Database and Knowledge Base Integration Method to Support Decision-Making Related to Quality of Application and Use of Agricultural Sprayers

2017 ◽  
Author(s):  
Elmer A. G. Penaloza ◽  
Paulo E. Cruvinel ◽  
Vilma A. Oliveira ◽  
Augusto G. F. Costa
Keyword(s):  
Decision Making ◽  
Knowledge Base ◽  
Integration Method ◽  
Support Decision Making

scholarly journals How Cognitive Biases Influence the Data Verification of Safety Indicators: A Case Study in Rail

Safety ◽  
2019 ◽  
Vol 5 (4) ◽  
pp. 69
Author(s):  
Burggraaf ◽  
Groeneweg ◽  
Sillem ◽  
van Gelder
Keyword(s):  
Decision Making ◽  
Cognitive Biases ◽  
Decision Makers ◽  
Human Cognition ◽  
Quality Data ◽  
Verification Process ◽  
Support Decision Making ◽  
Good Quality Data

The field of safety and incident prevention is becoming more and more data based. Data can help support decision making for a more productive and safer work environment, but only if the data can be, is and should be trusted. Especially with the advance of more data collection of varying quality, checking and judging the data is an increasingly complex task. Within such tasks, cognitive biases are likely to occur, causing analysists to overestimate the quality of the data and safety experts to base their decisions on data of insufficient quality. Cognitive biases describe generic error tendencies of persons, that arise because people tend to automatically rely on their fast information processing and decision making, rather than their slow, more effortful system. This article describes five biases that were identified in the verification of a safety indicator related to train driving. Suggestions are also given on how to formalize the verification process. If decision makers want correct conclusions, safety experts need good quality data. To make sure insufficient quality data is not used for decision making, a solid verification process needs to be put in place that matches the strengths and limits of human cognition.

Assessing Knowledge Management Systems Usage in Supporting Decision Making Processes in Organizations

2014 ◽  
pp. 326-340 ◽  
Author(s):  
Mahmoud Abdelrahman ◽  
K. Nadia Papamichail ◽  
Simon French
Keyword(s):  
Decision Making ◽  
Knowledge Management ◽  
Knowledge Economy ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Critical Factors ◽  
Public And Private ◽  
Decision Making Processes ◽  
Support Decision Making

With the advent of the knowledge economy and the growing importance of knowledge societies, organizations are constantly seeking new ways of leveraging knowledge assets to support Decision Making (DM) processes. This chapter presents an initial insight to the little-researched phenomenon of how Knowledge Management Systems (KMSs) can support DM processes in organizations. A synthesis of ideas from a literature review suggests a new conceptual framework with several critical factors that organizations should take into account to assess the usage of KMSs tools in supporting DM processes in organizations. The proposed framework, “USUQ,” will benefit managers in both public and private sectors in knowing how the Usage, Satisfaction, Usefulness, and the Quality of using KMSs can support DM processes.

scholarly journals GERANDO INTELIGÊNCIA ATRAVÉS DE MICRODADOS: UMA PROPOSTA DE BUSINESS INTELLIGENCE PARA A ÁREA DE ENSINO DO INSTITUTO FEDERAL DA BAHIA (IFBA)

2020 ◽  
Vol 13 (4) ◽  
pp. 463
Author(s):  
Iara Margarida de Souza Barreto ◽  
Allan Edgard Silva Freitas
Keyword(s):  
Decision Making ◽  
Business Intelligence ◽  
Academic Life ◽  
Educational Institutions ◽  
Strategic Decisions ◽  
Business Intelligence Systems ◽  
Technology Market ◽  
Educational Indicators ◽  
Support Decision Making

Educational indicators are instruments of significant importance for assessing the outcomes and quality of educational institutions. In order to provide information for strategic decisions, Business Intelligence systems are gaining more and more space in the Information Technology market. This article intends to identify the main educational indicators and their various approaches, in order to evaluate their contributions and/or inadequacies to the pedagogical management of the Instituto Federal da Bahia, besides addressing the Business Intelligence theme, identifying their origin, concepts and applicability. In conclusion, it was presented a proposal to develop a BI system to generate intelligence through microdata extracted from IFBA's academic and administrative systems and, finally, to produce strategic indicators to support decision making regarding students' academic life.

scholarly journals Analisis dan perancangan data warehouse evaluasi mahasiswa studi kasus pada jurusan Teknik Informatika UMM

Repositor ◽  
2020 ◽  
Vol 1 (1) ◽  
pp. 59
Author(s):  
Mohammad Agung Alifferiza Maulana ◽  
Maskur S.Kom, M.Kom. ◽  
Wildan Soeharso
Keyword(s):  
Decision Making ◽  
Data Warehouse ◽  
Business Processes ◽  
Student Evaluations ◽  
Multidimensional Analysis ◽  
Quality Of Education ◽  
Management Level ◽  
Concise Information ◽  
Support Decision Making

 AbstrakDalam rangka meningkat kualitas pendidikan secara berkelanjutan diperlukan suatu trobosan yang mampu melakukan analisa proses bisnis yang bertujuan untuk memudahkah eksekutif dalam melakukan pengambilan keputusan. Untuk mengatasi hal tersebut dibangun sebuah data warehouse yang berdasarkan laporan borang akreditasi khusus standard 3 mengenai mahasiswa. Penerapan data warehouse berguna untuk mendukung pengambilan keputusan di tingkat management. Model data warehouse yang di gunakan dalam penelitian ini adalah menggunakan Skema Star, dan menggunakan nine Step Metodology. Dengan pembangunan data warehouse, diharapkan dapat menghasilkan informasi yang berkenaan dengan evaluasi mahasiswa berdasarkan standard akreditasi dengan lebih cepat, sesuai dengan kebutuhan, serta menghasilkan informasi yang lebih ringkas. Dengan menggunakan sistem data warehouse juga dapat dihasilkan analisis multidimensi  yang bersifat informasi analitis. Sehingga bermanfaat dalam pengambilan keputusan berkenaan dengan evaluasi mahasiswa.AbstractIn order to improve the quality of education sustainably, a breakthrough is needed. A breakthrough that able to analyze business processes that aim to make the processes itself easier for executives to make decisions. Data warehouse was built to overcome that, based on the report of the third standard  special accreditation forms about students. The application of data warehouse is useful to support decision-making at the management level. The data warehouse model used in this study is using Star Scheme and uses the Nine-Step Methodology. With the construction of a data warehouse, it is expected to produce information relating to student evaluations based on accreditation standards more quickly, according to needs, and produce more concise information. Using a data warehouse system can also produce a multidimensional analysis, which is an analytical information. So it can be useful in decision making regarding to the student evaluations.

scholarly journals Design of a Diabetic Diagnosis System Using Rough Sets

2013 ◽  
Vol 13 (3) ◽  
pp. 124-139 ◽  
Author(s):  
Margret Anouncia S. ◽  
Clara Madonna L. J. ◽  
Jeevitha P. ◽  
Nandhini R. T.
Keyword(s):  
Decision Making ◽  
Knowledge Base ◽  
Clinical Data ◽  
Uncertain Data ◽  
Decision Making Process ◽  
Diagnosis System ◽  
Adequate Knowledge ◽  
Simple Set ◽  
Made In

Abstract Traditionally the diagnosis of a disease is done by medical experts with experience, clinical data of the patients and adequate knowledge in identifying the disease. Such diagnosis is found to be approximate and time-consuming since it purely depends on the availability and the experience of the medical experts dealing with imprecise and uncertain clinical data of the patients. Hence, to improve decision making with uncertain data and to reduce the time consumption in diagnosing a disease, several simulated diagnosis systems have been developed. Most of these diagnosis systems are designed to possess the clinical data and symptoms associated with a specific disease as knowledge base. The quality of the knowledge base has an impact not only on the consequences, but also on the diagnostic precision. Most of the existing systems have been developed as an expert system that contains all the diagnosis facts as rules. Notably, applying the concept of a fuzzy set has shown better knowledge representation to improve the decision making process. Therefore an attempt is made in this paper to design and develop such diagnosis system, using a rough set. The system developed is evaluated using a simple set of symptoms that is added to clinical data in determining diabetes and its severity.

A Model Approach to Infer the Quality in Agricultural Sprayers Supported by Knowledge Bases and Experimental Measurements

2017 ◽  
Vol 11 (03) ◽  
pp. 279-292 ◽  
Author(s):  
Elmer A. G. Peñaloza ◽  
Paulo E. Cruvinel ◽  
Vilma A. Oliveira ◽  
Augusto G. F. Costa
Keyword(s):  
Decision Making ◽  
Knowledge Base ◽  
Experimental Tests ◽  
Knowledge Bases ◽  
Operating Conditions ◽  
Semantic Interpretation ◽  
Data Consistency ◽  
Flow Measurements ◽  
Spraying Process

This paper presents a method to infer the quality of sprayers based on data collection of the drop spectra and their physical descriptors, which are used to generate a knowledge base to support decision-making in agriculture. The knowledge base is formed by collected experimental data, obtained in a controlled environment under specific operating conditions, and the semantics used in the spraying process to infer the quality in the application. The electro-hydraulic operating conditions of the sprayer system, which include speed and flow measurements, are used to define experimental tests, perform calibration of the spray booms and select the nozzle types. Using the Grubbs test and the quartile-quartile plot an exploratory analysis of the collected data was made in order to determine the data consistency, the deviation of atypical values, the independence between the data of each test, the repeatability and the normal representation of them. Therefore, integrating measurements to a knowledge base it was possible to improve the decision-making in relation to the quality of the spraying process defined in terms of a distribution function. Results shown that the use of advanced models and semantic interpretation improved the decision-making processes related to the quality of the agricultural sprayers.

scholarly journals Implementasi Fuzzy Tsukamoto Dalam Menentukan Harga Gabah Pada Petani

2020 ◽  
Vol 1 (2) ◽  
pp. 121-125
Author(s):  
Josua Fernando Simanjuntak ◽  
Agnes Prawita Sari ◽  
Aulia Nada Syahputri
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Knowledge Base ◽  
Grain Quality ◽  
Fuzzy Inference ◽  
Human Life ◽  
Selling Price ◽  
Rice Farmers ◽  
Base Formation

In human life, many things require decision making, including in agriculture. One of them is rice farmers who make the decision to determine the selling price of their grain according to the quality of their grain. By using Fuzzy logic, the grain price can be determined by going through the following stages: Fuzzification, Knowledge Base Formation, Fuzzy Inference, and Defuzzification. One of the Fuzzy logic methods that can be used is the Tsukamoto method, where this method has an output in the form of firm values. To be able to determine the price of grain, the data is taken from the Central Statistics Agency website, so that later prices and levels of grain quality can be determined properly. With this research, the farmers can determine the price of their grain exactly according to the quality of the grain. So that the problem of determining their grain prices can be overcome properly.

scholarly journals METHOD OF AUTOMATED CONSTRUCTION AND EXPANSION OF THE KNOWLEDGE BASE OF THE BUSINESS PROCESS MANAGEMENT SYSTEM

2018 ◽  
Vol 4 ◽  
pp. 29-35 ◽  
Author(s):  
Viktor Levykin ◽  
Oksana Chala
Keyword(s):  
Decision Making ◽  
Process Control ◽  
Knowledge Representation ◽  
Knowledge Base ◽  
Business Process ◽  
Business Process Management ◽  
Process Management ◽  
Process Implementation ◽  
Knowledge Intensive ◽  
Support Decision Making

The problem of constructing and using the knowledge representation in the process control system is studied. It is shown that when implementing knowledge-intensive business process management, it is necessary to use automated construction and expansion knowledge base to support decision-making in accordance with the current state of the context for the implementation of business process actions. The state of the context is specified as a set of weighted logical facts, the arguments of which are the values of the attributes of the events of the business process log. The sequence of the process implementation at each moment of time is displayed in the form of a probabilistic distribution of the possible rules of executing the actions of the business process in this context. The method of automated construction and updating of the knowledge base of the information system of process control is proposed. The method includes the stages of forming knowledge representation templates, constructing context descriptions, logical facts, constructing rules, and calculating the probability distribution for rules. The method creates opportunities to support decision-making on the management of the business process in the event of a discrepancy between the current implementation of the business process and its model.

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