scholarly journals Implementation of fuzzy logic method for automation of decision making of Boeing aircraft landing

2021 ◽  
Vol 10 (3) ◽  
pp. 545
Author(s):  
Winda Pratiwi ◽  
Aghus Sofwan ◽  
Iwan Setiawan
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Wind Velocity ◽  
Wind Direction ◽  
Intelligent System ◽  
Fuzzy Simulation ◽  
Safety Factors ◽  
Aircraft Landing ◽  
Pilot Experience ◽  
Fuzzy Logic Method

In the landing process, airplanes have many safety factors that must be protected. Weather advice and information is very important as a consideration in determining the feasibility of landing an aircraft. The main objective of this research is the implementation of Mamdani fuzzy simulation in determining the feasibility of landing aircraft at Ahmad Yani Airport in Semarang using ATC police and pilot coordination on runway number 31. Wind direction, wind velocity, visibility, and pilot experience are used to determine eligibility aircraft landing. An intelligent system based on fuzzy logic produces three decisions that are feasible, careful, and not feasible in landing an aircraft on a runway. The results of the study concluded from an intelligent system based on fuzzy logic can be used to determine aircraft landing decisions on the runway of Ahmad Yani Airport Semarang on runway number 31.

Pengembangan Aplikasi Pendukung Keputusan Pemilihan Program Studi dengan Metode Fuzzy Logic (Studi Kasus: Universitas Multimedia Nusantara)

2016 ◽  
Vol 7 (1) ◽  
pp. 12-18
Author(s):  
Joko Haryanto ◽  
Seng Hansun
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
System Application ◽  
Prospective Students ◽  
Fuzzy Logic Method ◽  
Index Terms ◽  
Selection Of

This paper describes the development of decision support system application to assist students who want to enter college so that no one choose the majors incorrectly. This application uses fuzzy logic method because fuzzy logic is very flexible in data which are vague and can be represented as a linguistic variable. The purpose of this application is to assist students to choose available majors at University Multimedia Nusantara which are appropriate with his/her capabilities. This application accepts five kinds of input values i.e. Mathematics, Indonesian, English, Physics, and TIK. Received input will be processed by the calculation of the system for decision-making and the application will generate output that shows how great a match for each majors. With this application, prospective students can find out where the majors that match his/her capabilities. This application has ninety nine percentage of match result accuracy. Index Terms—fuzzy logic, decision support system, UMN, selection of major

scholarly journals The improvement of the method for developing the knowledge data base for the intelligent support system of decision making on the Fuzzy Logic principles

2018 ◽  
pp. 26-41
Author(s):  
V. B. Kropyvnytska ◽  
O. V. Yefremov ◽  
H. N. Sementsov
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Fuzzy Sets ◽  
Data Base ◽  
Support System ◽  
Fuzzy Simulation ◽  
Automated Control ◽  
Intelligent Support ◽  
Fuzzy Models

The article deals with the issue of Fuzzy-simulation of controllers for solving practical problems of automated control. The peculiarities of Fuzzy-simulation of cascade controllers in the Matlab environment are studied. The presentation is accompanied by examples of the development of individual Fuzzy models and an illustration of conducting all necessary operations with fuzzy sets.

FUZZY LOGIC APPROACH IN DETERMINING POOR FAMILIES IN THE POVERTY DATABASE IN MALANG DISTRICS

Tibuana ◽  
2019 ◽  
Vol 2 (01) ◽  
pp. 58-65
Author(s):  
Prihono Prihono
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Multi Criteria Decision Making ◽  
Poor Families ◽  
Fuzzy Logic Approach ◽  
Fuzzy Logic Method ◽  
Logic Approach ◽  
Family Classification ◽  
Logic Method

Determination of poor families in the poverty database is still less than perfect. There is still no multi criteria decision making (MCDM) technique in the grouping of poor families, making the results of the criteria in grouping poor families still far from expectations. So, this article discusses the use of the multi criteria decision making (MCDM) technique for grouping poor families in the poverty database in the Malang district. Fuzzy logic is one technique of MCDM which is commonly used for affirmation of decisions. In a random sampling of 35 families taken from the Malang District poverty database, the classification that was originally obtained was only obtained by 2 (two) classifications of poor families, namely: very poor families and poor families. But after it was calculated using the Fuzzy Logic method, it was found 3 (three) classifications of poor families, namely very poor families, poor families, and almost poor families. The magnitude of the distribution of the poor family classification is: 17 (seventeen) very poor families which previously were 14 (fourteen), 17 (seventeen) families were categorized as poor families that were previously 21 (twenty one), and 1 (one) family in the category of near-poor families that were not previously found. With these results, it can be concluded that the Fuzzy Logic method can and is able to provide better and more diverse results in determining poor families in the Malang District poverty database.

scholarly journals Measurement of Employees on Human Resources with Fuzzy Logic

2021 ◽  
Vol 11 (2) ◽  
pp. 1-7
Author(s):  
Zehra Demirel ◽  
Ceren Çubukçu
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Fuzzy Logic ◽  
Human Resources ◽  
Human Resources Management ◽  
Rule Base ◽  
Resources Management ◽  
Fuzzy Logic Method ◽  
Increase Productivity ◽  
The Right

Artificial intelligence, which is the indispensable technology of our age, has started to gain a place in many institutions. Institutions give great importance to human resources management because hiring the right employee for the job will increase productivity within the organization. When recruiting personnel for the position, human resources face difficulties such as measuring the success levels of applicants and deciding whether they are suitable. In this study, in order to provide solutions to the difficulties encountered, a decision-making mechanism is created by using the fuzzy logic method, which is one of the artificial intelligence techniques. This decision-making mechanism measures the performance of people applying for recruitment. While measuring performance, all applications are taken into consideration, and a rule base is formed according to graduation status and experience. The system, which is based on this rule base, evaluates people according to the inputs and finds out their success levels in return. According to the results, it is decided whether the persons are suitable for the position sought. When human resources departments in corporations are combined with artificial intelligence technologies, an advantage will be achieved in the competitive environment between corporations.

scholarly journals A Fuzzy Logic Based Intelligent System for Measuring Customer Loyalty and Decision Making

Symmetry ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 761 ◽  
Author(s):  
Usman Ghani ◽  
Imran Bajwa ◽  
Aimen Ashfaq
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Intelligent System ◽  
Online Reviews ◽  
Data Set ◽  
Specific Product ◽  
Fuzzy Logic Approach ◽  
Logic Approach ◽  
Customer's Loyalty ◽  
Intelligent Approach

In this paper, an intelligent approach is presented to measure customers’ loyalty to a specific product and assist new customers regarding a product’s key features. Our approach uses an aggregated sentiment score of a set of reviews in a dataset and then uses a fuzzy logic model to measure customer’s loyalty to a product. Our approach uses a novel idea of measuring customer’s loyalty to a product and can assist a new customer to take a decision about a particular product considering its various features and reviews of previous customers. In this study, we use a large sized data set of online reviews of customers from Amazon.com to test the performance of the customer’s reviews. The proposed approach pre-processes the input text via tokenization, Lemmatization and removal of stop words and then applies fuzzy logic approach to take decisions. To find similarity and relevance to a topic, various libraries and API are used in this work such as SentiWordNet, Stanford Core NLP, etc. The approach utilized focuses on identifying polarity of the reviews that may be positive, negative and neutral. To find customer’s loyalty and help in decision making, the fuzzy logic approach is applied using a set of membership functions and rule-based system of fuzzy sets that classify data in various types of loyalty. The implementation of the approach provides high accuracy of 94% of correct loyalty to the e-commerce products that outperforms the previous approaches.

Fuzzy Logic Models for Non-Programmed Decision-Making in Personnel Selection Processes Based on Gamification

Informatica ◽  
2018 ◽  
Vol 29 (1) ◽  
pp. 1-20 ◽  
Author(s):  
Javier Albadán ◽  
Paulo Gaona ◽  
Carlos Montenegro ◽  
Rubén González-Crespo ◽  
Enrique Herrera-Viedma
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Personnel Selection ◽  
Logic Models ◽  
Selection Processes

MEMPREDIKSI JUMLAH PRODUKSI ULOS BATAK DENGAN MENGGUNAKAN LOGIKA FUZZY DENGAN METODE TSUKAMOTO (Studi Kasus Cv. Ala Dos Roha)

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Sri Handayani Sianipar ◽  
Fince Tinus Waruwu ◽  
Lince Tomoria Sianturi
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Production Method ◽  
Production Data ◽  
Speed Up

Ulos batak toba is one of indonesia traditional fabric, precisely the traditional cloth of the batak toba. From time to time the ulos fabric was growing in terms of  type and motif. One of the companies that produces ulos batak is cv. Ala dos roha. The authors conducted this study aimed at predicting the amount of production of ulos batak to produced later. The author uses the previous request, inventory and production data using fuzzy logic tsukamoto. The final result of the calculation with this method will be more effective and efficient so as to speed up the decision making time to predict the amount of production to be produced next.Keywords: prediction, amount of  production, method of tsukamoto

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