm as decision trees. According to the results of the research the effectiveness of the method was proved, but only with sufficient amount of data available. However, such data collection has a number of significant problems. These problems can be attributed to the following factors: the data for the analysis are presented with varying frequency, there is no possibility to use data over longer time intervals, the lack of a common list of indicators of economic security, which are used in different countries. The purpose of this paper is to analyze the existing problems of the data collection and to submit proposals of solving them. Keywords: Economic security, Issues of data collection, Data Mining, thresholds.

Behavioral Targeting Online Advertising

2011 ◽  
pp. 213-232 ◽  
Author(s):  
Jun Yan ◽  
Dou Shen ◽  
Teresa Mah ◽  
Ning Liu ◽  
Zheng Chen ◽  
...  
Keyword(s):  
Data Mining ◽  
Data Collection ◽  
Predictive Modeling ◽  
Rapid Growth ◽  
Online Advertising ◽  
Research Challenges ◽  
Behavioral Targeting ◽  
The Us ◽  
Collection Data ◽  
Complex Technology

With the rapid growth of the online advertising market, Behavioral Targeting (BT), which delivers advertisements to users based on understanding of their needs through their behaviors, is attracting more attention. The amount of spend on behaviorally targeted ad spending in the US is projected to reach $4.4 billion in 2012 (Hallerman, 2008). BT is a complex technology, which involves data collection, data mining, audience segmentation, contextual page analysis, predictive modeling and so on. This chapter gives an overview of Behavioral Targeting by introducing the Behavioral Targeting business, followed by classic BT research challenges and solution proposals. We will also point out BT research challenges which are currently under-explored in both industry and academia.

The Importance of Data Within Contemporary CRM

2009 ◽  
pp. 96-109 ◽  
Author(s):  
Diana Luck
Keyword(s):  
Data Mining ◽  
Data Collection ◽  
Data Storage ◽  
Relationship Management ◽  
Cost Savings ◽  
Customer Relationship ◽  
Evidence Based ◽  
Essential Components ◽  
Collection Data ◽  
Data Collation

In recent times, customer relationship management (CRM) has been defined as relating to sales, marketing, and even services automation. Additionally, the concept is increasingly associated with cost savings and streamline processes as well as with the engendering, nurturing and tracking of relationships with customers. Much less associations appear to be attributed to the creation, storage and mining of data. Although successful CRM is in evidence based on a triad combination of technology, people and processes, the importance of data is unquestionable. Accordingly, this chapter seeks to illustrate how, although the product and service elements as well as organizational structure and strategies are central to CRM, data is the pivotal dimension around which the concept revolves in contemporary terms. Consequently, this chapter seeks to illustrate how the processes associated with data management, namely: data collection, data collation, data storage and data mining, are essential components of CRM in both theoretical and practical terms.

scholarly journals Evaluasi Penempatan Pegawai Pada Badan Kepegawaian Dan Pengembangan Sumber Daya Manusia Kabupaten Merauke

2020 ◽  
Vol 12 (03) ◽  
pp. 213-231
Author(s):  
Maria Margareta Reginaldis ◽  
Johanis Ohoiledyaan
Keyword(s):  
Data Collection ◽  
Human Resources ◽  
Evaluation Criteria ◽  
Human Resources Development ◽  
Organizational Goals ◽  
Development Agency ◽  
Existing Problems ◽  
Collection Data ◽  
Personnel Administration ◽  
Resources Development

This study aims to determine (1) employee placement in accordance with the evaluation criteria at the Merauke Regency Personnel and Human Resources Development Agency, (2) the principles of assigning employees to the Merauke Regency Personnel and Human Resources Development Agency, (3) challenges in placement employees at the Merauke Regency Civil Service and Human Resources Development Agency. This research is a qualitative descriptive study. The research informants were the Head of the Personnel and Human Resources Development Agency of Merauke Regency, the Secretary of the Agency, the Head of the Personnel Administration, the Head of the Program and Evaluation Subdivision. The data collection techniques used were observation, interview and documentation. Data analysis uses the steps of data collection, data reduction, data presentation, and drawing conclusions. The results showed that the implementation of the evaluation of the placement of employees according to the evaluation criteria and placement principles was optimal and also not fully optimal, because there were still some obstacles, however, there were strategic steps taken so that the problem could be resolved. There are challenges in implementing employee placement, however these challenges are handled wisely and can be resolved immediately. In principle, the Merauke Regency Personnel and Human Resources Development Agency has taken strategic steps in dealing with existing problems and constraints so that the achievement of organizational goals can be achieved, in accordance with the programs that have been set.

The Importance of Data Within Contemporary CRM

2010 ◽  
pp. 2041-2054
Author(s):  
Diana Luck
Keyword(s):  
Data Mining ◽  
Data Collection ◽  
Data Storage ◽  
Relationship Management ◽  
Cost Savings ◽  
Customer Relationship ◽  
Evidence Based ◽  
Essential Components ◽  
Collection Data ◽  
Data Collation

In recent times, customer relationship management (CRM) has been defined as relating to sales, marketing, and even services automation. Additionally, the concept is increasingly associated with cost savings and streamline processes as well as with the engendering, nurturing and tracking of relationships with customers. Much less associations appear to be attributed to the creation, storage and mining of data. Although successful CRM is in evidence based on a triad combination of technology, people and processes, the importance of data is unquestionable. Accordingly, this chapter seeks to illustrate how, although the product and service elements as well as organizational structure and strategies are central to CRM, data is the pivotal dimension around which the concept revolves in contemporary terms. Consequently, this chapter seeks to illustrate how the processes associated with data management, namely: data collection, data collation, data storage and data mining, are essential components of CRM in both theoretical and practical terms.

Behavioral Targeting Online Advertising

Data Mining ◽  
2013 ◽  
pp. 1320-1338
Author(s):  
Jun Yan ◽  
Dou Shen ◽  
Teresa Mah ◽  
Ning Liu ◽  
Zheng Chen ◽  
...  
Keyword(s):  
Data Mining ◽  
Data Collection ◽  
Predictive Modeling ◽  
Rapid Growth ◽  
Online Advertising ◽  
Research Challenges ◽  
Behavioral Targeting ◽  
The Us ◽  
Collection Data ◽  
Complex Technology

With the rapid growth of the online advertising market, Behavioral Targeting (BT), which delivers advertisements to users based on understanding of their needs through their behaviors, is attracting more attention. The amount of spend on behaviorally targeted ad spending in the US is projected to reach $4.4 billion in 2012 (Hallerman, 2008). BT is a complex technology, which involves data collection, data mining, audience segmentation, contextual page analysis, predictive modeling and so on. This chapter gives an overview of Behavioral Targeting by introducing the Behavioral Targeting business, followed by classic BT research challenges and solution proposals. We will also point out BT research challenges which are currently under-explored in both industry and academia.

scholarly journals Kompetensi Dakwah Dan Praktek Safari Romadlon Santri Darussalam Sumbersari Kencong Kepung Kediri

2019 ◽  
Vol 9 (2) ◽  
pp. 173-186
Author(s):  
Rohmad
Keyword(s):  
Data Collection ◽  
Boarding School ◽  
Research Approach ◽  
Analysis Model ◽  
Design Data ◽  
Existing Problems ◽  
Interactive Analysis ◽  
Analysis Technique ◽  
Collection Data ◽  
Qualitative Phenomenological

This study concerns the competence of da'wah and Romadlon safari practices which are specifically directed at santri in the Islamic Boarding School of Sumbersari Kencong Kepung, Kediri Regency relating to the plunge of students studying in the community for nasyrul ilmi waddin related to da'wah which is manifested in the form of safari Romadlon. This type of research approach is qualitative phenomenological, with a case study design. Data collection is done by in-depth interview techniques, observation, and study documentation. While the data analysis technique, researchers used an interactive analysis model that contained four interrelated components, namely: data collection, data simplification, data exposure, withdrawal and submission of conclusions. Finally, this study managed to obtain findings in accordance with the problem questions which in general can be concluded as follows: 1). Da'wah planning implemented at Darussalam Sumbersari Islamic boarding school in general can be said to be good which includes training, screening of all Romadlon safari participants so that safari activities can go well, 2). Romadlon safari practices by recording areas that will be occupied by the students went well, 3). Santri who was deployed assisted by the Romadlon safari committee was felt to be able to overcome the existing problems both internally and externally.

MONITORING OF OPERATIONAL LOGISTIC PROCESSES IN GENERAL CARGO WAREHOUSES USING PREDICTIVE ANALYSIS

2019 ◽  
Vol 13 (1) ◽  
pp. 27-36
Author(s):  
Andreas Neubert
Keyword(s):  
Data Mining ◽  
Human Error ◽  
Predictive Analysis ◽  
Data Mining Algorithm ◽  
It Infrastructure ◽  
Monitoring Procedure ◽  
Manual Recording ◽  
Mining Tool ◽  
General Cargo ◽  
Different Characteristics

Due to the different characteristics of the piece goods (e.g. size and weight), they are transported in general cargo warehouses by manually-operated industrial trucks such as forklifts and pallet trucks. Since manual activities are susceptible to possible human error, errors occur in logistical processes in general cargo warehouses. This leads to incorrect loading, stacking and damage to storage equipment and general cargo. It would be possible to reduce costs arising from errors in logistical processes if these errors could be remedied in advance. This paper presents a monitoring procedure for logistical processes in manually-operated general cargo warehouses. This is where predictive analysis is applied. Seven steps are introduced with a view to integrating predictive analysis into the IT infrastructure of general cargo warehouses. These steps are described in detail. The CRISP4BigData model, the SVM data mining algorithm, the data mining tool R, the programming language C++ for the scoring in general cargo warehouses represent the results of this paper. After having created the system and installed it in general cargo warehouses, initial results obtained with this method over a certain time span will be compared with results obtained without this method through manual recording over the same period.

Implementation of data mining as a support of business application strategy

2018 ◽  
Vol 5 (1) ◽  
pp. 47-55
Author(s):  
Florensia Unggul Damayanti
Keyword(s):  
Data Mining ◽  
Random Forest ◽  
Business Strategy ◽  
Input Parameter ◽  
Data Mining Algorithm ◽  
Complex Data ◽  
Business Decision ◽  
Marketing Department ◽  
Business Application ◽  
Complex Data Sets

Data mining help industries create intelligent decision on complex problems. Data mining algorithm can be applied to the data in order to forecasting, identity pattern, make rules and recommendations, analyze the sequence in complex data sets and retrieve fresh insights. Yet, increasing of technology and various techniques among data mining availability data give opportunity to industries to explore and gain valuable information from their data and use the information to support business decision making. This paper implement classification data mining in order to retrieve knowledge in customer databases to support marketing department while planning strategy for predict plan premium. The dataset decompose into conceptual analytic to identify characteristic data that can be used as input parameter of data mining model. Business decision and application is characterized by processing step, processing characteristic and processing outcome (Seng, J.L., Chen T.C. 2010). This paper set up experimental of data mining based on J48 and Random Forest classifiers and put a light on performance evaluation between J48 and random forest in the context of dataset in insurance industries. The experiment result are about classification accuracy and efficiency of J48 and Random Forest , also find out the most attribute that can be used to predict plan premium in context of strategic planning to support business strategy.

UPAYA MENINGKATKAN KOMPETENSI GURU SMP DALAM MENYUSUN TES HASIL BELAJAR BERBASIS KETERAMPILAN BERPIKIR KRITIS MELALUI SUPERVISI AKADEMIK

2019 ◽  
Vol 3 (4) ◽  
pp. 772
Author(s):  
Leni Suryani
Keyword(s):  
Critical Thinking ◽  
Data Collection ◽  
Learning Outcomes ◽  
Student Learning Outcomes ◽  
Thinking Skills ◽  
Critical Thinking Skills ◽  
Teacher Competence ◽  
Collection Data ◽  
High Level ◽  
Teacher Data

This research is motivated by the competence of teachers in preparing poor learning outcomes tests and has not been able to measure high-level thinking skills, especially critical thinking skills. Therefore the researcher seeks to improve teacher competence in compiling tests on student learning outcomes based on critical thinking skills through academic supervision. This study uses a school action research design that has stages of planning, implementation, observation, and reflection. This research was conducted for 2 months starting April 9 to May 17, 2019 for Physics teachers in the 7 target schools. Data is sourced from interviews with teachers and test documents prepared by the teacher. Data collection techniques include observation, interviews and documentation. Data analysis through the stages of data collection, data simplification, data presentation, conclusion drawing. Data were analyzed using assessment rubrics adjusted to indicators of critical thinking skills. The results of this study conclude that teacher competence in preparing tests of learning outcomes based on critical thinking skills has increased from the first cycle with a percentage of 61% with sufficient categories to 76% with good categories in cycle II.

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