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INDONESIA
ELINVO (Electronics, Informatics, and Vocational Education)
Published by Universitas Negeri Yogyakarta
ISSN : 25806424     EISSN : 24772399     DOI : 10.21831
Core Subject : Science, Education, Engineering,
Computer Science & IT Education Electrical & Electronics Engineering
ELINVO (Electronics, Informatics and Vocational Education) is a peer-reviewed journal that publishes high-quality scientific articles in Indonesian language or English in the form of research results (the main priority) and or review studies in the field of electronics and informatics both in terms of their technological and educational development.
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 247 Documents
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Usability of Mobile Application for Implementing Genetic Counselling Intervention among Thalassemia Patients and Caregivers: A Case Study of Cyber Gen Setiawan, Henri; Hidayat, Nur; Farihatun, Atun; Indriastuti, Marlina; Kurniawan, Rudi; Firmansyah, Andan; Andarini, Esti; Lutfi Sandi, Yudisa Diaz
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 8 No. 1 (2023): Mei 2023
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/elinvo.v8i1.55688

Abstract

Utilization of communication and information technology has been widely used in the health sector, especially nursing. As one of the nursing interventions for thalassemia patients and caregivers, genetic counseling is not only done face to face but can use android-based telenursing facilities through the complete features available in the Cyber Gen application. This study aims to measure the usability level of Cyber Gen application as an indirect genetic counseling medium for thalassemia patients. This application was developed with four main services: basic information about diseases, consultation rooms, social support, and direct surveys. This application is built using the Flutter Framework, the Dart programming language, and Cloud Firestore as the database. Usability was measured by using the System Usability Scale in two groups of 30 respondents each with an incidental sampling technique. The usability score shows 81.75 for personal users and 82.25 for counselor users with a 100% readiness level for use. These results indicate that the Cyber Gen application can be used to deliver genetic counseling intervention to thalassemia patients and caregivers.
Comparison of Convolutional Neural Network Architecture on Detection of Helmet Use by Humans Hartatik, H.; Anam, Muhammad Khoirul
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 8 No. 1 (2023): Mei 2023
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/elinvo.v8i1.52104

Abstract

The helmet is one of the protective equipment for the head when driving. Although it is a protector, some criminals misuse helmets to disguise their identities, such as robbery at ATMs. Some places have put a sticker not to wear a helmet in the ATM room. However, this advice is often violated. The research adopted the Convolutional Neural Network (CNN) algorithm to identify humans who use helmets and do not use helmets based on digital images. Several CNN models, such as MobileNet-V2, ResNet-50, and VGG-16, were compared in performance. The experiment was carried out using a dataset consisting of 3,207 images which were divided into two classes. The first class is used for classifying human images using helmets with 1,603 images. At the same time, the second class is for images of humans who do not use helmets, with a total of 1,604 images. The test results show that the architecture with the highest accuracy value is ResNet-50, 97.81%. At the same time, the mobileNet-V2 architecture obtained a lower accuracy value of 96.36% and the VGG-16 architecture of 52.25%.
Development of Electrical Machine Training Kits to Increase Competency in Practical Learning and Work Readiness in The Industry Budiastuti, Pramudita; Damarwan, Eko Swi; Triatmaja, Adhy Kurnia; Setyanto, Barry Nur
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 8 No. 1 (2023): Mei 2023
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/elinvo.v8i1.57884

Abstract

This study aims to develop Electrical Machine Training Kit for electrical machine practice media in vocational education. This type of research with Analyze, Design, Development, Implementation, and Evaluation (ADDIE) model. The background of this research is that the need for electrical machine competency, which students should have mastered, is still insufficient due to inadequate tools. Many graduates still have difficulty getting a job in the industry because competence has not been fulfilled during college. Electronic engineering vocational education is a study program that has the goal of producing superior graduates in achieve electrical machine competence and being ready to work in the industry. Electronic engineering vocational education is a new study program that is still in the development stage to achieve this goal. The media aspect obtains a minimum value of 87.5% and a maximum value of 90%. Material aspects get a value of 88.40% for suitability material and 90.2% for the quality of learning. The user feasibility test obtained a value of 89.80% in review from motivation, 88.0% in terms of convenience, and 90.3% in terms of material. It is concluded that the Electrical Machine Training Kit is included in the "very feasible" category.
Classification of Corn Seed Quality using Residual Network with Transfer Learning Weight Koeshardianto, Meidya; Agustiono, Wahyudi; Setiawan, Wahyudi
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 8 No. 1 (2023): Mei 2023
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/elinvo.v8i1.55763

Abstract

Corn is one of the main ingredients in farm animal feed. Currently, corn is preferable because widely available and cheaper in the market than others. However, it needs quality control on corn production. The company that manufactures animal feed has certain quality standards to receive corn material. On the other hand, the quality of corn produced varies greatly. Thus, quality control when receiving corn from suppliers greatly affects the quality of animal feed. The quality of feed ingredients is classified into physical properties and analytical values. Physical properties are determined so that the resulting corn can be accepted or rejected, while the analytical value is used as the basis for formulating the diet. The physical properties of corn are determined by the human senses, such as sight and smell, while the analytical value is by chemical analysis. Physical quality control by relying on human senses is certainly limited and takes time. Based on these problems, it needs to make a classification system of corn seeds automatically. This study uses corn seed images as classification data. The system uses public data from Naagar which consists of four classes:  pure, discolored, silk cut, and broken. Image classification uses a Convolutional Neural network (CNN) with ResNet152v2 architecture. The hyperparameters used consist of a learning rate of 0.001, a batch size of 512, and an epoch of 25. Adaptive Moment Estimation (Adam) for the optimizer. Percentage of data training vs validation 80:20. The validation results show an accuracy of 65%, precision of 66%, and recall of 64%.
A Comparison of OpenNMT Sequence Model for Indonesian Automatic Question Generation Indrihapsari, Yuniar; Jati, Handaru; Nurkhamid, N.; Wardani, Ratna; Setialana, Pradana; Mahali, Muhamad Izzudin; Wijaya, Danang; Ardiansyah, Dhista Dwi Nur; Ardy, Satya Adhiyaksa; Tiala, Maria Bernadetha Charlotta Wonda; Al-khawarizmi, Andi Hakim; Ardiyanto, Widya
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 8 No. 1 (2023): Mei 2023
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/elinvo.v8i1.56491

Abstract

Evaluation of learners is a crucial aspect of the educational system. However, creating evaluation instruments is a process that demands teachers' time and energy. The researcher developed the Indonesia Automatic Question Generator in this study using an architecture modified from past studies. The primary goals of this project are (1) to construct an AQG tool utilizing the OpenNMT series and (2) to analyze and compare the model's performance. As a data source, this study employs the SQuAD 2.0 dataset and numerous sequence techniques, including BiGRU, BiLSTM, and Transformer. The researcher trained the models using OpenNMT-py and Google Collaboratory. This approach generates questions that are relevant to the context of the source. This study found that the model was acceptable.
Front Matter Vol 8 No 1 Team, Editorial
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 8 No. 1 (2023): Mei 2023
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/elinvo.v8i1.64163

Abstract

Classification of Beef and Pork Images Based on Color Features and Pseudo Nearest Neighbor Rule Baiti, Ahmad Awaluddin; Fachrie, Muhammad; Diwandari, Saucha
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 8 No. 2 (2023): November 2023
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/elinvo.v8i2.64810

Abstract

This research is motivated by the need for halal foods in Muslim society with the purpose of avoiding non-halal foods, such as pork, that are sold in the market. Although beef and pork basically have different characteristics, not all Muslims know the differences. Moreover, people nowadays sell beef mixed with pork to obtain more profits. Hence, this paper proposed the implementation of the Pseudo-Nearest Neighbor Rule (PNNR) in classifying images of beef and pork slices based on color features. Based on the image dataset that has been collected, the very significant difference that can be identified visually between beef and pork is the color. The color features were extracted from the image using a color histogram from two different color channels, RGB and HSV. As the result, PNNR that used color features from the RGB channel achieved up to 87.43% accuracy, while using the HSV channel, it can reach up to 93.78% of accuracy. Additionally, this paper evaluates the stability of the proposed method by assessing the variance of classification accuracy across different values of k. It is also noticed that PNNR's performance is relatively consistent for various values of k compared to the traditional kNN algorithm.
Electronic Learning Media E-Module Open Source-Based on Planetary Type Starter System for Vocational Students Setiyawan, Andri; Firdaus, Doni Yusuf; Suwahyo, Suwahyo; Apristia, Lelu Dina; Faksi, Sanli; Iman, Muhammad Syamsuddin Nurul; Abrori, Fadhlan Muchlas; Bautista, Guillermo
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 9 No. 1 (2024): Mei 2024
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/elinvo.v9i1.66448

Abstract

Post-pandemic COVID-19 learning that is carried out in a hybrid manner experiences problems, one of which is minimal self-learning supplements, which affect students' understanding of the material. This study aims to develop an e-module using Sigil software on planetary-type starter system material. Hopefully, it can support improving students' knowledge of the material. This research uses the Research and Development (RnD) method with the ADDIE model. The results of this product were tested on a limited basis by using a one-group pretest-posttest design in class XI TKRO-A with 30 students. The results showed that the E-module that had been developed received a very decent category from media experts, who scored 89.26%, and from material experts, who scored 95.5%. The e-module developed can increase the understanding of the material with a gain value of 0.64 with a moderate category, and a score of 93.75% from the students' responses showed that the e-module is feasible. The conclusion is that the e-module developed is very feasible to use in independent learning and the learning process at school.
The Flipped-Classroom Instructional Procedure Development and Its Implementation Effectiveness in Improving Procedural Knowledge Learning Outcomes at Vocational High Schools Herlambang, Admaja Dwi; Fransisca, Olivia Dyah; Afirianto, Tri
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 8 No. 2 (2023): November 2023
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/elinvo.v8i2.57845

Abstract

The students' number limitation in a classroom and the compression of face-to-face time challenge teachers to present practical learning scenarios to achieve learning objectives. This study aims to develop student learning procedures with the flipped classroom (FC) instructional model and determine its use in improving student learning outcomes. The research was conducted at a public information technology vocational high school in Malang, East Java Province, Indonesia. The FC instructional procedure development approach is based on the ADDIE (analysis, design, development, implementation, and evaluation) phase. The FC instructional procedure was developed in conjunction with a constructivist instructional strategy, consisting of five primary stages: (1) perception, (2) exploration, (3) restructuring, (4) implementation, and (5) review and evaluation. FC instructional procedure effectiveness was tested using the Randomized Pre-test and Post-test Control Group Design research design. The control and experimental groups consist of 30 students with randomization. The research found that the learning outcomes of the experimental group (EGLO = 70.00) were greater than those of the control group (CGLO = 64.30). The normalized gain index of the experimental groups (g = 0.50) was more significant than the control groups (g = 0.41). The conclusion is that the FC procedures with a constructivist approach have proven more effective in improving student learning outcomes.
Improvement of Performance E-Learning Moodle Service in Vocational High School with Optimization of Web Server and Database Server Irfan, Rahmatul; Pratama, Cannavaro Yogi
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 9 No. 1 (2024): Mei 2024
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/elinvo.v9i1.42878

Abstract

Since COVID-19, online learning has taken on an increasingly prominent role. Moodle is a popular online learning platform. Its implementation necessitates various support components, including a web server and an e-learning database server. The purpose of this study is to examine the optimization of web servers and database servers when there are multiple large connections at SMK N 2 Depok's E-learning. A pre-experimental one-group pretest-posttest design was used to conduct experimental research before and after optimization. Response time and throughput performance variables are used to assess performance on the Web Server, whereas response time and transaction per second performance are measured on the Database Server. The tools utilized in this study were Apache Benchmark and Sysbench. The population in this study was 2180 active users, with a total sample of 338 connections to access e-learning. The results of this research indicate that the performance of the Moodle e-learning web server can be optimized by tuning the web server configuration. There was a significant increase in performance on the web server after optimization. The performance of the moodle e-learning database server performance can be optimized by optimizing the database server configuration tuning.  There is a significant increase in the performance of the database server after optimization. To use e-learning efficiently when using several connections at the same time, the web server and database server must be optimized through server tuning. This can boost the effectiveness of e-learning in the classroom. As a result, e-learning developers should consider optimizing e-learning server settings.

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