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Construction of fuzzy radial basis function neural network model for diagnosing prostate cancer Agus Maman Abadi; Dhoriva Urwatul Wutsqa; Nurlia Ningsih
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 4: August 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i4.20398

Abstract

In this paper, we propose a construction of fuzzy radial basis function neural network model for diagnosing prostate cancer. A fuzzy radial basis function neural network (fuzzy RBFNN) is a hybrid model of logical fuzzy and neural network. The fuzzy membership function of the fuzzy RBFNN model input is developed using the triangle function. The fuzzy C-means method is applied to estimate the center and the width parameters of the radial basis function. The weight estimation is performed by various ways to gain the most accurate model. A singular value decomposition (SVD) is exploited to address this process. As a comparison, we perform other ways including back propagation and global ridge regression. The study also promotes image preprocessing using high frequency emphasis filter (HFEF) and histogram equalization (HE) to enhance the quality of the prostate radiograph. The features of the textural image are extracted using the gray level co-occurrence matrix (GLCM) and gray level run length matrix (GLRLM). The experiment results of fuzzy RBFNN are compared to those of RBFNN model. Generally, the performances of fuzzy RBFNN surpass the RBFNN in all accuracy calculation. In addition, the fuzzy RBFNN-SVD demonstrates the most accurate model for prostate cancer diagnosis.
Classification of heart disease based on PCG signal using CNN Aditya Wisnugraha Sugiyarto; Agus Maman Abadi; Sumarna Sumarna
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 5: October 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i5.20486

Abstract

Cardiovascular disease is the leading cause of death in the world, so early detection of heart conditions is very important. Detection related to cardiovascular disease can be conducted through the detection of heart signals interference, one of which is called phonocardiography. This study aims to classify heart disease based on phonocardiogram (PCG) signals using the convolutional neural networks (CNN). The study was initiated with signal preprocessing by cutting and normalizing the signal, followed by a continuous wavelet transformation process using a mother wavelet analytic morlet. The decomposition results are visualized using a scalogram, then the results are used as CNN input. In this study, the PCG signals used were classified into normal, angina pectoris (AP), congestive heart failure (CHF), and hypertensive heart disease (HHD). The total data used, classified into 80 training data and 20 testing data. The obtained model shows the level of accuracy, sensitivity, and diagnostic specificity of 100%, 100%, and 100% for training data, respectively, while the prediction results for testing data indicate the level of accuracy, sensitivity, and specificity of 85%, 80%, and 100%, respectively. This result proved to be better than the mother wavelet or other classifier methods, then the model was deployed into the graphical user interface (GUI).
Pemodelan Tingkat Inflasi di Indonesia dengan Menggunakan Sistem Fuzzy Agus Maman Abadi; Ali Muhson
Jurnal Ekonomi dan Pendidikan Vol 2, No 2 (2005)
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (63.671 KB) | DOI: 10.21831/jep.v2i2.638

Abstract

Tujuan penulisan ini adalah untuk memperkirakan tingkat inflasi di Indonesia. Jika data-data tentang nilai tukar rupiah dan pendapatan nasional dipandang sebagai input data, kemudian tingkat inflasi di Indonesia dipandang sebagai output data, maka akan dibuat suatu model untuk output data berdasarkan input data tersebut dengan menggunakan sistem fuzzy. Model ini diujicobakan untuk data-data diluar sampel. Selanjutnya dengan pemilihan parameter yang tepat akan diperoleh model yang sesuai dengan tingkat kesalahan yang diinginkan.
Perancangan Logika Kabur untuk Memperbaiki Kinerja Toto Sukisno; Agus Maman Abadi
Jurnal Pendidikan Matematika dan Sains No 1 (2006): Jurnal Pendidikan Matematika dan Sains Tahun XI
Publisher : Faculty of Mathematics and Natural Sciences, Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (211.918 KB) | DOI: 10.21831/jpms.v14i1.769

Abstract

Tujuan penulisan artikel ini adalah untuk mendapatkan rancangan kendali logika fuzzy guna menggantikan kendali Proportional Integral Derivative Power System Stabilizer pada sistem eksitasi.Studi stabilitas yang tepat dan kontinyu sangat diperlukan untuk menganalisis sistem supaya dapat beklerja dengan efektif. untuk mempelajari stabilitas dinamis yaitu stabilitas generator yang mengalami perubahan beban, maka digunakan permodelan terhadap komponen-komponen seperti generator sinkron, saluran transmisi, dan beban yang diturunkan dari persamaan-persamaan matematis yang mewakili perilaku dinamis sistem. Penurunan persamaan-persamaan matematis yang mewakili perilaku dinamis sistem dapat dideskripsikan dengan menggunakan persamaan diferensial linear dan akibat yang terjadi yang berupa osilasi frekuensi rendah dapat distabilkan kembali dengan menambahkan sinyal kendali tambahan. Penambahan sinyal kendali tersebut dilakukan dengan menambahkan blok PSS berupa blok washout dan lead compensator dengan memasukan berupa perubahan kecepatan rotor, perubahan frekuensi atau perubahan akselerasi daya.Upaya memperbaiki kompensator mendahului untuk saat ini menggunakan kendali kompensator PID(Proportional Integral Derivative). Kendali PID dapat memperbaiki tanggapan transien dan mengeliminasi galat kondisi tunak. Tetapi di sisi lain, PID juga mempunyai kelemahan yaitu timbulnya lonjakan yang relatif besar dan waktu pencapaian kondisi tunak yang relatif lama. Berdasarkan kelemahan-kelemahan tersebut, dalam tulisan ini akan mencoba mendesain sistem kendali logika kabur untuk menggantikan kendali PID yang diharapkan dapat mengatasi kelemahan-kelemahan pada kendali PID.Kata kunci: kendali PID, logika fuzzy, kestabilan
Pengaruh PMR dengan TGT terhadap Motivasi, Sikap, dan Kemampuan Pemecahan Masalah Geometri Kelas VII SMP Mohammad Saeful Amri; Agus Maman Abadi
PYTHAGORAS Jurnal Pendidikan Matematika Vol 8, No 1: June 2013
Publisher : Department of Mathematics Education, Faculty of Mathematics and Natural Sciences, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (564.563 KB) | DOI: 10.21831/pg.v8i1.8494

Abstract

Penelitian ini bertujuan untuk mendeskripsikan: (1) keefektifan Pembelajaran Matematika Realistik (PMR) dan Pembelajaran Matematika Realistik (PMR) dengan metode belajar kooperatif tipe Teams Games Tournaments (TGT) ditinjau dari motivasi, sikap, dan kemampuan pemecahan masalah; (2) apakah PMR dengan TGT lebih baik dari pada PMR ditinjau dari motivasi, sikap, dan kemampuan pemecahan masalah Geometri pada siswa kelas VII SMP Budi Mulia Yogyakarta. Penelitian ini merupakan penelitian eksperimen semu dengan pretest-postest non equivalent group design. Populasi penelitian ini adalah seluruh siswa kelas VII yang terdiri atas tiga kelas. Kemudian diambil dua kelas secara acak sebagai sampel. Kelas VIIA diberi perlakuan PMR sedangkan VIIB diberi perlakuan PMR dengan TGT. Instrumen yang digunakan berupa angket motivasi, sikap, dan tes kemampuan pemecahan masalah. Validasi instrumen menggunakan validasi isi dan validasi konstruk. Reliabilitas instrumen menggunakan Alpha Cronbach. Data dianalisis dengan uji t-test one sample dan uji Manova. Hasil penelitian ini menunjukkan bahwa: (1) PMR dan PMR dengan TGT efektif ditinjau dari motivasi, sikap dan kemampuan pemecahan masalah; (2) MPR dengan TGT tidak lebih baik dari pada PMR ditinjau dari motivasi, sikap, dan kemampuan pemecahan masalah Geometri pada siswa kelas VII SMP Budi Mulia Yogyakarta.Kata Kunci: PMR, metode belajar kooperatif tipe TGT, motivasi, sikap, kemampuan pemecahan masalah matematika. AbstractThis study aimed to describe: (1) the effectiveness of Realistic Mathematic Education (RME) and Realistic Mathematic Education (RME) with cooperative learning of Teams Games Tournaments (TGT) type in terms motivation, attitude, and problem solving skills; (2) whether the RME with of TGT was better than RME in terms motivation, attitudes, and problem solving skills in geometry of The grade VII SMP Budi Mulia Dua Yogyakarta. This research is a quasi experiment with pretest-postest non equivalent group design. The research population was all students of grade VII SMP that tree classes. Two classes were taken randomly as the sample. VIIA class implemented RME while VIIB class implemented RME with TGT. The instruments used to collect the data were motivation and attitude questionnaires, and problem solving skills test. The instruments were validated using their content and construct. Reliability was measured using Cronbach Alpha. The data were analyzed statistically using the one sample t-test and Manova. The results of research show that: (1) RME and RME with TGT are effective in terms of motivation, attitudes, and mathematical problem solving skills; (2) RME with TGT is not better than RME in terms of motivation, attitude, and mathematical problem solving skills in geometry of grade VII SMP Budi Mulia Dua Yogyakarta.Keywords: RME (Realistic Mathematics Education), cooperative learning of TGT type, motivation, attitude, mathematical problem solving skills
Keefektifan Pembelajaran Kooperatif Tipe TGT dan GI Ditinjau dari Ketercapaian Standar Kompetensi, Sikap, Minat Matematika Abd. Haris; Agus Maman Abadi
PYTHAGORAS Jurnal Pendidikan Matematika Vol 8, No 2: December 2013
Publisher : Department of Mathematics Education, Faculty of Mathematics and Natural Sciences, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (731.702 KB) | DOI: 10.21831/pg.v8i2.8930

Abstract

Penelitian ini bertujuan untuk mendeskripsikan (1) keefektifan model pembelajaran kooperatif tipe TGT dan GI dan (2) mendeskripsikan perbandingan keefektifan model pembelajaran kooperatif tipe TGT dan GI ditinjau dari ketercapaian standar kompetensi, sikap, dan minat siswa terhadap matematika. Populasi penelitian ini adalah siswa kelas VII SMP Negeri 1 Unter Iwes Sumbawa yang terdiri atas 6 kelas. Dua kelas diambil secara acak sebagai sampel, yaitu kelas VII.3 dan VII.4. Kelas VII.3 belajar dengan model pembelajaran kooperatif tipe TGT, sedangkan kelas VII.4 belajar dengan model pembelajaran kooperatif tipe GI. Data penelitian dianalisis dengan uji One sample t test, uji T2 hoteling’s pada signifikansi 5% dan uji Independent t test. Hasil penelitian menunjukkan bahwa (1) pembelajaran matematika dengan model pembelajaran kooperatif tipe TGT dan GI efektif ditinjau dari ketercapaian standar kompetensi, sikap, dan minat siswa terhadap matematik dan (2) model pembelajaran kooperatif tipe TGT lebih efektif dibandingkan dengan model pembelajaran kooperatif tipe GI ditinjau dari ketercapaian standar kompetensi, sikap, dan minat siswa terhadap matematika.Kata Kunci: pembelajaran kooperatif, TGT, GI, ketercapaian standar kompetensi, sikap, minat. The Effectiveness of Cooperative Learning of TGT and GI Types in Terms of Achievement of Competence Standard, Attitude, Interest Mathematics AbstractThis study aims to describe (1) the effectiveness of cooperative learning model of TGT and GI type and (2) describe the comparison between the effectiveness of cooperative learning model of TGT and GI type in terms of achievement of competence standard, attitude, and interest of student toward mathematics. The research population was a Class VII student of SMP Negeri 1 Unter Iwes Sumbawa which consisted of 6 classes. Two classes, namely Class VII.4 and Class VII.3 as the research sample. Class VII.3 learned through the cooperative learning of TGT type and Class VII.4 learned through the cooperative learning of GI type. The data were analyzed using One sample t test, T2 Hoteling’s at the significance level of 5% and Independent t test. The results of the study show that: (1) mathematics learning with cooperative learning model of TGT and GI type is effective in terms of achievement of competence standard, attitude, and interests of student towards mathematic, and (2) cooperative learning model of TGT type is more effective compared with the cooperative learning model of GI type in terms of achievement of competence standard, attitude, and interest of student toward mathematics.Keywords: cooperative learning, TGT, GI, achievement of competency standard, attitude, interest.
Model Analysis of Motorcycle Suspension System Using the Fourth Order of Runge-Kutta Method Umi Nurofi’atin; Agus Maman Abadi
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 18, ISSUE 2, August 2018
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/eksakta.vol18.iss2.art3

Abstract

The suspension system is part of motorcycle that serves to absorb vibration and shocks of the road surface so as to improve the safety and comfort while driving. Motorcycle typically use double shockbreaker system which analogous to a two-spring system arranged in parallel. The aim of this researh is to analyze the model of the model of double shockbreaker motorcycle suspension system that working without outside force using passive suspension system. The data used are from damper tester experiment, then model analyzed using analytical method and the fourth order of numerical Runge-Kutta method. This research use shockbreaker observation datas that is the measurment data of spring constant and damping constant by performing damper tester using 4 different loads. The process model analysis using Matlab R2013a. Input variables are spring constant, damping constant, and the mass of the load. Methods of analysis using analytical method and the fourth order of Runge-Kutta method. While the resulting outputs are 2 spring constants, change the length of the spring, damping ratio, the optimal damping of the suspension, and the spring deflection chart against time. This model motorcycle suspension system uses solution of differential equations for the under damped suspension condition, that is the suspension system will be insulated a few moments before reaching the equilibrium position. Therefore, the resulting damping rate of the motorcycle is not optimal yet. This study found the optimal damping for each model of the suspension system. The level of accuracy of the fourth order of runge-kutta method for model analysis of the suspension system is quite high with error <0.1 and the timing of analysis is faster than the analytic method. Future research may use other methods or other input variables for more accurate analysis results.
Diagnosing Heart Disease using Wavelet Transformation and Adaptive Neuro Fuzzy Inference System (ANFIS) Based on Electrocardiagram (ECG) Indah Puspita; Agus Maman Abadi
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 19, ISSUE 1, February 2019
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/eksakta.vol19.iss1.art7

Abstract

Heart disease is the leading cause of death in the world. Heart disease is called the silent killer, because it often occcurs suddenly. Therefore, periodic cardiac examination is very necessary to reduce cases of death from heart disease.Heart disease can be known through electrocardiogram (ECG) examination. This study aims to explain the process of diagnosing heart disease through ECG using wavelet transformation and Adaptive Neuro Fuzzy Inference System (ANFIS).The process of diagnosing heart disease begins with cutting ECG signal consisting of 9-11 waves into one ECG wave, then decomposition and extraction are performed using wavelet transformation to obtain 6 parameters. The parameters will be used as input in ANFIS model. Data obtained from ECG extraction are divided into 70% training data and 30% testing data The output from the ANFIS model is a diagnosis of heart diseases, such as left bundle branch block (LBBB),  right bundle branch block (RBBB), and normal. ANFIS learning is divided into 6 stages, namely clustering data with Fuzzy C-Means method, computing the degree of membership of each data, determining fixed neurons, looking for normalized firing strength, calculating the consequent parameter values, and determining network output.The results of the study obtained the best ANFIS model with 10 clusters. The level of accuracy, specificity, and sensitivity for training data is 100%, 100%, and 100%, respectively and for the testing data, the level of accuracy, specificity, and sensitivity is 100%, 100%, and 100%, respectively.
Fuzzy Logic Application for Drought Risk Determination in Kulon Progo Regency, Daerah Istimewa Yogyakarta Province, Indonesia Bertolomeus Laksana Jayadri; Agus Maman Abadi
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 2, ISSUE 1, February 2021
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol2.iss1.art9

Abstract

This study aims to determine the drought risk of Kulon Progo Regency using fuzzy logic and study the characteristics. The input variables used in this study are the drought level, exposed population, and vulnerable population. The Mamdani method used in the fuzzy inference to obtain the output variable, that is, the Drought Risk Index (DRI). Then, the DRI are mapped to generate the drought risk map. The result shows that the fuzzy logic can be used to determine the drought risk. The drought risk level of the subdistricts in Kulon Progo Regency was fluctuated from 2010 to 2019. The drought risk level in 2010-2015 and 2019 were dominated by the low category. Meanwhile, the drought risk level in 2016-2018 was dominated by the very low category. Furthermore, the result also shows that the subdistricts located in the southern region of Kulon Progo Regency had a higher risk than those in the middle and northern regions during the last 10 years
PRELIMINARY STUDY ON APPLICATION OF MAX PLUS ALGEBRA IN DISTRIBUTED STORAGE SYSTEM THROUGH NETWORK CODING Agus Maman Abadi; Musthofa Musthofa; Emut Emut
Jurnal Sains Dasar Vol 4, No 1 (2015): April 2015
Publisher : Faculty of Mathematics and Natural Science, Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (95.393 KB) | DOI: 10.21831/jsd.v4i1.8420

Abstract

The increasing need in techniques of storing big data presents a new challenge. One way to address this challenge is the use of distributed storage systems. One strategy that implemented in distributed data storage systems is the use of Erasure Code which applied to network coding. The code used in this technique is based on the algebraic structure which is called as vector space. Some studies have also been carried out to create code that is based on other algebraic structures such as module.  In this study, we are going to try to set up a code based on the algebraic structure which is a generalization of the module that is semimodule by utilizing the max operations and sum operations at max plus algebra. The results of this study indicate that the max operation and the addition operation on max plus algebra cannot be used to establish a semimodule code, but by modifying the operation "+" as "min", we get a code based on semimodule. Keywords:   code, distributed storage systems, network coding, semimodule, max plus algebra