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All Journal Jurnal Presipitasi : Media Komunikasi dan Pengembangan Teknik Lingkungan Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) REKAYASA International Journal of Artificial Intelligence Research The Spirit of Society Journal : International Journal of Society Development and Engagement Jurnal Otomasi Kontrol dan Instrumentasi Jurnal Teknik Elektro dan Komputer TRIAC Applied Technology and Computing Science Journal Infotekmesin Jurnal Elkolind : Jurnal Elektronika dan Otomasi Industri Jurnal Ners Jurnal Pembelajaran Pemberdayaan Masyarakat (JP2M) Journal of Soft Computing Exploration JURNAL POLI-TEKNOLOGI Indonesian Journal of Innovation Multidisipliner Research Jurnal Cakrawala Maritim Indonesian Journal of Innovation Multidisipliner Research
Agus Khumaidi
Politeknik Perkapalan Negeri Surabaya
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Ball Direction Prediction for Wheeled Soccer Robot Goalkeeper Using Trigonometry Technique Bagus Setiawan, Danis; Khumaidi, Agus; Priyonggo, Projek; Basuki Rahmat, Mohammad; Sutrisno, Imam; Nasikhin, Khoirun; Wisnu Sahputera, Adi
TEKNOLOGI DITERAPKAN DAN JURNAL SAINS KOMPUTER Vol 2 No 1 (2019): June
Publisher : Unusa Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33086/atcsj.v2i1.1204

Abstract

In this research Trigonometry Technique was implemented to predict the ball movement direction for Wheeled Soccer Robot Goalkeeper. The performance of goalkeeper robot in Wheeled Soccer Robot Contest is very important. The crucial problem with goalkeeper robot is the delay in ball detection by the camera because the results of the camera images captured are always slower than the pictures that have been captured. This causes the robot's response to blocking the opponent's kick ball being late. Trigonometry Technique is one technique that can be used to predict the direction of the ball movement based on trigonometry mathematical formulas. The input data used is the location of the last ball position (x?last ball and y-last ball) and the location of the current ball position (x-current ball and y-current ball). The outputs are the prediction of the next ball location (x-predict ball and y-predict ball) and the prediction of ball movement direction prediction. The results are the goalkeeper's robot successfully predicts the opponent's kick direction with 90% accuracy and can predict the location of the next ball very well. By implementing this method, it is expected to optimize the performance of the goalkeeper robot in saving the goal.
Radial Basis Function Neural Network sebagai Pengklasifikasi Citra Cacat Pengelasan Rinanto, Noorman; Wahyudi, Mohammad Thoriq; Khumaidi, Agus
Rekayasa Vol 11, No 2: Oktober 2018
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (937.111 KB) | DOI: 10.21107/rekayasa.v11i2.4418

Abstract

Tingginya resiko kesalahan manusia dalam inspeksi visual untuk cacat pengelasan yang masih mengandalkan kemampuan manusia sulit untuk dihindari. Oleh sebab itu, penelitian ini mengusulkan sebuah klasifikasi cacat las visual dengan menggunakan algoritma Radial Basis Function Neural Network (RBFNN). Masukan RBFNN berupa citra las yang terdiri dari 5 (lima) kelas cacat las visual dan 1 (satu) kelas citra las normal. Citra las tersebut diproses terlebih dahulu menggunakan metode ekstraksi fitur Fast Fourier Transform (FFT) dan Descreate Cosine Transform (DCT). Hasil kedua metode ekstraksi fitur tersebut kemudian akan saling dibandingkan untuk mengetahui kinerja RBFNN. Hasil pengujian menunjukkan bahwa sistem dengan metode FFT-RBFNN dapat menggolongkan citra cacat las dengan akurasi sebesar 91.67% dan DCT-RBFNN sekitar 83.33% dengan jumlah neuron hidden layer sebanyak 15 dan parameter spread adalah 4.Kata Kunci: Radial Basis Function Neural Network (RBFNN), FFT, DCT, cacat las, klasifikasi.Radial Basis Function Neural Network as a Weld Defect Classifiers ABSTRACTThe high risk of human error in visual inspection of welding defects that still rely on human capabilities is difficult to avoid. Therefore, this study proposes a classification of visual welding defects using the Radial Base Function Neural Network (RBFNN) algorithm. The RBFNN input is in the form of a welding image consisting of 5 (five) visual welding defect classes and 1 (one) normal welding image class. The weld image is processed first using the Fast Fourier Transform (FFT) and Descreate Cosine Transform (DCT) feature extraction methods. The results of these two feature extraction methods will be compared to find out the RBFNN performance. The test results show that the system with FFT-RBFNN method can classify the image of weld defects with an accuracy of 91.67% and DCT-RBFNN around 83.33% with the number of hidden layer neurons as much as 15 and the parameters of spread are 4.Keywords: Radial Basis Function Neural Network (RBFNN), FFT, DCT, weld defect, classification.
Ball Direction Prediction for Wheeled Soccer Robot Goalkeeper Using Trigonometry Technique Danis Bagus Setiawan; Agus Khumaidi; Projek Priyonggo; Mohammad Basuki Rahmat; Imam Sutrisno; Khoirun Nasikhin; Adi Wisnu Sahputera
TEKNOLOGI DITERAPKAN DAN JURNAL SAINS KOMPUTER Vol 2 No 1 (2019): June
Publisher : Unusa Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33086/atcsj.v2i1.1204

Abstract

In this research Trigonometry Technique was implemented to predict the ball movement direction for Wheeled Soccer Robot Goalkeeper. The performance of goalkeeper robot in Wheeled Soccer Robot Contest is very important. The crucial problem with goalkeeper robot is the delay in ball detection by the camera because the results of the camera images captured are always slower than the pictures that have been captured. This causes the robot's response to blocking the opponent's kick ball being late. Trigonometry Technique is one technique that can be used to predict the direction of the ball movement based on trigonometry mathematical formulas. The input data used is the location of the last ball position (x–last ball and y-last ball) and the location of the current ball position (x-current ball and y-current ball). The outputs are the prediction of the next ball location (x-predict ball and y-predict ball) and the prediction of ball movement direction prediction. The results are the goalkeeper's robot successfully predicts the opponent's kick direction with 90% accuracy and can predict the location of the next ball very well. By implementing this method, it is expected to optimize the performance of the goalkeeper robot in saving the goal.
Obstacle Avoidance using Fuzzy Logic Controller on Wheeled Soccer Robot Noorman Rinanto; Irfan Marzuqi; Agus Khumaidi; Sryang T Sarena
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 5, No 1 (2019): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (556.96 KB) | DOI: 10.26555/jiteki.v5i1.13298

Abstract

The purpose of this study is to apply Fuzzy Logic Controller on a wheeled soccer robot to avoid the collision with other robots in the field. The robot equipped by an omnidirectional camera as a vision sensor, a mini-PC for the image processing device, a microcontroller to handle I/O system, and three wheel's omnidirectional mover system. Omni-camera produces four input-values, namely: X coordinate ball position, Y coordinate ball position, distance and angle from obstacle to the point of interest in the camera frame. These inputs processed by a mini-PC and then forward to a microcontroller to calculate the output using Fuzzy Logic Controller. The output variables are the movement rate of the robot in the X, and Y coordinate.  These outputs will be used by the kinematics controller to manage the speed of three Omni-wheels driven by 24 volts DC motors. The experiment shows a good result with the percentage of the success of the robot catching the ball is around 70% and 80% in avoiding the obstacle. In time performance, the soccer robot with Fuzzy Logic Controller is superior by 4.67 seconds compared to the robot without this method.
Development of SCADA Dynamic Application Design Joesianto Eko Poetro; M. Basuki Rahmat; Agus Khumaidi; Hananta A; Bhakti Bhakti
THE SPIRIT OF SOCIETY JOURNAL : International Journal of Society Development and Engagement Vol 5 No 1 (2021): September 2021
Publisher : LPPM of NAROTAMA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29138/scj.v5i1.1576

Abstract

The COVID-19 pandemic has changed major habits in learning patterns. Before the pandemic, almost all learning activities took place face-to-face. Especially vocational education, where competence or expertise is an absolute achievement that must be achieved. Learning patterns where practical learning reaches 60% of students must obtain practical learning directly. During the pandemic, direct learning activities cannot be carried out in full. This will have an impact on student competence. Solution is needed to solve it. One of them is how students can practice virtually. This article does not discuss the extent of competence achieved by a student through online practice. The focus of this article is to discuss how practical devices can be controlled remotely by designing a virtual system on the platform and running it in real time or known as dynamic application. And technicians or PLP will still supervise the operation of equipment in the laboratory. The device will be built using the MODBUS communication protocol.
Design of a System for Checking Paint Results on the Ship's Hull to Prevent corrosion Rahmat, M. Basuki; Wardani, Dianita; Khumaidi, Agus; Budiawati, Ratna; Mudjanarko, Sri Wiwoho
THE SPIRIT OF SOCIETY JOURNAL : International Journal of Society Development and Engagement Vol 7 No 2: March 2024
Publisher : LPPM of NAROTAMA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29138/scj.v7i2.2906

Abstract

Corrosion is damage caused by chemical reactions between metal materials and other natural elements and is destructive to metal. Corrosion is a weakness in ships made of steel, namely because the rate of ship corrosion, fatigue life is reduced, tensile strength and other mechanical properties are reduced. Corrosion is concentrated on only certain parts. In metal corrosion current flow out onto other parts of the metal surface. Corrosion gastric plates result in reduction Hull panel strength, slowing the ship and reduces security guarantees. The hull must be protected from corrosive attacks routine to prevent loss of additional plates substantially due to seawater corrosion. For Prevent hull corrosion in the painting process for coating, cathodic protection process. In this article, a system for automatically detecting ship hull painting results using image processing is explained. This system will be developed into a portable system. The results obtained show that the system is able to recognize whether the painting results can be accepted or rejected. Accepted means no need to repaint. and if it is rejected, it means a repainting process is needed.
Coating Inspection on Sea Transportation Equipment (Ship) Using Image Processing Wardani, Dianita; Khumaidi, Agus; Fahmi, Rizal; Kusminah, Imah Luluk; Rahmat, Basuki
Indonesian Journal of Innovation Multidisipliner Research Vol. 2 No. 2 (2024): June
Publisher : Institute of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/ijim.v2i2.133

Abstract

Research in the last decade, particularly in this research there are methods and steps for completion, namely 4 process steps, including: First of all, take samples and image data from the parts of the ship that are being repaired and maintained, Then, in making the prototype tool resulting from the coating, it is assembled using several tools, mini PC is installed with a web camera, next the image for the observation further processes and processed using the edge method contours detection with the help of cany to obtain the contrast and contour from the ship's hull. For next process, uses Neural Network for image creation processes taken from prototype plating or plating on observed ship parts. Some mixed results from the process. The images taken areand thenthe data obtained is processed and its form is observedfor shape, pattern,corrosion, contour and so on layers formed. There are two classifications of RGB and GLCM results, the rejected results can match the corrosion spot found on the hull, and the accepted results mean no corrosion spot found.
Design of ANFIS system to detect the condition of generator set model P22-6 based on Omron CJ1M PLC Rahmawati, Nanda Putri; Adhitya, Ryan Yudha; Widodo, Hendro Agus; Afianto, Afif Zuhri; Khumaidi, Agus; Budiawati, Ratna; Hardiyanti, Fitri; Santoso, Mochamad Yusuf
Journal of Soft Computing Exploration Vol. 5 No. 3 (2024): September 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v5i3.435

Abstract

The application of machine monitoring systems is currently increasingly needed, one of which is on generators. Generator sets are one of the important elements in providing energy needed in company operations. However, to ensure optimal performance and prevent unexpected engine damage, careful monitoring of the generator set's operational conditions is required, especially of key variables such as temperature, rotation speed, and engine vibration. The purpose of this study is to identify the condition of the generator set using three parameters. In this research, adaptive neuro fuzzy inference system (ANFIS) is used as a tool to model the relationship between inputs (temperature, speed, and vibration) and outputs (engine condition). The dataset for normal conditions amounted to 25 data and for abnormal conditions amounted to 25 data. From this data, an RMSE of 0.000032 was obtained in the 3-3-5 membership function structure with a trapezoidal type membership function. And at the stage of applying fuzzy to the Omron PLC, the RMSE is 0. Simulations are carried out to test the effectiveness of ANFIS in predicting machine conditions based on monitored parameters.
Kontrol Kestabilan Kapal Autonomous Submarine Surface Vehicle Dengan Metode Fuzzy logic Abdul Hafizh Abyan Faruq; Joko Endrasmono; Isa Rachman; Agus Khumaidi; Ryan Yudha Adhitya; Zindhu Maulana Ahmad Putra
Infotekmesin Vol 14 No 2 (2023): Infotekmesin: Juli, 2023
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v14i2.1920

Abstract

The Autonomous Submarine Surface Vehicle is a type of unmanned underwater vehicle. When the ship performs maneuvers, there are large Pitch and Roll motions. This research aims to control the stability of the Autonomous Submarine Surface Vehicle with Fuzzy. The first process is taking Pitch and Roll data followed by the Fuzzification process to change input data with firm values into Fuzzy values. The next stage is Inference by using the rules (if – then) and the Deffuzification process to change the results of the inference stage into output values. The last is the process of stabilizing the ship with a Thruster dc motor. When the system is activated, it has a time of 0.518 seconds faster to steady state than the deactivated system with a roll tilt of (plus) 11°. On the roll tilt of (plus) 20° the highest PWM rotation is 1600µs with a time of 9,342 seconds to steady state and the roll tilt is (plus) 11° with the highest PWM of 1500µs with a time of 4,335 seconds. Based on this research, the Fuzzy Method can control the stability of the Autonomous Submarine Surface Vehicle ship.
Sistem Diagnosis Kesehatan Manusia dan Monitoring Tanda Tanda Vital Manusia menggunakan metode Natural Language Processing berbasis Website Zazila, Mujtaba Fa'akuli; Khumaidi, Agus; Disrinama, Am Maisarah; Jami’in, Mohammad Abu; Adianto, Adianto; Arfianto, Afif Zuhri
Jurnal Ners Vol. 9 No. 1 (2025): JANUARI 2025
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jn.v9i1.31213

Abstract

Rumah sakit merupakan fasilitas penting dalam masyarakat untuk memberikan pelayanan kesehatan yang efisien. Pada era modern ini, penting untuk memiliki rumah sakit yang efisien dalam pelayanan. Dalam penelitian ini, peneliti telah merancang sistem monitoring dan diagnosis kesehatan manusia berbasis website untuk mempercepat proses antrian di rumah sakit. Kesehatan seseorang bisa diidentifikasi dari beberapa tanda vital yang dimilikinya. Penggunaan Natural Language Processing (NLP) digunakan untuk klasifikasi penyakit dan pengambilan keputusan berdasarkan screening digital yang dilakukan oleh manusia dengan dukungan tanda-tanda vital hingga ke tahap validasi oleh expert judgement. Penelitian ini telah diuji menggunakan prototipe pada pergelangan tangan manusia di Poliklinik Politeknik Perkapalan Negeri Surabaya dengan pendampingan expert judgement. Terdapat 40 jenis gejala penyakit yang dimuat dalam website untuk 10 penyakit yang umum dalam diagnosis dalam kesehatan manusia. Hasil penelitian ini mendapatkan akurasi sebesar 91,6%. Dari inovasi tersebut maka peneliti mengharapkan bahwa prototipe ini dapat bermanfaat bagi Masyarakat, meningkatkan pelayanan rumah sakit, dan sebagai bentuk implementasi metode Natural Language Processing (NLP).
Co-Authors Abdul Hafizh Abyan Faruq Achmad, Vandy Adhitya, Ryan Yudha Adi Rahmad Ramadhan Adi Wisnu Sahputera Adianto Adianto Afianto, Afif Zuhri Am Maisarah Disrinama Anggarjuna Puncak Pujiputra Ardiana, Mirza Arfianto, Afif Zuhri Arief Subekti Arninputranto, Wibowo Arumsari, Nurvita Astutik, Rina Puji Aulia Rahma Annisa Bagus Setiawan, Danis Basuki Rahmat Basuki Rahmat Masdi Siduppa Basuki Rahmat, Mohammad Bayu, Nurissabiqoh Binta Bhakti Bhakti Budi, Perdinan Setia Budiawati, Ratna Budiyanto, Ekky Nur C. I. Sutrisno Cahyono, Ferry Budi Danis Bagus Setiawan Darmawan, Wahyu Dewi Kurniasih Dianita Wardani Dianita Wardani Dika Rahayu Widiana Endrasmono, Joko Fadlol, Muhammad Thoriq Faturrahman, Bima Fitri Hardiyanti Hafid, Mohammad Arigo Al. Hananta A Hasin, M. Khoirul Hasin, Muhammad Khoirul Hendro Agus Widodo, Hendro Agus Ihsania, Tsabita Ii Munadhif Imah Luluk Kusminah Imam Sutrisno Imam Sutrisno Imam Sutrisno Indriawati, Melta Anindya Irfan Marzuqi Irma Rustini Aju Jami’in, Mohammad Abu Joesianto Eko Poetro Joko Endrasmono Joko Endrasmono Khoirun Nasikhin Kusminah, Imah Luluk Kusumah, Adam Lilik Subiyanto M. Basuki Rahmat Mades Darul Khairansyah Malik, Alfianto Taufiqul Mat Syai’in Mochamad Yusuf Santoso Mohammad Basuki Rahmat Mustika Kurnia Mayangsari Nasikhin, Khoirun Noorman Rinanto Oktavia, Shelly Pradana, Rizal Lucky Prahasta, Brendi Pristovani Riananda, Dimas Pristovani, Dimas Projek Priyonggo Sumangun Lukitadi Pujiputra, Anggarjuna Puncak Putra, Zindhu Maulana Ahmad Rafsanjani, Zainu Rahmat, M. Basuki Rahmawati, Nanda Putri Ramadhani, Mifta Aulia Riananda, Dimas Pristovani Rinanto, Noorman Rizal Fahmi Rizal Fahmi Rizky, Sofi Berliana Romadloni, Faiz Ryan Yudha Adhitya Santoso, Agus Dwi Setiani, Vivin Setyawati, Emeralda Eka Putri Sholahuddin Muhammad Irsyad Sholihah, Mar'atus Sri Wiwoho Mudjanarko, Sri Wiwoho Sryang T Sarena Suwandi, Donny Aryo Seno Syai’in, Mat Syai’in Wahyudi, Mohammad Thoriq Wibowo, Sekarsari Wisnu Sahputera, Adi Yudha Adhitya, Ryan Yugowati Praharsi Yuning Widiarti, Yuning Zazila, Mujtaba Fa'akuli Zindhu Maulana Ahmad Putra