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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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Breaking Down Computer Networking Instructional Videos: Automatic Summarization with Video Attributes and Language Models Sukardiyono, Totok; Luthfi, Muhammad Irfan; Septiyanti, Nisa Dwi
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.v8i1.60741

Abstract

Instructional videos have become a popular tool for teaching complex topics in computer networking. However, these videos can often be lengthy and time-consuming, making it difficult for learners to obtain the key information they need. In this study, we propose an approach that leverages automatic summarization and language models to generate concise and informative summaries of instructional videos. To enhance the performance of the summarization algorithm, we also incorporate video attributes that provide contextual information about the video content. Using a dataset of computer networking tutorials, we evaluate the effectiveness of the proposed method and show that it significantly improves the quality of the video summaries generated. Our study highlights the potential of using language models in automatic summarization and suggests that incorporating video attributes can further enhance the performance of these models. These findings have important implications for the development of effective instructional videos in computer networking and can be extended to other domains as well.
Intelligent Security System in A Campus Building Using RFID to Improve Security for Elevator Users Desmira, D.; Hamid, Mustofa Abi; Noviawati, Lilis; Munandar, Tb. Ai; Martias, M.; Aribowo, Didik
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.v8i1.57848

Abstract

This study aims to develop an intelligent system of elevator access with RFID (Radio Frequency Identification) using fuzzy logic as an intelligent system, a safety controller of elevator doors that will open when the power goes out. This research made an Arduino Uno-based elevator access system with an RFID card using fuzzy logic as an intelligence system and markers for each floor. Each floor has an RFID card that contains the information data of each floor.  This research uses research and development (R&D) methods with a waterfall development model. The research procedure consists of several stages, namely the requirement analysis stage, design, implementation, testing, operation, and maintenance. Based on the research and development of the elevator control intelligent system, it can be concluded that the intelligent control lift system was developed using a waterfall model. integration and system testing includes RFID-RC522 reading distance testing, component function testing, and RFID response time measurement testing. The test results show that the RFID-RC522 is readable, and the RFID response time is fast. In addition, the components and all features function well as an elevator control system.
Arduino-Based High-Frequency Signal Data Acquisition for Learning Media on Antenna and Wave Propagation Practices Marpanaji, Eko; Zakarijah, Masduki; Bayu Nugraha, Nikko Aji
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.v8i1.60182

Abstract

This paper discusses the research results on the development of learning media and the results of the feasibility test for the learning process. This study aims to: (1) obtain the design and prototype of Arduino-based high-frequency signal data acquisition learning media; (2) find out the level of feasibility of learning media that has been made for the learning process of Antenna Practice and Wave Propagation courses. The research model uses Research and Development with the ADDIE development method. The research stages in the ADDIE method are Analyze, Design, Develop, Implement, and Evaluate. The research began with the development of learning media called Antenna Pattern Radiation Learning Media and the Practicum Module containing a collection of lab sheets for practicum activities using the media. The next step involves assessing the viability of the media. Validation tests gather expert feedback on materials, media, and users. In this study, data was collected using a questionnaire and analyzed quantitatively using descriptive analysis techniques. This research and development effort led to the creation of Antenna Pattern Radiation Learning Media and its practical modules. The test results showed that the material experts gave it a score of 95%, media experts rated it at 85.4%, and users (students) gave it a score of 80.65%. Based on the evaluations of the material experts, media experts, and users, it can be concluded that the Antenna Pattern Radiation learning media falls into the highly feasible category and can be utilized as a learning resource in courses related to Antenna and Wave Propagation.
Development of an Android-Based Cultural Heritage Map App Luthfi, Muhammad Irfan; Wardani, Ratna; Septiyanti, Nisa Dwi
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.v8i1.55729

Abstract

This study aims to (1) develop an Android-based cultural heritage map app that can provide the location of cultural heritages in the Special Region in Yogyakarta along with its descriptions, images, and videos; and (2) understand the quality of the app based on standard software quality testing ISO / IEC 25010 on functional suitability, performance efficiency, and compatibility. The development method utilized a waterfall software development model that consists of communication, planning, modeling, construction, and deployment. The results of this study are 1) an Android-based cultural heritage map app that can provide the location of cultural heritages in the Special Region of Yogyakarta along with its descriptions, pictures, and videos. and 2) the test results indicate the app meets the standards of ISO / IEC 25010 on the aspect of (1) functional suitability, entire functions of the app running 100%, (2) the compatibility of the app, compatible 100% of the co-existence, various operating systems, device types, and screen dimensions, (3) performance efficiency, the app successfully executed in 312 of the 321 test devices without any memory leak with the average of time behavior, CPU utilization, and memory utilization for Dalvik Virtual Machine are 0.022 seconds/thread, 10.71%, and 33.11 MB and the average of time behavior, CPU utilization, and memory utilization for Android Run Time are 0.020 seconds/thread, 9.9918%, and 154.582 MB.
Development of Hazard and Risk Simulation Applications in Electrical Power Installation Workshops Based on Android in Vocational High Schools Susilowati, Brigitta Endah; Hartoyo, H.
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.v8i1.57811

Abstract

This study aims to: (1) develop a hazard and risk simulation application, (2) find out the function test, (3) find out the feasibility of the hazard and risk simulation application, and (4) determine the effectiveness of using the hazard and risk simulation application. This research uses the Research and Development method with the ADDIE development model, according to Lee and Owens. It consists of 5 stages, including analysis, design, development, implementation, and evaluation. The research subjects were 70 students in the Electrical Power Installation Engineering Expertise Package at SMK Negeri 2 Yogyakarta. Data collection used a questionnaire that had been validated by media experts and material experts, each with two validators. Data analysis using descriptive methods. The results of the study concluded that: (1) the development of hazard and risk simulation applications can be used to support learning in the subject of Basic Electromechanical Work for Class X students, Competence of Electrical Power Installation Engineering Expertise, (2) function tests of hazard and risk simulation applications are included in the category of " Very Good", (3) the feasibility of the hazard and risk simulation application is included in the "Very Eligible" category according to media experts, material experts, and user response, (4) Wilcoxon test known Asymp value. Sig. (2-tail) of 0.00 shows that there is a difference in value after using hazard and risk simulation learning media. The effectiveness of media applications is known to have increased learning outcomes and is included in the "Moderate" category with a gain value of 0.43. This shows that the media application of hazard and risk simulation applications is effectively used as a learning medium to improve student learning outcomes.
Cross-Language Tourism News Retrieval System Using Google Translate API on SEBI Search Engine Husni, H.; Muntasa, Arif; Putro, Sigit Susanto; Osman, Zulfi
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.v8i1.55851

Abstract

Cross-Language Information Retrieval (CLIR) is responsible for retrieving information stored in a language different from the language of the query provided by the user. Some translation methods commonly used in CLIR are Dictionary, Parallel corpora, Comparable corpora, Machine translator, Ontology, and Transitive-based. The query must be translated to the target language, followed by preprocessing and calculating the similarity between the query and all documents in the corpus. The problem is the time and accuracy of query translation. Moreover, the queries are not written as complete sentences according to certain language rules. Stemming, for example, every language has its own method. Indonesian has basic words and affixes in the form of prefixes, suffixes, infixes, and confixes, while English only has suffixes. Stemming takes a long time in text processing. In the Indonesian search engine (SEBI), the provision of cross-language tourism news retrieval is realized using the Google Translate API, which translates the Query and all documents into English, Porter's stemming technique to convert each term to its general form, and cosine similarity to calculate similarity. This approach can deliver cross-language tourism news instantly while increasing the precision and efficiency of the SEBI search engine, although some improvements are needed to provide a more precise and efficient similarity computation.
Classification of Organic and Inorganic Waste Types Based on Neural Networks Arifin, Fatchul; Habiburrahman, M.; Gusti, Wahyu Ramadhani
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.v8i1.53284

Abstract

Garbage is the   residue of unused industrial production and household consumption. In Indonesia, waste is divided into 2 types, namely organic and inorganic waste. The two types of waste can be recycled in diverse ways, so they must be separated. So far, it is often difficult for the community to sort waste. This paper presents the process of recognizing and sorting waste automatically by utilizing Artificial Intelligence technology, especially Artificial Neural Networks (ANN). The ANN architecture used in this study consists of 4 layers. The number of neurons in each layer consists of 3 neurons in the input layer, 4 neurons in the hidden layer-1, 4 neurons in the hidden layer-2 and 1 neuron in the output layer. The ANN model that has been designed is trained, so that the best weight and bias model will be obtained, which in turn gives the ANN the ability to be able to sort waste properly. The best weights and biases will then be implanted into the Arduino UNO Microcontroller hardware. In this developed system, the microcontroller is given input obtained from 3 kinds of sensors, namely capacitive proximity, inductive proximity, and photodiode. While the input consists of 2 pieces of organic or in organic waste conditions. From the test results, it was found that the system has 100% training accuracy and 100% test accuracy.  
Comparison of Support Vector Machine (SVM), K-Nearest Neighbor (K-NN), and Stochastic Gradient Descent (SGD) for Classifying Corn Leaf Disease based on Histogram of Oriented Gradients (HOG) Feature Extraction Solihin, Firdaus; Syarief, Muhammad; Rochman, Eka Mala Sari; Rachmad, Aeri
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.v8i1.55759

Abstract

Image classification involves categorizing an image's pixels into specific classes based on their unique characteristics. It has diverse applications in everyday life. One such application is the classification of diseases on corn leaves. Corn is a widely consumed staple food in Indonesia, and healthy corn plants are crucial for meeting market demands. Currently, disease identification in corn plants relies on manual checks, which are time-consuming and less effective. This research aims to automate disease identification on corn leaves using the Support Vector Machine (SVM), K-Nearest Neighbor (K-NN) with K=2, and Stochastic Gradient Descent (SGD) algorithms. The classification process utilizes the Histogram of Oriented Gradients (HOG) feature extraction method with a dataset of corn leaf images. The classification results achieved an accuracy of 71.44%, AUC of 79.16%, precision of 70.08%, recall of 71.44%, and f1 score of 67.11%. The highest accuracy was obtained by combining HOG feature extraction with the SGD algorithm.
Development of a Conveyor-Based Practice Performance Assessment Tool with Android Control to Improve Vocational High School Students' Work Readiness Ghozali, Fanani Arief; Tentama, Fatwa; Sudarsono, Bambang; Syamsuddin, Arief; Setyanto, Barry Nur; Bhakti, Wirayudha Pramana
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.v8i1.57868

Abstract

The unemployment rate for vocational high school graduates is still very high. Unemployment occurs because the level of work readiness is still low. Work readiness can be improved by applying competence mastery-oriented learning. Competence that is complete requires measurement tools or assessment of student work competencies to measure competency success. Therefore, this study aims to: (1) produce a product in the form of a practical performance assessment tool for students in the conveyor-based pandemic era with android control; (2) know the quality and performance of the developed tools; This research is development research using the method of combining the waterfall method and Borg & Gall. This research focuses on product functionality so that testing is carried out by technicians with input from experts from the industry. The research data were obtained from observations, interviews, document studies, and questionnaires. The results of this study are as follows: (1) the product developed already has basic functions and can be operated using Android; (2) the results of testing by technicians from the aspects of functionality, reliability, efficiency, maintainability, and portability obtained a conformity percentage of 90% (Very Good), so that the tool can be used to test student work readiness in vocational schools or training institutions.
Soybean Collect Recommender Based on Distance and Productivity Cluster Using K-means Clustering and Simple Addictive Weighting Method Ningtyas, Mega Wahyu; Pribadi, Feddy Setio
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.v8i1.53208

Abstract

Soybeans are an essential agricultural product that is one of the primary food sources in Indonesia, such as tempeh, tofu, soy milk, soy sauce, and other preparations. However, production yields, harvested land area, and soybean productivity in each district or city in Central Java Province vary widely. Differences in soybean productivity in each area are due to production factors such as area, use of fertilizers, seeds, and labor. This study tries to provide recommendations for soybean harvesting based on the distance and productivity of an area using K-means clustering and the simple addictive weighting method. In the Central Java Province, 35 regions will be divided into four clusters: the first with high productivity, the second with medium productivity; the third with low productivity; and the fourth with very low productivity. Additionally, based on the fourth cluster clustering results, it will be advised to take soybeans from other clusters by taking the closest distance and cluster members into account. According to the research, four clusters have formed: the first has five members, the second has fourteen, the third has nine, and the fourth has seven. The fourth cluster, which consists of seven members who do not grow soybeans, is advised to buy soybeans from the following regions: Kendal Regency, Klaten Regency, Magelang Regency, Batang Regency, and Brebes Regency.

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