scholarly journals Perancangan Alat Pendeteksi Kualitas Minyak Goreng Dengan Parameter Viskositas Dan Densitas Mengggunakan Metode Fuzzy Logic

2021 ◽  
Vol 11 (1) ◽  
pp. 22-28
Author(s):  
Alex Surapati ◽  
Azam Zyaputra ◽  
Reza Satria Rinaldi
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Oil Quality ◽  
Test Results ◽  
Inference System ◽  
The Public ◽  
Cooking Oil ◽  
Market Needs

AbstrakThe quality of cooking oil sold in the market needs to be checked to ensure its health. cooking oil quality detector is designed to make it easier for the public to know the quality of the cooking oil. The research method is to make tools and conduct testing. The test is carried out by measuring the viscosity and density using the tool made. When the viscosity of 985 fuzzification was "good", and the density was 542.93 Kg/mL of "good" fuzzification, the fuzzification was processed by a fuzzy inference system, then defuzzification occurred in the form of oil quality results. fried "good". When the viscosity of 932 fuzzification is "sufficient", and the density is 618.69 Kg/mL of "moderate" fuzzification, a fuzzy inference system occurs, a defuzzification process is "moderate", when the viscosity of 926 fuzzification is "bad", and a density of 631.31 Kg/mL fuzzification "bad", fuzzy inference system occurs, defuzzification process occurs with "bad" results. To ensure that the results are accurate, the sample is taken to the BPOM which measures free fatty acids. From the BPOM test results converted to viscosity and density. In order to obtain an accurate conversion value between viscosity and density, it is recommended that a large number of samples be tested..Keywords: viscosity, density, fuzzy logic

scholarly journals Risk Prediction of Delay in the Execution of Public Works Through Fuzzy Logic

2021 ◽  
Vol 9 (11) ◽  
pp. 317-337
Author(s):  
Andrey Valente ◽  
Manoel Nascimento
Keyword(s):  
Fuzzy Logic ◽  
Public Administration ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Real Data ◽  
Public Works ◽  
Inference System ◽  
Public Agency ◽  
The Public ◽  
Public Company

In Manaus, delays in public constructions are not uncommon as their execution deadlines are often extrapolated, even though such deadlines are obtained through preliminary technical studies. The causes that give rise to such delays are varied ranging from the occurrence of rain to the addition of quantities of existing services or additions of new services. In this research, we sought to obtain a model, using fuzzy logic, to predict the risk of delay that some variables may cause in the period of execution of the work, allowing the public administration or the contracted company to adopt measures they consider essential to mitigate this delay. Initially, documentary and bibliographic research were carried out to identify the causes that most contribute to the occurrence of delays in the works. Once these causes were identified, the construction of the fuzzy inference system was started, with six of the most significant causes identified in the research being considered as linguistic variables, namely: the hiring factor, which corresponds to the quotient between the value of the proposal. of the company and the amount budgeted by the administration; the value of the work, which is the value of the contract for the work; the engineering execution drawing, which are the engineering drawings used in the works; the alteration of quantities, which are changes in the quantities of existing services or addition of new services; authorization from public agencies, which corresponds to the permission or support of any public agency or public company for the execution of the work; and the rain. For the simulation of the created fuzzy inference system, real data from four public works were entered, and the answers of this simulation were satisfactory because they are confirmed by the documentation of the respective works. It is concluded that the system proved to be useful, as it was possible to predict the risk of delay in the execution of public works in the city of Manaus, and it can be used by both the public administration and the contractor to mitigate the causes of delays in the execution of public works.

FIS-Based Collaborative/Metacognitive Data Modeling

2015 ◽  
pp. 260-302 ◽  
Keyword(s):  
Fuzzy Logic ◽  
Online Learning ◽  
Instructional Design ◽  
Adult Learning ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Learning Cycle ◽  
Inference System ◽  
Computer Mediated

This chapter presents an instructional design (ID) that facilitates the use of fuzzy logic (FL) systems to model the collaborative and metacognitive data that are logged while a computer-mediated collaboration takes place. The materialization of this approach, namely collaboration/metacognition fuzzy inference system (C/M-FIS), along with experimental uses and extensions of it are described in detail. The quality of the collaboration (QoC) is defined on the basis of the balance of the collaborative activity within the dynamic of the pair. The ID of this online learning environment (OLE) materializes an adult learning cycle and foresees triggering of collaborative and metacognitive interaction. Experimental efforts, using the CSCL Lin2k tool, underline the potentiality of the presented approach to enhance the QoC. The latter is discussed under different ecological perspectives at the micro-, meso- and macro-level that further contribute to a broader perception of C/M-FIS model offerings on the basis of FL.

scholarly journals IMPLEMENTASI FUZZY LOGIC DALAM SISTEM PAKAR UNTUK MENDETEKSI PENYAKIT KANKER SERVIKS

2017 ◽  
Vol 15 (1) ◽  
Author(s):  
Siti Rochana, Andriani KKW, Yustina Retno Wahyu Utami
Keyword(s):  
Cervical Cancer ◽  
Weight Loss ◽  
Fuzzy Logic ◽  
Fuzzy Inference System ◽  
Death Rate ◽  
Vaginal Discharge ◽  
Fuzzy Inference ◽  
Test Results ◽  
Inference System ◽  
Bladder Pain

Cervical cancer is one of the most frequent cancer in women with the incidence and death rate from cervical cancer is quite high and is expected to continue to rise. This research will be discussed how to detect cervical cancer by implementing fuzzy logic. Fuzzy logic used is fuzzy Tsukamoto. The input parameters in the form of symptoms such as bleeding, vaginal discharge, pelvic pain, weight loss, and bladder pain. Based on 10 cases tested, there were 8 cases properly, so that the system test results by 80%.Keyword : Cervical Cancer, Fuzzy Logic, Fuzzy Inference System, Tsukamoto.

scholarly journals A Soft Computing Approach to Crack Detection and Impact Source Identification with Field-Programmable Gate Array Implementation

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Arati M. Dixit ◽  
Harpreet Singh
Keyword(s):  
Fuzzy Logic ◽  
Soft Computing ◽  
Fuzzy Inference System ◽  
Source Identification ◽  
Field Programmable Gate Array ◽  
Crack Detection ◽  
Fuzzy Inference ◽  
Inference System ◽  
Field Programmable ◽  
Computing Approach

The real-time nondestructive testing (NDT) for crack detection and impact source identification (CDISI) has attracted the researchers from diverse areas. This is apparent from the current work in the literature. CDISI has usually been performed by visual assessment of waveforms generated by a standard data acquisition system. In this paper we suggest an automation of CDISI for metal armor plates using a soft computing approach by developing a fuzzy inference system to effectively deal with this problem. It is also advantageous to develop a chip that can contribute towards real time CDISI. The objective of this paper is to report on efforts to develop an automated CDISI procedure and to formulate a technique such that the proposed method can be easily implemented on a chip. The CDISI fuzzy inference system is developed using MATLAB’s fuzzy logic toolbox. A VLSI circuit for CDISI is developed on basis of fuzzy logic model using Verilog, a hardware description language (HDL). The Xilinx ISE WebPACK9.1i is used for design, synthesis, implementation, and verification. The CDISI field-programmable gate array (FPGA) implementation is done using Xilinx’s Spartan 3 FPGA. SynaptiCAD’s Verilog Simulators—VeriLogger PRO and ModelSim—are used as the software simulation and debug environment.

scholarly journals Aplikasi Pengambilan Keputusan dengan Metode Tsukamoto pada Penentuan Tingkat Kepuasan pelanggan

CAUCHY ◽  
2015 ◽  
Vol 4 (1) ◽  
pp. 10 ◽  
Author(s):  
Venny Riana Riana Agustin ◽  
Wahyu Henky Irawan
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Fuzzy Inference ◽  
Weighted Average ◽  
Fuzzy Rules ◽  
Quality Of Services ◽  
Inference System ◽  
A Value ◽  
Fuzzy Logic Analysis

Tsukamoto method is one method of fuzzy inference system on fuzzy logic for decision making. Steps of the decision making in this method, namely fuzzyfication (process changing the input into kabur), the establishment of fuzzy rules, fuzzy logic analysis, defuzzyfication (affirmation), as well as the conclusion and interpretation of the results. The results from this research are steps of the decision making in Tsukamoto method, namely fuzzyfication (process changing the input into kabur), the establishment of fuzzy rules by the general form IF a is A THEN B is B, fuzzy logic analysis to get alpha in every rule, defuzzyfication (affirmation) by weighted average method, as well as the conclusion and interpretation of the results. On customers at the case, in value of 16 the quality of services, the value of 17 the quality of goods, and value of 16 a price, a value of the results is 45,29063 and the level is low satisfaction

scholarly journals A Fuzzy Logic Based System for Secure Scrum

2019 ◽  
Vol 8 (4) ◽  
pp. 8961-8964
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Inference System ◽  
System Performance ◽  
Fuzzy Inference ◽  
System Model ◽  
Basic System ◽  
Inference System ◽  
General Functioning ◽  
Software Engineers

Software is a basic system that acts as a major key part in general functioning system like securing the need of performance and scope of the system. Here the security is given to unauthorized user as unauthorized client that casually gets the change or modification within the system by effecting the efficiency and functionality of the system. So in order to overcome this issue new improved software is taken that improves the system performance and security. the paper represents a new fuzzy logic based system for handling secured attribute and assessment in software. Based on this reason we propose PC1 and bugs dataset for fuzzy inference system can be used. This secured system model helps software engineers to select secured and safety software for the performance and ambiguity.

EKSTRAKSI FITUR PEMBULUH DARAH CITRA FUNDUS RETINA MENGGUNAKAN FUZZY LOGIC

2021 ◽  
Vol 26 (2) ◽  
pp. 163-175
Author(s):  
Asyaroh Ramadona Nilawati ◽  
Taufik Hidayat
Keyword(s):  
Fuzzy Logic ◽  
Optic Disc ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Median Filtering ◽  
Inference System

Ekstraksi pola pembuluh darah retina dapat dimanfaatkan dalam sistem biometrik sebagai otentikasi keamanan. Citra hasil ekstraksi pola pembuluh darah retina dapat dimasukkan ke dalam fitur untuk identifikasi sistem biometrik. Salah satu metode yang dapat dilakukan untuk melakukan segmentasi pembuluh darah retina adalah metode fuzzy logic. Pada penelitian ini, dilakukan ekstraksi pembuluh darah citra fundus retina menggunakan implementasi fuzzy logic. Peneliti menggunakan sejumlah 20 citra fundus yang diperoleh dari dataset DRIVE berformat .tif. Proses segmentasi dimulai dengan tahap preprocessing yang berisikan konversi citra menjadi grayscale, median filtering, perataan histogram CLAHE, dan eliminasi optic disc, kemudian dilanjutkan dengan pembuatan fuzzy inference system. Tahapan preprocessing yang digunakan merupakan hasil dari rangkaian uji coba peneliti dengan melihat hasil dari setiap uji coba yang dilakukan, sehingga mendapatkan citra yang menonjolkan fitur pembuluh darah dan menghilangkan noise atau fitur retina yang tidak diperlukan seperti optic disc. Uji coba segmentasi dilakukan pada Polyspace R2020a sebagai media untuk menjalankan program mulai dari preprocessing hingga segmentasi menggunakan fuzzy logic. Keluaran dari segmentasi ini berupa citra segmentasi hasil dari metode fuzzy logic dan crisp value. Metode fuzzy logic berhasil diterapkan untuk melakukan ekstraksi pembuluh darah retina dan menghasilkan crisp value. Hasil penelitian ini diharapkan dapat digunakan sebagai salah satu fitur sistem identifikasi biometrik retina.

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