scholarly journals The influence of crosses, shots, corner kicks and defensive movements in the results of Premier League matches

2021 ◽  
Vol 10 (16) ◽  
pp. e477101624072
Author(s):  
Eric Matheus Rocha-Lima ◽  
Ivan Wallan Tertuliano ◽  
Carlos Norberto Fischer
Keyword(s):  
Data Mining ◽  
Performance Analysis ◽  
Performance Indicators ◽  
Predictive Analysis ◽  
Premier League ◽  
Quantitative Descriptive ◽  
Technology Growth

The technology growth allowing analysis acts to gain more efficiency in football has increased, with performance analysis researches being conducted, since the knowledge of performance indicators that can determine success in football and the need for more predictive analysis to better comprehend them are essential. So, in account of these aspects this research aimed to investigate the influence of crosses, shots, corner kicks and defensive movements in winning Premier League (PL) football matches. The methodology adopted consists of a quantitative, descriptive and documentary research, which the sample is represented by all PL 2015/2016 matches. The analysis acts were made by the utilization of the association technique, present at data mining process, with the support of the software Weka. Results demonstrated the influence of variables in PL victories, suggesting that making a higher number of crosses than opponents was not effective to win PL matches, but that making more shots on goal than opponents was a positive indicative to predict victories, as having more defensive movements and less crosses than opponents as well. About corner kicks, results demonstrated that there is no influence of this component at match results.

scholarly journals The influence of ball possession, passes and shots on target in winning premier league football matches

2021 ◽  
Vol 10 (8) ◽  
pp. e55110817824
Author(s):  
Eric Matheus Rocha-Lima ◽  
Ivan Wallan Tertuliano ◽  
Carlos Norberto Fischer
Keyword(s):  
Data Mining ◽  
Analysis Process ◽  
Premier League ◽  
Football Clubs ◽  
The World ◽  
Quantitative Descriptive

Football is the most popular sport in the world and involves the availability of information of footballers and teams to investigate success in this sport. In account of these aspects, the current study aims to analyze the influence of ball possession time, passes and shots on target in winning Premier League football matches. The methodology adopted consists of a quantitative, descriptive and documentary research, in which the sample is represented by all the 380 Premier League (PL) matches of the 2015/2016 season. The analysis process was made by the use of the association technique, present in the data mining process, with the support of the Weka software. The results suggest that shots on target, as well as its interaction with ball possession and passes - total passes, accuracy of passes, accuracy of passes inside the opponent’s field and long passes - influenced the final result of the match. Based on the results, the conclusion is that direct play alternatives, such as presenting less ball possession time and more long passes, associated with more shots on target, showed to be more beneficial for football clubs to win football matches.

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.

scholarly journals Data mining untuk memprediksi prestasi siswa berdasarkan sosial ekonomi, motivasi, kedisiplinan dan prestasi masa lalu

2014 ◽  
Vol 4 (2) ◽  
Author(s):  
Heri Susanto ◽  
Sudiyatno Sudiyatno
Keyword(s):  
Data Mining ◽  
Decision Tree ◽  
Multiple Regression ◽  
Economic Status ◽  
Predictive Analysis ◽  
Research Approach ◽  
Significance Level ◽  
Achievement Prediction ◽  
Interaction Detection ◽  
Chi Squared

Penelitian ini bertujuan untuk membuat prediksi prestasi belajar siswa berdasarkan status sosial ekonomi orang tua, motivasi, kedisiplinan siswa dan prestasi masa lalu menggunakan metode data mining dengan algoritma J48. Sebagai perbandingan, data penelitian dianalisis juga dengan CHAID (Chi Squared Automatic Interaction Detection) dan regresi ganda. Pendekatan penelitian yang digunakan adalah kuantitatif. Subyek penelitian ini adalah siswa tingkat X SMK Negeri 4 Surakarta berjumlah 416 siswa. Teknik pengumpulan data yang digunakan adalah dokumentasi dan angket. Hasil penelitian menunjukkan bahwa analisis prediksi menggunakan decision tree algoritma J48 memiliki akurasi sebesar 95,7%, sedangkan analisis prediksi menggunakan CHAID memiliki tingat akurasi 82,1% dan analisis regresi ganda menghasilkan tingkat signifikansi sebesar 90,6%. Berdasarkan hasil tersebut bisa disimpulkan bahwa metode J48 lebih baik dibandingkan dengan metode CHAID dan regresi ganda. DATA MINING TO PREDICT STUDENT’S ACHIEVEMENT BASED ON SOCIO-ECONOMIC, MOTIVATION, DISCIPLINE AND ACHIEVEMENT OF THE PASTAbstractThis study aims to make student achievement prediction based on socio-economic status of parents, motivation, discipline students and past achievements using data mining methods with the J48 algorithm. For comparison, the data were analyzed also with CHAID (Chi Squared Automatic Interaction Detection) and multiple regression. The research approach is quantitative. The subjects of this study were student-first level at SMK Negeri 4 Surakarta totaled 416 students. Data collection techniques used are documentation and questionnaires. The results showed that the predictive analysis using J48 decision tree algorithm has an accuracy of 95.7%, while the predictive analysis using CHAID has the rank of an accuracy of 82.1% and a multiple regression analysis resulted in a significance level of 90.6%. Based on these results it can be concluded that the J48 method is better than the CHAID and multiple regression methods.

scholarly journals Performance Analysis and Prediction Student Performance to build effective student Using Data Mining Techniques

2019 ◽  
Vol 3 (2) ◽  
pp. 10
Author(s):  
Ardalan Husin Awlla
Keyword(s):  
Data Mining ◽  
Performance Analysis ◽  
Student Performance ◽  
Fraud Detection ◽  
Classification Model ◽  
Data Mining Techniques ◽  
Incipient Stage ◽  
The Everyday ◽  
Using Data

In this period of computerization, schooling has additionally remodeled itself and is not restrained to old lecture technique. The everyday quest is on to discover better approaches to make it more successful and productive for students. These days, masses of data are gathered in educational databases, however it stays unutilized. To be able to get required advantages from such major information, effective tools are required. Data mining is a developing capable tool for examination and expectation. It is effectively applied in the field of fraud detection, marketing, promoting, forecast and loan assessment. However, it is in incipient stage in the area of education. In this paper, data mining techniques have been applied to construct a classification model to predict the performance of students.

scholarly journals Peningkatan Keselamatan Pada Simpang Dengan Menerapkan RHK Sepeda Motor (Studi Kasus Simpang Empat Bersinyal Srikandi Di Kabupaten Pasuruan)

2020 ◽  
Vol 3 (1) ◽  
pp. 40
Author(s):  
Yordan Suryoatmojo
Keyword(s):  
Economic Development ◽  
Performance Analysis ◽  
Queue Length ◽  
Traffic Management ◽  
Degree Of Saturation ◽  
Average Delay ◽  
The North ◽  
Qualitative Descriptive ◽  
Quantitative Descriptive ◽  
Performance Results

Pasuruan Regency is one of the regions in Indonesia which is precisely located in the province of East Java. With a very rapid economic development will certainly affect the flow of traffic, especially at the intersection. One of the most populous intersections is the Srikandi Four Intersection which is located in Pandaan District. To improve safety at an intersection, traffic management is necessary. This study aims to analyze the performance of the intersection by using the MKJI calculation and calculate the area of the Special Stop Room (RHK) of a motorcycle that refers to the Guidelines for Designing Motorcycle RHK at a Signed Intersection in the Urban Area planned on Jalan R.A. Kartini and Jalan A. Yani. The method used to plan the RHK of this motorcycle uses quantitative descriptive methods and qualitative descriptive methods. Intersection performance results obtained from calculations for the existing conditions of the North approach capacity (Jalan Urip Sumoharjo) 252 pcu / hour, queue length 131 m, degree of saturation of 0.85. Eastern approach capacity (Jalan Pahlawan Sunaryo) 265 pcu / hour, queue length 146 m, degree of saturation 0,85. South approach capacity (Jalan R.A. Kartini) 579 pcu / hour, queue length 134 m, degree of saturation of 0.85. The Western approach capacity (Jalan A. Yani) is 730 pcu / hour, the queue length is 104 m, the degree of saturation is 0.85, while the average delay is 59.10 seconds / pcu. From the performance analysis of the intersection, the length of the RHK motorcycle for the R.A. Kartini is 11.5 meters long, while for Jalan A. Yani it is 10.3 meters long.

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