Article Per Year (5 Year)
p-Index From 2020 - 2025
6.226
P-Index
This Author published in this journals
All Journal MEDIA ELEKTRIKA Jurnal Teknologi Informasi dan Ilmu Komputer Teknika: Jurnal Sains dan Teknologi Setrum : Sistem Kendali-Tenaga-elektronika-telekomunikasi-komputer Jurnal Informatika dan Teknik Elektro Terapan Jurnal Rekayasa Mesin Sistemasi: Jurnal Sistem Informasi JTERA (Jurnal Teknologi Rekayasa) Jurnal Sisfokom (Sistem Informasi dan Komputer) KOMPUTIKA - Jurnal Sistem Komputer Jurnal Mnemonic International Journal of Engineering, Technology and Natural Sciences (IJETS) Devotion: Journal of Research and Community Service Fidelity : Jurnal Teknik Elektro International Journal Engineering and Applied Technology (IJEAT) Medika Trada Journal of Artificial Intelligence and Digital Business Journal of Community Service in Science and Engineering Jurnal Pengabdian dan Pemberdayaan Masyarakat Indonesia
Muchtar Ali Setyo Yudono
Department Of Electrical Engineering, Faculty Of Engineering, Universitas Sultan Ageng Tirtayasa
Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation

Published : 48 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 48 Documents
Search

 1   2   3   4   5 
Klasifikasi Katarak Objek Optic Disc Citra Fundus Retina Menggunakan Support Veactor Machine Ri Munarto
Setrum : Sistem Kendali-Tenaga-elektronika-telekomunikasi-komputer Vol 8, No 1 (2019): Edisi Juni 2019
Publisher : Fakultas Teknik Elektro - Universitas Sultan Ageng Tirtayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36055/setrum.v8i1.5793

Abstract

Katarak kerap disebut-sebut sebagai penyebab kebutaan nomor satu di Indonesia. Bahkan, mengacu pada data World Health Organization (WHO) katarak menyumbang sekitar 48% kasus kebutaan didunia dan nomer satu di Indonesia. Penelitian yang pernah dilakukan katarak diklasifikasikan melalui bebabagai macam objek seperti pembuluh darah, optic disc dan pupil dari mata. Pada penelitian ini menggunakan objek optic disc pada citra kamera fundus retina. Tujuan penelitian ini untuk menghasilkan program aplikasi deteksi dini katarak secara otomatis melalui klasifikasi katarak kedalam 4 kategori yaitu normal, mild, medium dan severe. Pemeriksaan dini pada pasien penderita katarak bagi masyarakat yang memiliki kemampuan ekonomi yang kurang seperti mayoritas penduduk pada negara sedang berkembang dirasakan akan sangat membantu. Klasifikasi diperlukan untuk membantu dokter dalam memutuskan kapan dilakukan operasi pada pasien penderita katarak. Pengolahan 60 data citra fundus retina mata pasien yang terdiri dari 15 citra retina normal, 15 citra katarak mild, 15 citra katarak medium dan 15 citra katarak severe yang yang diperoleh dari Rumah Sakit Islam Sultan Agung Semarang. Selanjutnya dilakukan proses pengklasifikasian menggunakan Static Vector Machine yang diolah dengan matlab R2014a. Dari hasil pelatihan dan pengujian diperoleh hasil akurasi rata-rata sebesar 82,14% pada seluruh kelas retina.Kata Kunci— Katarak, Optic Disc, Gray Level Coocurancy Matrix (GLCM), Static Vector Machine.
Backpropagation and Radial Basis Function Methods for Predicting Rainfall in Sukabumi City Using Artificial Neural Networks: A Comparative Analysis Sholahudin Sholahudin; Andika Kurniawan; Wahyu Dwi Nurhidayat; Muhammad Alif Alfaturisya; Ilyas Aminuddin; Anggi Dwiyanto; Yordanius Damey; Akhmad Afifuddin; Muhammad Syahrul Fauzi; Fandi Sugih; Muchtar Ali Setyo Yudono
FIDELITY : Jurnal Teknik Elektro Vol 4 No 2 (2022): Edisi Mei 2022
Publisher : Universitas Nusa Putra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52005/fidelity.v4i2.69

Abstract

The weather has a substantial impact on the ability to live organisms to carry out everyday activities, particularly outside activities. Weather data is helpful in various fields, including marine, aviation, and agriculture. The maritime domain is beneficial for establishing the optimal navigation time for a fisherman, the aviation domain helps reduce climate-related mishaps, and the agriculture sector uses weather information to develop harvest season models for agricultural products. Indonesia is a tropical nation with heavy precipitation. Utilized for various objectives, rainfall forecasting models seek the utmost precision, particularly in specialized areas such as flood control. This study is based on two techniques: the Radial Basis Function Neural Network (RBFNN) and Backpropagation Neural Network (BPNN) techniques using multiple training functions. The RBFNN approach yields less accurate results for predicting precipitation, but the multi-practice BPNN method yields more accurate results.
Bitcoin USD Closing Price (BTC-USD) Comparison Using Simple Moving Average And Radial Basis Function Neural Network Methods Muchtar Ali Setyo Yudono; Aryo De Wibowo Muhammad Sidik; Ilman Himawan Kusumah; Anang Suryana; Anggy Pradiftha Junfithrana; Adi Nugraha; Marina Artiyasa; Edwinanto Edwinanto; Yufriana Imamulhak
FIDELITY : Jurnal Teknik Elektro Vol 4 No 2 (2022): Edisi Mei 2022
Publisher : Universitas Nusa Putra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52005/fidelity.v4i2.74

Abstract

Bitcoin is a decentralized electronic money that is not controlled nor insured by a central authority. Because it is still a young system, the price of Bitcoin is extremely unpredictable, making Bitcoin users and investors uneasy. A typical difficulty for investors and traders is predicting the future movement of the value of Bitcoin electronic money based on historical data. Because investors and traders only notice swings in global currency prices and make Bitcoin buy/sell decisions instinctively, they frequently make the erroneous buy/sell decisions. Many investors and traders suffered significant losses as a result of this error. Losses can be reduced by employing an algorithm that predicts the movement of the value of Bitcoin electronic money. Using a comparison of two methodologies, the Simple Moving Average and RBFNN, we will anticipate the closing price of Bitcoin USD (BTC-USD) from January 1, 2021 to January 31, 2021. The results obtained using the simple moving average method MSE = 0.01 percent and MAPE = 36.67 percent, and the results obtained using the RBFNN method MSE = 9.97 x 10-7 and MAPE = 9.97 x 10-5, indicating that the RBFNN method with an accuracy rate of 99.9995 percent is better than the simple moving average method in forecasting the closing price of bitcoin.
Fluid Volume Detector on a Horizontal Tube Using an Ultrasonic-based Water Level Sensor Anang Suryana; Paikun; Muchtar Ali Setyo Yudono
Fidelity : Jurnal Teknik Elektro Vol 4 No 1 (2022): Edisi Januari 2022
Publisher : Universitas Nusa Putra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52005/fidelity.v4i1.80

Abstract

Measurement of the volume of liquid in a vertical cylinder can be done by multiplying the area of the circle with the length of the cylinder. Likewise, measuring the volume of liquid in a horizontal pipe can also be done by multiplying the area by the length of the cylinder. There is a difference between the two measurements of the volume of liquid in the cylinder. In a horizontal cylinder, the measurement of area used is a measurement of the segment of the circle that is exposed to the liquid. To get the value of the circle area segment that is with geometric analysis. In this study, in measuring the volume of liquid in a horizontal cylinder using the multiplication between the circle area segment and the horizontal pipe length. The variables used in measuring the volume of liquid in a horizontal cylinder are, cylinder diameter 2r, liquid level H, and cylinder length L. So that in making this measuring instrument the volume of liquid in a horizontal cylinder has two variables, namely fixed and variable variables. free. For the fixed variables, namely the diameter and length of the cylinder, and for the independent variables, namely the level of the liquid level in the H pipe. In measuring the independent variables, a proximity sensor Type HC-SR04 is used. Installation of a volume measuring device on a horizontal cylinder using a PVC pipe connection type equal tee which is connected to other pipes with the same diameter with a predetermined total length. The fixed variable that has been determined is the cylinder diameter of 10.16 cm with a length of 100 cm.
Decision-Making Employee Performance Evaluation at XYZ University Using the Mamdani Fuzzy Logic Method Irvan Syah Riadi; Fahmi Fauzi; Arsal Adriana Yusuf; Muchtar Ali Setyo Yudono
FIDELITY : Jurnal Teknik Elektro Vol 3 No 2 (2021): Edisi Mei 2021
Publisher : Universitas Nusa Putra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52005/fidelity.v3i2.92

Abstract

Human resources (HR) of high quality will provide excellent job outcomes. Through the execution of quality and quality education, human quality is developed. As a tool for assessing the quality of education in Indonesia, the evaluation of a lecturer's performance plays a crucial role in education. This research intends to aid in assessing the performance of Lecturers using Fuzzy Logic. Mamdani is the fuzzy logic approach used in this study. The assessment input factors consist of Lecturer Presence in Teaching, Discipline Level, Student Assessment Results, loyalty, and Communication Level or engagement with students to provide two judgments based on a Lecturer's poor and excellent performance. This system may assist and give options for assessing the performance of Lecturers, allowing Lecturers to make optimum adjustments to recruit the most outstanding and competent lecturers. Based on the study findings, it can be inferred that an intelligent system based on fuzzy logic may be utilized to identify Lecturer performance judgments with a 90 percent degree of accuracy
Rancang Bangun Sistem Deteksi Harga Perkakas Dengan Menggunakan Augmented Reality Muchtar Ali Setyo Yudono; Rian Maulana Yusup; Fajar M.Syam; Eneng Siti Anisa Nurhasanah
FIDELITY : Jurnal Teknik Elektro Vol 3 No 3 (2021): Edisi September 2021
Publisher : Universitas Nusa Putra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52005/fidelity.v3i3.97

Abstract

Augmented Reality (AR) merupakan teknologi yang dapat menampilkan informasi yang bersifat virtual namun di sajikan pada pandangan dunia nyata. Dengan teknologi ini dalam dunia usaha yang memadai penyajian informasi dapat dilakukan dengan tepat dan akurat. Tujuan penelitian ini adalah untuk membuat aplikasi yang dapat menampilkan informasi harga barang menggunakan kamera pada smartphone android. Metode untuk mencapai tujuan dari penulisan ini yaitu dengan metode eksperimen memanfaatkan database sebagai tempat penyimpanan data harga barang dan mengumpulkan sample objek yang ada sebagai target yang akan dikenali oleh kamera untuk menampilkan informasi harga barang. Hasil dari penelitian ini yaitu menampilkan informasi harga perkakas dengan cara mengambil data dari database yang akan secara otomatis ditampilkan oleh aplikasi menggunakan kamera pada smartphone
Sistem Aplikasi Kalkulator Indeks Massa Tubuh (IMT) dengan Menggunakan Bahasa C++ Odi Akhyarsi; Muchtar Ali Setyo Yudono; Eko Susilo Budi Utomo; Idrus Firdaus; Dede Ajudin; Ajat; Yasser Arafat; Febriansyah; Hamid
Fidelity : Jurnal Teknik Elektro Vol 4 No 3 (2022): Edisi September 2022
Publisher : Universitas Nusa Putra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52005/fidelity.v4i3.129

Abstract

The Body Mass Index (BMI) calculator system is a program that can help users monitor their weight. The purpose of this research paper is to create a body mass index calculator that will make it easier for users to calculate body mass index values, classify body weight based on body mass index, and manage it. The C++ programming language is used in this procedure. The script software is visually designed and built into the Delphi IDE toolbox. The IMT calculator system was successfully designed using the C++ programming language, and the system worked well. The calculator can calculate, categorize, and provide suggestions to make it easier to determine the value of body mass index, group weight based on ideal body mass index, and manage disease so that it can be prevented early.
EEG-Based Classification of Schizophrenia and Bipolar Disorder with the Fuzzy Method Aryo Sidik; Harurikson Lumbantobing; Anang Suryana; Muchtar Ali Setyo Yudono; Edwinanto; Yudha Putra; Yufriana Imamulhak; Bayu Indrawan
INTERNATIONAL JOURNAL ENGINEERING AND APPLIED TECHNOLOGY (IJEAT) Vol. 5 No. 2 (2022): November 2022
Publisher : Nusa Putra University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52005/ijeat.v5i2.68

Abstract

This study demonstrates various fuzzy-based strategies for classifying and diagnosing people with mental illnesses such as schizophrenia and bipolar disorder. The signals collected from 32 unipolar electrodes during non-invasive electroencephalogram analysis were examined to determine their key characteristics. This research uses a sophisticated fuzzy-based radial basis function neural network. Entropy analysis and analysis of variance of other statistical parameters are also used. Three hundred and twelve schizophrenic patients and 105 individuals with bipolar disorder were examined. In contrast to healthy controls, the data indicated that the patients were correctly classified. With close to 96% accuracy, the suggested method outperforms existing machine learning methods, such as support vector machines and k-nearest neighbors. Conclusion: This categorization method will enable the development of highly accurate algorithms to identify and classify various mental illnesses.
Adaptive Neuro-Fuzzy Inference System (ANFIS) Method for Developing a Decision Support System for Determining Landslide Susceptibility Dede Sukmawan; Muchtar Ali Setyo Yudono; Danang Purwanto; Dio Damas Permadi; Anang Suryana; Utamy Sukmayu Saputri; Marina Artiyasa
Fidelity : Jurnal Teknik Elektro Vol 5 No 1 (2023): Edisi Januari 2023
Publisher : Universitas Nusa Putra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52005/fidelity.v5i1.131

Abstract

Landslide catastrophes are one of the disasters that frequently occur in Indonesia owing to the weather and climatic features, regional terrain, and geological formations that make this nation prone to landslides. The primary goal of this research is to compare the application of the fuzzy logic technique and the adaptive neuro-fuzzy inference system (ANFIS) approach to landslide detection sensors based on prior research in order to identify landslide-prone locations more easily. The Adaptive Neuro-Fuzzy Inference System (ANFIS) technique analyzes the landslide area using three factors. Rainfall, land slope, and soil moisture are examples of these factors. This variable is used to assess the area's level of vulnerability to landslides: very safe, relatively safe, relatively potential, potential, and very potential. In the study, each piece of data is subjected to a training and testing procedure to identify landslide vulnerability, with the factors and weighting methods aligned with current government standards. This study compares the rules outcomes to those of past studies as well as the system results. Based on the studies findings, it can be stated that the decision support system for the degree of landslide vulnerability utilizing the ANFIS approach is superior to the fuzzy logic method, with an accuracy rate of 86.21%.
PERAMALAN KINERJA AIR PREHEATER PLTU PELABUHAN RATU MENGGUNAKAN METODE JARINGAN SYARAF TIRUAN PERAMBATAN BALIK wahyu irwan putra; muchtar ali setyo yudono
MEDIA ELEKTRIKA Vol 16, No 1 (2023): MEDIA ELEKTRIKA
Publisher : PSTE UNIMUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/me.v16i01.11320

Abstract

Air preheater merupakan salah satu komponen pada Pembangkit Listrik Tenaga Uap (PLTU). Air preheater merupakan alat penukar panas yang berguna untuk memanaskan udara dengan memanfaatkan kembali udara pada gas buang. menjaga efisiensi kinerja Air preheater menjadi salah satu indikator penting dalam rencana pemeliharaan untuk keandalan proses produksi listrik di PLTU, maka untuk membuat rencana pemeliharaan yang baik dibutuhkan peramalan kondisi kinerja Air preheater di PLTU menggunakan Jaringan Syaraf Tiruan Perambatan Balik. Data yang digunakan untuk melakukan peramalan diambil dari data konidisi kinerja Unit 1, Unit 2, dan Unit 3 PLTU Pelabuhan Ratu pada tahun 2017 hingga tahun 2021. Peramalan ini dilakukan dengan membagi data menjadi 2 yaitu data latih dan data uji. Data latih merupakan data AHGSE pada tahun 2017 sampai 2019, data uji merupakan data AHGSE pada tahun 2020 sampai 2021. Dengan menggunakan algoritma perambatan balik dan lapisan tersembunyi satu berjumlah 25 node, lapisan tersembunyi dua berjumlah 5 node, fungsi aktivasi logsig, purelin, purelin. Penelitian ini memiliki hasil terbaik didapat pada pengujian 3 dengan nilai MSE sebesar 1,0004x10-6. Penelitian ini dapat dikatakan baik karena memiliki nilai MSE yang kecil.
Co-Authors Abdul Haris Kuspranoto Adhitia Erfina Adi Nugraha Adi Nugraha Adi Nugraha Adi Nugraha Agusutrisno, Agusutrisno Ajat Akbar, Jiwa Akhmad Afifuddin Al Bantani, Rahmat Ato'ullah Gumilang Al-Ghozi, Faturrohman Alfatih, Muhammad Fa'iz Alun Sujjada Alya Abdul Zabar Anang Suryana Andika Kurniawan Anggi Dwiyanto Anggy Pradifth Anggy Pradiftha Junfithrana Any Elvia Jakfar Arsal Adriana Yusuf Artiyasa, Marina Aryo de Wibowo Aryo De Wibowo Bayu Indrawan Budianto, Anwar Ceri Ahendyarti Danang Purwanto Dani Mardiyana Dede Ajudin Dede Sukmawan Diky Zakaria Dio Damas Permadi DM, Dwigian Netha Putra Dodi Iwan Sumarno Edwinanto Edwinanto Edwinanto Eko Susilo Budi Utomo Elok Setianingtyas Eneng Siti Anisa Nurhasanah Erlindriyani, Ratu Verlaili Erlindriyani, Ratu Verlaili Fahmi Fauzi Fajar M.Syam Fandi Sugih Fauzan, Akmal Nuur Fauzan, Anugrah Nuur Febriansyah Felycia, Felycia Franata, Nauval Franata, Nauval Franata, Nauval Futri, Dila Aura Grahito Hamid Hamidi, Eki Ahmad Zaki Handrea Bernando Tambunan Harurikson Lumbantobing Haryanto, Heri Haryanto, Heri Himawan, Ganda Idrus Firdaus Ilman Himawan Kusumah Ilyas Aminuddin Irawati, Nur Bebi Ulfah Irma Saraswati Irvan Syah Riadi Irwan, Sobriansyah Isep Tedi Jumadi Jumadi Kumaran, Ivano Lazuardi Akmal Islami Lucia Kharisma, Ivana Lufianawati, Dina Estining Tyas Luluk Hermawati M.Syam, Fajar Mansyur, Mansyur Marina Artiyasa Marina Artiyasa Marina Artiyasa Masjudin, Masjudin Maulana, Aldi Maulana, Alief Moch Rizky Muhammad Alif Alfaturisya Muhammad Syahrul Fauzi Muhammad, Fadil Muntasiroh, Laily Muttakin, Imamul Narputo, Panji Nugraha, Adi Odi Akhyarsi Otong, Muhamad Paikun Pratiwi, Septiya Hanum Putra, Wahyu Irwan Ramadhani Pratama, Mochammad Firdian Ramadhani, Ahmad Ramadhani, Ahmad Ramadhani, Ahmad Rian Fahrizal Rian Maulana Yusup Ridha, Fabrobi Fazlur Saputri, Utamy Sukmayu Saraswati, Irma Saraswati, Irma Sholahudin Sholahudin Sholahudin, Sholahudin Sriwijaya, Sayid Bahri Sutisna, Muhamad Galuh Syam, Fajar M Verlaili Erlindriyani, Ratu Wahyu Dwi Nurhidayat Wahyu Irwan Putra Wiryadinata, Romi Yasser Arafat Yordanius Damey Yudha Putra Yufriana Imamulhak Zulfiqar, Danial