scholarly journals Penerapan Metode Fuzzy Mamdani untuk Menentukan Jumlah Pendapatan Pegadaian Berdasarkan Jumlah Omset Harga Emas dan Kurs

2020 ◽  
Vol 10 (1) ◽  
pp. 89-104
Author(s):  
Rahmawati ◽  
Rahima Dina ◽  
Wartono
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Exchange Rates ◽  
Total Income ◽  
Corporate Planning

Corporate planning in determining the amount income decision making for the period based on turnover, gold and exchange rates at the Pegadaian Syariah Branch Subrantas Sidomulyo Unit Pekanbaru. The Purpose of this study is to investigate the use of fuzzy logic aplication using Mamdani methos for dicision making determination of total income. The results of this study indicate that the prediction of income with accuracy reaches 87,4632%.

DEVELOPMENT OF MODELS FOR DIAGNOSTIC DIABETES BASED ON FUZZY LOGIC METODS

2021 ◽  
pp. 90-95
Author(s):  
Евгений Николаевич Коровин ◽  
Екатерина Ивановна Новикова ◽  
Олег Валерьевич Родионов
Keyword(s):  
Mathematical Modeling ◽  
Decision Making ◽  
Information Technology ◽  
Fuzzy Logic ◽  
Human Body ◽  
Patient Information ◽  
Decision Making Process ◽  
Speed Up ◽  
Definition Of

В статье рассматриваются разработки методов интеллектуальной поддержки процесса диагностики сахарного диабета, а также определение его типа. В последние годы количество людей, страдающих данным заболеванием, неуклонно растет, а без своевременной диагностики эта патология может нанести огромный вред организму человека. Сахарный диабет 1 типа опасен тем, что в основном возникает у людей молодого возраста. Оперативное обнаружение диабета, а также определение его типа, поможет не только избежать возможных осложнений, но и в некоторых случаях предотвратить смерть пациента. Информационные технологии все чаще используются в различных сферах деятельности для разработки новых или совершенствования существующих методов обработки данных, особенно это можно заметить в сфере медицины. В настоящее время врач самостоятельно ставит диагноз, основываясь на результатах различных анализов, однако, для ускорения процесса принятия решения, можно воспользоваться методами математического моделирования, а именно: моделями диагностики диабета на основе нечеткой логики. Для наибольшего удобства данный способ распознавания заболевания впоследствии можно реализовать в информационно-программное обеспечение, которое сможет еще больше увеличить эффективность и скорость распознавания патологии The article discusses the issues of the incidence of diabetes in the population, in particular, the definition of its type. In recent years, the number of people suffering from this disease has been steadily growing, and without timely diagnosis, this pathology can cause enormous harm to the human body. Prompt detection of diabetes, as well as determination of its type, will help not only avoid possible complications, but also in some cases prevent the death of the patient. Information technology is increasingly being used in various fields of activity to develop new or improve existing methods of data processing, especially in the field of medicine. Currently, the doctor independently makes a diagnosis based on the results of various analyzes, however, to speed up the decision-making process, you can use the methods of mathematical modeling, namely, models of diabetes diagnostics based on fuzzy logic. For the greatest convenience, this method of disease recognition can subsequently be implemented in information software, which can further increase the efficiency and speed of pathology recognition

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 Development of the generic system of inference rules by knowledgebase

2021 ◽  
pp. 1-9
Author(s):  
Andrey Sergeevich Kopyrin ◽  
Alina Olegovna Kopyrina
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Fuzzy System ◽  
Fuzzy Inference ◽  
Structural Characteristics ◽  
Fuzzy Cluster ◽  
Inference Rules ◽  
Digital Information ◽  
Subject Field

The authors propose to align logical inference with the apparatus of fuzzy sets. When each solution is associated with a set of possible results with the known transitional probabilities, the solution is based on the digital information under uncertainty. Therefore, the main purpose of using fuzzy logic in expert systems consists in creation of computing devices (or software applications) that can imitate human-level reasoning and explain the techniques of decision-making. The goal of this research consists in detailed description of the reproducible standard method of setting rules of inference of the expert system for various economic subject fields, using a universal pattern of knowledgebase. For decision-making in a fuzzy system, the author suggests using the process of identification rule framework – determination of structural characteristics of fuzzy system, such as the number of fuzzy rules, number of linguistic terms the incoming variables are divided to. Such identification is conducted based on the fuzzy cluster analysis, using fuzzy decision trees. The authors present the structural chart of inference method on the basis of fuzzy logic. The presented in the article method of setting rules and fuzzy inference algorithm presented can be implemented in different areas of economics. The novelty of this work consists in automation and integration of the system for determination of fuzzy inference rules with the stage of input data collection in the subject field.

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

IMPLEMENTASI MANAJEMEN PEMBELAJARAN TAHFIDZUL QUR’AN DI MI ISTIQOMAH SAMBAS PURBALINGGA

2018 ◽  
Vol 19 (2) ◽  
pp. 104-120
Author(s):  
Maulana Khusen
Keyword(s):  
Decision Making ◽  
Teacher Performance ◽  
Learning Program ◽  
Target Class ◽  
Class 1 ◽  
Second Year ◽  
Learning Management ◽  
Coordination Meeting

Abstract: The results of the study show that: (1) Tahfidzul Qur'an learning planning is done through the preparation of memorization targets and the determination of effective weeks and days in each semester; (2) Organizing is carried out through the division of tasks and responsibilities as well as the construction of the structure of the tutoring teacher; (3) The mobilization is carried out through the coordination meeting of the Tahfidz coordinator as a shering forum for decision making and direction of the Tahfidzul Qur'an learning program and the implementation of learning is carried out every Monday-Friday; and (4) Supervision is carried out through assessing teacher performance at the end of December and June. The highest achievement target for the second year of the implementation of the Tahfidzul Qur'an's 2017/2018 year program is juz 29 and 30, the lowest target for class 1 is juz 30 to Surat al Ghosyiyyah. For class 1, 85% of the target is achieved and 11% of students exceed the target. Class 2 targets reached 19%. Class 3, 10.86% reached the target and 0.35% of students exceeded the target. Class 4 tarjet reached 12.44%. Class 5 targets reached 4.24%, and the last grade 6 target reached 13.79% and 1.5% of students exceeded the target. Keywords: Learning Management, Tahfidzul Qur'an.

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

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 A New Grey Approach for Using SWARA and PIPRECIA Methods in a Group Decision-Making Environment

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1554
Author(s):  
Dragiša Stanujkić ◽  
Darjan Karabašević ◽  
Gabrijela Popović ◽  
Predrag S. Stanimirović ◽  
Muzafer Saračević ◽  
...  
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Multiple Criteria Decision Making ◽  
Grey System Theory ◽  
Multiple Criteria ◽  
Decision Making Process ◽  
Grey System ◽  
Criteria Weights

The environment in which the decision-making process takes place is often characterized by uncertainty and vagueness and, because of that, sometimes it is very hard to express the criteria weights with crisp numbers. Therefore, the application of the Grey System Theory, i.e., grey numbers, in this case, is very convenient when it comes to determination of the criteria weights with partially known information. Besides, the criteria weights have a significant role in the multiple criteria decision-making process. Many ordinary multiple criteria decision-making methods are adapted for using grey numbers, and this is the case in this article as well. A new grey extension of the certain multiple criteria decision-making methods for the determination of the criteria weights is proposed. Therefore, the article aims to propose a new extension of the Step-wise Weight Assessment Ratio Analysis (SWARA) and PIvot Pairwise Relative Criteria Importance Assessment (PIPRECIA) methods adapted for group decision-making. In the proposed approach, attitudes of decision-makers are transformed into grey group attitudes, which allows taking advantage of the benefit that grey numbers provide over crisp numbers. The main advantage of the proposed approach in relation to the use of crisp numbers is the ability to conduct different analyses, i.e., considering different scenarios, such as pessimistic, optimistic, and so on. By varying the value of the whitening coefficient, different weights of the criteria can be obtained, and it should be emphasized that this approach gives the same weights as in the case of crisp numbers when the whitening coefficient has a value of 0.5. In addition, in this approach, the grey number was formed based on the median value of collected responses because it better maintains the deviation from the normal distribution of the collected responses. The application of the proposed approach was considered through two numerical illustrations, based on which appropriate conclusions were drawn.

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