Ariyono Setiawan
@poltekbangsby.ac.id
Air Transportation Management
Politeknik Penerbangan Surabaya
RESEARCH, TEACHING, or OTHER INTERESTS
Artificial Intelligence, Human-Computer Interaction, Multidisciplinary, Computer Graphics and Computer-Aided Design
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Arjon Turnip, Exelindo Yeremia, Gilbert Sihombing, Ariyono Setiawan, and Giraldo Sihombing
IEEE
When selecting a leader, it is necessary to consider their traits based on existing criteria. The criteria for a good leader are excellent decision-making skills, disciplined emotions, and accepts criticism. A leader must not have a high level of impulsivity because they will act according to their whims and desire a high position of power over others. That kind of behavior illustrates that the leader might take action without prior planning or considering any consequences. Experiments for this research are done by recording the condition open eye relaxation. This research uses alpha, beta 1, and beta 2 wave activities using the Support Vector Machine (SVM) method. Signal Electroencephalography (EEG) is recorded using Mitsar EEG-202. Then, the signal is filtered using a Band Pass Filter (BPF) with a cut-off of 0.5 Hz - 50 Hz. The resulting tabulation data for each subject were classified using SVM, which showed an accuracy rate of 94.40% with 60% training result data and 40% validation. The results of this study concluded that the level of impulsivity can be observed based on the classification results from the SVM method
I Gede Susrama Mas Diyasa, Agus Prayogi, Intan Yuniar Purbasari, Ariyono Setiawan, Sugiarto, and Prismahardi Aji Riantoko
IEEE
For a company engaged in the service and health sector, it is essential to read consumers' characteristics to develop the company and produce the right products. It is still challenging to determine patients' nutritional treatment, with many patients' healthy treatment remained appropriate and accurate for each patient. Patient data collection and patient interviews are needed to obtain suitable treatment data for the patient. However, to get appropriate further treatment, a system must process past patient data, resulting in more accurate follow-up treatments. The method used in this study is to calculate the value of the training data and K point with the K-Nearest Neighbors (K-NN) Algorithm. The goal is to determine the treatment package menu recommendations for consumers. The K-Nearest Neighbors algorithm is one of the algorithms used for the implementation of this system development. The patient characteristics and data distance calculation using the euclidean distance function can produce a category used to determine a more accurate and good nutritional treatment for each patient. The scenario in the test with a comparison of training data and test data 3: 1 has the highest program accuracy reaching 88%, precision reaching 91%, and recall going 95% among all the results of the test scenario
I Gede Susrama Mas Diyasa, Akhmad Fauzi, Moch. Idhom, Ariyono Setiawan, Tresna Maulana Fahrudin, and Prismahardi Aji Riantoko
IEEE
The speed and timeliness of ferry service users in the Ketapang-Gilimanuk crossing port is not optimal. This is due to the ineffectiveness of work productivity of management at the ferry port. Based on this, an Integrated Vehicle and Passenger Registration System (Manifest) was made in IoT-based with Android and Web systems. The android-based system will be used by passengers and dock operators to make arrangements for berths, while the web-based system is used by officers to process the issuance of the SAL “Approval Letter”. This system can reduce service processing time so that it is not difficult for the harbormaster officers to issue a “Sailing Approval Letter” (SPB) as well as vehicle loading/unloading arrangements and passenger boarding/unloading
I Gede Susrama Mas Diyasa, Akhmad Fauzi, Ariyono Setiawan, Moch. Idhom, Radical Rakhman Wahid, and Alfath Daryl Alhajir
IEEE
Malaria is a disease caused by the Plasmodium falciparum parasite carried by female Anopheles mosquitoes. This disease is still a severe threat in eastern Indonesia which is an endemic area of Malaria. A data-driven computer-aided diagnostic approach can be an innovative solution. From the experiment results using the Pre-trained Deep Convolutional Neural Network algorithm that was trained with the transfer learning method, the GoogLeNet model was able to achieve a detection accuracy of 93.89%. In comparison, the ShuffleNet V2 model gained 95.20% accuracy with training times three times faster than GoogLeNet.
A Setiawan, Y Suprapto, M I Fachrurrozi, K R N Manab, N R Sasmita, and G S M Diyasa
IOP Publishing
Yuyun Suprapto, Achmad Setiyo Prabowo, Mochammad Rifai, Ariyono Setiawan, and B.B. Harianto
IOP Publishing
The need for telecommunication in this era is very important and increasing. Including communication that uses digital data such as VoIP (Voice over Internet Protocol). One of the SIP servers (Session Initials Protocol) that worked well is the Kamailio server. It’s operating on an open-source and operating on the Linux system. The SIP communication system at the airport designed on this research uses Kamailio as SIP server. The goal is to make communication easier at the airport by using existing network facilities such as wi-fi. The quality of service parameters (QoS) of this study is a delay, throughput, and packet loss on the transmission of text messages, voices, and videos. Results obtained indicate the good value of that communication standard. 114 with 86.62 ms delay parameters for text, 110.10 ms for votes, and 127.52 ms for the video. The throughput shows the average varies with 330 kbps, 45.71 kbps, and 72.3 kbps according to the type of communication. The zero-percent value of packet loss shows all communication on this system is sent to the user in real-time. In this study, it can be concluded that the Kamailio server can be used as a SIP-based communication system at the airport. Testing shows good results on QoS text messages, voice calls, and video calls.
G S M Diyasa, A Fauzi, M Idhom, and A Setiawan
IOP Publishing
Eva Y Puspaningrum, Wahyu S.J. Saputra, and Ariyono Setiawan
IEEE
There are lots of old pictures in black-and-white and grayscale. When a grayscale image is painted, it can show the clarity of the past image. Many methods were proposed to perform a color transformation on greyscale images. Some include using manual methods and chemicals to more modern ones using graphic design software. However, all of these methods require special skills and a long time. We need a system that can automatically perform color transformations on gray images. The system developed in this study uses the Self-attention and Spectral Normalization GAN (SSN-GAN) algorithm, which automatically transforms grayscale images. This method was chosen because it can solve various image-to-image translation problems. This method produces a better initial score and a more stable training process. Self-attention is used to increase the initial score of the image generated by the GAN. The addition of spectral normalization makes the training process on the GAN run more stable. At the same time, by increasing the learning rate on the generator and discriminator, the model can produce a better image. In this study, researchers used two loss functions, namely, using SSIM Loss and without SSIM Loss. The highest accuracy value in the test with an epoch value of 50 and using SSIM loss, the accuracy value obtained is 59.9
Yuyun Suprapto, Moch. Rifai, Fiqqih Faizah, and Ariyono Setiawan
IEEE
This study aims to know the changes that happened in the learning environment caused by the information technology development applied in online learning during the pandemic COVID-19. The rapid changes in information technology have affected many learning strategies and environments, and also improved teacher and student capabilities in information technology. To obtain the solution, this study uses a qualitative descriptive approach as a method. The objects in this research are teachers and students in Aviation Polytechnic of Surabaya, a vocational college that implemented a ruled-boarding school system. The pandemic condition has changed the learning system from face-to-face traditional learning into online learning from their home. The result shows that information technology has successfully shifted the student tendency to do face-to-face learning system. This situation also encourages teachers to be able to choose and use information technology as a learning medium for student learning success. In this study, it was stated that teachers, students, and the Aviation Polytechnic of Surabaya as a vocational school institution need to make some adjustments in learning techniques to accommodate a pandemic learning environment. The learning design allows many models, methods, and media in the online learning system to facilitate the distance learning process to reach certain goals. The implication of this COVID-19 online study-research is a shift in the learning environment caused by the knowledge level of information technology.
Eva Y Puspaningrum, Budi Nugroho, Ariyono Setiawan, and Nuraini Hariyanti
IOP Publishing
I Gede Susrama Mas Diayasa, Ni Luh Wiwik Sri R.G, Slamet Winardi, Ariyono Setiawan, M. Sri Wiwoho, Benediktur Anindito, and Tri Andjarwati
IOP Publishing
Ariyono Setiawan, I Gede Susrama Mas Diyasa, Moch Hatta, and Eva Yulia Puspaningrum
Universitas Ahmad Dahlan, Kampus 3
Healthy and superior sperm is the main requirement for a woman to get pregnant. To find out how the quality of sperm is needed several checks. One of them is a sperm analysis test to see the movement of sperm objects, the analysis is observed using a microscope and calculated manually. The first step in analyzing the scheme is detecting and separating sperm objects. This research is detecting and calculating sperm movements in video data. To detect moving sperm, the background processing of sperm video data is essential for the success of the next process. This research aims to apply and compare some background subtraction algorithms to detect and count moving sperm in microscopic videos of sperm fluid, so we get a background subtraction algorithm that is suitable for the case of sperm detection and sperm count. The research methodology begins with the acquisition of sperm video data. Then, preprocessing using a Gaussian filter, background subtraction, morphological operations that produce foreground masks, and compared with moving sperm ground truth images for validation of the detection results of each background subtraction algorithm. It also shows that the system has been able to detect and count moving sperm. The test results show that the MoG (Mixture of Gaussian) V2 (2 Dimension Variable) algorithm has an f-measure value of 0.9449 and has succeeded in extracting sperm shape close to its original form and is superior compared to other methods. To conclude, the sperm analysis process can be done automatically and efficiently in terms of time.
I Gede Susrama Mas Diyasa, Intan Yuniar Purbasari, Ariyono Setiawan, and Slamet Winardi
IEEE
Problems with the management of city bus in Surabaya, East Java, Indonesia include the absence of a system that can detect and report the number of passengers in every city bus / bus stop. At present, the counting is conducted manually with a paper-based recording system done by two employees in general. This condition makes the passenger movement data and the report addressed to the city bus management invalid. In addition, a city bus passenger reporting system is required to facilitate the city bus passenger counting system so that passenger data can be obtained quickly, electronically stored, and easily analyzed for decision-making in the development of public transportation service. The reporting system developed in this study included detecting bus location, recording the number of passengers who get on and off the bus, and sending the information regarding the location and the number of passenger movement to the IoT-based data processing center. The system consists of RFID and IoT Microcontroller (Wemos d1 mini). RFID serves as the data entry of the passengers who get on and off the bus. Whereas D1 Wemos Mini will process the data of the number of passengers read by the RFID sensor, then the Wemos d1 Mini will connect WiFi to the access point installed at bus stops. After that, the data will be sent to the cloud database through an Internet network and displayed on the website. □ This system has been implemented and tested in real-time to find out the number of bus passengers. According to the test results, the information regarding passenger movements at every bus stop for one bus could be recorded properly. Thus, it provided important information in making decisions about the development of city buses as public transportation in Surabaya.
I Gede Susrama Mas Diyasa, Eva Y Puspaningrum, Moch. Hatta, and Ariyono Setiawan
IEEE
Two factors that cause male infertility include spermatozoa and nonspermatozoa factors. To discover infertility caused by spermatozoa factor, sperm analysis can be conducted. One of the analysis processes is analyzing the morphology (that is related to the shape of head, neck, and tail) of spermatozoa. The analysis of sperm abnormality is based on the current morphology by observing and calculating the normal shape of sperms manually. Therefore, a system to analyze spermatozoa automatically is required so as to provide essential information regarding sperm condition accurately and quickly. The contribution of this research is to classify spermatozoa automatically and distinguish objects that are not spermatozoa. The novel element of this research is the analysis of sperm morphology based on microscopic videos of spermatozoa by comparing it with the previous researches with images as input data. Hence, what was conducted in this research is automation in analyzing spermatozoa with microscopic video or moving images of spermatozoa as the input data. The research method was initiated with a preprocessing procedure, which included extracting video into images, erosion and dilation operations. It was followed by the process of object segmentation and detection based on edge line, color, and color intensity using contour detection, feature extraction based on eccentricity and Equivalent Circular Diameter (ECD), and finally, classification using decision tree with accuracy result of 83.81%.