Identifying the relationship between human self-esteem and general health using data mining

2021 ◽  
Author(s):  
Milad Motallebi Shabestari ◽  
Ali Ahmadi
Keyword(s):  
Data Mining ◽  
General Health ◽  
Self Esteem ◽  
Using Data ◽  
The Relationship

scholarly journals EVALUASI PELAPORAN KAMSELTIBCAR LANTAS DALAM MENDUKUNG PELAPORAN DEKADE AKSI KESELAMATAN JALAN

2019 ◽  
Vol 2 (1) ◽  
pp. 1
Author(s):  
Nunung Nuring Hayati ◽  
Ni Nyoman Suartini ◽  
Achmad Wicaksono ◽  
Ike Fibriani ◽  
Mirtha Firmansyah ◽  
...  
Keyword(s):  
Data Mining ◽  
Road Safety ◽  
Road Transport ◽  
Public Knowledge ◽  
Traffic Law ◽  
Using Data ◽  
Two Parameters ◽  
Self Protection ◽  
The Relationship ◽  
Made In

Kamsebtibcar Lantas or secure, safety, orderliness, and fluency of traffic are made in support of road safety actions reporting on traffic due to the lack of public knowledge about the importance of using self-protection tools that have been determined in traffic law number 22 of 2009 concerning traffic and road transport. By using this program, you can find out the relationship between the factors that cause accidents. From those collected from various regions in East Java, taken from 2016 to 2018. The data obtained can be processed using data mining techniques. This technique works by using a pattern that is a reference for decision making. By using the Fp-Growth algorithm that works with the data tree system to find out the patterns of reporting activities that are happening, this pattern is determined by two parameters, namely support (support value) and confidence (certainty value). With this system, it can help the parties concerned to improve facilities in various Kamseltibcar Lantas reporting activities. Kamsebtibcar lantas atau keamanan, keselamatan, ketertiban, dan kelancaran lalu lintas dibuat dalampedalam mendukung pelaporan aksi keselamatan jalan pada lalu lintas yang dikarenakan minimnya pengetahuan masyarakat tentang pentingnya penggunaan alat perlindungan diri yang telah ditentukan pada undang-undang nomor 22 tahun 2009 tentang lalu lintas dan angkutan jalan. Dengan menggunakan program ini dapat mengetahui hubungan antara faktor-faktor penyebab kecelakaan. Data yang dikumpulkan dari berbagai daerah yang ada di wilayah Jawa Timur diambil pada tahun 2016 sampai dengan 2018. Data yang telah didapat dapat diolah menggunakan teknik data mining. Teknik ini berfungsi dengan menggunakan pola yang menjadi acuan untuk penentuan keputusan. Dengan menggunakan algoritma Fp-Growth yang bekerja dengan sistem data tree untuk mengetahui pola kegiatan pelaporan kamsebticar lalu lintas yang sedang terjadi, pola ini ditentukan dengan dua parameter, yaitu support (nilai penunjang) dan confidence (nilai kepastian). Dengan sistem ini dapat membantu pihak yang berkaitan untuk meningkatkan fasilitas dalam berbagai kegiatan pelaporan Kamseltibcar Lantas.

A predictive analytics of physicians prescription and pharmacies sales correlation using data mining

2019 ◽  
Vol 13 (3) ◽  
pp. 346-363
Author(s):  
Babak Sohrabi ◽  
Iman Raeesi Vanani ◽  
Nastaran Nikaein ◽  
Saeideh Kakavand
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Pharmaceutical Industry ◽  
Predictive Analytics ◽  
Customer Relationship ◽  
Sales Managers ◽  
Content Type ◽  
Using Data ◽  
The Impact ◽  
The Relationship

Purpose In the pharmaceutical industry, marketing and sales managers often deal with massive amounts of marketing and sales data. One of their biggest concerns is to recognize the impact of actions taken on sold-out products. Data mining discovers and extracts useful patterns from such large data sets to find hidden and worthy patterns for the decision-making. This paper, too, aims to demonstrate the ability of data-mining process in improving the decision-making quality in the pharmaceutical industry. Design/methodology/approach This research is descriptive in terms of the method applied, as well as the investigation of the existing situation and the use of real data and their description. In fact, the study is quantitative and descriptive, from the point of view of its data type and method. This research is also applicable in terms of purpose. The target population of this research is the data of a pharmaceutical company in Iran. Here, the cross-industry standard process for data mining methodology was used for data mining and data modeling. Findings With the help of different data-mining techniques, the authors could examine the effect of the visit of doctors overlooking the pharmacies and the target was set for medical representatives on the pharmaceutical sales. For that matter, the authors used two types of classification rules: decision tree and neural network. After the modeling of algorithms, it was determined that the two aforementioned rules can perform the classification with high precision. The results of the tree ID3 were analyzed to identify the variables and path of this relationship. Originality/value To the best of the authors’ knowledge, this is one of the first studies to provide the real-world direct empirical evidence of “Analytics of Physicians Prescription and Pharmacies Sales Correlation Using Data Mining.” The results showed that the most influential variables of “the relationship between doctors and their visits to pharmacies,” “the length of customer relationship” and “the relationship between the sale of pharmacies and the target set for medical representatives” were “deviation from the implementation plan.” Therefore, marketing and sales managers must pay special attention to these factors while planning and targeting for representatives. The authors could focus only on a small part of this study.

scholarly journals Application of Data Mining in the Analysis of Martial Arts Athlete Competition Skills and Tactics

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Lingrong Tao
Keyword(s):  
Data Mining ◽  
Martial Arts ◽  
Statistical Data ◽  
Practical Significance ◽  
Data Mining Techniques ◽  
Develop Technology ◽  
Competitive Success ◽  
Daily Training ◽  
Using Data ◽  
The Relationship

In martial arts, data mining technologies are used to describe and analyze the moves of athletes and changes in the process and sequences. Martial arts is a process in which athletes use all kinds of strengths and actions to make offensive and defensive changes according to the tactics of opponents. One such martial arts is Wushu arts as it has a long history in reference to Chinese martial arts. During the Wushu competition, Wushu athletes show their adaptability and technical level in complex, random, and nonlinear competitive abilities, organized and systematic skills, tactics, and position movement. Using data mining techniques, in-depth mining a particular type of martial arts competition technology and tactics behind statistical data, and using the data to find the law of change to solve some problems, for martial arts athletes in daily training to develop technology and tactics and improve competition results, is the practical significance of data mining in martial arts athletes competition. This research explored the relationship between goal-oriented and mental intensity and their effect on competitive success outcomes.

scholarly journals Analisis Komparasi Metode Altman Z-Score – Financial Ratio dan Metode Beneish M-Score Model – Data Mining dalam Mendeteksi Fraudulent Financial Reporting

2018 ◽  
Vol 2 (1) ◽  
pp. 14
Author(s):  
Fanny Magdalena ◽  
Hendang Tanusdjaja
Keyword(s):  
Data Mining ◽  
Financial Reporting ◽  
Z Score ◽  
Model Data ◽  
Fraudulent Financial Reporting ◽  
Public Companies ◽  
Financial Ratio ◽  
Score Model ◽  
Using Data ◽  
The Relationship

Abstract: The research tries to investigate which methods i.e. Altman Z Score – Financial Ratio or the method of Beneish M-Score Model – Data Mining, detect significantly to the Fraudulent Financial Reporting by comparing analysis on those methodologies. We argue those methods could detect the Fraudulent Financial Reporting significantly on the basis of the financial reporting in the go public companies. It is assumed that the financial reporting is formulated as good as possible before publish to the outsiders for taking another purpose of it. Thus, the research formulizes the comparison analysis on the methods for detecting the fraudulent financial reporting. Following this logic, we hypothesize that the higher the relationship to the indicator of ratios may affect to which method could more significantly in detecting positive relationship to the fraudulent financial reporting. Moreover, we test this hypothesis for the industry in consumer sector using data from IDX Database and run by PLS – SEM. Evidence strongly supports our hypothesis for detecting the fraudulent financial reporting by those methods, but the method of Altman Z Score – Financial Ratio is more influence in detecting the fraudulent financial reporting than the other.Keywords: fraud, financial, Altman Z Score, financial ratio, Beneish M-Score, Data Mining. Abstrak: Riset ini mencoba untuk menginvestigasi metode manakah diantara, Altman Z Score – Financial Ratio and metode Beneish M-Score Model – Data Mining, yang mendeteksi secara signifikan terhadap Fraudulent Financial Reporting dengan menggunakan analisis komparasi diantara metodologi yang diatas. Kami berargumentasi bahwa kedua metode tersebut dapat digunakan untuk mendekteksi Fraudulent Financial Reporting pada perusahan terbuka. Hal tersebut diasumsikan bahwa laporan keuangan dibuat sedemikian rupa sebelum dipublikasikan kepada pihak luar dalam rangka penggunaan untuk tujuan tertentu. Oleh karena itu, riset ini memformulasikan sebuah analisis komparasi metode untuk mendeteksi fraudulent financial reporting. Secara logika, penelitian ini menunjukkan suatu hipotesis dimana semakin tinggi hubungan antara metode dengan indikator rasio, maka metode tersebut semakin signifikan dalam mendektesi secara positif terhadap fraudulent financial reporting. Oleh karena itu, kami melakukan uji hipotesis ini pada industri sektor barang konsumsi dengan menggunakan data dari IDX dan dijalankan dengan PLS – SEM. Hasil uji telah membuktikan bahwa hipotesis di atas dapat mendeteksi fraudulent financial reporting, akan tetapi metode Altman Z Score – Financial Ratio  lebih berpengaruh dalam mendeteksi fraudulent financial reporting daripada metode Beneish M-Score Model.Kata kunci: kecurangan, keuangan, Altman Z Score, rasio keuangan, Beneish M-Score, data mining

Self-Esteem and Men's Negative Stereotypes of Women Who Work

1998 ◽  
Vol 83 (3) ◽  
pp. 920-922 ◽  
Author(s):  
Sean Valentine
Keyword(s):  
Self Esteem ◽  
Longitudinal Survey ◽  
Attitudes Toward Women ◽  
Adult Males ◽  
Negative Stereotypes ◽  
Unequal Treatment ◽  
Women In The Workplace ◽  
Employment Of Women ◽  
Using Data ◽  
The Relationship

The relationships between self-esteem and attitudes toward women who work were explored using data from the National Longitudinal Survey of Youth for 4,386 young adult males Significant, negative associations were found among the measures, which suggests that men with low scores on self-esteem tend to oppose the employment of women, while men with high self-esteem scores are likely to approve of women working. These findings support previous research on the relationship between self-esteem and prejudice as well as indicate possible sources of unequal treatment of men and women in the workplace.

The moderating effects of polychronicity and achievement striving on the relationship between task variety and organization-based self-esteem of mid-level managers in China

2010 ◽  
Vol 63 (9) ◽  
pp. 1395-1416 ◽  
Author(s):  
Chun Hui ◽  
Cynthia Lee ◽  
Xiongying Niu
Keyword(s):  
Middle Managers ◽  
Self Esteem ◽  
Moderating Effects ◽  
Organizational Member ◽  
Multiple Tasks ◽  
High Motivation ◽  
Using Data ◽  
Task Variety ◽  
The Relationship

Employees’ organization-based self-esteem (OBSE), defined as ‘the degree to which an individual believes him/herself to be capable, significant, and worthy as an organizational member’ (Pierce and Gardner, 2004: 593), can be increased by giving them tasks that fit their dispositions. The primary purpose of our study is to examine combinations, instead of individual dispositions separately, on OBSE. Specifically, to increase OBSE, we propose that giving employees who prefer to handle multiple tasks simultaneously (people who are polychronic) more task variety. This effect will be stronger for employees with high motivation to achieve (achievement striving). The hypotheses were tested using data collected from 260 middle managers and their immediate supervisors in three Chinese organizations. We found that offering more task variety to polychronic employees with high levels of achievement striving resulted in the highest levels of OBSE.

Prayer, Attachment to God, and Changes in Psychological Well-Being in Later Life

2017 ◽  
Vol 30 (5) ◽  
pp. 667-691 ◽  
Author(s):  
Matt Bradshaw ◽  
Blake Victor Kent
Keyword(s):  
Life Satisfaction ◽  
Later Life ◽  
Well Being ◽  
Self Esteem ◽  
Attachment To God ◽  
Secure Attachment ◽  
Psychological Well Being ◽  
Aging And Health ◽  
Using Data ◽  
The Relationship

Objective: The aim of this study was to investigate the effects of prayer and attachment to God on psychological well-being (PWB) in later life. Method: Using data from two waves of the nationwide Religion, Aging, and Health Survey, we estimate the associations between frequency of prayer and attachment to God at baseline with cross-wave changes in three measures of PWB: self-esteem, optimism, and life satisfaction. Results: Prayer does not have a main effect on PWB. Secure attachment to God is associated with improvements in optimism but not self-esteem or life satisfaction. The relationship between prayer and PWB is moderated by attachment to God; prayer is associated with improvements in PWB among securely attached individuals but not those who are insecurely attached to God. Discussion: These findings shed light on the complex relationship between prayer and PWB by showing that the effects of prayer are contingent upon one’s perceived relationship with God.

IDENTIFICATION OF CRITICAL INFRASTRUCTURE USING DATA MINING TECHNIQUES

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Su-Ling Fan ◽  
Chang-Saar Chai ◽  
Kumar Vikram
Keyword(s):  
Data Mining ◽  
Continuous Flow ◽  
Critical Infrastructure ◽  
Economic Factors ◽  
Data Mining Techniques ◽  
The Social ◽  
Using Data ◽  
Disaster Protection ◽  
The Relationship

Critical Infrastructure (CI) is a term used to describe important national assets for producing or distributing a continuous flow of essential goods or services. They are marked by immense complexity, characterized predominantly by strong intra and interdependencies as well as hierarchies. These interconnections take many forms, including flows of information, shared security, physical flows of commodities, and others. Previous research has illustrated the relationship between the physical impacts of natural disasters and the social and economic factors on CI. Some research emphasized more the role of CI interdependencies and their importance and influence over the functioning of industries while others have looked the impacts due to disruption of CI after disasters. Nowadays comprehensive identification of all interdependency relationships of CI remains a challenge. As the complexity and interconnectedness of a country's CI evolve, threats and vulnerabilities increase. Thus, investigating how a set of CI interacts and identification of criticality of CI becomes an important topic. This research has made utilization of data mining techniques and proposes a method to identify the criticality of Critical Infrastructure so that to develop better disaster protection and prevention management.

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