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All Journal International Journal of Electrical and Computer Engineering Jurnal Gamma Transmisi: Jurnal Ilmiah Teknik Elektro Bulletin of Electrical Engineering and Informatics Proceeding of the Electrical Engineering Computer Science and Informatics JOIN (Jurnal Online Informatika) Jurnal Abdimas BSI: Jurnal Pengabdian Kepada Masyarakat Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Indonesian Journal of Artificial Intelligence and Data Mining Seminar Nasional Teknologi Informasi Komunikasi dan Industri CYCLOTRON Multitek Indonesia : Jurnal Ilmiah Journal of Robotics and Control (JRC) Jurnal ABDINUS : Jurnal Pengabdian Nusantara Community Development Journal: Jurnal Pengabdian Masyarakat International Journal of Robotics and Control Systems JITEL (Jurnal Ilmiah Telekomunikasi, Elektronika, dan Listrik Tenaga) Jurnal Nasional Teknik Elektro dan Teknologi Informasi SinarFe7
Zulfatman Zulfatman
Universitas Muhammadiyah Malang
Aerospace Engineering Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Public Health

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SIGNATURE PSO: MODIFIED PARTICLE SWARM OPTIMIZATION DENGAN FUZZY SIGNATURE DAN IMPLEMENTASI PADA OPTIMALISASI KENDALI LQR Novendra Setyawan; Ermanu Azizul Hakim; Zulfatman Zulfatman
MULTITEK INDONESIA Vol 13, No 2 (2019): Desember
Publisher : Universitas Muhammadiyah Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1094.723 KB) | DOI: 10.24269/mtkind.v13i2.2227

Abstract

Particle Swarm Optimization (PSO) is an optimization that is simple and reliable to complete optimization. In this method, the distribution of particles through global search and local search is the key obtained through searching with PSO through the inertia parameter. This paper describes the method of changing the weights on PSO using fuzzy signatures. In this paper, the method used to solve the problem of optimizing the LQR control parameters on the stabilization of a double inverted pendulum. Performance evaluation is done by another weight change algorithm. Integral Time Absolute Error (ITAE) 7% compared to other algorithms. PSO signatures have resilience and are optimal in fulfilling these interests.
KOORDINASI OPTIMAL DIRECTIONAL OVERCURRENT RELAY DENGAN CUCKOO SEARCH ALGORITHM PADA SISTEM DISTRIBUSI MESH Zsa Zsa Septina Atsil; Zulfatman; Diding Suhardi
SinarFe7 Vol. 3 No. 1 (2020): Sinarfe7-3 2020
Publisher : FORTEI Regional VII Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (518.015 KB)

Abstract

Sistem distribusi mesh IEEE 8 bus merupakan salah satu bagian penting dalam sistem tenaga listrik yang berfungsi menyalurkan listrik kepada kelompok beban atau konsumen, dimana permasalahan umum yang ada pada sistem distribusi tersebut adanya gangguan di sistem proteksi yang dapat dihindari dengan adanya koordinasi sistem proteksi yang baik. Pemilihan Directional Over Current Relay (DOCR) pada jaringan distribusi ini sangat cocok karena dapat bekerja 2 arah . Tujuan dari studi ini adalah mencari nilai koordinasi DOCR dengan mengoptimalkan parameter Time Dial Setting (TDS) dan Ipickup menggunakan metode Cuckoo Search Algorithm (CSA). Hasil yang didapatkan dari metode CSA akan dimasukkan ke dalam setting DOCR untuk mengetahui koordinasi pada jaringan distribusi mesh. Nilai TDS yang didapatkan dengan menggunakan metode CSA yaitu sebesar 2,438 detik daripada perhitungan manual sebesar 6,134 detik pada jaringan distribusi dengan DG. Hal ini membuktikan bahwa metode CSA mampu digunakan dalam mengoptimalkan nilai TDS serta koordinasi antara rele primer dan rele backup yang didapatkan pada jaringan distribusi mesh ini telah berjalan dengan baik
Comparison of Machine Learning Classification Methods in Hepatitis C Virus Lailis Syafa’ah; Zulfatman Zulfatman; Ilham Pakaya; Merinda Lestandy
JOIN (Jurnal Online Informatika) Vol 6 No 1 (2021)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v6i1.719

Abstract

The hepatitis C virus (HCV) is considered a problem to the health of societies are the main. There are around 120-130 million or 3% of the world's total population infected with HCV. Without treatment, most major infectious acute evolve into chronic, followed by diseases liver, such as cirrhosis and cancer liver. The data parameters used in this study included albumin (ALB), bilirubin (BIL), choline esterase (CHE), -glutamyl-transferase (GGT), aspartate amino-transferase (AST), alanine amino-transferase (ALT), cholesterol (CHOL), creatinine (CREA), protein (PROT), and Alkaline phosphatase (ALP). This research proposes a methodology based on machine learning classification methods including k-nearest neighbors, naïve Bayes, neural network, and random forest. The aim of this study is to assess and evaluate the level of accuracy using the algorithm classification machine learning to detect the disease HCV. The result show that the accuracy of the method NN has a value of accuracy are high, namely at 95.12% compared to the method KNN, naïve Bayes and RF in a row amounted to 89.43%, 90.24%, and 94.31%.
Peta Elektronik Sebagai Media Informasi Bagi Tunanetra Berbasis Labview dan NI MyRio-1900 Zulfatman; Akhyar Anadiansyah; Nurkasan
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 1: Februari 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1912.636 KB)

Abstract

Electronic map is one of the learning media developed for the blind. The media can fulfill the blind needs in acquiring knowledge. This study aims to develop electronic map as learning media for the blind. On this electronic map, the TCS3200 color sensor was used to recognize embossed maps that have been given different colors. Each color had different RGB frequencies and values. NI MyRio-1900 served as an interface that integrated personal computer as a human machine interface with sensors. Through NI MyRio-1900, personal computer can find out the responses generated by the sensor in matching colors, acquire the period, duty cycle, total frequency, and frequency graph, and can sort the information to be conveyed to the blind. Information about the area whose color was read by the sensor would be delivered through a loudspeaker. From the tests performed, it appeared that the TCS3200 color sensor was able to detect 28 color areas on the map correctly, with RGB sensor values were slightly different from the RGB values in the literature. Malang, for example, was light green, had a frequency value of each R = 345, G = 226, and B = 117, which was converted to obtain the RGB sensor value of R = 140, G = 194, B = 64, with period value of 0.00001715 s, 52.2145% duty cycle, and voice issued in the form of information and potential in the area of Malang.
Comparison of Machine Learning Classification Methods in Hepatitis C Virus Lailis Syafa’ah; Zulfatman Zulfatman; Ilham Pakaya; Merinda Lestandy
JOIN (Jurnal Online Informatika) Vol 6 No 1 (2021)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v6i1.719

Abstract

The hepatitis C virus (HCV) is considered a problem to the health of societies are the main. There are around 120-130 million or 3% of the world's total population infected with HCV. Without treatment, most major infectious acute evolve into chronic, followed by diseases liver, such as cirrhosis and cancer liver. The data parameters used in this study included albumin (ALB), bilirubin (BIL), choline esterase (CHE), -glutamyl-transferase (GGT), aspartate amino-transferase (AST), alanine amino-transferase (ALT), cholesterol (CHOL), creatinine (CREA), protein (PROT), and Alkaline phosphatase (ALP). This research proposes a methodology based on machine learning classification methods including k-nearest neighbors, naïve Bayes, neural network, and random forest. The aim of this study is to assess and evaluate the level of accuracy using the algorithm classification machine learning to detect the disease HCV. The result show that the accuracy of the method NN has a value of accuracy are high, namely at 95.12% compared to the method KNN, naïve Bayes and RF in a row amounted to 89.43%, 90.24%, and 94.31%.
Perancangan Early Warning System pada Bencana Alam Berbasis IoT dengan Standalone Global Positioning System Delliar Khafid Nur Fahmi; Zulfatman; Widianto
SinarFe7 Vol. 2 No. 1 (2019): Sinarfe7-2 2019
Publisher : FORTEI Regional VII Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Penelitian ini membahas tentang perancangan sistem peringatan dini pada bencana alam berupa kebakaran hutan dan tanah longsor. Sistem peringatan dini ini dirancang menggunakan modul ESP8266 yang terhubung dengan sensor api, suhu dan asap sebagai pendeteksi kebakaran dan sensor kelebaban tanah, berat sebagai pendeteksi tanah lonsgor serta disemaatkan GPS sebagai penentu titik lokasi bencana dan jalur evakuasi yang akan digunakan. Sistem ini dapat dipantau secara real time pada aplikasi android. Dengan 3 level peringatan yaitu “AMAN”, “WASPADA” dan “BAHAYA”. Hasil pengujian menunjukkan jika alat pendeteksi dapat mengirimkan informasi bancana ke aplikasi android secara real time dengan waktu pengiriman informasi kurang dari 5 menit dengan jarak yang jauh. Serta lokasi terjadinya bencana dapat ditunjukan pada peta google maps secara akurat. Dengan demikian, diharapkan Early Warning System ini dapat membantu masyarakat serta pihak terkait untuk meminimalisir kerugian akibat bencana yang terjadi dengan informasi yang didapat dari alat peringatan dini pendeteksi bencana ini.
Buck-boost Converter using GA-based MPPT for Solar Energy Optimization Syafaah, Lailis; Faruq, Amrul; Noor Cahyadi, Basri; Hidayat, Khusnul; Setyawan, Novendra; Lestandy, Merinda; Zulfatman
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 8, No. 3, August 2023
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v8i3.1658

Abstract

Energy optimization in the Solar Power Plant system needs to have more attention. Indonesia is a tropical country that has two seasons, where the weather and cloud movements are frequently unpredictable, especially in the southern region of Java Island. To overcome this problem, an inverter equipped with maximum power point tracking (MPPT) was used. However, the current MPPT switching system was still not optimal with an efficiency of around 90%. In this study, the installation of MPPT was carried out in order to optimize the power in solar photovoltaic (PV) system due to the fluctuations of solar irradiation at PT. Jatinom Indah Agri, Blitar City. The maximum power generated by solar photovoltaic could be achieved by using the combination of DC - DC converter and artificial intelligence. In this study, the modeling of solar PV system was made using MATLAB software, where the design of the solar PV system consisted of a PV module with capacity 240W, DC to DC converter, battery and MPPT. Genetic Algorithm (GA)-based MPPT had been tested and compared to Particle Swarm Optimization (PSO)-based MPPT and conventional MPPT, where the GA-based MPPT worked well in finding the maximum power point in the solar photovoltaic system. It was found that GA-based MPPT produced a maximum power point close to PV power with an efficiency of 92%, while the effciciency of PSO-based MPPT and conventional MPPT were 85% and 79% respectively. In selecting the method for designing MPPT, a method with a wide range of sample data is required. This is due to the fluctuation of solar irradiance received by the solar PV.
Hybrid Fuzzy-PID Design Based on Flower Pollination Algorithm for Frequency Control of Micro-Hydro Power Plant Hakim, Ermanu Azizul; Norazizah; Zulfatman; Setyawan, Novendra
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 9, No. 2, May 2024
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v9i2.1755

Abstract

Micro-Hydro Power (MHP) Plant System is the renewable energy resource that utilizes water potential energy. In MHP, the energy flows depend on the rotation speed of the generator which cause instability and nonlinearity in the frequency of electrical power. It is also supported by the fluctuation on the electricity load. Therefore, this study used Fuzzy Logic Controller combined with FPA-tuned PID to control the power frequency of the load. This test consisted of 4 stages, namely testing the system without a controller, testing the system using PID, testing the MHP system with a PID controller tuned to the Flower Pollination Algorithm, and testing the system using a Fuzzy PID tuned by the Flower Pollination Algorithm. Based on these tests, the Micro-Hydro Power Plant system response using a Fuzzy PID-tuned FPA controller performed best, especially in accelerating the time to a steady state, reducing overshoot and undershoot with the fastest rise time. As for the output signal from the controller used in the MHP, optimizing the Flower Pollination Algorithm for the Kp, Ki, and Kd parameters is effective and smooth in improving all elements in the Micro-Hydro Power Plant frequency stabilization. Meanwhile, the role of the fuzzy logic controller (FLC) is not very significant, and there is relatively a lot of noise in the output signal of the Fuzzy PID controller itself in terms of stabilizing the load frequency on the Micro-Hydro Power Plant.
Enhanced Hybrid Robust Fuzzy-PID Controller for Precise Trajectory Tracking Electro-Hydraulic Actuator System Ali, Nur Husnina Mohamad; Ghazali, Rozaimi; Tahir, Abdul Wafi; Jaafar, Hazriq Izzuan; Ghani, Muhammad Fadli; Soon, Chong Chee; Has, Zulfatman
International Journal of Robotics and Control Systems Vol 4, No 2 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i2.1407

Abstract

The Electro-Hydraulic Actuator (EHA) system integrates electrical and hydraulic elements, enabling it to generate a rapid reaction, a high power-to-weight ratio, and significant stiffness. Nevertheless, EHA systems demonstrate non-linear characteristics and modeling uncertainties, such as friction and parametric uncertainty. Designing a controller for accurate trajectory tracking is greatly challenging due to these limitations. This paper introduces a hybrid robust fuzzy proportional-integral-derivative (HFPID) and (HF+PID) controller. The controller is designed to effectively control a third-order model of an EHA system for trajectory tracking. It is a significant contribution to the development of an intelligent robust controller that can perform well in different environments. Initially, a mathematical model for the EHA system was created using a first-principle approach. Subsequently, the Ziegler-Nichols method was employed to fine-tune the PID controller, while a conventional Fuzzy Logic Controller (FLC) was constructed in MATLAB Simulink utilizing linguistic variables and rule-based control. Without further tuning, the FL and PID controller are combined as a hybrid controller with different structures: Hybrid Fuzzy-PID (HFPID) and Hybrid Fuzzy+PID (HF+PID) controller. The Mean Square Error (MSE) and Root Mean Square Error (RMSE) are utilized as indices to assess the tracking accuracy and robustness of the four controllers. A greater value of MSE and RMSE indicates poorer performance of the controller. The results demonstrate that the HF+PID controller surpasses the other controllers by reaching the lowest MSE and RMSE values. It showcases the efficacy and accuracy in monitoring sinusoidal, multi-sinusoidal, and point-to-point trajectory tracking.  Future work should focus on implementing the designed controller on hardware for real-time performance and experimenting with various types of FLC or Hybrid controllers, such as self-tuning fuzzy-PID, to further explore their potential.
Power Quality Improvement in Micro Hydro Power Plant Based-ELC and VSI using Fuzzy-PI Controller Pakaya, Ilham; Zulfatman; Faruq, Amrul; Irfan, Muhammad
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 10, No. 1, February 2025
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v10i1.1913

Abstract

The stability of frequency and voltage in micro hydro power plants (MHPP) depends on the ability to maintain balance between active and reactive power while managing load variations. Active power is typically regulated by an Electronic Load Controller (ELC), while reactive power is managed by a Voltage Source Inverter (VSI), with the VSI specifically compensating for reactive power induced by inductive loads. This study aims to enhance the control of active and reactive power in an MHPP system under varying load conditions by improving the ELC and VSI using Fuzzy-PI controller. The Fuzzy-PI controller applied in the ELC ensures a more precise TRIAC firing angle, enabling accurate control of the ballast load to balance the active power. Similarly, Fuzzy-PI controller applied in the VSI provides precise reactive power compensation to counteract inductive load effects. The performance of the proposed Fuzzy-PI-based ELC and VSI was evaluated using a complete MHPP model simulated in Matlab. Results demonstrated that the improved ELC and VSI effectively enhanced the system performance. Specifically, the Fuzzy-PI controller enabled the ELC to achieve accurate active power balance, while the VSI delivered suitable reactive power compensation. Consequently, the system achieved improved frequency and voltage stability under load variations, leading to enhanced power quality in the MHPP.
Co-Authors A. F. Z. Abidin Ahzen Habibidin Muslim Ailin Rohmatul Fajria Akhyar Anadiansyah Ali, Nur Husnina Mohamad Alvian Widianto Amrul Faruq Anadiansyah, Akhyar Annas Alif Putra Basolle, Azfar Waris Basri Nor Cahyadi Bella Retno Budhi Priyanto Chai Mau Shern Chong Chee Soon Chong Chee Soon Delliar Khafid Nur Fahmi Delliar Khafid Nur Fahmi Dezar Septiantono Diding Suhardi Dirman Hanafi Dwi Nur Fajar Een Hutama Putra Effendy, Machmud Ermanu Azizul Hakim Fachmy Faizal Faizal, Fachmy Fajria, Ailin Rohmatul Fauziyah, Lailatul Fua'ad Rahmat, Mohd Ghani, Muhammad Fadli Gowdie Palmer Derai Haris Rahmana Putra Hazriq Izzuan Jaafar Ilham Pakaya Jaafar, Hazriq Izzuan Jayanegara, M Mulyadi Khusnul Hidayat Komarudin Achmad Lailatul Fauziyah Lailis Syafa'ah Lailis Syafa’ah Leonardo Kamajaya M Mulyadi Jayanegara M. F. Rahmat M. Irfan Machmud Effendy Machmud Effendy Machmud Effendy Mardiyah, Nur Alif Mardiyah, Nur Alif Mardiyah, Nuralif Marhainis Othman, Siti Marzuki, Mohammad Mas Nurul Achmadiah Md Rozali, Sahazati Merinda Lestandy Merinda Lestandy Mohammad Marzuki Mohd Fua'ad Rahmat Muhamad Fadli Ghani Muhamad Fadli Ghani Muhammad Haziq Hakim Rosman Muhammad Ikhwanul Khair Muhammad Irfan Muhammad Nasar Muslim, Ahzen Habibidin Noor Cahyadi, Basri Norazizah Novendra Setyawan Nur Alif Mardiyah Nur Alif Mardiyah Nur Alif Mardiyah Nur Alif Mardiyah, Nur Alif Nuralif Mardiyah Nuralif Mardiyah Nuralif Nuralif Nurhadi Nurhadi Nurhadi, Nurhadi Nurhadi, Nurhadi Nurkasan Nurkasan, Nurkasan Pratama, Rido Octa Putra, Annas Alif Putra, Een Hutama Retno, Bella Rido Octa Pratama Rozaimi Ghazali Rozaimi Ghazali Rozaimi Ghazali S. M. Rozali Sahazati Md Rozali Septiantono, Dezar Siti Marhainis Othman Siti Marhainis Othman Soon, Chong Chee Syafa'ah, Lailis Syafaah, Lailis Tahir, Abdul Wafi WIDIANTO Yahaya Md Sam Yahaya Md. Sam Zsa Zsa Septina Atsil