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1st Paris Van Java International Seminar on Computer, Science, engineering, and Technology, PVJ ISComSET 2020

作者： Widaningsih, S. Suheri, A. Informatics Engineering Program Suryakancana University Cianjur Indonesia

Waste management is one of the problems faced in almost every city in Indonesia. One way to manage waste is through the waste bank. The business process of a waste bank is similar to a bank, but it is processed in the form of inorganic waste that has been sorted. In general, data management in waste banks is still conventional but the others have used of web-based or mobile technology. But in this way there are still some weaknesses such as the the time needed to input the collected waste data because the data cannot be directly entered into the system. In addition it can occur inaccurately entered data. The proposed method is using the QR code for the waste management system. In this method, admin only need to scan the QR code label attached on the waste bin stored above the weighing device using a smartphone camera. With this system QR scanner application based on mobile can be synchronized automatically with anroid smartphone. Admin then input the weight of the waste that is weighed and will be stored in the database. In this way the data input process can be faster and with the use of QR code, more data can be stored. © Published under licence by IOP Publishing Ltd.

关键词： Information management

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Identification of Software Bugs by Analyzing Natural Language-Based Requirements Using Optimized Deep Learning Features

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Computers, Materials & Continua 2024年第3期78卷 4379-4397页

作者： Qazi Mazhar ul Haq Fahim Arif Khursheed Aurangzeb Noor ul Ain Javed Ali Khan Saddaf Rubab Muhammad Shahid Anwar Department of Computer Science and Engineering and International Bachelor’s Program in Informatics Yuan Ze UniversityZhongliTaoyuan320315Taiwan Department of Computer Science National University of PakistanRawalpindiPunjab46000Pakistan Department of Computer Software Engineering MCSNational University of Sciences and TechnologyIslamabad44000Pakistan Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Department of Computer Science School of PhysicsEngineering and Computer ScienceUniversity of HertfordshireHatfieldAL109ABUK Department of Computer Engineering College of Computing and InformaticsUniversity of SharjahSharjah27272United Arab Emirates Department of AI and Software Gachon UniversitySeongnam-SI13120South Korea

Software project outcomes heavily depend on natural language requirements,often causing diverse interpretations and issues like ambiguities and incomplete or faulty *** are exploring machine learning to predict software bugs,but a more precise and general approach is *** bug prediction is crucial for software evolution and user training,prompting an investigation into deep and ensemble learning ***,these studies are not generalized and efficient when extended to other ***,this paper proposed a hybrid approach combining multiple techniques to explore their effectiveness on bug identification *** methods involved feature selection,which is used to reduce the dimensionality and redundancy of features and select only the relevant ones;transfer learning is used to train and test the model on different datasets to analyze how much of the learning is passed to other datasets,and ensemble method is utilized to explore the increase in performance upon combining multiple classifiers in a *** National Aeronautics and Space Administration(NASA)and four Promise datasets are used in the study,showing an increase in the model’s performance by providing better Area Under the Receiver Operating Characteristic Curve(AUC-ROC)values when different classifiers were *** reveals that using an amalgam of techniques such as those used in this study,feature selection,transfer learning,and ensemble methods prove helpful in optimizing the software bug prediction models and providing high-performing,useful end mode.

关键词： Natural language processing software bug prediction transfer learning ensemble learning feature selection

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Design Technology of Geographical Information System of Rice Pandanwangi Cianjur Prediction Factors Products 1

Design Technology of Geographical Information System of Rice...

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1st Paris Van Java International Seminar on Computer, Science, engineering, and Technology, PVJ ISComSET 2020

作者： Musrifah, Ai Adikusuma, Andri Sutono Informatics Engineering Study Program Faculty of Engineering University of Suryakancana Indonesia

Cianjur is one of the renowned rice producers, particularly with the presence of Pandanwangi rice that can be grown in the Cianjur area. Pandanwangi has become one of Cianjur City's icons, the rice supremacy created by Pandanwangi Cianjur's tenacity and distinctive scent (pandanus fragrance). The Interest of pandanwangi was very high, both within the town of Cianjur and outside the town of Cianjur, but this was inversely proportional to the desires of the groups of farmers who appeared to prefer to plant rice other than Pandanwangi, on the grounds that the planting of Pandanwangi had a long harvest and that the likelihood of crop failure was also very high. Problems with information flows that are not well integrated between farmers' groups, farmers' group organizations, and the Agriculture Department in adjusting land details, planting time, planting location, estimating total harvest and harvesting time. To solve this problem, a framework must be built that can integrate the information needed for Pandanwangi Cianjur Harvest Prediction with Pandanwangi farmers' regional analysis based on geographic information system technology, using Google Maps Service. © Published under licence by IOP Publishing Ltd.

关键词： Harvesting

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A Comparison of Multi Class Support Vector Machine vs Deep Convolutional Neural Network for Brain Tumor Classification

A Comparison of Multi Class Support Vector Machine vs Deep C...

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2023 International Seminar on Application for Technology of Information and Communication, iSemantic 2023

作者： Cahyo, Nur Ryan Dwi Sari, Christy Atika Rachmawanto, Eko Hari Jatmoko, Cahaya Al-Jawry, Rabei Raad Ali Alkhafaji, Mohamed Ayad University of Dian Nuswantoro Department of Informatics Engineering Semarang Indonesia University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia Northern Technical University Department Computer Science Semarang Indonesia Northern Technical University Department of Computer Engineering Technology Mosul Iraq National University of Science and Technology Department of Computer Sciece DhiQar Iraq

ISBN: (纸本)9798350339215

Multi SVM has long been one of the popular methods in classification, while DCNN has recently gained significant attention in image processing and pattern recognition. This research evaluates the effectiveness of Multi Class Support Vector Machine (M-SVM) and Deep Convolutional Neural Network (DCNN) techniques in classifying brain tumors. A dataset of 2660 3D medical images with dimensions 227 x 227 x 3;including Glioma, Meningioma, and Pituitary tumors, has been partitioned into distinct sets for both training and testing purposes. DCNN approach achieves excellent accuracy in identifying tumor names, with a training accuracy of 97.8% and 100% success rate in 9 experiments. The Multi SVM method demonstrates relatively good accuracy, with training accuracies ranging from 70% to 90% based on different kernel functions. These findings provide valuable insights for selecting appropriate methods in brain tumor classification and encourage further exploration of hybrid Multi SVM-DCNN approaches to enhance accuracy and reliability. © 2023 IEEE.

关键词： Convolutional neural networks

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Multiplayer Ludo Game Application Based on Mixed Reality Using UrhoSharp and RabbitMQ Message Broker 9

Multiplayer Ludo Game Application Based on Mixed Reality Usi...

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9th International Conference on Wireless and Telematics, ICWT 2023

作者： Sukoco, Agus Apriliansyah, Aghil Alfhauzhi Nurmalasari, Rin Rin Pratama, Vitradisa Prihatmanto, Ary Setijadi Juhana, Agus School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Uin Sunan Gunung Djati Department of Electrical Engineering Bandung Indonesia Universitas Pendidikan Indonesia Multimedia Education Study Program Bandung Indonesia

ISBN: (纸本)9798350305029

This paper describes the design and implementation of the Ludo game on Microsoft Hololens to create a mixed reality-based application with Hololens technology connected to many services. The Ludo game is made for two players, with player one playing on Hololens and player two sending and receiving player one's data via the console. The Ludo game with Hololens is one of the results of the development of Hololens technology and the RabbitMQ Messaging Server. The Ludo game is made on Visual Studio software using UrhoSharp Framework and RabbitMQ Messaging Server service with the AMQP protocol. As application frameworks, Hololens and UrhoSharp function as devices for visualization and running games. At the same time, the RabbitMQ Messaging Server and AMQP protocol serve as services that connect two players from the Hololens and console by sending the data needed by the application. The test results show that Hololens is running successfully and communicating with other console players. Thus, the results obtained are the purpose of this paper, which is to create a mixed reality-based application with Hololens technology connected to many services. © 2023 IEEE.

关键词： Mixed reality

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Conceptual Model of Graph-based Individual Tree and Its Utilization in Digital Twin and Metaverse of Urban Forest

Conceptual Model of Graph-based Individual Tree and Its Util...

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2024 Symposium on Spatial Information to Empower the Metaverse

作者： Ambarwari, Agus Suwardhi, Deni Rani, Medria Shekar Husni, Emir Junaidy, Deny Willy Agirachman, Fauzan Alfi Murtiyoso, Arnadi Griess, Verena Christiane Doctoral Program of Electrical Engineering and Informatics School of Electrical Engineering and Informatics Institut Teknologi Bandung Jl. Ganesha No.10 Bandung40132 Indonesia Faculty of Earth Sciences and Technology Institut Teknologi Bandung Indonesia School of Architecture Planning and Policy Development Institut Teknologi Bandung Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Indonesia Faculty of Art and Design Institut Teknologi Bandung Indonesia Department of Environmental Systems Science Forest Resources Management Institute of Terrestrial Ecosystems Zurich8092 Switzerland

3D city models are an important cornerstone in the development of digital twin cities, allowing for various analyses and simulations. CityGML, as an open standard for 3D city models, emphasizes five main aspects: scale or level of detail (LoD), semantics, geometry, topology, and appearance. One of the important elements in CityGML 3D city models is representation of vegetation. Vegetation in CityGML, especially individual trees, is still limited in terms of detail and resolution, reducing its effectiveness for specific applications. This paper proposes a graph-based conceptual model for individual trees that conforms to the CityGML v2.0 specification. The model refers to the morphological structure of a tree consisting of roots, trunk, and crown (including branches, twigs, and leaves), and considers the five main aspects of CityGML. By enhancing semantic information and geometric details, the model aims to provide an information-rich and realistic representation of individual trees in a 3D city environment. The 3D tree model created based on this conceptual model may be applicable in the development of digital twin urban forests and virtual forest simulations that utilize immersive technologies such as the metaverse. This research opens up new opportunities in the development of solitary vegetation objects through CityGML ADE by including more detailed semantic and topological information. © Author(s) 2024.

关键词： Digital elevation model

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Mammogram Breast Cancer Classification Based on Deep-Convolutional Neural Network

Mammogram Breast Cancer Classification Based on Deep-Convolu...

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2023 International Seminar on Application for Technology of Information and Communication, iSemantic 2023

作者： Amadea, Avissa Aurellia Sari, Christy Atika Rachmawanto, Eko Hari Sari, Wellia Shinta Noori, Mohammed S. Alkhafaji, Mohamed Ayad University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia University of Dian Nuswantoro Study Program in Information Systems Semarang Indonesia Northern Technical University Department of Computer Engineering Technology Mosul Iraq National University of Science and Technology Department of Computer Science DhiQar Iraq

ISBN: (纸本)9798350339215

Based on WHO's data, breast cancer is one of the most deadly diseases that has claimed many victims, especially women. This disease begins with the presence of an undetected and eventually turns into malignant (cancer). This happens due to ignorance of the importance of having a medical check-up even though in good health. Doctors and researchers can prevent the development of tumor cells through treatment that begins with radiological examinations to identify the possibility of a person being affected by this disease. One of the most frequently used techniques is Mammography. This technique can detect the presence of tumor cells using advanced technology and several methods in displaying the patient's diagnostic results on low-dose X-rays in the form of mammogram images. The technology is inseparable from the methods used to identify the presence of tumor cells. In this study, we have proposed the CNN method based on the deep-CNN model to identify mammogram images in the detection of breast cancer cells with average evaluation results in terms of accuracy, precision, recall, specificity, and f-measure on mammogram image datasets of 99.52%, 99.72%, 99.31%, 99.72%, and 99.5%. These results showed that this method has a good performance in breast cancer detection. © 2023 IEEE.

关键词： Diseases

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Implementation of the Fuzzy Inference System Tsukamoto Method in the Decision Support System

Implementation of the Fuzzy Inference System Tsukamoto Metho...

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2022 International Symposium on Electronics and Smart Devices, ISESD 2022

作者： Alamsyah, Doni Purnama Ramdhani, Yudi Nurbeni, Resza Dendi Bina Nusantara University Binus Business School Undergraduate Program Entrepreneurship Department Jakarta Indonesia Universitas Adhirajasa Reswara Sanjaya Informatics Engineering Program Bandung Indonesia

ISBN: (数字)9798350396607

ISBN: (纸本)9798350396607

Education is one of the basic and initial formations for the growth and development of a child in the process of obtaining a better future. Once the importance of education, the state really supports every citizen in achieving a decent education. The assessment system in each school has a different system, but the assessment system refers to the national education regulations that have been set by the government. Grade promotion aims to measure the achievement of learning outcomes in accordance with the standard of graduate ability and measure the value of quality. An important decision-making, especially in the field of education, is the decision-making to increase grades in school for students. In making the decision to increase this class, it should refer to the results of the competence or academic ability of the student, not because of the intervention of several parties who do not have the capacity to determine whether or not a student is promoted. Therefore, it is necessary to make a decision support system that will assist in obtaining a decision on the feasibility of a grade increase in students using the Fuzzy Inference System of the Tsukamoto Method. The results of this study are a decision support system that can determine the decision to increase grades in students. © 2022 IEEE.

关键词： Decision support systems

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Harnessing YOLO for Loose Fruits Detection: Boosting Productivity in Palm Oil Plantations

Harnessing YOLO for Loose Fruits Detection: Boosting Product...

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Advancement in Data Science, E-learning and Information Systems (ICADEIS), International Conference on

作者： Elly Warni Indrabayu Andani Achmad Aldilah Rezki Rhamadani Syahsir Doctoral Program of Electrical Engineering Department Informatics Department Universitas Hasanuddin Makassar Indonesia Electrical Engineering Department Universitas Hasanuddin Makassar Indonesia Informatics Department Universitas Hasanuddin Makassar Indonesia

ISBN: (数字)9798331513320

ISBN: (纸本)9798331513337

This study explores the use of the YOLOv5 algorithm to detect loose fruits palm oil in plantations, improve collection efficiency, and reduce reliance on manual labor. Loose fruits have high economic value due to their oil content, but they are often not collected, resulting in financial losses and the growth of weeds around oil palm trees. Conventional manual methods are often ineffective; thus, automatic detection is required. The dataset comprises 525 images of loose fruits, covering complex conditions on plantations, and secondary data from Roboflow, including nontarget objects, such as rocks and dry leaves, to train the model to accurately distinguish loose fruits. During training, several parameters were optimized: batch size, learning rate, optimizer type, weight decay, and momentum, which showed that small batch sizes provided higher mAP50 values, whereas large batches increased mAP50:95, indicating the ability to detect objects at higher levels of complexity. Testing in a scenario with loose fruits clearly visible and partially covered with leaves or grass showed that YOLOv5 could detect loose fruits well despite some constraints in the obstructed environment. The results of this study show that, with appropriate parameter settings, YOLOv5 can be a reliable basis for automated loose fruit collection systems, potentially improving operational efficiency in oil palm plantations and contributing to the development of automation in the agricultural sector.

关键词： YOLO Productivity Training Automation Oils Plantations Manuals Rocks Robustness Testing

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Automated Test on Multiple Platform Framework Development 22

Automated Test on Multiple Platform Framework Development

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Proceedings of the 7th International Conference on Sustainable Information engineering and Technology

作者： Muhammad Fadhli Ubaidilah Desy Intan Permatasari Fadilah Fahrul Hardiansyah Informatics Engineering Study Program Politeknik Elektronika Negeri Surabaya Indonesia

ISBN: (纸本)9781450397117

Software testing is a phase in software development to ensure software quality. As more and more software is developed for web and mobile platforms, Software Quality Assurance (SQA) Engineer is responsible to test software on both platforms to ensure functionality on each platform. While automated test can be implemented to reduce the workload of SQA Engineer, it has its setbacks as automated test needs a huge effort to maintain it and available tools to develop automated test currently only support one platform. In this research, an automated test framework is proposed and developed that can test both web and mobile platforms. Compared to an automated test project that uses separate tools, a project that uses the proposed framework has 2.57% higher maintainability index. A user test to 3 SQA Engineers has also been conducted and the proposed framework has generally been given high maintainability rating.

关键词： software testing selenium multi-platform automated test appium

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