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Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI)
Published by Universitas Pendidikan Ganesha
ISSN : 20898673     EISSN : 25484265     DOI : -
Core Subject : Science, Education, Engineering,
Computer Science & IT Education Engineering
Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) is a collection of scientific articles in the field of Informatics / ICT Education widely and the field of Information Technology, published and managed by Jurusan Pendidikan Teknik Informatika, Fakultas Teknik dan Kejuruan, Universitas Pendidikan Ganesha. JANAPATI first published in 2012 and will be published three times a year in March, July, and December. This journal is expected to bridge the gap between understanding the latest research Informatika. In addition, this journal can be a place to communicate and enhance cooperation among researchers and practitioners.
Arjuna Subject : -
Articles 17 Documents
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Search results for , issue "Vol. 12 No. 1 (2023)" : 17 Documents clear
Decision Support System to Determine The Price of Used Computer Based On Specification and Usage Duration Using Fuzzy Logic Anik Vega Vitianingsih; Ravino Rahman; Anastasia Lidya Maukar; Litafira Syahadiyanti; Seftin Fitri Ana Wati
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 12 No. 1 (2023)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v12i1.51547

Abstract

Using computers at work or others has many positive impacts, including a special program that simplifies data and media processing. Certain software applications will, for some time, require high computer specifications. Many people have computers and want to fulfill the application requirements by selling computers to upgrade the specifications. However, some people are not very knowledgeable about calculating the cost of a used computer. One of the things that are done to make it easier for users to determine the price of a used computer is to create a decision support system that will assist in determining the price of a used computer based on specifications and usage duration. The Fuzzy Logic method was used in this study by comparing the accuracy results of the Fuzzy Mamdani and Sugeno methods. The parameters are based on the purchase price of all computer components, including Processor, Motherboard, RAM, SSD, HDD, VGA, PSU, and Case and usage duration. Fuzzy Mamdani is proven to have a higher accuracy with a value of 71% when compared to Fuzzy Sugeno. Based on measurement findings and a comparison of the methods used. Therefore, Fuzzy Mamdani is recommended for future studies using the same parameters. The benefits of this research include a recommendation system that will make it simpler for the general public to determine the selling price of used computers based on their specifications and usage duration. Another advantage is that it makes it easier for the general population to become a reference when buying or selling used computers, mainly assembled computers.
Educational Game for Learning Computational Thinking in a Low Budget Virtual Reality Environment Sukirman Sukirman; Dias Aziz Pramudita; Abdylla Adhiyasa Nugroho; Muhammad Rizky Aminudin
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 12 No. 1 (2023)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v12i1.52743

Abstract

Virtual reality (VR) is a technology that can create a simulation of real objects in a virtual environment more interactively. In terms of budget, VR devices can be categorized into low budget and high end. However, both of them can still carry out the same interactive simulations, such as educational games. This research aims to develop an educational game based in low-budget VR environment for learning computational thinking (CT), one of the 21st century skills that students need to learn. The method used is Design and Development Research (DDR) that consists of five stages: analysis, design, development, testing, and evaluation. Participants involved in this study are 30 students of vocational school (SMK) majoring Computer and Network Engineering. Evaluation conducted through Technology Acceptance Model (TAM) framework that consists of perceived usefulness (PU), perceived ease of use (PEU), attitude toward using (ATU), and intention to use (ITU). Based on the data obtained and the analysis performed, the Cronbach’s alpha score of PU and PEU were 0.714 and 0.614, respectively. Meanwhile, the Cronbach’s alpha score of ATU and ITU were 0.754 and 0.882, respectively. PU and PEU are positively correlated with ATU, while ATU is also positively correlated with ITU. It means that the ease of use of the application and the usability aspects of the developed application have a positive effect on user attitudes. This positive behavior is also positively correlated with the intention to use it again on another occasion. Thus it can be concluded that this educational game based in low-budget VR environment can be used for learning CT. It can be seen from the analysis and some positive comments from students, like participants wish they can use this learning approach in the other subject.
Mobilenet-based Transfer Learning for Detection of Eucalyptus Pellita Diseases Deviana Sely Wita; Agus Subekti
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 12 No. 1 (2023)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v12i1.53220

Abstract

Currently, the pulp industry in Indonesia is ranked eighth in the world and the paper industry is ranked sixth in the world. One of the advantages in supporting the industry is that Indonesia has a large Industrial Plantation Forest (HTI) where the plants for pulp and paper raw materials originate. Eucalyptus pellita species belonging to the Myrtaceae family is one of the priority species for Industrial Plantation Forests (HTI) because of its adaptability and its wood can be used as raw material for pulp. Industrial Plantation Forests of this type can be found mainly in Kalimantan and Sumatra. This species shows good growth in stem shape, growth speed and good wood quality and has high germination and has a shorter cutting cycle of about 7-8 years so that it is quickly harvested. Prevention and treatment of leaf disease is one of the main processes of planting. Early diagnosis and accurate recognition of Eucalyptus Pellita disease can control the spread of the disease and reduce production costs and treatment costs. Disease detection on Eucalyptus pellita leaves can be done automatically faster by utilizing digital image processing and artificial intelligence. In this study, we propose a detection method with Deep Learning architecture. Our proposed method is based on pre-trained transfer learning using MobileNet. Image datasets from PT. Surya Hutani Jaya's land in East Kalimantan were used to train the model. The dataset is divided into three classes where 1 class is healthy leaves and 2 classes are sick leaves, namely Xanthomonas Bacteria and Cylindrocladium Fungi. With a dataset ratio of 70: 20: 10 the number of training datasets is 2370, validation is 591, and Testing is 177. Hyperparameter scenarios were carried out on the MobileNet model to optimize performance on the Eucalyptus Pellita leaf dataset. The experimental results show a fairly good accuracy, reaching 98%.
Factors Affecting the Adoption of Artificial Intelligence Voice Control Technology: A Case Study of Xiaomi Smart Devices Punyanut Traiyatha; Jiroj Buranasiri
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 12 No. 1 (2023)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v12i1.53524

Abstract

The research aims to examine the factors influencing the adoption of artificial intelligence voice control technology. The purposive sampling technique was applied to collect the sample of 400 people who had experience in using Xiaomi smart device. The online questionnaire is the instrument for data collection. Descriptive statistics are used to analyze the respondents’ characteristic. The inferential statistics include Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM) are applied to disclose the impact of utilitarian benefits, hedonic benefits, symbolic benefits, social presence, and social attraction on the adoption of artificial intelligence voice control technology. The results of this research can be used to improve the voice command technology for future users. Additionally, the study’s report can be used for developing voice control systems in smart devices for other business enterprises. Subsequently, the users’ concern about the risk of using voice commands would subside and this technology would be widely accepted. 
Design Thinking Approach in The Development of Cirgeo's World Media Made Juniantari; Saida Ulfa; Henry Praherdhiono
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 12 No. 1 (2023)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v12i1.55203

Abstract

The circle concept is one of the contents in mathematics that has high complexity and is still a problem in visualization and concept exploration. This study aims to develop interactive digital media on circular material based on material characteristics, learning styles, user needs, and ease of learning in various contexts which are hereinafter named Cirgeo's World media. Media Cirgeo's World was developed using the design thinking method which has five stages, namely: 1) recognize and empathize; 2) defined; 3) ideate; 4) prototypes, and; 5) tests. Based on user responses obtained using questionnaires, the results obtained are that Cirgeo's World media is able to provide convenience for users in understanding learning objectives, learning by accommodating diverse learning styles, exploring abstract concepts more dynamically, measuring learning progress, and can be directly operated on the user's smartphone. From the results of user responses, it was also found that there were still things that were not optimal in Cirgeo's World media, namely in the user's ease of understanding the instructions for using the media. This can be followed up by improving things related to the instructions for using media that are easily accessible to users based on the results of interviews with users.
Quality Analysis of Service Load Balancing Using PCC, ECMP, and NTH Methods Kurnianto Tri Nugroho; Bagus Julianto; Dhodit Rengga Tisna; Danny Febryan Nur M S
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 12 No. 1 (2023)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v12i1.55894

Abstract

One of the solutions to get a better quality of internet service is to utilize load balancing technology. We can use more than one different ISP (Internet Service Provider) which is then balanced with load balancing technology, where this technique is used to distribute the traffic load on two or more connection lines in a balanced way so that traffic can run optimally, maximizing throughput, minimizing response time. and avoid overload on any of the connection lines. This study aims to determine the comparison of Quality of Service load balancing with the PCC, ECMP and NTH methods on Mikrotik. The test method uses the web application www.speedtest.cbn.id, www.fast.com (1 connection), the results will show ping, download speed, upload speed, and monitoring from the Mikrotik router side. The research stages used the Network Development Life Cycle method, namely analysis, design, prototype simulation, implementation, monitoring and management. The results of the research are in the form of a performance comparison between load balancing on 2 internet lines using the PCC, ECMP and NTH methods on the proxy router. Based on the tests carried out as a whole the load balance using the ECMP method is superior and more reliable in terms of failover effects.
Domain Analysis and Audit of IT Governance Based On COBIT 5 at Denpasar Industrial Training Center I Made Artana; Nyoman Putra Sastra; Dewa Made Wiharta
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 12 No. 1 (2023)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v12i1.55989

Abstract

Information technology has become a key element of organizations and one of institutions’ added value and competitive advantages. Therefore, IT must be properly managed and measured. Denpasar Industrial Training Center (BDI) has implemented the IT Governance Education and Training Information System, SISDIKLAT. These applications have never been evaluated from an IT governance perspective. This study aimed to determine domains and assess SISDIKLAT using methods relevant to COBIT 5. To assist the organization in focusing on its main objectives and strategies, a tailored governance system based on the specificities of SISDIKLAT is required. This research assist BDI Denpasar in establishing healthy governance and IT management by utilizing the COBIT 5 framework. Both qualitative and quantitative approaches are used to select relevant governance/management objectives. Four domains and nine subdomains were chosen based on the domain analysis. According to the assessment results, the capability value of each subdomain was 2--3, with a gap value of 0.2--0.8. To reach the target level, the nine subdomains were advised.
Demand Forecasting for Improved Inventory Management in Small and Medium-Sized Businesses Dian Indri Purnamasari; Vynska Amalia Permadi; Asep Saepudin; Riza Prapascatama Agusdin
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 12 No. 1 (2023)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v12i1.57144

Abstract

Small and medium-sized businesses are constantly seeking new methods to increase productivity across all service areas in response to increasing consumer demand. Research has shown that inventory management significantly affects regular operations, particularly in providing the best customer relationship management (CRM) service. Demand forecasting is a popular inventory management solution that many businesses are interested in because of its impact on day-to-day operations. However, no single forecasting approach outperforms under all scenarios, so examining the data and its properties first is necessary for modeling the most accurate forecasts. This study provides a preliminary comparative analysis of three different machine learning approaches and two classic projection methods for demand forecasting in small and medium-sized leathercraft businesses. First, using K-means clustering, we attempted to group products into three clusters based on the similarity of product characteristics, using the elbow method's hyperparameter tuning. This step was conducted to summarize the data and represent various products into several categories obtained from the clustering results. Our findings show that machine learning algorithms outperform classic statistical approaches, particularly the ensemble learner XGB, which had the least RMSE and MAPE scores, at 55.77 and 41.18, respectively. In the future, these results can be utilized and tested against real-world business activities to help managers create precise inventory management strategies that can increase productivity across all service areas.
Development of Non-Intrusive Low-Power Digital Water Meter Reading System Based On Wireless Mesh Network and Internet of Things Rifki Muhendra
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 12 No. 1 (2023)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v12i1.57180

Abstract

The application of WMN and IoT technology to the metering infrastructure is proven to provide convenience in data collection, access to information, and management of metering devices. Unfortunately, the use of this technology is still minimal in developing countries like Indonesia. In this study, the development of a digital meter reading system that focuses on low-power non-intrusive reading devices and the application of WMS in the water meter reading system is carried out. This system consists of a series of meter reader sensors that are connected mesh to a gateway where meter data can be monitored in real-time and remotely. This sensor circuit is an integrated circuit added to the existing mechanical water meter which allows recording the volume of water consumption digitally. This circuit consists of an optical sensor, real-time clock (RTC), microcontroller, Lora Transmitter, and power supply. The use of solar cells to supply energy for meter reading devices is another interesting aspect of the development of this system. A gateway is a circuit built to bridge the transmission of meter data from a radio-based sensor network to the internet. The result of this research is the establishment of a meter reading system capable of accurately reading water consumption, low power where the meter data is easily accessible using a device connected to the internet. This system has been evaluated for every part of development such as reading water consumption, power consumption, and also communication in the mesh network. The contribution of this research is that it can be used as a reference for developing a digital meter system that is more effective, has low power, and has easy access to meter data
Effect of Word2Vec Weighting with CNN-BiLSTM Model on Emotion Classification Merinda Lestandy; Abdurrahim
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 12 No. 1 (2023)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v12i1.58571

Abstract

Emotion is an element that can influence human behavior, which in turn influences a decision. Human emotion detection is useful in many areas, including the social environment and product quality. To evaluate and categorize emotions derived from text, a method is required. As a result, the CNN-BiLSTM model, a classification method, aids in the analysis of the text's emotional content. A word weighting technique employing word2vec as a word weighting will help the model. The CNN-BiLSTM model with Word2vec as a pre-trained model is being used in this study to find the findings with the highest accuracy. The information is split into two groups: training and testing, and it is categorized into six categories according to how each emotion manifests itself: surprise, sadness, rage, fear, love, and joy. The best outcome from the CNN-BiLSTM model's accuracy of emotion classification is 92.85%.

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