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YoBagi's User Experience Evaluation using User Experience Questionnaire 7

YoBagi's User Experience Evaluation using User Experience Qu...

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7th International Conference on Informatics and Computing, ICIC 2022

作者： Juniawan, Fransiskus Panca Sylfania, Dwi Yuny Putra, Rendy Rian Chrisna Henderi Program Study of Technology Information University of Bangka Belitung Pangkalpinang Indonesia Program Study of Informatics Engineering Institut Sains Dan Bisnis Atma Luhur Pangkalpinang Indonesia University of Raharja Informatics Engineering Faculty of Science and Technology Tangerang Indonesia

ISBN: (纸本)9798350345711

The pandemic has brought many negative impacts on human life. One of the negative impacts is economic downturn of Micro, Small, and Medium Enterprise (MSME) actors in Bangka Belitung Province. To solve this problem, a website-based marketplace platform called Yobagi was created. As we know, a new software product must have a good user experience. By having a good user experience means that the product has met the needs of its users. For this reason, an evaluation of the user experience is necessary. This study aims to measure the user experience of using Yobagi. The evaluation uses the User Experience Questionnaire (UEQ) tool, which consists of six scales: Attractiveness, Efficiency, Perspicuity, Dependability, Stimulation, and Novelty. There were 40 respondents who were taken from the top of MSME actors. As the UX evaluation results, it is known that the final score of the six scales is above 0.8 and at the excellent level. This means that Yobagi users have a very good user experience in using Yobagi. In addition, Yobagi has met the criteria for good software by having an excellent user experience value. © 2022 IEEE.

关键词： User experience

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Defect Detection of Agricultural Commodities using Image Processing and Artificial Neural Networks

Defect Detection of Agricultural Commodities using Image Pro...

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2022 International Seminar on Application for Technology of Information and Communication, iSemantic 2022

作者： Suprijono, Herwin Kartikadarma, Etika Yusianto, Rindra Marimin, Marimin Dian Nuswantoro University Faculty of Engineering Department of Electrical Engineering Semarang53192 Indonesia Dian Nuswantoro University Study Program of Information Technology Faculty of Computer Science Semarang53192 Indonesia Dian Nuswantoro University Faculty of Engineering Department of Industrial Engineering Semarang53192 Indonesia Faculty of Agricultural Engineering and Technology Department of Agro-Industrial Technology West Java Bogor16002 Indonesia

ISBN: (数字)9781665488396

ISBN: (纸本)9781665488396

Production losses of agricultural commodities on agricultural land due to product defects depend on the level of pest and disease attacks. Defects cause the product not to be harvested or rejected by the market. Data from the Ministry of Agriculture of the Republic of Indonesia in 2021 shows the percentage of defective products for this commodity is 5%. This study aims to detect defects in agricultural products using image processing and artificial neural networks. We used the screening threshold method with potato research samples from Dieng, Indonesia. The study results for spot defects showed that from 100 training data, there were five incorrect identification data, so the accuracy of the training process was 95%. At the same time, the hole defect accuracy is better, which is 97%. It shows that defects in agricultural commodities can be detected using this method. For further research, the development of agricultural product sorting can combine sorting techniques with this method. © 2022 IEEE.

关键词： Defects

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Development of Support Vector Machine Method to Forecast Dengue-Endemic Areas

Development of Support Vector Machine Method to Forecast Den...

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2023 International Conference on Informatics, Multimedia, Cyber and Information Systems, ICIMCIS 2023

作者： Meileni, Hetty Ermatita Abdiansah Husni, Nyayu Latifah Desmawati Doctoral Program in Engineering Science Palembang30139 Indonesia Universitas Sriwijaya Faculty of Computer Science Palembang30139 Indonesia Palembang30139 Indonesia Politeknik Negeri Sriwijaya Palembang Department of Electrical Engineering Palembang30139 Indonesia Universitas Pembangunan Nasional Veteran Jakarta Faculty of Health Science Jakarta12450 Indonesia

ISBN: (纸本)9798350307306

The cases of dengue hemorrhagic fever (DHF) in Indonesia have increased significantly since 2020. Data shown by the Central Statistics Agency, for example, in South Sumatra Province, there were 6,348 cases of DHF during that period. To suppress the case number of DHF, forecasting areas that are susceptible to this disease is urgently needed. This research aims to develop a machine learning method Support Vector Machine (SVM). The data used include area data, population density data, weather data, and dengue fever case data. The development of the SVM model is carried out using a machine learning method that combines regional data, population density data, weather data, and dengue case data. In the end, using the SVM method can be used to forecast dengue-endemic areas, so that the government and society can take further action to reduce the negative impact of DHF. © 2023 IEEE.

关键词： Forecasting

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Interconnected Through Robotic System in English Foreign Language Education 5th

Interconnected Through Robotic System in English Foreign Lan...

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5th International Conference on Advances in Information Communication Technology and Computing, AICTC 2024

作者： Muthmainnah, M. de Barros Cardoso, Luís Miguel Oliveira Kaur, Dalwinder Burhamzah, Muftihaturrahmah Aeni, Nur Al Yakin, Ahmad Sharma, Aditi Teacher Training and Education Faculty Indonesian Language Study Program Universitas Al Asyariah Mandar Polewali Mandar Indonesia Portugal Department of Languages and Communication Sciences Polytechnic Institute of Portalegre Portalegre Portugal Manipal Globalnxt University Kuala Lumpur Malaysia English Study Program Universitas Negeri Makassar Makassar Indonesia Teacher Training and Education Faculty Civic Education Study Program Universitas Al Asyariah Mandar Polewali Mandar Indonesia Department of Computer Science and Engineering Symbiosis Institute of Technology Symbiosis International [Deemed University Pune India

ISBN: (纸本)9789819761050

Robots have become increasingly important in a variety of life domains as a result of the rapid advancement of technology. Additionally, robots are employed in education as teaching assistants in science, art, and language courses. This research aims to explore the potential of robotic systems as a multipurpose tool for increasing cultural awareness, language proficiency, and communicative competence in the GenAI era. Language games, conversation simulations, and real-time feedback mechanisms are just a few examples of interactive scenarios enabled by virtual robot systems or tutor robots that enable immersive language experiences that go beyond the limitations of conventional schooling. This research contributes knowledge that explores how AI can be used to personalize language teaching according to the needs and learning styles of each student in higher education. The total population of undergraduate students involved in this research was 350 for the 2023 academic year, with 24 students selected purposefully based on sample characteristics from this group who were exposed to using AI for one semester. The research method used is a mix method with quantitative analysis of the results of surveys and interviews with students who are known to have given positive responses and proposes a comprehensive strategy for using AI robot technology in EFL classrooms, which can significantly improve effective learning outcomes. The survey results also show that if educators have a solid understanding of the relationship between linguistic acquisition and technological advances, they will be better prepared to design engaging, individualized lessons that prepare their students to use the language effectively in real-world contexts. The robot-assisted language learning (RALL) approach used in this study, with the integration of robots in the classroom, has the potential to change the way people learn languages to make it more interesting, fun, and motivating, increase engagement

关键词： Students

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Impact of Multimedia Sensor Placement to Car Licence Number Detection 2022

Impact of Multimedia Sensor Placement to Car Licence Number ...

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11th International Conference on Software and Computer Applications, ICSCA 2022

作者： Amelia, Afritha Zarlis, Muhammad Suherman, Suherman Efendi, Syahril Graduate Program of Computer Science Faculty of Computer Science and Information Technology University of Sumatera Utara Indonesia Computer Science Faculty of Computer Science and Information Technology University of Sumatera Utara Indonesia Electrical Engineering Faculty of Engineering University of Sumatera Utara Indonesia

ISBN: (纸本)9781450385770

A vehicle has a license plate and can be identified by the license number attached to the vehicle plate. For detection and recognition, multimedia sensors can be used so that it requires a vehicle tracking application that has a vehicle monitoring function and has implications for various fields. One of them is a multimedia sensor that requires an optimal design and method in the form of the number of multimedia sensors to be used, the placement of the multimedia sensor positions and solutions in the event of a system failure. To achieve multimedia sensor performance, research on multimedia sensors is carried out using a camera type with Phase Detection Auto Focus (PDAF) technology which is similar to a pair of right and left eyes to see an object. The objects detected were 2 cars, where the car passed the camera sensor at a speed of 10-15 km/hour 20 times. Changes in the distance of the vehicle to the camera affect the disparity value and the object's accuracy value, namely and the object's Accuracy value of the minimum disparity value of 6.20×106 of 16.88×109. © 2022 ACM.

关键词： Disparity Vehicle plate Phase Detection Auto Focus (PDAF) Tracking application Object accuracy

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A Dynamic Model for Pauses in the Synthesized Speech of Mathematical Expressions in MathML 14

A Dynamic Model for Pauses in the Synthesized Speech of Math...

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14th International Conference on Education Technology and Computers, ICETC 2022

作者： Souza, Adriana Freitas, Diamantino Bahia Federal Institute of Education Science and Technology Porto Seguro Bahia Brazil Doctoral Program in Digital Media Faculty of Engineering Faculty of Engineering of University of Porto Porto Portugal Department of Electrical and Computer Engineering Faculty of Engineering of University of Porto Porto Portugal

ISBN: (纸本)9781450397766

Voice synthesizers still present several challenges in the speech of mathematical content, as spoken mathematics has quite peculiar rules. In the synthesized speech, pauses help blind and visually impaired students identify the limits of mathematical operators and subexpressions. However, most studies on pauses define them uniformly or use simple punctuation marks to force the synthesizer to introduce pauses in certain parts of the expression. Speech is a dynamic process and pauses in expressions also need to be dynamic to make the synthetic speech of expressions more natural, as this can help in memorizing this type of content. This work proposed a dynamic model of pauses for mathematical expressions. Collected math expressions spoken by teachers were used to create the model. These expressions were useful for identifying patterns and creating a linear regression model. Blind and visually impaired students evaluated the model. Some improvements were observed when we compared the synthesized mathematical expressions with the model and Audiomath, the parameter tool used in this study. © 2022 ACM.

关键词： Dynamic models

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Salt Hash Password Using MD5 Combination for Dictionary Attack Protection 6

Salt Hash Password Using MD5 Combination for Dictionary Atta...

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6th International Conference on Computer and Informatics engineering, IC2IE 2023

作者： Nugroho, Agung Mantoro, Teddy The Republic of Indonesia Defense University Cyber Defense Engineering Study Program Sains and Defense Technology Faculty Bogor Indonesia Sampoerna University Media-Tech Lab Departement of Computer Science Jakarta Indonesia

ISBN: (纸本)9798350345162

Using MD5 hashing of passwords in web logins is highly vulnerable to dictionary attacks. One online application for cracking hashed passwords using a dictionary attack that is free and easy to use is ***. Even so, the use of hashing passwords using MD5 which has a low level of security is still commonly found to secure web login passwords. This research presents an increase in security through a combination of salt hash passwords when using MD5. The methodology of this study uses a quantitative experimental method to apply hash salt passwords using the MD5 combination. The password cracking test was carried out using the *** online hash cracking application on weak passwords such as 'admin' with the addition of a password hash salt using the MD5 combination. The results showed that Salt Password using the MD5 combination could not be cracked by *** using a dictionary attack. © 2023 IEEE.

关键词： dictionary attack md5 password hash salt

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Telematics and Its Multimedia Applications: A Bibliometric Evaluation Over the Last Two Decades and a Half 9

Telematics and Its Multimedia Applications: A Bibliometric E...

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9th International Conference on Wireless and Telematics, ICWT 2023

作者： Juhana, Agus Nurmalasari, Rin Rin Nurhidayatulloh, Nurhidayatulloh Anggraeni, Aprellia Padmasari, Ayung Candra Sari, Maya Purnama Universitas Pendidikan Indonesia Multimedia Education Study Program Bandung Indonesia Uin Sunan Gunung Djati Department of Electrical Engineering Bandung Indonesia Universitas Pendidikan Indonesia Faculty of Technology and Vocational Education Bandung Indonesia

ISBN: (纸本)9798350305029

The development of telematics technology is increasing rapidly and this capability is supported by multimedia devices or even telematics that supports the development of multimedia itself. For instance, in the configuration of telematics with websites to control air traffic with a voice communication system, multimedia applications serve as devices for monitoring the use of this technology. Consider the research trends, this study aims to evaluate the current development and trends of research on telematics and its multimedia applications through bibliometric analysis over the last two decades and a half (1999-2023). Several publication characteristics were analyzed, including the most cited articles in this field. This study uses data from the Scopus database to evaluate the productivity, impact, countries, research institutions, authors, and research performance of journals based on the impact factor, citation counts, and h-index. According to the result, the annual number of publications on this topic fluctuates but tends to increase, with Germany being the most prolific country producing articles in this field. Additionally, the most researched telematics and its multimedia applications and most cited lists offer insight into the future. This is the first study to use bibliometric analysis to evaluate research on telematics and its multimedia applications and is expected to be useful for telematics researchers by identifying potential research directions. In addition, this research serves as a valuable resource for future researchers and practitioners. However, improvements can be made by incorporating additional analysis, such as content analysis. © 2023 IEEE.

关键词： Telematics

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A Performance study of Selected Machine Learning Techniques for Predicting Heart Diseases 2nd

A Performance Study of Selected Machine Learning Techniques ...

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2nd International Conference on Security and Information Technologies with AI, Internet Computing and Big-data Applications, SITAIBA 2023

作者： Olorunfemi, Blessing Oluwatobi Ogunde, Adewale Opeoluwa Adeniyi, Abidemi Emmanuel Awotunde, Joseph Bamidele Imoize, Agbotiname Lucky Li, Chun-Ta Faculty of Natural Sciences Department of Computer Science Redeemer’s University Osun Nigeria Department of Computer Science Bowen University Iwo Nigeria Faculty of Information and Communication Sciences Department of Computer Science University of Ilorin Ilorin240003 Nigeria Faculty of Engineering Department of Electrical and Electronics Engineering University of Lagos Lagos Akoka100213 Nigeria Bachelor’s Program of Artificial Intelligence and Information Security Fu Jen Catholic University New Taipei City24206 Taiwan

ISBN: (纸本)9789819777853

Heart Disease remains a leading cause of mortality worldwide. It alarmingly rises at a quick rate, making early heart disease prediction crucial for effective prevention and timely intervention. Heart disease diagnosis is a difficult process that requires technical skills and accuracy to complete. With improvements in technology, computing has lent its voice to simplify the diagnosis of various health problems. Machine learning uses past or existing history to predict future results. Various machine learning techniques have been developed over the years and used in predicting heart diseases with various levels of performance. Identifying the best-suited machine learning technique to use for prediction purposes can be a challenging task. This research work analyses the performance of seven (7) machine learning techniques, comprising AdaBoost Algorithm, KNN, Logistic Regression, Naïve Bayes Classifier, Random Forest, SVM, and XGBoost. The heart disease dataset was downloaded from the UCI repository and analysed using Python programming language in the Jupyter Notebook environment. A comparative analysis of the seven (7) techniques was performed based on Accuracy, Precision, and Recall. From the results obtained, KNN, Random Forest, and XGBoost showed superior performance over the others with an accuracy of 100%, AdaBoost Algorithm followed with an accuracy of 92.2%, SVM followed with an accuracy of 91.71%, Naïve Bayes Classifier followed with an accuracy of 88.29% while Logistic Regression has the least accuracy of 86.34%. KNN, RF, and XGBoost outperformed AdaBoost, SVN, and LR. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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LoRa Network Design for Monitoring Landslides on 150 KV Delivery Tower

LoRa Network Design for Monitoring Landslides on 150 KV Deli...

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International Conference on Smart Computing & Communications (ICSCC)

作者： I Wayan Dikse Pancane I Putu Gelgel Astika Putra I Wayan Gede Suarjana Agus Supranartha Electrical Engineering Study Program Universitas Pendidikan Nasional Denpasar Indonesia Department of Public Health Faculty of Sport Science and Public Health Universitas Negeri Manado Sulawesi Indonesia Electro Enginering Elektrical Engineering Program Study Politechnic Negeri Bali Badung Indonesia

ISBN: (数字)9798350363104

ISBN: (纸本)9798350363111

The objective of this research is to design and develop an integrated landslide early detection system at Tower Number Eight, 150 kV Gianyar. The research is expected to result in the construction of a communication system based on LoRa technology that will serve to reduce the potential damage from landslides. In order to achieve this, several parameters must be considered as benchmarks. These include RSSI, SNR, BER and PDR. The device operates by monitoring changes in position, soil moisture and rainfall, and then transmitting the data via LoRa technology. At the sink, the data is recorded and monitored for RSSI, SNR, PDR and BER values. In the test, the source 1 node, situated 300 metres away, exhibited an RSSI value of −100 to −109 dBm and an SNR value of 6.75 to −6.7 in both sunny and rainy weather, with a PDR value of 100%. The source 2 node, situated 600 metres away, exhibited an RSSI value of −97 to −109 dBm and an SNR value of 8.5 to −11.75 dB, with a PDR value of 70 to 100%. It should be noted that the number of bits in the sensor data sent is always complete. This is evidenced by the bit error ratio (BER) value, which is always 0 on both source nodes.

关键词： Rain Electricity Poles and towers Soil moisture LoRa Terrain factors Reliability Monitoring Signal to noise ratio Meteorology

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