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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 15 Documents
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Search results for , issue "Vol. 8 No. 2 (2023): November 2023" : 15 Documents clear
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.
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.
Visitor Decision System in Selection of Tourist Sites Based on Hybrid of Chi-Square And K-NN Methods Anamisa, Devie Rosa; Mufarroha, Fifin Ayu; Jauhari, Achmad
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.v8i2.55702

Abstract

Madura Island is one of the islands with a lot of tourism spread over four districts, such as natural, religious, and cultural tourism. And every year, various visitors visit various tourist sites in Madura, so an increase in the number of visitors has been found in multiple places. This is influenced in addition to the type of tourist attraction but also changes in tourist behavior in making decisions to visit tourist objects. Most of the researchers have applied the right decision-making with intelligence-based measurement. However, the accuracy obtained has not yet reached the optimal solution. Therefore, this study uses the Chi-Square and K-Nearest Neighbors (K-NN) methods to recommend tourist attraction locations based on visitor characteristics to increase visitor attractiveness in tourist attractions scattered in Bangkalan, Madura. Chi-Square is used to select features that affect tourist attraction visitor factors by testing the relationship between the variables involved. Meanwhile, K-NN is a method of classifying potential visitor attractions based on their characteristics by using the closest membership calculation, which is the largest from the test data. The calculation is carried out by the square of the Euclidian distance from each object, then sorted from the smallest to the largest value and looking for the value of k as the result of the decision. There are ten features used in the classification, such as tourism type, management services, facilities, gender, age, occupation, education, visitor status, ticket prices, and sales trends. There are three classes classified: low, medium, and high visitor attractiveness. The contribution of this study is to analyze the effect of the characteristics of tourist attraction visitors on increasing visitor attractiveness using the chi-square and K-NN methods. Based on the results of system testing using K-Fold Cross Validation with five folds from 315 datasets, it produces the highest accuracy at k-fold = 3 worth 84.12% with eight selected features.
LoRA Gateway Coverage and Capacity Analysis for Supporting Monitoring Passive Infrastructure Fiber Optic in Urban Area Enriko, I Ketut Agung; Gustiyana, Fikri Nizar; Giri, Gede Chandrayana
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.v8i2.59280

Abstract

In the era of digital transformation, telecommunications infrastructure has become the backbone of global connectivity. Optical Distribution Cabinet (ODC) is a crucial part of an optical network that distributes signals to various points in the network. Maintenance and monitoring of ODCs have become essential to ensure optimal availability and performance. However, conventional approaches are often expensive and difficult to implement. The objective of this study is to develop a LoRaWAN network with the purpose of determining the required number of gateways. Additionally, the research aims to devise an IoT-basedODC device monitoring system within the FTTH network, utilizing data from PT. Telkom Witel Bandung. The approach involves employing simulation techniques through the Atoll apps v 3.40. Multiple calculation stages are applied to expect RSSI and SINR parameters within an area spanning 188.96 km². The study employs a frequency of 920 MHz, a bandwidth of 125 kHz, and a spreading factor of 10. The data analysis includes RSSI and SINR signals. As a result of calculations and planning simulations, this study recommended the use of nine gateways and achieved an RSSI parameter of -70. 35 dBm and a SINR parameter of 17. 33 dBm.
The Determination of A Place of Popular Tourism on The Island of Madura Using Weighted Product (WP) Putro, Sigit Susanto; Rochman, Eka Malasari; Rachmad, Aery
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.v8i2.55693

Abstract

This research explored the diverse aspects of Madura Island, including its cultural, societal, and touristic facets. The primary focus was on developing a recommendation system to identify Madura's most popular tourist destinations. Utilizing the Weighted Product (WP) method, a decision support system model, this study assessed the popularity of various tourist attractions in Madura, aiding tourists in selecting destinations through a multi-criteria weighting process. Key parameters included the number of both foreign and local visitors, proximity to the city center, and visitor ratings. The study encompassed 62 tourist sites across four districts in Madura, evaluating the most popular attractions in each. Findings revealed the top destinations in each district: Bangkalan featured Makam Syeichona Cholil (preference value: 0.113), Sampang showcased Hutan Kera Nepa (0.127), Pamekasan highlighted Batu Ampar (0.171), and Sumenep was known for Makam Asta Tinggi (0.076). This research offered valuable insights for both tourists and stakeholders in the tourism industry of Madura Island.
Using Discovery Learning and Problem-Based Learning to Increase Students' Motivation for Accomplishment Suhada, Sitti; Sunardi, Sunardi; Amali, Lanto Ningrayati; Katili, Muhammad Rifai; Lahinta, Agus; Kilo, Juriah R.
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.v8i2.58612

Abstract

According to initial observations made during the Basics of Computer Network Engineering and Telecommunications course in class X at TKJ SMK Negeri 5 Gorontalo, students were generally still passive and did not participate much in their education, preferring to listen to what their teachers said. This research aims to analyse: (1) the influence of the Problem Based Learning model on students' achievement motivation; (2) the influence of the Discovery learning model on students' achievement motivation; and (3) differences in achievement motivation between classes treated with Problem Based Learning. This study used a Non-equivalent Control Group Design research design in conjunction with a Quantitative Quasi-Experimental research method. This design consists of two groups that are not randomly selected, then given a pre-test to find out whether there are differences between the experimental group and the control group. The analytical test tool used in testing this research is the Paired Sample T-test with the following test results: (1) The Problem Based Learning model influences students' achievement motivation as indicated by the Sig value; (2) the Discovery Learning model influences students' achievement motivation as indicated by the Sig value (2-tailed) of 0.000 < 0.05. These results show that there are differences in the average achievement motivation of students in classes given the Discovery Learning model; and (3) Apart from that, the independent t test showed that there was no difference in achievement motivation between classes given the Problem Based Learning model and classes given the Discovery Learning model.
Implementation of FDSS (Fuzzy Decision Support System) Sugeno Model in Optimizing Bandwidth Requirement Management of Web-Based Networks Lahiya, Indah Wardati; Arifin, Fatchul
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.v8i2.57557

Abstract

To increase the efficacy of bandwidth allocation at PT. Digdaya Monokrom Group, this study describes the development of a Fuzzy Decision Support System (FDSS) utilizing the Sugeno methodology. The Waterfall development process is employed for the purposes of system planning, construction, and maintenance. The study consists of three primary stages: the creation of fuzzy sets, the development of fuzzy rules, and the process of defuzzification. The study findings demonstrate that the utilization of FDSS has effectively improved the distribution of bandwidth. The distribution has shifted from a uniform one to a more optimized allocation, focusing on the Execution, Content Creator, Administration, and Research Team departments. During a four-week monitoring period, modifications were implemented to distribute bandwidth based on the preferences and needs of various departments, while adhering to the limitations of the current broadband subscription. This has enhanced the efficient exploitation of network resources. The research findings highlight the efficacy of FDSS in prioritizing resource allocations according to specific departmental requirements, consequently improving service quality and maximizing bandwidth subscription capacity. This demonstrates the implementation of strategic management methodologies to optimize the allocation of network resources, resulting in enhanced organizational efficiency and production.
Machine Learning System Implementation of Education Podcast Recommendations on Spotify Applications Using Content-Based Filtering and TF-IDF Raharjo, Muhammad Mukti; Arifin, Fatchul
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.v8i2.58014

Abstract

Spotify, this popular music and podcast streaming service, has a fundamental problem in assisting clients in finding podcasts that fit their interests. Thus, the goal of this project is to develop a podcast recommendation system that would enhance users' capacity to identify pertinent content, particularly in the educational genre. By using content-based filtration techniques, this system analyzes the user's listening preferences and interests before recommending educational podcasts. The podcast data source is Spotify, and the suggestions are produced using the TF-IDF and Cosine Similarity techniques. The recommendations provide a list of educational podcasts catered to the user's specific interests. The Confusion Matrix Classification Report was tested to assess system performance during the review phase. Precision values show how accurate the system was at recommending educational podcasts; on average, they range from 0.52 to 0.74. Additionally, the recall value showed a mean of 0.51 and a mean of 0.79, indicating that the algorithm successfully located the relevant content. To put it briefly, this custom recommendation engine enhances the listening experience for Spotify customers by suggesting educational podcasts based on their preferences. The system's ability to match users with material that aligns with their interests was demonstrated by the metrics used to assess its performance. With more user interactions with the system, it was anticipated by Cosine Similarity, a statistic used to determine the quality of recommendations, will continue to improve. To improve user experience and personalize the podcast listening experience on Spotify, this research addresses the challenge of locating suitable podcasts.
Design and Development of Industrial Practice Monitoring and Assessment Systems using Tsukamoto Fuzzy Logic Pahtoni, Tri Yuli; Arifin, Fatchul
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.v8i2.57669

Abstract

Vocational high schools are given flexibility for their students to carry out direct learning in the industry as part of the practical education activities of implementing student skills. The implementation of industrial practice requires a special way to find out and monitor each student's activities so that the achievements of the implementation of industrial practice can be carried out properly.  The implementation of industrial work practice assessment has several assessment criteria. These criteria include attendance, neatness, attitude, skills, and knowledge. The problems found in the assessment system are still done manually so that the effectiveness is minimal. This study aims to create a system that can monitor and assess the implementation of industrial practices.  The system developed will be tested as a medium for monitoring and assessing industrial practices.  This research uses Fuzzy Tsukamoto's logic approach as a scoring logic  model and  uses the waterfall method as a development model consisting of analysis, design, coding, and testing. The results of the research conducted resulted in a system that can monitor and assess the implementation of industry practices.  The test was carried out by 24 people consisting of guidance teachers and students. Testing is done by testing aspects of functionality and aspects of usability. Based on the test results, the functionality aspect scored 100% (very feasible) and the usage aspect got a score of 84.8% (very feasible)
Decision Support System for Major Selection in Higher Education for Multimedia Graduate Students using Fuzzy Mamdani Logic Fauziah, Khasna Nur; Arifin, Fatchul
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.v8i2.57643

Abstract

Students at the vocational high school level are indeed prepared to be able to work directly, but it does not rule out the possibility that vocational high school students can continue higher education such as universities. But the problem that will be faced again if students who graduate from vocational high schools choose to continue their education in college is what major they will take. One of the vocational high school majors, namely Multimedia, has a wide scope, so grade 3 vocational high school students who want to go to college have a dilemma in deciding on a major. This research applies the fuzzy logic mamdani to help make decisions for majors in higher education. This study is based on 5 input parameters, namely Komputer dan Jaringan Dasar, Desain Grafis Percetakan, Dasar Desain Grafis, Teknik Audio Visual, and Animasi. There are outputs of 5 majors in Teknik Komputer, Desain Komunikasi Visual, Animasi, TV dan Film, and Fotografi. The results of this research can make it easier and can provide support for grade 3 vocational high school students, especially the Multimedia department in choosing a major in higher education. The results of the decision support system with the highest student score data in Animasi will appear a recommendation score of 79.8 in the Animasi department, and on the highest student score data on the Komputer dan Jaringan Dasar, a recommendation score of 79.8 will appear in the Teknik Komputer major in accordance with the major taken and lived by the current student.

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