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Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI)
Published by Universitas Ahmad Dahlan
ISSN : 23383070     EISSN : 23383062     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
JITEKI (Jurnal Ilmiah Teknik Elektro Komputer dan Informatika) is a peer-reviewed, scientific journal published by Universitas Ahmad Dahlan (UAD) in collaboration with Institute of Advanced Engineering and Science (IAES). The aim of this journal scope is 1) Control and Automation, 2) Electrical (power), 3) Signal Processing, 4) Computing and Informatics, generally or on specific issues, etc.
Arjuna Subject : -
Articles 17 Documents
 1   2 
Search results for , issue "Vol 7, No 2 (2021): August" : 17 Documents clear
New Hybrid Deep Learning Method to Recognize Human Action from Video Md Shofiqul Islam; Sunjida Sultana; Md Jabbarul Islam
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 7, No 2 (2021): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v7i2.21499

Abstract

There has been a tremendous increase in internet users and enough bandwidth in recent years. Because Internet connectivity is so inexpensive, information sharing (text, audio, and video) has become more popular and faster. This video content must be examined in order to classify it for different purposes for users. Several machine learning approaches for video classification have been developed to save users time and energy. The use of deep neural networks to recognize human behavior has become a popular issue in recent years. Although significant progress has been made in the field of video recognition, there are still numerous challenges in the realm of video to be overcome. Convolutional neural networks (CNNs) are well-known for requiring a fixed-size image input, which limits the network topology and reduces identification accuracy. Despite the fact that this problem has been solved in the world of photos, it has yet to be solved in the area of video. We present a ten stacked three-dimensional (3D) convolutional network based on the spatial pyramid-based pooling to handle the input problem of fixed size video frames in video recognition. The network structure is made up of three sections, as the name suggests: a ten-layer stacked 3DCNN, DenseNet, and SPPNet. A KTH dataset was used to test our algorithms. The experimental findings showed that our model outperformed existing models in the area of video-based behavior identification by 2% margin accuracy.
Crude Oil Price Forecasting Using Long Short-Term Memory Muhamad Fariz Maulana; Siti Sa’adah; Prasti Eko Yunanto
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 7, No 2 (2021): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v7i2.21086

Abstract

Crude oil has an important role in the financial indicators of global markets and economies. The price of crude oil influences the income of a country, both directly and indirectly. This includes affecting the prices of basic needs, transportation, commodities, and many more. Therefore, understanding the future price of crude oil is essential in helping to budgeting and planning for a better economy. The contribution of this research is in finding the best hyperparameters and using early stopping methods in the LSTM model to predict oil prices. This research implemented Long Short-Term Memory (LSTM), an artificial neural network that can handle long-term dependencies and the problems of time series data. The LSTM method will be used to predict Brent oil prices on daily and weekly time frames. The experiment has been conducted by tuning some parameters to obtain the best result. From the daily time frame experiment, the model obtained RMSE and MAE of 1.27055 and 0.92827, respectively, while the weekly time frame has RMSE and MAE of 3.37817 and 2.60603, respectively. The results show that the LSTM model can improve to the trends that occur in the original data.
Analysis and Implementation of Microservice Architecture Related to Patient Drug Schedule Based on FHIR Standard Ariq Musyaffa Ramadhani; Andrian Rakhmatsyah; Rahmat Yasirandi
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 7, No 2 (2021): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v7i2.21169

Abstract

In several previous studies, smart devices have been developed to help improve a patient's medication adherence but have problems, namely data management that is not centralized and not integrated, so that mitigation is quite vulnerable. In this study, a platform was built that can manage data centrally and apply the FHIR (Fast Healthcare Interoperability Resources) health data standard. The main components used to implement the FHIR standard are resources and REST APIs. The resource is a data model that defines the structure and data elements that are exchanged. This data exchange is carried out on top of the REST API using the HTTP protocol. Platform testing uses positive/negative testing and stress testing methods to be able to see the performance of the platform. The test results show that the platform prototype can provide a response that is in accordance with the request given and has a very tolerant error value of 0% with a latency value of 3 to 22 seconds with a total of 100 to 130 users.
Comparison Support Vector Machine and Naive Bayes Methods for Classifying Cyberbullying in Twitter Nur Chamidah; Reiza Sahawaly
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 7, No 2 (2021): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v7i2.21175

Abstract

Twitter users in Indonesia in 2019 were recorded at 6.43 million. The high level of Twitter users makes it allows for free opinion to anyone, it can cause cyberbullying. Victims of cyberbullying experienced higher levels of depression than other verbal acts of violence. The forms of cyberbullying that occurs on Twitter are Flamming, Denigration, and Body Shaming. The research contribution is able to make social media developers and users more aware of the type of cyberbullying that social media users sometimes do without realizing it. Social media developers can prevent cyberbullying by using policies such as word detection and filtering features that indicate cyberbullying more accurately by classifying it by type and using the most accurate method. To classify cyberbullying forms in twitter, in this study we use the Naïve Bayes method and Support Vector Machine (SVM) and compare them based on classification accuracy. This research will also identify words that are characteristic of each category of cyberbullying so that each category is easy to identify by social media users and makes it easier to avoid cyberbullying. The results of this study are the classification accuracy of Naïve Bayes of 97.99% and the classification accuracy of SVM of 99.60%. It means that SVM is better than Naïve Bayes for classifying the forms of cyberbullying in Twitter.
Evaluation of IoT-Based Grow Light Automation on Hydroponic Plant Growth Yuda Prasetia; Aji Gautama Putrada; Andrian Rakhmatsyah
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 7, No 2 (2021): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v7i2.21424

Abstract

This research aims to design, create, and evaluate a hydroponic automation system by monitoring the quality of plant growth that uses LED grow lights and natural light conditions on hydroponics. Checking whether the proposed system has a significant effect on the box Choy hydroponic growth is also an important aspect and becomes the contribution of this paper. The contribution of this paper is by discussing in detail the automation of LED grow lights using RTC modules and relays while also discussing the significance of LED light performance in hydroponic growth. On the proposed hydroponic automation systems, light-feeding is done automatically, this can be carried out with the help of a real-time clock (RTC) module and relays. Furthermore, the monitoring function is carried out through temperature and humidity measurement sensors. The data obtained from the sensor will be stored in the database for research on plant quality. The results of a comparison test show that the LED grows lights are superior in terms of fresh weight, the number of leaves, and plant height respectively with an average value of 23.6 grams, 11.2 leaves, and 18.1 cm on the 30th day. Compared to sunlight, respectively with an average value of 20.2 grams, 9.3 leaves, and 17.1 cm on the 30th day. PDF calculation and t-test are used to calculate the growth significance. The results are that the H0 for fresh weight and leaf growth rate is rejected and the H0 for plant growth rate is not rejected. It can be concluded that the LED grow lights give a significant effect on the fresh weight and leaf growth rate of IoT-based box Choy hydroponics if compared to sunlight.
An Improved DC Motor Position Control Using Differential Evolution Based Structure Specified H∞ Robust Controller Petrus Sutyasadi
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 7, No 2 (2021): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v7i2.21103

Abstract

Traditional synthesis of an H∞ controller usually results in a very high order of controller that is not practical for a low-cost embedded system such as a microcontroller. This paper presents a synthesis method of a low-order H∞ robust controller to control the position of a dc motor. The synthesis employed Differential Evolution optimization to find a controller that guarantees robust stability performance and robust stability against system perturbation. A second-order PID structure was chosen for the synthesized controller because this structure is simple and very famous. The proposed controller performance under uncertainties was compared to some other controllers. The first was compared with a conventional PID controller that had been finely tuned using the trial and error method in the nominal transfer function of the plant. Secondly, the proposed controller was compared with a full-order H∞ robust controller generated from a traditional synthesis method. Thirdly, the proposed controller was compared with another structure specified H∞ robust controller generated differently from the proposed method. All of the controllers result in a stable response. However, the proposed controller gives a better response in terms of overshoot and response time.
Integration between Moodle and Academic Information System using Restful API for Online Learning Novian Adi Prasetyo; Yudha Saintika
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 7, No 2 (2021): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v7i2.21816

Abstract

During the current pandemic, it is encouraging educational institutions to carry out distance learning, so many learning management system (LMS) platforms can be used to support distance learning. Each LMS has a different process flow but has the same goal of making it easier to manage learning content. When an LMS is implemented in an educational institution, it requires matching data for courses, students and lecturers that are available in the academic information system (AIS) at the institution, this is one of the weaknesses of all LMS because the data are not interrelated between AIS and LMS. The purpose of this research is to create an integrated system to equalize data between AIS and LMS using the synchronization method through the Application Programming Interface (API). The results of this application will combine data from AIS and LMS which will then be tested for automatic course creation according to class data, courses, lecturers and students at AIS. The test results of this system are said to be successful because each function that is designed has been running well without any fatal errors. The most important thing that needs to be considered when synchronizing is that there is a link between the data on the AIS and LMS, failure occurs on some courses because the email users in the AIS and LMS are different.

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