Article Per Year (5 Year)
p-Index From 2020 - 2025
2.63
P-Index
This Author published in this journals
All Journal Indonesian Journal of Electronics and Instrumentation Systems Jurnal Edukasi Elektro Jurnal Ilmu Komputer JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Manajemen Informatika Buletin Ilmiah Sarjana Teknik Elektro International Journal of Advances in Data and Information Systems Journal of Soft Computing Exploration Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal Jarlit Adopsi Teknologi dan Sistem Informasi
Faisal Fajri Rahani
Universitas Ahmad Dahlan
Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences

Published : 16 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 16 Documents
Search

 1   2 
Penalaan Mandiri Full State Feedback dengan LQR dan JST Pada Kendali Quadrotor Faisal Fajri Rahani; Tri Kuntoro Priyambodo
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 9, No 1 (2019): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1015.952 KB) | DOI: 10.22146/ijeis.37212

Abstract

Quadrotor is one type of unmanned aerial vehicle that has the ability to vertical takeoff and landing. In this research, a system designed to stabilize quadrotor during flight condition by maintaining at angle of roll, pitch, yaw, and x, y, and z axis position using LQR full state feedback with artificial neural network (ANN).The LQR full state feedback method uses 12 states with each K constant being tuned with ANN. This research implements ANN method to change feedback constant at angle of roll, pitch, and yaw and x, y, and z axis. The artificial neural network method uses 12 input layers, 12 hidden layers, and 1 output layer.Testing with ANN improved the rise time to ± 2.18 seconds at the roll angle, ± 1.23 seconds at the pitch angle, and ± 0.31 seconds at the yaw angle. Improved settling time value up to ± 2.41 seconds at roll angle, ± 1.23 seconds at pitch angle, and ± 1.07 seconds at yaw angle. Improved steady state eror value of ± 0.61% at roll angle, ± 4.88% at pitch angle, and ± 0.82% at the yaw angle.
Analisis Epitope Sel T pada SARS-Cov2 dengan Pendekatan Bioinformatika Miftahurrahma Rosyda; Faisal Fajri Rahani
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 9 No 3: Agustus 2020
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1048.241 KB) | DOI: 10.22146/.v9i3.408

Abstract

At the beginning of 2020, the world was shocked by the spread of global outbreaks that attacked respiratory like the SARS outbreak in 2003, namely COVID-19. The virus that causes the outbreak called SARS-Cov2. It turns out to have a similarity of ~ 87.5% with SARS-Cov. This similarity can be used to develop drugs and vaccines that are compatible with the current virus. In this case, the bioinformatics approach can be carried out as an initial stage of vaccine development. One way to develop vaccines is epitope-based vaccines. Biological data available and submitted to the public regarding T cell epitopes and protein sequences in viruses can be processed with several bioinformatics tools available online. This study compared the calculation of physicochemical characters between the SARS-Cov epitope and the SARS-Cov2 protein sequence at the same location. The characters being compared are molecular weight, point of isoelectric, aliphatic index, GRAVY, instability index, and antigenicity. Data processing is evaluated by correlation matrix. The results of the processing show that the physicochemical character between SARS-Cov and SARS-Cov2 has a strong relationship.
Model Penahan Ketinggian Quadrotor Berbasis PID dengan Jaringan Syaraf Tiruan Propagasi Mundur Faisal Fajri Rahani; Dinan Yulianto
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 10 No 2: Mei 2021
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1321.932 KB) | DOI: 10.22146/jnteti.v10i2.1249

Abstract

A quadrotor is a type of Unmanned Aerial Vehicle (UAV) or an unmanned flying vehicle flying remotely or using automatic control. In carrying out its mission, a quadrotor requires a good control system. One of the control systems in the quadrotor system is the altitude control system. Altitude control will control the quadrotor according to the desired altitude, whether there are interference and the quadrotor load. The widely used control method is the PID control. Unfortunately, the PID control produces a poor response because the PID constant is fixed, whereas the interference when the quadrotor flies will fluctuate. Therefore, this study offers control that can make a self-adjustment when exposed to specific interference. The method offered in this study is a PID control with Artificial Neural Networks (ANN). The ANN system will tune the PID components in real-time according to the occurring interference. The use of the PID with ANN results in a faster rise time response of 0.0594 seconds, a decrease in overshoot of 7.58%, a decrease in the steady-state error of ± 0.0672, and a decrease in settling time of 1.031 seconds compared to conventional PID. It shows that the PID with ANN results in better control than the PID alone.
Implementasi Full State Feedback LQR dengan JST pada Kendali Ketinggian Quadrotor Faisal Fajri Rahani; Tri Kuntoro Priyambodo
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 8 No 4: November 2019
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1164.793 KB)

Abstract

One type of unmanned aircraft that is often used today is quadrotor. This type of aircraft has the ability to take off vertically. This study implemented an altitude control system on the z-axis quadrotor. The control used is the full state method of Linear Quadratic Regulator (LQR) with artificial neural networks. The LQR full state feedback method used in this system is 12-states with each feedback constant Ktuned to the neural network method. This study implements the artificial neural network method to change the feedback constant on the z-axis. Artificial neural network architecture used 12 input layers, 48 hidden layers, and 1 output layer. This study compares the value of the results of the simulation with the response value of the system implementation results applied to the quadrotor. Testing with full state LQR feedback using artificial neural networks improves the system response to ±0.77 seconds and improves steady state error values up to ±12 cm. Based on the results of these studies, this system can be implemented to control other systems.
Peningkatan Kestabilan Quadrotor menggunakan Kendali Linear Quadratic Regulator dengan Kompensasi Integrator dalam Mempertahankan Posisi Oktaf Agni Dhewa; Faisal Fajri Rahani
Buletin Ilmiah Sarjana Teknik Elektro Vol. 4 No. 2 (2022): Agustus
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v4i2.6808

Abstract

The quadrotor's ability to maintain position is a major requirement for the completion of various current missions. However, the large steady-state error (SSE) and multiple overshoots due to environmental disturbances cause flight instability. This condition makes Quadrotor unable to complete the mission optimally. Therefore, in this study applying a linear quadratic regulator control method, this research contributes to the addition of integrator compensation in handling the translational movement of the quadrotor. System model design testing is carried out by comparing quadrotor control using the LQR method without an Integrator and LQR with an Integrator. The value of R=1 for all states and Q_x=0.87, Q_y=124.6, Q_(v_x)=1.77, Q_(v_y)=124.6 and Ki_x=0,004, Ki_y=0.002 makes the SSE tendency that occurs 0.10 meters for the x-axis and -0.28 for the y-axis, while the multi-overshoot that occurs is 0.41 m for the maximum deviation and -1.35 m for the minimum deviation on the x-axis and 0.40 m maximum deviation and 0.47 m minimum deviations on the y axis. The test results show that the LQR control method with Integrator compensation is able to minimize and improve SSE and multiple overshoots that occur in quadrotor flights. In addition, it is able to significantly increase accuracy to 100% from 71.38% and precision to 37.71% from 35.91%.Kemampuan quadrotor dalam mempertahankan posisi menjadi kebutuhan utama untuk penyelesaian berbagai misi saat ini. Namun, besarnya steady state error (SSE) dan multiple overshoot karena gangguan lingkungan menyebabkan ketidakstabilan gerak terbang. Kondisi tersebut menjadikan quadrotor tidak mampu menyelesaikan misi secara optimal. Maka dari itu, pada penelitian ini menerapkan sebuah metode kendali Linear Quadratic Regulator penelitian ini memiliki kontribusi dengan penambahan kompensasi Integrator dalam menangani pergerakan translasi quadrotor. Pengujian desain model sistem, dilakukan dengan membandingkan antara pengendalian quadrotor menggunakan metode LQR tanpa Integrator dan LQR dengan Integrator. Nilai R=1 untuk semua state serta Q_x=0,87; Q_y=124,6; Q_(v_x)=1,77; Q_(v_y)=124,6 dan Ki_x=0,004; Ki_y=0,002 menjadikan kecenderungan SSE yang terjadi sebesar 0,10 m untuk sumbu x dan -0,28 m untuk sumbu y, sedangkan multi overshoot yang terjadi sebesar 0,41 meter simpangan maksimal dan -1,35 m simpangan minimal pada sumbu x serta 0,40 m simpangan maksimal dan 0,47 meter simpangan minimal pada sumbu y. Hasil pengujian tersebut menunjukkan bahwa metode LQR dengan kompensasi Integrator mampu meminimalkan dan memperbaiki SSE maupun multiple overshoot yang terjadi pada penerbangan quadrotor. Selain itu juga mampu meningkatkan akurasi secara signifikan sebesar 100% dari 71,38% serta presisi sebesar 37,71% dari 35,91%.
Prediksi Kualitas Air Menggunakan Metode Seasonal Autoregressive Integrated Moving Average (SARIMA) Ayunita Agustin; Faisal Fajri Rahani; Fitri Indra Indikawati
Jurnal Manajemen Informatika (JAMIKA) Vol 12 No 2 (2022): Jurnal Manajemen Informatika (JAMIKA)
Publisher : Program Studi Manajemen Informatika, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jamika.v12i2.8022

Abstract

Water conservation is very necessary to support the creation of clean water quality that is free from harmful substances that can disturb the environment. So a system is needed to monitor water quality to determine the level of pollution that occurs. This system will work to see water quality in real time with several quality parameters such as pH, temperature, and water turbidity. The purpose of this research is to produce a predictive model and find out the prediction results of a data mining-based system. The method used to predict water quality uses the Seasonal Autoregressive Integrated Moving Average (SARIMA) method, because the water quality data is thought to contain seasonal patterns. The results of this study indicate that the SARIMA model can be applied to the dataset used and obtain the accuracy of the forecasting results on each of the tested parameter data. The results of water quality forecasting with this parameter are the result data for testing at a dataset of a depth of 30 cm and a depth of 60 cm for temperature parameters, namely MSE<0.1, and RMSE<0.02. For pH parameters, MSE<0.1, and RMSE<0.1. As well as the turbidity parameter, the results of MSE<0.02, and RMSE<0.13. From these results indicate that this system can predict water quality with past data.
Data Mining Dalam Penentuan Pemesanan Buku Perpustakaan UAD dengan Menggunakan Metode Naïve Bayes Muhammad Iqbal Hadiwibowo; Faisal Fajri Rahani
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 4 (2022): Oktober 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i4.4381

Abstract

Library Universitas Ahmad Dahlan (UAD) has not utilized technology in the book ordering process. The process of ordering books from distributors requires many considerations such as the number of requests, recommendations for study programs, location, year and language. This consideration made the UAD Library take more than 2 weeks in the book selection process. This study aims to apply data mining in determining book orders using the Naïve Bayes method. This study uses 1106 book procurement data for the past year with criteria, namely the number of requests, study program recommendations, location, year, and language. Implementation of data mining using the Naïve Bayes algorithm is carried out in stages including data cleaning, data selection, data transformation, sharing of training data and data testing, implementation and results of the Nave Bayes algorithm and system testing. System testing using the Confusion Matrix method. Based on the Confussion Matrix calculation on the testing data, the accuracy is 90.24%, the precision is 89.69%, the recall is 93.54%, the specificity is 91.04%, and the F1 score is 91.57%. It was concluded that the system test results were said to be good.
Prediction of Planning Value School Shopping Income Budget with Multiple Linear Regression Cahyani Hana Bestari; Faisal Fajri Rahani
International Journal of Advances in Data and Information Systems Vol. 4 No. 1 (2023): April 2023 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v4i1.1285

Abstract

The School Expenditure Budget Plan or RAPBS is the pillar of school management for allocating the revenue budget and use of school funds to meet all school needs for one year. However, there are problems that occur in the management of the RAPBS, namely the difficulty of grouping the RAPBS data annually, making it difficult to predict the budget for the coming year. This research was conducted to study and implement the Multiple Linear Regression algorithm in predicting the value of data on income and expenditure budget plans which are a reference in planning future budgets. To support predictions of planned school budgets and income, BUMS data, Aid data, School Program Cost data, Original School Revenue data, Other Sources data, and Total Budget data are used. The prediction system method used consists of the planning stage, the analysis stage, the modeling stage, interface design, and implementation using the PHP and MySQL programming languages for database management and system testing and analysis. The results of testing the data analysis using the multiple linear regression method with SPSS software have a 100% result according to the manual calculations performed.
Quadrotor Altitude Control using Recurrent Neural Network PID Faisal Fajri Rahani; Phisca Aditya Rosyady
Buletin Ilmiah Sarjana Teknik Elektro Vol. 5 No. 2 (2023): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v5i2.8455

Abstract

The quadrotor is one type of Unmanned Aerial Vehicle (UAV) or unmanned flying vehicle. Quadrotor can be operated by a remote controller or autonomously. Quadrotor control is a challenging problem because it takes into account complex things such as parametric uncertainty, external disturbances, and so on. At the spatial level, three linear degrees of freedom along three axes and three degrees of freedom rotating along three axes are used for the control of a quadrotor. Conventional controls for quadrotors are widely used such as PID, state feedback, and so on. However, because the control is linear, non-linear control has begun to be developed. Some of these controls, for example, use a sliding mode control system, fuzzy methods, and controls by combining linear control with artificial intelligence. This paper will use PID control and an artificial neural network for the quadrotor direction control system. The results of this control test indicate that the combination of PID and RNN on the directional control shows a better response than conventional PID.
AMARTO (DAMAGED ROAD DETECTOR): PURWARUPA SISTEM DETEKSI DAN ANALISATOR KERUSAKAN JALAN RAYA KOTA YOGYAKARTA BERBASIS CITRA DIGITAL DAN GPS Rosyady, Phisca Aditya; Rahani, Faisal Fajri; Baswara, Ahmad Raditya Cahya
Jurnal Jarlit Vol. 17 No. 1 (2021): PERCEPATAN PEMULIHAN SOSIAL EKONOMI UNTUK KESEJAHTERAAN MASYARAKAT
Publisher : Badan Perencanaan Pembangunan Daerah Kota Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70154/jid.v17i1.10

Abstract

Jalan raya merupakan salah satu aspek penunjang kehidupan bermasyarakat. Namun terkadan jalan raya tidak selalu dalam kondisi baik, terdapat beberapa jenis kerusakan jalan seperti lubang, retak, jalan tidak rata dan kerusakan-kerusakan lain yang dapat menyebabkan pengguna jalan terganggu. Untuk itu berdasarkan undang-undang nomor 22 tahun 2009, dimana pemerintah bertanggung jawab dalam melakukan perbaikan jalan, maka setiap adanya kerusakan yang terjadi pada suatu jalan raya, sudah menjadi kewajiban pemerintah untuk segera memperbaikinya. Permasalahan yang ada adalah proses deteksi dan pengecekan kerusakan jalan oleh Bina Marga Dinas Pekerjaan Umum dan Perumahan Rakyat Pemkot Yogyakarta masih berjalan secara manual. Penelitian ini akan membuat solusi pemanfaatan teknologi dalam hal pendeteksi, klasifikasi, analisis dan pencatatan data kerusakan jalan raya, agar proses perbaikan jalan raya dapat dikerjakan dengan lebih cepat dan efisien. Metode penelitian ini adalah Research and Development yang digunakan untuk menghasilkan produk tertentu, dan menguji keefektifan produk atau sistem yang diteliti. Pendeteksian kerusakan lubang jalan raya ini digunakan sensor HC-SR04 dan Modul GPS GY- NEO6MV2, sedangkan untuk analisis beban kerusakan lubang jalan tersebut digunakan pengolahan citra dengan input kamera Webcam Logitech dan kedalaman menggunakan sensor HC-SR04. Pemrosesan utama menggunakan Raspberry Pi 4 dan sistem juga berbasis Internet of Things dengan ThinkSpeak. Dalam penelitian ini telah terbuat purwarupa deteksi kerusakan lubang jalan berbasis citra digital dan GPS. Sistem ini mampu menganalisa dan menghitung luas jalan berlubang dengan tingkat error 0.358% - 4.19%, namun nilai parameter lower, upper HSV, gaussian blur kernel, aplha, beta pada fungsi masih beragam. Program yang berperan penting dalam proses pendeteksian jalan berlubang adalah equalizer histogram. Berdasarkan pengujian sensor jarak HC-SR04 dalam penelitian ini adalah ping sensor didapatkan bahwa untuk kedalaman lubang dengan pengukuran metode tidak bergerak maka didapatkan hasil error sebesar lebih kecil yaitu 1,66 % dan deteksi GPS dengan rata-rata selisih Latitude 0.0006144 dan Longitude 0.0000396. Implementasi IoT berbasis Thinkspeak sudah bisa dimanfaatkan sehingga monitoring bisa dipantau melalui web dan aplikasi android. Luaran penelitian ini berupa paper di Jurnal Nasional dan Hak Cipta.
Co-Authors Arsianto, Muhammad Alif Rahmat Novian Ayunita Agustin Baswara, Ahmad Raditya Cahya Cahyani Hana Bestari Cahyani Hana Bestari Fathurrahman, Haris Imam Karim Fitri Indra Indikawati Miftahurrahma Rosyda Muhammad Iqbal Hadiwibowo Nugraha, Abiema Febrian Oktaf Agni Dhewa Phisca Aditya Rosyady Putri, Arisda Dwi Rosyady, Phisca Aditya Rosyida, Miftahurrahma Tri Kuntoro Priyambodo Yulianto, Dinan