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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 311 Documents
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Modification of Control Oil Feeding with PLC Using Simulation Visual Basic and Neural Network Analysis Yuliza Yuliza; Rachmat Muwardi; Danang Widya Pratama; Makmur Heri Santoso; Mirna Yunita
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 1 (2022): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i1.22336

Abstract

The oil feeding system is an oil distribution system used in engine lubrication by flowing it directly to the engine parts to be lubricated through pipes. In addition, it is also a raw material for the production process by collecting the oil first in the storage tank, then weighing it on the oil scale before use in the production process. The current control is still using the conventional model. The operating system is still manual, and the absence of identity and damage information makes it difficult for the engineer to troubleshoot. The research method is to modify the oil feeding system control using PLC (Programmable Logic Controller) and Visual Basic to display process information. This process uses the Neural Network (NN) method. The simulation results show that the PLC program and visual basic software can be connected properly. The speed of the data transfer test connection that can be obtained is 32 ms. The prediction process of the oil feeding system using the backpropagation algorithm Neural Network and the activation function, which uses the binary sigmoid function (logsig) with the 17-10-1 architecture having very good performance getting the MSE value below the error value of 0.001 maximum epoch 961 and hidden layer 10 with an MSE value of 0.00099915.
Multi-hop ESP-Mesh Network and MQTT Protocol for Smart Light Systems in High-Rise Buildings Januarman Maulana Putra; Misbahuddin Misbahuddin; Sudi Mariyanto Al Sasongko
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 1 (2022): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i1.22535

Abstract

When a high-rise building's lights are not required because they are frequently left on, electrical energy is wasted as a result of this.  The smart light is one of the effective ways to energy saving in a building. This study aims to create a smart light system using the ESP-Mesh network and the MQTT protocol to control the turn on/off of all lights in all rooms of a high-rise building. The ESP-Mesh network is a mesh of ESP8266 devices that are designed for multi-hop transmission. The MQTT is one of the widely used IoT protocols that allows a smartphone to control the lights in every room in a mesh topology via the internet remotely. The performance evaluation shows that a multi-hop ESP-Mesh is better than that a Single-hop ESP8266 in signal strength. The signal strength of the ESP8266 single-hop is bad. Meanwhile, the signal strength of the multi-hop ESP-Mesh is good in all rooms. Furthermore, The functional tests of the multi-hop ESP-Mesh show that although there are various broken paths caused by several disconnected nodes, all lights can be turned on or off suitably through the command from the smartphone switch. Turning off the not-required lights by smart light systems can help save energy.
Detection of Oxygen Levels (SpO2) and Heart Rate Using a Pulse Oximeter for Classification of Hypoxemia Based on Fuzzy Logic Mazaya Zata Dini; Andrian Rakhmatsyah; Aulia Arif Wardana
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 1 (2022): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i1.22139

Abstract

This study made the digital system to perform screening (early prediction) of Hypoxemia using MAX30102 sensor with the fuzzy value from SpO2 level and heart rate. This research also uses the Internet of Things (IoT) system to gather data from devices to the cloud. Hypoxemia is a lack of oxygen in the blood flowing in the body. Hypoxemia conditions in the body due to lack of oxygen levels in the blood will cause an increased heart rate. Hypoxemia conditions that are not immediately recognized cause damage to cells, tissues, and organs. Hypoxemia is an essential condition because information about oxygen levels in the blood is closely related to health conditions. In this project, researchers built a Hypoxemia early detection system. From the research results, it is found that the accuracy rate of the system to detect hypoxemia is 80%, with 60% sensitivity and 100% specificity. Based on the experiment, this research is able to help screening detection (early prediction) of Hypoxemia.
Simulation of Logic Circuit Tests on Android-Based Mobile Devices Abdülkadir Çakir; Ümmüsan Çitak
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 1 (2022): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i1.22200

Abstract

In this study, an application that can run on Android and Windows-based mobile devices was developed to allow students attending such classes as Numerical/Digital Electronics, Logic Circuits, Basic Electronics Measurement, and Electronic Systems in Turkey’s Vocation and Technical Education Schools to easily carry out the simulation of logic gates, as well as logic circuit tests performed using logic gates. A 2D-mobile application that runs on both platforms was developed using the C# language on the Unity3D editor. To assess the usability of the mobile application, a one-hour training session was administered in March of the 2017-2018 academic year to two groups of students from a single class in the sixth grade of an Imam Hatip Secondary School affiliated with the Ministry of National Education. Each of the two groups contained 12 students who were assumed to be equivalent and who had no prior knowledge of the subject. The training of the first group began with a lecture on basic logic gates using a blackboard and involved no simulations. In comparison, the second group was given the same lecture and received additional training involving demonstrations of the developed mobile application and its simulations. Following the lectures, a written exam was applied to both groups. An evaluation of the exam results revealed that 83 percent of the students who had been given demonstrations of the mobile application were able to perform the circuit task completely, whereas only 50 percent of the others were able to complete the task. It was concluded that the application was both useful and facilitating for the students, and it was also noted that students who were supported by the mobile application had gained a better grasp of the topic by being able to see and practice the simulations firsthand.
The Artificial Intelligence (AI) Model Canvas Framework and Use Cases Aldian Nurcahyo; Jarot Suroso; Gunawan Wang
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 1 (2022): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i1.22206

Abstract

Artificial Intelligence (AI) has grown increasingly in the past decade. The growth and development bring up several issues for a successful AI project. The AI project requires communication across different domains, like specialists, engineers, data scientists, stakeholders, and ecosystem partners (analytic, storage, labeling, and open-source platforms). It offers numerous vital qualities to give deeper insights into user behavior and give recommendations based on the data. The AI project is hard to define, it requires more than mastery of data, and every enterprise needs guidance and a simple plan on how to use AI. This research creates a wide-view approach of different types of AI Model Canvas for companies that do projects, produce, promote and provide AI technology to organizations. We selected three canvases that represented AI, Machine Learning (ML), and Deep Learning (DL) method. We illustrate and interpret those canvas along with some case studies. We conclude our research by writing the final case report for each use case from the AI model canvas. By filling the one-page Canvas, it will help us explain what AI will provide, how it will interact with humans judgment, and how it will be used to influence decisions, how you will measure success & outcome, and the type of data needed to train, operate, and improve AI. The AI Model Canvas purposed a clear description and differentiation of the roles of stakeholders, customers, and AI strategy. This canvas also can be used in analytical and assembly projects in making new product lines.
Effect of Continuous Working Fluid Flow Direction on Power Generation from Piezoelectric Sensors Elin Yusibani; Farah Dina; Cut Khairunnisa; Fashbir Fashbir; Muhammad Syukri Surbakti; Bambang Joko Suroto
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 1 (2022): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i1.22700

Abstract

This paper presents an experimental study to support the concept of generating energy by a continuous flow of water using piezoelectric sensors. This study is aimed to determine the effect of external force direction of continuous water flow, i.e., vertical and horizontal, on the output of the piezoelectric sensors. The piezoelectric type of ABT-441-RC is used and arranged in parallel. IC MAX471 as an amplifier and Arduino Uno R3 to read the flow rate, voltage, and current were employed. Flow rates with variations of 0.00011 up to 0.00030 m3/s are set to study the voltage and current of the output. The numbers of piezoelectric sensors used are 4, 6, 8, and 20. As a result, it is found that the pressure in the vertical direction differs up to 68% from the pressure in the horizontal one. The voltage and current in the vertical direction, compared to that of the horizontal direction, differ as much as 85% at a low flow rate and decrease down to 63% at a high flow rate for voltage and 86% to 34% at a low to high flow rate for current. In conclusion, the current generation by the present arrangement is within the micro-ampere range, and the voltage is in a volt range, respectively.
Sentiment Analysis and Topic Modelling of The COVID-19 Vaccine in Indonesia on Twitter Social Media Using Word Embedding Kartikasari Kusuma Agustiningsih; Ema Utami; Omar Muhamammad Altoumi Alsyaibani
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 1 (2022): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i1.23009

Abstract

This study aims to analyze the sentiments of the Indonesian people towards the COVID-19 vaccine on Twitter. Data collection was carried out from September 2020 to June 2021 with the keyword "covid vaccine," which resulted in 262306 tweets. After filtering and cleaning, there are 83384 tweets left. The labeling process was done manually by an expert. The label composition in the data is 35209 tweets of positive sentiment, 41596 tweets of neutral sentiment, and 6579 tweets of negative sentiment. The remaining data is preprocessed using case folding, removing punctuation, stopword removal, stemming, and the application of slang words. The highest number of tweets appeared in January 2021, after Joko Widodo became the first person in Indonesia to receive a vaccine injection. The number of tweets reached 23492 tweets. At the topic modeling stage, measurements were conducted using the Coherence Score. The distribution of the optimal number of topics is 3 topics. The first topic, with a token percentage value of 51.8%, leads to positive sentiment, while the second and third topics, with token percentage values of 24.5% and 23.7%, lead to neutral sentiment. Bidirectional LSTM architecture was implemented to perform sentiment classification. Fasttext and GloVe word embedding was tested to vectorize tweet data. The test accuracy generated by Fasttext word embedding reached 75,7690%, while the test accuracy produced with GloVe word embedding reached 74.7017%. The usage of slang words could not increase the test accuracy in this study. The use of the Modelcheckpoint to monitor model performance during training could produce a model with a slightly higher test accuracy, about 1.07% (in scenario 1 and scenario 6), compared to a model whose performance was monitored using Early Stopping. In future research, it can be tried to apply a lower learning rate to produce better accuracy in a large number of epochs, or it could be by changing the dropout parameter.
Sentiment Analysis of Facebook Posts through Special Reactions: The Case of Learning from Home in Indonesia Amid COVID-19 Ahmad R Pratama
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 1 (2022): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i1.23615

Abstract

In contrast to several other countries, Indonesian sentiment analysis research is primarily focused on the text-based analysis of Twitter. Given that Twitter users in Indonesia account for less than a seventh of those on Facebook, sentiment analysis on the latter may have a greater impact than on the former. This research sought to close that gap in the literature by pioneering the use of Facebook special reactions as an alternative to text-based sentiment analysis on social media posts about Indonesian social issues. The topic of learning from home in the midst of the COVID-19 pandemic was chosen because it is both timely and relatable to almost everyone in the country. Through CrowdTangle, a total of 39,657 Facebook posts containing the key phrase “belajar dari rumah” were gathered, but only 9,310 of them received special reactions and thus remained to be analyzed quantitatively. The results indicated that with the exception of ‘love,’ all special reactions are somewhat correlated, suggesting that they can be used to indicate the negative valence of a Facebook post. Further analysis revealed a significant increase in the proportion of posts with a negative valence during the second year of the COVID-19 pandemic. The textual analysis of the posts revealed that those with a negative valence primarily discuss internet access and other IT infrastructure issues that presumably impede learning from home activities for some. The main contribution of this study is to demonstrate how to analyze special reactions on Facebook for sentiment analysis purposes, particularly in the context of Indonesia. Additionally, it lays out how Facebook's special reactions have the potential to be used in conjunction with text-based sentiment analysis to provide a complete picture of the social issue being investigated.
IoT for Residential Monitoring Using ESP8266 and ESP-NOW Protocol Mochamad Fajar Wicaksono; Myrna Dwi Rahmatya
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 1 (2022): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i1.23616

Abstract

This research aims to create a cluster housing monitoring system. This system combines IoT with the ESP-NOW protocol. In this system, the head of security and homeowners can unify the state of the house through a web application and an android application. The system will send notifications via the web and the LINE messaging application if there is an intrusion or gas leak or no fire is detected. The contribution of this research is to shorten the path and time of data transmission and make it easier for homeowners and heads of security to monitor and take action as soon as possible when something goes wrong in the residential area. The method used in this research is experimental. There are 4 main parts to this system, namely ESP-NOW sender, ESP-NOW receiver, gateway module, and server. All microcontrollers in this system use the NodeMCU ESP8266 because the NodeMCU, apart from being a controller, also functions as a WiFi module. By using the ESP-NOW protocol, it is possible for every microcontroller, both the sender and the receiver, to communicate without using WiFi WAP. In this study, the ESP-NOW sender collected 10 installed in each house to unify the conditions of the house. The ESP-NOW receiver worked to receive data from all senders. Any data received by the receiver will be sent to the gateway serially. The gateway module functions to send all messages to the server online. Application on the server-side built using PHP and MySQL. The display of the system can be opened through the android application or web application. The results of this test indicate that the system is running well with a 100% success proportion where every message from the sender is stored on the server-side, and the application can provide notifications according to the scenario of the system.
Proposed Modification of K-Means Clustering Algorithm with Distance Calculation Based on Correlation Muhammad Ibnu Choldun Rachmatullah
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 1 (2022): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i1.23696

Abstract

Clustering is a technique in data mining that groups a set of data into groups (clusters) of similar data. In general, there are two methods of clustering, namely the hierarchical method and the partition method. One of the most commonly used partition clustering methods in clustering is K-Means. The use of K-means method has been widely used in various fields with various purposes. Many research has been carried out to improve the performance of the K-Means method, for example, by modifying the method of determining the initial centroid or determining the appropriate number of clusters. In this research, the modification of the K-Means algorithm was carried out in calculating the distance by considering the correlation value between attributes. Attributes that have a high correlation value are assumed to have similar characteristics so that they determine the location of data in a particular cluster. The steps of the proposed method are: calculating the correlation value between attributes, determining the cluster centroid, calculating the distance by considering the value of correlation, and determining the data into certain clusters. The first contribution of this research is to propose a new distance calculation technique in the K-Means algorithm by considering correlation and the second contribution is to apply the proposed algorithm to a specific dataset, namely Iris dataset. In this research, the performance calculation of the modified algorithm was also carried out. From the experimental results using the Iris dataset, the proposed modification of the K-Means algorithm has fewer iterations than the original K-Means method, so that it requires less processing time. The original K-Means method requires 8 iterations, while the proposed method requires only 6 iterations. The proposed method also produces a higher accuracy rate of 89.33% than the original K-Means method, which is 82.67%.

Page 18 of 32 | Total Record : 311

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