Prediction of characteristics on the performance analysis data of Grand Slam tennis

2020 ◽  
Vol 29 (3) ◽  
pp. 1021-1030
Author(s):  
Hyong-Jun Choi ◽  
Yun-Soo Lee
Keyword(s):  
Performance Analysis ◽  
Analysis Data

scholarly journals Trends in Offensive Team Activity in Basketball

2018 ◽  
Vol 2 (61) ◽  
Author(s):  
Boris Bazanov ◽  
Priit Võhandu ◽  
Rein Haljand
Keyword(s):  
Data Mining ◽  
Performance Analysis ◽  
Transition Period ◽  
Analysis Data ◽  
Main Indicator ◽  
Effi Ciency ◽  
Competitive Activity ◽  
Team Activity ◽  
The Mean ◽  
Analytical System

The purpose of this paper is to analyze the structure of the models of offense and to determine their effi ciency. We were able to determine the teamwork structure by using a system of analysis of the offensive process. The analysis of the team activity as an integrated whole becomes very important. For this research we observed the Tallinn University basketball team, which plays in Division One of the Estonian league. The data was gathered from 600 ball possessions in 8 recorded games of the regular season. The data we collected was analyzed by the means of data mining. This research has helped to work out the basics of the analytical system of the teamwork aspect. The analyzing system of the competitive activity of the game, enables us to fi nd out interesting offensive models from the data. The results show that the team scoring (points/possession) as the main indicator of analyzed offenses was equal to 1.13 on average with a frequency of 48%. The 1—2 s duration period of ball possession in offensive zone proves to be most effective (scoring 68%). The most effective transition period is under 1.82 s (62%). The scoring of set offense is 44% in the mean. On the basis of this information, the coach can fi nd more convenient time lapses in the game’s performance. The analyzing system worked out through that, helps coaches to develop performance and promote learning.Keywords: performance analysis, data mining, efficiency.

DISCIPLINE ANALYSIS, MOTIVATION AND PERFORMANCE

2019 ◽  
Vol 1 (2) ◽  
pp. 57-74
Author(s):  
Andi Mayasari Patongai ◽  
Zulhawati ◽  
Bambang Moertono Setiawan
Keyword(s):  
Performance Analysis ◽  
Job Performance ◽  
Public Service ◽  
Data Use ◽  
Analysis Data ◽  
Self Esteem ◽  
Likert Scale ◽  
Normal Curve ◽  
Self Actualization ◽  
And Performance

The purpose of this research is to determine wheater discipline, motiation and job performance having high rates on Public Service in MPP Kulon Progo. The respondens are 30 from Samsat Kulon Progo consist of 10 from Satintelkan and 20 from Satlantas. Data use questionnaire with Likert scale for measurement. Queastionnaire consist of 13 for dicipline, 14 for motivation and 10 for job performance. Analysis data use means analysis that compared by normal curve score. This research aims to analyzing the indicators of each dimention with means scales. The result of the research has evidanced that firmness of disciplines, need for self esteem of motivation and job quantity of job performance have 4.43, 4.47, and 4.70 which highest means, having best category. Justice of diciplines, self actualization of motivation and attitude of job performance have 4.23, 4.25 and 4.53 whisch lowest means, having best category. The main conclution that can be drawn in this study are disciplines, motivation and job performance officer Polres Kulon Progo in MPP Kulon Progo have been very good for firmsness, self esteem and job quantity also needed enhancement on justice, self actualization and attitude for better public service.

scholarly journals PERENCANAAN PENINGKATAN JALAN PADA RUAS JALAN PACITAN-NGADIROJO

2018 ◽  
Vol 1 (2) ◽  
Author(s):  
Bakhtiar Andhi Harsono ◽  
Sigit Winarto ◽  
Yosef Cahyo
Keyword(s):  
Performance Analysis ◽  
Agricultural Land ◽  
Analysis Data ◽  
Road Segment ◽  
Degree Of Saturation ◽  
The Road ◽  
Road Section ◽  
Road Performance ◽  
On The Road ◽  
Pavement Thickness

ABSTRACT The Pacitan-Ngadirojo road section is one of the East Java Province Roads located in Pacitan District, which includes cross-district roads. The condition of the Pacitan-Ngadirojo road segment is generally a flat road that has several bends, inclines and derivatives along the link. Passing through a number of sub-districts and villages in the Pacitan Regency area which has right and left sides, there are settlements, agricultural land, plantations, gardens, rice fields, and traditional shopping places.To analyze road performance, the writer uses the method Manual Kapasitas Jalan Indonesia (MKJI, 1997), while to calculate the thickness of road pavement, we use the method Bina Marga (1987).From the results of the road performance analysis, data were obtained as follows: Degree of Saturation (DS) on the Pacitan-Ngadirojo road segment beginning in 2011 amounted to 0.047 while the performance analysis for the next 10 years obtained a DS of 0,078. This means that the level of road services on the road segment has not yet taken into account traffic actions or management, which in this case is road widening.For the calculation of pavement thickness with the Bina Marga Method the flexible pavement thickness on the Pacitan-Ngadirojo road section is 7,5 cm. Key words : Road Improvement Planing, Pavement Thickness, Degree of Saturation

scholarly journals Project Performance Analysis Using Hierarchical Clustering Method

2021 ◽  
Vol 11 (7) ◽  
pp. 28-37
Author(s):  
Marian Halaj ◽  
Keyword(s):  
Performance Analysis ◽  
Hierarchical Clustering ◽  
Automotive Industry ◽  
Analysis Data ◽  
Project Performance ◽  
Manufacturing Facility ◽  
Common Causes ◽  
Technical Discipline ◽  
The Common ◽  
Engineering Projects

This paper deals with the project management performance analysis in automotive industry and usage of the advanced analytics to optimize the performance of the engineering projects within the vehicle manufacturing facility. The aim is to identify and mitigate the common causes of project delay (slippage) in various engineering projects that are independent of the technical discipline where a particular project belongs to. We have used the hierarchical clustering technique here to identify the sub-groups of similar projects and further deeply analysed those ones with the highest average slippage. Keywords—Cluster analysis, Data, Delay, Distance, Hierarchical clustering, Metric, Project, Slippage, Strategy

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