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Grading System Recommendations for Students using Fuzzy Mamdani Logic
... Fuzzification is a process that places a crisp value, also called as a firm value, with a membership degree value of only 0 and 1 into a fuzzy set form with a membership degree value located in the range of values 0 to 1. In boolean logic, the result is always 0 or 1 (true or false), while in fuzzy logic, the result is somewhere between 0 and 1 [10]. The fuzzy set is a linguistic value that is then processed based on the membership function limits [11]. ...
... Defuzzification is the process of combining the outputs of the previous processes (fuzzification and inference) to produce a fuzzy output, which is transformed back into firm numbers [14]. In this study, defuzzification was carried out using the centroid method to calculate the crisp value with the centre point (y*) of the fuzzy region [10]. The formula for the centroid method is shown in (1) ...
Counting is a material that is considered not easy for most elementary school students. Not only from the considerations that are considered challenging but also the influence of the teacher's teaching style which makes bored, and boring is also a problem. In this study, an educational game balloon shooter prime numbers were made. In game design, the Mamdani fuzzy algorithm is applied to calculate the jumrance of balloons with the input variables of remaining_balloon and remaining_time. The application of the Mamdani fuzzy algorithm is considered successful, as evidenced by the high percentage rate of appearance of all balloons, reaching 76.4%.
... Motode fuzzy yang digunakan pada penelitian ini menggunakan Metode Fuzzy Mamdani yang terdiri dari tiga tahapan: fuzzifikasi, mesin inferensi, dan defuzzifikasi [17] yang digunakan untuk merekomendasikan nilai kadar unsur hara Nitrogen (N), Fosfor (P), dan Kalium (K) yang terkandung dalam tanah. Rekomendasi diambil berdasarkan besar nilai NPK yang masuk dalam klasifikasi Rendah, Sedang, atau Tinggi. ...
Profil kesuburan tanah merupakan hal yang penting dalam pertanian karena merupakan media utama dalam bercocok tanam. Penggunaan pupuk kimia dan pestisida secara terus menerus dan berlebihan akan dapat menimbulkan perubahan sifat fisika dan kimia tanah yang pada akhirnya akan dapat menyebabkan tanah menjadi kritis. Hal ini akan berpengaruh pada produktivitas hasil panen para petani. Salah satu upaya untuk mengetahui tingkat kesuburan tanah adalah melalui diagnosa unsur hara dalam tanah. Tujuan penelitian ini adalah untuk membuat pemodelan sistem optimalisasi deteksi kadar unsur hara dalam tanah menggunakan fuzzy. Melalui simulasi ini akan didapatkan data kadar unsur hara tanah dengan parameter unsur hara N (Nitrogen), P (Fosfor) , K (Kalium) menggunakan labview. Berdasarkan parameter tersebut kemudian dihasilkan berapa nilai kadar unsur hara NPK dalam tanah apakah rendah, sedang atau tinggi.
... In the Boolean system truth value, one represents the absolute truth value, and zero represents the absolute false value. i.e., one is true, and zero is false [2]. However, in the case of a fuzzy logic system, we have intermediate values, which are partially true and partially false. ...
This study aims at developing a fuzzy approach for the educational grading systems. Through this study a fuzzy logic-based grading card is suggested. The grading system based on crisp approach just deals with numbers. Fuzziness, being an important property of language, motivates us to work and study in this fuzzy environment. Before discussing the actual grade card some introduction about the key concepts is given for the readers. We have also analyzed the difference in grading and evaluating systems followed from the decades and the new fuzzy logic-based evaluation system. It also includes connectivity levels, advantages, and disadvantages between both evolution methods. The future scope of the fuzzy grading system is also discussed. The report will conclude with the answer to the question, “Is a fuzzy logic- based grade card worth for the educational grading systems?”. Moreover, towards the end, suggestions will be provided on how to bring more of these fuzzy approaches into education systems.
... The approach to solving this problem is by using the Fuzzy Mamdani algorithm implemented in the system. This algorithm has quite a fast execution time and uses less memory usage [8]. It also can be used for grading based on some input points. ...
Over time, educational games that exist is increasing. It is very unfortunate that there are some educational games that are too focused on the educational aspect so that they forget their identity as games that aim to relieve fatigue. This research was conducted to avoid this problem. To provide an interesting experience from the game being played, the artificial intelligence system is implemented, the first one is Bezier Curve Algorithm. An algorithm that forms a curve trajectory that will become a cross motion of obstacles. Finite State Machine for the Non-Player Character (NPC) behavior. The last one is Fuzzy Mamdani algorithm, it is an algorithm that will be used in calculating the score in the game. By applying all the algorithm to some aspects of the game, there will be an interesting experience in every game play, because one gameplay will not be similar to the previous one. This game was developed on the Android platform. The test was conducted on 33 high school/vocational high school students with the age range (15-20 years). The results obtained, 97% of respondents agree that the game is interesting for them and 90.9% feel interested in Indonesian debate after playing the game.
... Based on these considerations and reasons, making equipment in the form of a prototype is necessary. Moreover, a tool to measure the level of turbidity of water with the fuzzy method [3,4,7,10,11] and a microcontroller still needs to improve the level of precision. so that it is obtained the water's turbidity level and as a guide for changing the water of ornamental fish aquariums. ...
Water is a source of much-needed living things such as daily needs and transportation routes, and also as a source of energy. Water is also essential as a water quality factor. Good water for treating cold-water ornamental fish with temperatures below 20o Celcius has a maximum water turbidity value of 10 NTU (Nephelometric Turbidity Unit); if the turbidity level is above 10 NTU, the water will be declared cloudy and affect fish health. The object of this research is ornamental aquarium fish with the type of goldfish. The research method used is qualitative. The research flow begins with observing the problem, then designing and simulating the Arduino Uno as a place to process the measuring data. The prototype of this tool aims to show changes in the level of turbidity of water from the value of water turbidity. This prototype uses the fuzzy method to assist the testing process. This study's results for five days showed that 1 out of 5 tests indicated that the aquarium water was cloudy, namely on the fifth day. The results of this study are expected to be implemented in a prototype for measuring water turbidity using the fuzzy method using a microcontroller. The design of this water turbidity measuring instrument is expected to estimate the turbidity of water or liquid correctly, precisely, accurately, with a small error rate, and notify warnings for replacing ornamental fish aquarium water.
... By comparing FIS and HFIS, it is observed that the HFIS has higher classification performance. Khomeiny et al. [32] used the Mandani fuzzy method to construct a fuzzy reasoning system that provides teachers with scoring suggestions. The system took students' test scores and students' behavior scores as input, and output suggestions by combining fuzzy rules obtained from artificial summaries. ...
From early 2020, a novel coronavirus disease pneumonia has shown a global “pandemic” trend at an extremely fast speed. Due to the magnitude of its harm, it has become a major global public health event. In the face of dramatic increase in the number of patients with COVID-19, the need for quick diagnosis of suspected cases has become particularly critical. Therefore, this paper constructs a fuzzy classifier, which aims to detect infected subjects by observing and analyzing the CT images of suspected patients. Firstly, a deep learning algorithm is used to extract the low-level features of CT images in the COVID-CT dataset. Subsequently, we analyze the extracted feature information with attribute reduction algorithm to obtain features with high recognition Then, some key features are selected as the input for the fuzzy diagnosis model to the training model. Finally, several images in the dataset are used as the test set to test the trained fuzzy classifier. The obtained accuracy rate is 94.2%, and the F1-score is 93.8%. Experimental results show that, compared with the deep learning diagnosis methods widely used in medical image analysis, the proposed fuzzy model improves the accuracy and efficiency of diagnosis, which consequently helps to curb the spread of COVID-19.
Nutritional status is something that should consider because it is related to the level of health. Poor health can lead to malnutrition and death. The purpose of this study is to create a tool with a system that can determine the value and category of Body Mass Index (BMI) automatically using fuzzy logic to maintain nutritional status. However, because BMI can only decide underweight or overweight, it is necessary to determine the fat percentage based on the British Journal of Nutrition. In determining BMI and fat percentage, a load cell weight sensor with a capacity of 200 kg as a bodyweight measurement, an ultrasonic sensor HCSR-04 as a body height measurement, and a keypad that functions to enter a name, age, gender, and type of activity data. Database in this system can provide and store easier and real-time data, so the data output is accessible directly. The results are analyzed by comparing the measurement with standard tools. The BMI test taken 5 times, showed that the categories in the system (very thin, thin, normal, heavy, obese) were the same as the MATLAB test and manual calculations. Meanwhile, the results of testing body fat percentage taken 4 times also show the same category as the Body Monitor tool. So, this system can use for daily to monitor the condition of nutritional status and fat percentage in real-time.
Sliding window analysis has been extensively applied in evolutionary biology. With the development of the high-throughput DNA sequencing of organisms at the population level, an application that is dedicated to visualizing population genetic test statistics at the genomic level is needed. We have developed the sliding window analysis viewer (SWAV), which is a web-based program that can be used to integrate, view and browse test statistics and perform genome annotation. In addition to browsing, SAV can mark, generate and customize statistical images and search by sequence alignment, position or gene name. These features facilitate the effectiveness of sliding window analysis. As an example application, yeast and silkworm resequencing data are analyzed with SWAV. The SWAV package, user manual and usage demo are available at http://swav.popgenetics.net.
The Utilization of renewable energy such as a photovoltaic system is the foremost alternative in transfers generated by conventional power plants, but the lack of photovoltaics is support for light intensity. The purpose of this research is to develop a pilot-scale smart grid photovoltaic system that can regulate the supply of electrical energy from either the battery or the power supply. The control system in this study uses the Mamdani fuzzy logic method in determining automatic system performance. This system monitors the intensity of light and battery which are then used as automatic safety parameters on the power supply, battery, and photovoltaic. The results of this study display the indicator results from the microcontroller in supplying electrical energy for the use of electrical loads, Power Supply has been served the load when the battery is in a low state which have a voltage <11 Volts, the battery has been served the load when the condition of the battery is in a medium and high condition which has a voltage of 11.5 <; ....; <13 Volts. PV has been served batteries or loads when the light intensity is cloudy and bright which have a light intensity of 3585 <; ...; <10752 Lux. This system can reduce dependence on conventional energy without reducing the quality of the energy supply at load and Photovoltaic system dependence on light intensity does not affect the supply of energy consumption to electrical loads.
Produksi merupakan salah satu kegiatan yang dilakukan dalam sebuah perusahaan khususnya PT Rigunas Agri Utama yang bergerak dalam bidang pengolahan minyak sawit (palm oil). Perencanaan pengambilan keputusan perusahaan dalam menentukan jumlah produksi pada satu periode selanjutnya, bergantung pada sisa persediaan dari satu periode sebelumnya dan juga perkiraan jumlah permintaan pada satu periode selanjutnya. Jumlah permintaan dan persediaan merupakan suatu ketidakpastian. Logika Fuzzy merupakan salah satu ilmu yang dapat menganalisa ketidakpastian. Tujuan dari penelitian ini adalah untuk mengetahui penggunaan aplikasi logika Fuzzy metode Mamdani dalam pengambilan keputusan penentuan jumlah produksi. Pada penelitian ini digunakan metode Mamdani dengan penggunaan perangkat lunak matlab sebagai alat bantu dalam proses prediksi, baik yang menggunakan dua variabel linguistik maupun yang menggunakan tiga variabel linguistik. Untuk mendapatkan keluaran dari metode ini diperlukan 4 tahapan yakni; 1) Pembentukan himpunan fuzzy; 2) Aplikasi fungsi keanggotaan; 3) Rule fuzzy ; 4) Defuzzifikasi, dari hasil defuzzifikasi inilah kita bisa menentukan keputusan yang akan diambil
The selection process among outstanding students in a department has a big problem. This process is not fair because only involve one criteria and ignore the other criteria. We need the best student to participate in a competition held by the Indonesia Security Incident Response Team on Internet Infrastructure (ID SIRTII) of the Ministry of Communication and Information. This process uses Weka software to calculate the best student. It provides the various method to explore the data. One of them is clustering method. There are many algorithms in clustering method. In this research, we will investigate widely about one of that algorithms. Its name is K-Means. This algorithm (K-Means) will give the recommendations about the best student based on the cluster. It will represent the many clusters of a student group. The best cluster can be calculated more to get the names of the best students group. They are eligible to enter the competition. K-means involve the GPA (Grade Point Average) and related course to support the academic skill in order to get the best student. This research helps the teacher select the best student to enter the competition. Many similar cases can use this algorithm in order to get the best student.
article's link : http://journal.umy.ac.id/index.php/st/article/view/708/858
Integrative and fuzzy transformation of sustainable education
A transformation of the education system based on the integrity logic of Piaget and Fuzzy Logic Zade is proposed.
Transformation is subject to the paradigm of learning, the knowledge structure of the subject programs, the goals of the tasks and exercises, the assessment and the technology of learning.
Subject knowledge will be modeled by the IFMK technology.
Decision Support System is a system commonly used to assist management in assisting decision-making in top managerial sections, Multi-Criteria Decision Making (MCDM) is one of many decision-making methods that can be used to select the best alternative from a number of alternatives based on certain criteria, one of the methods that can be utilized is the Elimination Et Choix Traduisant la Realite (ELECTRE) method that works based on the concept of outranking using pairwise comparisons of each alternative based on appropriate criteria, this paper applies the ELECTRE method in a web based application that can be employed for input and output dynamic for alternative, criteria, user values and also a fast ranking process, the choice of web based application because there is many research about decision support system but only few that applied to application, and this research tries to applied ELECTRE method to web based application.
Semakin pesatnya pertumbuhan pengetahuan dan teknologi di bidang konstruksi yang mendorong masyarakat lebih memperhatikan standar mutu serta produktivitas kerja untuk dapat berperan serta dalam meningkatkan sebuah pembangunan konstruksi dengan lebih berkualitas. Diperlukan suatu bahan bangunan yang memiliki keunggulan yang lebih baik dibandingkan bahan bangunan yang sudah ada selama ini. Jika beton yang digunakan memiliki kualitas rendah maka dapat menyebabkan bangunan yang dibangun tidak dapat bertahan lama. Untuk itu diperlukan suatu metode yang digunakan dalam mempercepat menentukan kualitas beton. Untuk memastikan metode yang digunakan maka dilakukanlah perbandingan logika Fuzzy metode Mamdani dan metode Sugeno sehingga nanti dihasilkan sebuah metode yang paling cocok dalam menentukan kualitas beton. Logika Fuzzy berbeda dengan logika digital biasa, di mana logika digital biasa hanya mengenal dua keadaan yaitu ya atau tidak. Sedangkan logika Fuzzy meniru cara berfikir manusia dengan menggunakan konsep sifat kesamaran suatu nilai.
Nowadays, employees are big assets to an institution. Every employee has a different educational background, degree, work skill, attitude and ethic that affect the performance. An institution including government institution implements a promotion system in order to improve the performance of the employees. Pangandaran Tourism, Industry, Trade, and SME Department is one of government agency that implements a promotion system to discover employees who deserve to get promotion. However, there are some practical deficiencies in the promotion system, one of which is the subjectivity issue. This work proposed a classification model that could minimize the subjectivity issue in employee promotion system. This paper reported a classification employee based on their eligibility for promotion. The degree of membership was decided using Mamdani Fuzzy based on determinant factors of the performance of employees. In the evaluation phase, this model had an accuracy of 91.4%. It goes to show that this model may minimize the subjectivity issue in the promotion system, especially at Pangandaran Tourism, Industry, Trade, and SME Department.
Membership function is a curve that shows mapping the input data points into the value or degree of membership which has an interval between 0 and 1. One way to get membership value is through a function approach. There are some membership functions can be used on mamdani fuzzy inference system. They are triangular, trapezoid, singleton, sigmoid, Gaussian, etc. In this paper only discuss three membership functions, are triangular, trapezoid and Gaussian. These three membership functions will be compared to see the difference in parameter values and results obtained. For case study in this paper is admission of students at popular school. There are three variable can be used, they are students' report, IQ score and parents' income. Which will then be created if-then rules.
Tujuan artikel ini adalah membuat simulasi untuk penilaian kinerja siswa menggunakan logika fuzzy untuk mengatasi masalah proses penilaian evaluasi siswa. Disamping itu belum adanya sistem khusus yang dapat mengoptimalkan dalam memberikan dukungan bagi guru dalam melakukan evaluasi yang masih bersifat perhitungan manual. Satu cara penentuan perhitungan hasil evaluasi siswa dapat dipermudah dengan menggunakan bantuan pertimbangan Artifical Intelligence (AI) sebagai optimasinya. Dalam pertimbangan evaluasi kinerja siswa ini menggunakan logika fuzzy dengan metode inference system sugeno. Metode sugeno ini merupakan metode inference fuzzy untuk aturan yang direpresentasikan dalam bentuk IF-THEN, dimana output sistem tidak berupa himpunan fuzzy, melainkan berupa persamaan linier. Kriteria yang digunakan dalam penilaian kinerja siswa meliputi very unsuccesusful, unsuccessful, average, successful, dan very successful. Pada simulasi ini hasil yang ditampilkan dengan perhitungan manual dan perhitungan Matlab sebagai pembandingnya hasil perhitungan secara manual nilai result 45,5 sedangkan pada perhitungan matlab nilai result sebesar 48,5. Sehingga dapat disimpulkan selisih yang disebabkan tingkat akurasi hasil inference rule pada perhitungan manual kurang efektif bahkan terkadang banyak inference rule yang harus disesuaikan.
In this study, a Mamdani fuzzy inference approach (MFIA) is developed for assessing ecological security of urban agglomeration. MFIA integrates pressure-state-response (PSR) model into a fuzzy logic framework, which can (1) effectively reflect the interrelationship between natural ecosystem and socio-economic systems under complex condition, and (2) capture the knowledge-based experts’ judgments and tackle the imprecise and/or vague information in the urban agglomeration ecosystem. MFIA is then applied to assessing ecological security of the Pearl River Delta urban agglomeration. Among all cities, Zhaoqing owns the highest ecological security level due to its low population pressure and rich resources (e.g., forest and arable land). The ecological security level of Foshan is the lowest due to its high population pressure, limited resources, and low response level. In order to facilitate sustainable development of the urban agglomeration, various strategies for improving ecological security level should be implemented. Foshan should both control population growth and adjust industrial structure; Shenzhen and Dongguan should promote their ecological security levels through increasing forest and green areas and controlling population; for three cities of Zhaoqing, Huizhou and Jiangmen, it is essential to enhance their infrastructures for mitigating pollutant discharges and reducing the environmental pressures. The findings could help identify ecological condition of the urban agglomeration and provide useful information for supporting regional ecological planning and management.
This paper presents a novel approach for extracting the knowledge base (KB) of a Mamdani fuzzy rule based system (FRBS) for stock market prediction. The KB, which is the most important component of the FRBS, has two main components: rule base (RB) and data base (DB). In the proposed model, the RB is learned using repeated incremental pruning to produce error reduction (RIPPER), which is state-of-the-art in classification rule induction. The RIPPER algorithm is applied to classification problems. In order to extend it for regression problems, unsupervised discretization of the target attribute and supervised discretization of continuous input attributes are used. Next, the classification rules obtained from RIPPER are fuzzified and the initial Mamdani FRBS is formed. The DB is tuned using a Genetic Algorithm (GA). The proposed model in this paper is the first model utilizing directly capabilities and benefits of rule-based classification systems in regression. The accuracy of the proposed model is tested in the context of stock market prediction, which is a complex and difficult area in regression problems. The proposed model is implemented using several indices from different stock markets such as the Taiwan Stock Exchange Index (TSE), Tehran Price Index (TEPIX). Other indices including the Industry Index, Top 50 Companies Index and Financial Group Index from Tehran Stock Exchange are also considered. Furthermore, the daily stock prices of multiple large companies such as Apple, DELL, IBM, British Airlines and Ryanair Airlines are incorporated. As shown by the mean absolute percentage error (MAPE) and non-parametric statistical tests, the proposed model offers superior performance compared to other models.
The article draws close attention to the need to consider the impact of risk on the value of estimated life cycle cost of a building object. The main goal of the proposed approach to the risk assessment is to answer the question of consideration of the impact of the identified risk factor for a given component of the life cycle cost of a building object. This model of the reasoning mechanism is built based on fuzzy interpretation of two distinctive input variables for risk, ie. the probability and effect of a unwanted phenomenon. Due to the small number of input variables and thus the minimal possible number of reasoning rules, to the construction of the model used the fuzzy reasoning model of Mamdani.
Drilling optimization aims to optimize controllable variables during drilling operations, such as weight on bit (WOB), in order to improve drilling rate of penetration and reduce well costs. Prediction models of Weight on Bit (WOB) are developed using two widely-applied fuzzy inference systems (FIS), Mamdani-type and Sugeno-type, for the Ahwaz oil field and Marun gas field formations; two large producing fields in Iran. The FIS are constructed based on field data involving multiple wells; six wells from Ahwaz field, and two wells from Marun field. The controllable input variable data for the FIS includes: rate of penetration, mud weight, formation type, pump pressure, pump flow rate and rotation rate. The key difference between these two FIS techniques is the manner in which they calculate their crisp output values. The Mamdani-type FIS requires defuzzification, whereas the Sugeno-type FIS applies a constant weighted-average technique avoiding defuzzification. The results for the two field cases evaluated convincingly demonstrate that the Sugeno-type FIS is superior to the Mamdani-type FIS for WOB prediction using the same input data and membership functions. There is scope for further refinement of FIS models for WOB prediction (e.g., by adding bit type information) and the Sugeno-type FIS methods should reduce the time and cost associated with the conventional rate of penetration methods for predicting WOB.
World Health Organization (WHO) estimated that approximately 80 thousand children died every year in view of Childhood Tuberculosis. The disease needs an appropriate treatment considering the difficulties in establishing a diagnosis in pediatric patients. The incapability of children to produce sputum becomes one of the difficulties. Sputum is used to diagnose a person suffering from tuberculosis, based on Mycobacterium tuberculosis in sputum. In this paper, Mamdani, Tsukamoto and Sugeno-types Fuzzy Inference System are applied to assist the tuberculosis diagnosis. The different technique in these three methods is aimed to determine the most appropriate method for such diagnosis. The results show that, of the three types of Fuzzy Inference System, the best model is Sugeno model. Sugeno-type FIS has a better accuracy compared to both Mamdani and Tsukamoto ones at 93%, equivalent to a fault diagnosis in 13 of 180 patients. Here, Mamdani-type FIS is provided the diagnostic accuracy of 89%, equivalent to the fault diagnosis in 20 of 180 patients. On the other hand, Tsukamoto is provided the diagnostic accuracy of 92%, equivalent to fault diagnosis in 15 of 180 patients. Based on the three systems, the most precise output is found in Sugeno-type Fuzzy with a value by 95.1% while for Fuzzy Mamdani and Tsukamoto, it values are 93.4% and 94.5%, respectively. Also, the highest level for the system sensitivity is found in Sugeno with 97.2% in comparison to Tsukamoto FIS by 96.67% and Mamdani at 94.4%.
In this letter, we investigate the sampled-data state feedback control (SDSFC) problem of Boolean control networks (BCNs). Some necessary and sufficient conditions are obtained for the global stabilization of BCNs by SDSFC. Different from conventional state feedback controls, new phenomena observed the study of SDSFC. Based on the controllability matrix, we derive some necessary and sufficient conditions under which the trajectories of BCNs can be stabilized to a fixed point by piecewise constant control (PCC). It is proved that the global stabilization of BCNs under SDSFC is equivalent to that by PCC. Moreover, algorithms are given to construct the sampled-data state feedback controllers. Numerical examples are given to illustrate the efficiency of the obtained results.
Through the use of ICT tools, such as the internet, portals, and telecommunication devices, the quality of healthcare has improved in local and global health; aiding in the development of a sustainable economy. Handbook of Research on ICTs and Management Systems for Improving Efficiency in Healthcare and Social Care brings together a valuable research collection on ICT elements needed to improve communication and collaboration between global health institutes, public and private organizations, and foundations. Highlighting the adoption and success factors in the development of technologies for healthcare, this book is essential for IT professionals, technology solution providers, researchers, and students interested in technology and its relationship with healthcare and social services.
Pendidikan: Hakekat, Tujuan, Dan Proses
- Yuli Sectio
Sistem Pengendali Lampu Lalulintas Berbasis Logika Fuzzy
- E A Nugroho
Implementasi Fuzzy Rule Based System Untuk Klasifikasi Buah Mangga
- S Hartanto
Pendidikan: Hakekat, Tujuan, Dan Proses
- rini