scholarly journals Simulasi Seleksi Pemain Futsal Porprov Bali Menggunakan Sistem Pendukung Keputusan Untuk Meningkatkan Kesiapan Atlet (Studi Kasus : Fakultas Olahraga dan Kesehatan, Undiksha)

2018 ◽  
Vol 4 (1) ◽  
Author(s):  
Ni Putu Dwi Sucita Dartini ◽  
Agus Aan Jiwa Permana ◽  
Kadek Wirahyuni
Keyword(s):  
Decision Support ◽  
Physical Education ◽  
Decision Support Systems ◽  
Support Systems ◽  
Assessment Process ◽  
Structured Problems ◽  
Selection Of

ABSTRACT<br />Based on the experience of the writers who participated in the Porprov Bali committee,<br />observations in the Futsal athlete's assessment involved more subjectivity. Subjective decisions<br />can be detrimental to many parties, especially among Futsal athletes themselves. The sports<br />branch is highly emphasized on the value of sportsmanship, so it is necessary to involve a tool to<br />help solve the problem. Decision support systems (SPK) can be used as tools that aim to reduce<br />the level of subjectivity in the assessment process for semi-structured problems. SPK is used as a<br />simulation that will be used for students majoring in physical education at the Sports and Health<br />Faculty, Undiksha to find out whether they are eligible to pass the Porprov selection. With SPK it<br />will produce more objective decisions in semi-structured situations such as determining futsal<br />athletes that can be passed to Porprov because the results of decisions issued minimize the use of<br />intuition.<br />Keywords: Selection of Futsal, Porprov Bali athletes, SPK, Semiterstructure Decisions<br />ABSTRAK<br />Berdasarkan pengalaman penulis yang ikut dalam kepanitiaan Porprov Bali secara observasi dalam<br />penilaian atlet Futsal lebih banyak melibatkan faktor subyektifitas. Keputusan yang bersifat<br />subyektif dapat merugikan banyak pihak, khususnya di kalangan atlet Futsal itu sendiri. Cabang<br />olahraga sangat ditekankan nilai sportifitas sehingga perlu dilibatkan sebuah tools (alat bantu)<br />untuk membantu memecahkan masalah tersebut. Sistem pendukung keputusan (SPK) dapat<br />digunakan sebagai tools yang vertujuan untuk menurunkan tingkat subyektifitas dalam proses<br />penilaian untuk permasalahan semiterstruktur. SPK digunakan sebagai simulasi yang akan<br />digunakan untuk mahasiswa jurusan pendidikan jasmani pada Fakultas Olahraga dan Kesehatan,<br />Undiksha untuk mengetahui apakah mereka layak untuk lolos dalam seleksi Porprov. Dengan SPK<br />akan menghasilkan keputusan yang lebih obyektif dalam situasi semiterstuktur seperti dalam<br />menentukan atlet futsal yang dapat diloloskan ke Porprov karena hasil keputusan yang dikeluarkan<br />memperkecil penggunaan intuisi..<br />Kata Kunci : Seleksi atlet Futsal, Porprov Bali, SPK, Keputusan Semiterstruktur

Decision Support Systems and Decision-Making Processes

2010 ◽  
pp. 135-143 ◽  
Author(s):  
Udo Richard Averweg
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Management Problem ◽  
Upper Management ◽  
Structured Problems ◽  
Decision Making Processes ◽  
Complex Decision Making ◽  
Computer Based

Decision support systems (DSS) deal with semi-structured problems. Such problems arise when managers in organisations are faced with decisions where some but not all aspects of a task or procedure are known. To solve these problems and use the results for decision-making requires judgement of the manager using the system. Typically such systems include models, data manipulation tools, and the ability to handle uncertainty and risk. These systems involve information and decision technology (Forgionne, 2003). Many organisations are turning to DSS to improve decision-making (Turban, McLean, & Wetherbe, 2004). This is a result of the conventional information systems (IS) not being sufficient to support an organisation’s critical response activities—especially those requiring fast and/or complex decision-making. In general, DSS are a broad category of IS (Power, 2003). A DSS is defined as “an interactive, flexible, and adaptable computer-based information system, specially developed for supporting the solution of a non-structured management problem for improved decision-making. It utilises data, it provides easy user interface, and it allows for the decision maker’s own insights” (Turban, 1995). There is a growing trend to provide managers with IS that can assist them in their most important task—making decisions. All levels of management can benefit from the use of DSS capabilities. The highest level of support is usually for middle and upper management (Sprague & Watson, 1996). The question of how a DSS supports decision-making processes will be described in this article. This article is organised as follows: The background to decisionmaking is introduced. The main focus (of this article) describes the development of the DSS field. Some future trends for the DSS field are then suggested. Thereafter a conclusion is given.

Decision Support Systems and Decision-Making Processes

2010 ◽  
pp. 218-224 ◽  
Author(s):  
Udo Richard Averweg
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Management Problem ◽  
Upper Management ◽  
Structured Problems ◽  
Decision Making Processes ◽  
Complex Decision Making ◽  
Computer Based

Decision support systems (DSS) deal with semi-structured problems. Such problems arise when managers in organisations are faced with decisions where some but not all aspects of a task or procedure are known. To solve these problems and use the results for decision-making requires judgement of the manager using the system. Typically such systems include models, data manipulation tools, and the ability to handle uncertainty and risk. These systems involve information and decision technology (Forgionne, 2003). Many organisations are turning to DSS to improve decision-making (Turban, McLean, & Wetherbe, 2004). This is a result of the conventional information systems (IS) not being sufficient to support an organisation’s critical response activities—especially those requiring fast and/or complex decision-making. In general, DSS are a broad category of IS (Power, 2003). A DSS is defined as “an interactive, flexible, and adaptable computer-based information system, specially developed for supporting the solution of a non-structured management problem for improved decision-making. It utilises data, it provides easy user interface, and it allows for the decision maker’s own insights” (Turban, 1995). There is a growing trend to provide managers with IS that can assist them in their most important task—making decisions. All levels of management can benefit from the use of DSS capabilities. The highest level of support is usually for middle and upper management (Sprague & Watson, 1996). The question of how a DSS supports decision-making processes will be described in this article. This article is organised as follows: The background to decisionmaking is introduced. The main focus (of this article) describes the development of the DSS field. Some future trends for the DSS field are then suggested. Thereafter a conclusion is given.

scholarly journals Seleksi Penyerang Utama Menggunakan K-Means Clustering Dan Sistem Pendukung Keputusan Metode Topsis

2017 ◽  
Vol 2 (1) ◽  
pp. 37-48
Author(s):  
Renenata Ardilesmana Siregar
Keyword(s):  
Data Mining ◽  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Selection Process ◽  
Ideal Solution ◽  
Major Player ◽  
The Right ◽  
Selection Of ◽  
The Ideal

Untuk  menentukan penyerang ideal dalam sepak bola agar sesuai karakter dan kriteria yang diharapkan,  diperlukan  pelatih  yang  mempunyai naluri  tajam  dan  juga  sistem  yang  bisa membantu pelatih dalam memberikan pilihan. Biasanya dalam proses penentuan pemain masih dilakukan  secara  manual dengan melihat dari karakter dan kriteria dari pemain tersebut. Tetapi terkadang hanya dengan melihat dari karakter dan kriteria dari pemain tersebut saja masih kurang cukup sehingga jauh dari apa yang diharapkan. Untuk  mempermudah dalam pemilihan penyerang ideal, maka diperlukan suatu sistem yang dapat membantu pelatih untuk  memilih penyerang yang dibutuhkan sesuai dengan kebutuhan tim yaitu dengan menggunakan teknik K-Means Clustering dalam metode data mining sebagai proses dalam menyeleksi pemain untuk bergabung  dalam  suatu  tim  dan  juga  didukung  dengan  metode  Sistem  Pendukung Keputusan (Decision Support Systems) The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) sebagai proses dalam menentukan penyerang yang akan bermain sebagai pemain utama dalam tim yang menggunakan beberapa kriteria untuk  memilih pemain yang tepat. Dengan hasil penelitian ini, diharapkan dapat membantu pelatih dalam proses seleksi pemain dan dapat mengubah cara penilaian terhadap sifat subjektif agar lebih obyektif dalam pengambilan keputusan. Kata Kunci :Data Mining, K-Means Clustering, Sistem Pendukung Keputusan To  determine  the  ideal  attacker  in football to match the expected character and criteria, a  coach who has a sharp instinct and a system that can assist the coach in providing choices. Usually  in  the  process  of  determining  the  player  is  still  done  manually  by  look ing  at  the characters  and  criteria  of  the  player.  But  sometimes just by look ing at the characters and criteria of the player is still not enough so far from what is expected. To facilitate the selection of ideal attackers, a system that can help the trainer to select the attacker needed according to the needs of the team is by using K-Means Clustering technique in the method of data mining as a process in selecting players to join a team and also supported by Decision Support Systems method The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is the process of determining which attack er will play as a major player in the team using multiple criteria to select the right player. With the results of this study, it is expected to assist trainers in the selection process of players and can change the way the assessment of the subjective nature to be more objective in decision making. Keywords: Data Mining, K-Means Clustering, Decision Support System.  

scholarly journals Implementation Of The SAW Method For Selection Of Best Operational Vehicles

2020 ◽  
Vol 4 (1) ◽  
pp. 67-75
Author(s):  
Irmawati Carolina ◽  
Fitra Hariman Hakim ◽  
Adi Supriyatna
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Decision Support Systems ◽  
Support System ◽  
Support Systems ◽  
Complex Problem ◽  
Alternative Form ◽  
Simple Additive Weighting ◽  
Selection Of

Operational Vehicle is one of the assets owned by the company to help transportation that aims to facilitate the carrying out of a job. With the existence of operational vehicles can increase company productivity. The problems that exist in the process of selecting the best operational vehicles are still simple or depend on the company's budget. The purpose of this study is to obtain a decision in determining the selection of operational vehicles using several criteria and can provide solutions to determine the best choice of operational vehicles for company management. The method used by the author is Simple Additive Weighting (SAW) which can help in making decisions to overcome a complex problem. The results of this study are the decision support system can be used as a tool for decision making recommendations for companies in determining the selection of operational vehicles using the Simple Additive Weighting (SAW) method, in addition to providing an alternative form of decision support systems to help and facilitate the company's stakeholders in decide on operational vehicles.Keywords: Decision Support System, Operational Vehicle, SAW Method.

scholarly journals Decision Support System For Selecting Bali Tourist Attractions Using The PROMETHEE Method

SinkrOn ◽  
2019 ◽  
Vol 3 (2) ◽  
pp. 1
Author(s):  
Eva Zuraidah
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Recommendation System ◽  
Support Systems ◽  
Descriptive Analysis ◽  
Tourist Attraction ◽  
Tourist Attractions ◽  
The Right ◽  
Selection Of

Tourism is currently very potential to be developed as a source of local income by providing information both online and offline to the community so that regional income increases. Bali is one of the tourist destinations in Indonesia which is visited by many local and foreign tourists. The island of Bali has many interesting sights consisting of natural attractions, royal festivals, culinary tours, traditional markets, and museums. There are many criteria that must be considered, so through this recommendation system, tourists can find out what places are in Bali they will visit. One of the problems of decision making with many criteria and attributes in the selection of attractions is to provide detailed decisions that refer to the scale of weight possessed. Decision support systems provide priority results of attractions that are suitable for every traveler. Traveling is very important because with tourism we can eliminate fatigue due to activity during the day. The selection of the right tourist attraction also affects this, so it is necessary to choose the right tourist attraction. This study focused on the application of multi-attribute decision making (MADM) to decision support systems (SPK) using preferred organizational methods for enrichment and evaluation (Promeethe). When a traveler fills out a questionnaire, he must be consistent with the answers to get the best results based on his willingness and characteristics. This research uses descriptive analysis method that presents a summary of the results of surveys and interviews of tourists who want to choose Bali tourist attractions according to costs, security, natural beauty, facilities, and infrastructure and location.

scholarly journals Sistem Pendukung Keputusan Untuk Seleksi Penerimaan Asisten Laboratorium Menggunakan Metode AHP

Respati ◽  
2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Helda Yunita
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Analytical Hierarchy Process ◽  
Support Systems ◽  
Ahp Method ◽  
Complex Problems ◽  
Laboratory Assistant ◽  
Hierarchy Process ◽  
Selection Of

INTISARISistem Pendukung Keputusan (SPK) merupakan suatu sistem yang mendukung suatu instansi dalam pengambilan keputusan untuk suatu permasalahan dengan tujuan sebagai alat bantu untuk memperluas kapabilitas dalam pengambilan keputusan. Pendukung keputusan pada dasarnya merupakan suatu hasil dari beberapa alternatif terbaik yang terpilih sesuai dengan berbagai macam kriteria. Salah satu metode sistem pendukung keputusan yaitu metode Analyitical Hierarchy Process (AHP) yang merupakan metode untuk melakukan pengambilan keputusan secara ilmiah dan rasional untuk memberikan solusi terhadap masalah kriteria yang kompleks dalam berbagai alternative dengan melakukan perhitungan dari perbandingan permasing – masing kriteria. Melalui metode AHP ini dapat diketahui hasil dari nilai para calon asisten laboratorium yang telah dihitung sesuai dengan kriterianya.Kata kunci—Sistem Pendukung Keputusan (SPK), Analytical Hierarchy Process (AHP), seleksi calon asisten laboratorium.ABSTRACTDecision support systems ( DSS ) is a system that supports an agency in decision-making to a problem with the destination as a tool to expand the decision making capabilities. Basicly, a decision support systems is a selection of some of the best alternative options from some criteria. A method of decision support systems is Analyitical Hierarchy Process ( AHP ) is a method to make decisions scientifically and rationally to provide solutions to complex problems in a variety of criteria alternatives. With this Analytical Hierarchy Process ( AHP ) method can be show the result from values of laboratory assistant candidate that calculate from their criteria.Keywords—Decision Support Systems (DSS), analytical hierarchy process (AHP), candidate laboratory assistant selection

scholarly journals Challenges of Developing Robust AI for Intrapartum Fetal Heart Rate Monitoring

2021 ◽  
Vol 4 ◽  
Author(s):  
M. E. O’Sullivan ◽  
E. C. Considine ◽  
M. O'Riordan ◽  
W. P. Marnane ◽  
J. M. Rennie ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Fetal Distress ◽  
Well Being ◽  
Fetal Heart Rate Monitoring ◽  
Non Invasive ◽  
Randomised Control Trials ◽  
Selection Of

Background: CTG remains the only non-invasive tool available to the maternity team for continuous monitoring of fetal well-being during labour. Despite widespread use and investment in staff training, difficulty with CTG interpretation continues to be identified as a problem in cases of fetal hypoxia, which often results in permanent brain injury. Given the recent advances in AI, it is hoped that its application to CTG will offer a better, less subjective and more reliable method of CTG interpretation.Objectives: This mini-review examines the literature and discusses the impediments to the success of AI application to CTG thus far. Prior randomised control trials (RCTs) of CTG decision support systems are reviewed from technical and clinical perspectives. A selection of novel engineering approaches, not yet validated in RCTs, are also reviewed. The review presents the key challenges that need to be addressed in order to develop a robust AI tool to identify fetal distress in a timely manner so that appropriate intervention can be made.Results: The decision support systems used in three RCTs were reviewed, summarising the algorithms, the outcomes of the trials and the limitations. Preliminary work suggests that the inclusion of clinical data can improve the performance of AI-assisted CTG. Combined with newer approaches to the classification of traces, this offers promise for rewarding future development.

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