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Level of awareness of Digital Banking Users on Risk and Security in Greater Jakarta

Level of awareness of Digital Banking Users on Risk and Secu...

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International Conference on Business and Industrial Research (ICBIR)

作者： Flourency Vellamy Dini Agnes Wijaya Anderes Gui Yuvaraj Ganesan Muhammad Shabir Shaharudin Anwar Allah Pitchay Information System Study Program School of Information Systems Bina Nusantara University Jakarta Indonesia Graduate School of Business Universiti Sains Malaysia Penang Malaysia School of Management Universiti Sains Malaysia Penang Malaysia

The development of technology in financial sector has change the monetary transaction system in the world. Currently, there are many banks provide services in digital banking because it is convenience to the users and, it has simplifies the movement and less time required compared to non-digital banking transaction. However, the side back of the digital banking to users are such as many frauds committed through digital banking, leaks or theft of users' data, when top-up balances are held up, interruptions when making transfers, and others. According to the OJK, with this digital transformation, cyber security attacks have increased by up to 86.70%. Therefore, it is important to seek and examine the awareness of digital banking users related to the risk and security of digital banking. 104 respondents participated in the self-administered questionnaire and we used a descriptive analysis to measure the level of awareness of risk and security of using digital banking. The descriptive results shows that more than 75% of respondents agree and are aware that digital banks have a fairly high-security risk, when doing top-ups there are frequent interruptions or pending, and the account is easy to access by anyone who knows our account. In addition, more than 15% of respondents feel that traditional banks have a higher risk, and fraud that occurs in digital banks does not occur often. The results of the study provides a preliminary information to the reader about the awareness of the digital banking in the context of Greater Jakarta.

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Stunting Classification in Toddlers: Implementation and Evaluation of the Decision Tree Algorithm

Stunting Classification in Toddlers: Implementation and Eval...

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information Technology and Computing (ICITCOM), International Conference on

作者： Debby Alita Imam Ahmad Rhaishudin Jafar Rumandan Moh Erkamim Widyasmoro Faculty of Engineering and Computer Science Universitas Teknokrat Indonesia Bandarlampung Indonesia Islamic Education Management Study Program Institut Agama Islam Negeri Ambon Ambon Indonesia Smart City Information Systems Study Program Universitas Tunas Pembangunan Surakarta Indonesia Department of Electrical Engineering Faculty of Engineering Universitas Muhammadiyah Yogyakarta Yogyakarta Indonesia

ISBN: (数字)9798350379839

ISBN: (纸本)9798350379846

Stunting in toddlers is a chronic nutritional issue that affects the physical and cognitive development of children, with serious long-term consequences such as reduced cognitive function and an increased risk of chronic diseases in adulthood. Therefore, early identification and prevention efforts for stunting are crucial. Classifying toddlers into categories of at-risk for stunting or not is essential to provide timely and appropriate interventions. This study employs data mining techniques using the decision tree algorithm to expedite the stunting detection process and improve the accuracy of nutritional status classification in children. The results indicate that the constructed decision tree model can classify children's nutritional status with an accuracy of 83.26%. The decision tree achieves high accuracy in classifying stunting in toddlers due to its ability to handle complex data and identify significant patterns within the data.

关键词： Pediatrics Accuracy Computational modeling Prevention and mitigation Data models Classification algorithms Decision trees Data mining information technology Diseases

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Classification Of Ornamental Fish Types Using CNN Method With VGG-16 And U-NET Architecture

Classification Of Ornamental Fish Types Using CNN Method Wit...

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Consumer Technology (ICCT-Pacific), International Conference on

作者： Ni Luh Wiwik Sri Rahayu Ginantra Christina Purnama Yati I Gusti Ayu Agung Diatri Indradewi I Komang Agus Yudiawan Technology and Informatics Informatics Engineering Institut Bisnis dan Teknologi Indonesia (INSTIKI) Denpasar Indonesia Department of Informatics Engineering Information Systems Study Program Faculty of Engineering and Vocational Studies Universitas Pendidikan Ganesha (UNDIKSHA) Denpasar Indonesia

ISBN: (数字)9798331504120

ISBN: (纸本)9798331504137

Ornamental fish are a type of fish that live in freshwater or seawater habitats and are typically maintained for aesthetic purposes, often in ornamental ponds or as household pets. The diversity of colors, shapes, and patterns observed in ornamental fish presents a challenge in their classification. Therefore, a method capable of accurately recognizing the visual characteristics of these fish is required. The objective of this study is to evaluate the performance of two Convolutional Neural Network (CNN) architectures, specifically VGG-16 and U-Net, using five distinct types of ornamental fish, namely Angel Fish, Betta Fish, Clown Fish, Gold Fish, and Guppy Fish. The dataset comprises 3.240 images that have been processed using TensorFlow and Keras on Google Collaboratory. The results demonstrated that U-Net demonstrated superior performance in segmentation, with an Average Intersection over Union (IoU) of 58.91 % and an Average Dice Coefficient of 73.72%. In contrast, VGG-16 exhibited signs of overfitting, as evidenced by lower evaluation metrics. To enhance the efficacy of the transfer learning model, further optimization is recommended.

关键词： Measurement Image segmentation Visualization Shape Transfer learning Fish Internet Convolutional neural networks Optimization Overfitting

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Business process improvement design of complaints on technical information system problems using the business process improvement method 3

Business process improvement design of complaints on technic...

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3rd International Conference on Vocational Education and Technology, IConVET 2020

作者： Pradnyana, I.M.A. Listartha, I.M.E. Information Systems Study Program Universitas Pendidikan Ganesha Jl. Udayana No.11 Banjar Tegal Singaraja KabupatenBuleleng.Bali81116 Indonesia

Various attempts were made to optimize the quality of ICT services. UPT. TIK Undiksha is one of the ICT organizational units that have been supporting business processes for Undiksha's main business processes to produce quality graduates. This study aims to provide recommendations for the improvement of one of the business processes at UPT. TIK Undiksha. The researcher proposes a business process design to be used as complaints regarding on technical information systems problems (To-Be) based on the results of the As-Is business process modelling and evaluation of the problems. Business Process Improvement (BPI) method was used for the analysis, evaluation, and recommendations for business process improvement. Further, the streamlining tools proposed to optimize the As-Is the business processes are standardization and upgrading. The simulation results show that the use of resources and time for the design business process was decreased compared to the current business process. © Published under licence by IOP Publishing Ltd.

关键词： Design

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D-ViShaDeRec: Double Intensity of Video Shadow Detection, Removal, and Re-coloring in Autonomous Vehicle 9

D-ViShaDeRec: Double Intensity of Video Shadow Detection, Re...

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9th International Conference on Computer, Control, Informatics and Its Applications: Digital Transformation Towards Sustainable Society for Post Covid-19 Recovery, IC3INA 2022

作者： Risnandar Nabila, Deeva Physics Study Program State University of Jakarta Jakarta Indonesia DKI Jakarta Jakarta Indonesia The IVDA Research Group-Research Center for Information and Data Sciences-BRIN Bandung Indonesia The Intelligent Systems Research Group-School of Computing-Telkom University Bandung Indonesia

ISBN: (纸本)9781450397919

Shadows are the obstacle parts of a vision-based during the driving an autonomous vehicle (AV). The shadow also can be detected as an object. It is feared the AV's system doesn't well-work or hits another object. Many methods of the images and video shadow detection and removal in the AVs. However, to handle the various backgrounds on the video shadow and objects, we need to exploit many scenarios of single video shadow detection, removal, and semantic segmentation. We propose a new novelty method in the shadow video detection and removal which is combined with the re-coloring method in the segmentation process. It's namely the D-ViShaDeRec. We also propose a new modified Sobel algorithm which has a kernel size of 5 × 5. The D-ViShaDeRec's outcomes show and of the recall, selectivity, precision, NPV, accuracy, and F1-Score, respectively. © 2022 ACM.

关键词： Autonomous vehicles

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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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International Seminar on Application for Technology of information and Communication (ISemantic)

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

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.

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Analysis Implementation of Chatbots to Increase Knowledge of Stunting Prevention in Indonesian Society with Bibliometric

Analysis Implementation of Chatbots to Increase Knowledge of...

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International Conference on information Management and Technology (ICIMTech)

作者： Indrajani Sutedja Lutfi Handayani Maryuni Hendry Mohammad Reza Faisal Information Systems Department School of Information Sytems Bina Nusantara University Jakarta Indonesia Faculty of Nursing and Midwifery Midwifery Study Program Binawan University Jakarta Indonesia Faculty of Information Technology Satya Wacana Christian University Salatiga Indonesia Department of Computer Science FMIPA Lambung Mangkurat University Banjarmasin Indonesia

ISBN: (数字)9798350390025

ISBN: (纸本)9798350390032

The healthcare industry uses AI, because it is more efficient. In Indonesia, the accuracy of measurements and transmission of children's growth and development is often wrong. Many small hospitals usually don't have length measuring equipment, so the results are inaccurate. This research aims to determine the effectiveness of the stunting prevention program in Indonesia using an information system. The methodology used is a qualitative method, to conduct subjective research and analysis. The results of the research are to improve the website/mobile application information system which can display a child's growth and development history and simple educational information related to nutrition. Digital recording methods can speed up the process of updating data with a central database in real time. The value of this research is to reach the public to utilize technology and obtain personalized and interactive information directly to individuals. The theoretical implications of this research focus on information dissemination and understanding how chatbots influence knowledge acquisition and behavior change in the context of stunting prevention can contribute to advancing these theories in the field of public health. Managerial implications can provide cost effectiveness as Chatbots offer potentially cost-effective solutions and data-driven insights where managers can leverage chatbot analytics.

关键词： Prevention and mitigation Scalability Bibliometrics Refining Chatbots Real-time systems Stakeholders Artificial intelligence Sustainable development Research and development

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The Analysis of B2B Sales information System Using SERVQUAL Model (A Case study Approach)

The Analysis of B2B Sales Information System Using SERVQUAL ...

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International Conference on information Management and Technology (ICIMTech)

作者： Sugiarto Hartono Faizah Shahudin Agri Adriel Bororing Tommy Hendrawan Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia School of Economics and Management Xiamen University Malaysia Selangor Malaysia Digital Business Study Program Universitas Parna Raya Manado Indonesia PT. Elgibor Solusi Digital Semarang Indonesia

The purpose of this research was to analyze a B2B sales information system at ABC Company. The analysis was based on the current problems found within the B2B sales transaction business process from the customer's perspective, and the result of the analysis was to design a web-based sales information system that could better support the B2B sales transaction activities. It was to be expected that through the design of this web-based sales information system, B2B customers of the company would be able to place orders and access important information by themselves without relying on the salesman, and the employees also could access information and handle B2B customers' orders based on their own roles in the system.

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The Effect of Data Augmentation on the Accuracy of Fish Species Classification Using Deep Learning

The Effect of Data Augmentation on the Accuracy of Fish Spec...

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International Conference on Informatics and Computing (ICIC)

作者： Ellya Helmud Catur Edi Widodo Oky Dwi Nurhayati Doctor Information System Postgraduate Diponegoro University Semarang Indonesia Faculty of Information Technology Information Systems Study Program Atma Luhur Institute of Science and Business Pangkalpinang Indonesia Physics Department Faculty of Science and Mathematics Diponegoro University Semarang Indonesia Department of Computer Engineering Faculty of Engineering Diponegoro University Semarang Indonesia

ISBN: (数字)9798331517601

ISBN: (纸本)9798331517618

Fish image classification presents an intriguing challenge in the field of computer vision. This research aims to develop an accurate classification model to differentiate between four different fish species using a convolutional neural network. The dataset used consists of $\mathbf{3 0 1 0}$ fish images, divided into training, validation, and testing sets. The convolutional neural network model was trained both with and without data augmentation. Evaluation results show that the model trained with data augmentation achieved an accuracy of $95 \%$ with a loss value of 0.0983, slightly better than the model without augmentation which achieved an accuracy of $94.56 \%$ with a loss value of $\mathbf{0. 1 7 9 4}$. This indicates that data augmentation techniques are effective in improving model performance, likely because augmentation helps the model generalize better to variations in fish image data. The results of this research demonstrate the significant potential of convolutional neural network for fish image classification tasks. The developed model can serve as a foundation for the development of computer vision-based applications such as automatic fish species identification in fisheries or educational applications. Further research can be conducted by exploring different convolutional neural network architectures, more advanced data augmentation techniques, and larger datasets to improve model performance.

关键词： Deep learning Training Accuracy Computational modeling Computer architecture Fish Data augmentation Data models Convolutional neural networks Image classification

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Understanding mobile payment continuance intention on mobile food ordering apps (MFOAs) during COVID-19 Pandemic 6

Understanding mobile payment continuance intention on mobile...

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6th International Conference on information Management and Technology, ICIMTech 2021

作者： Halim, Erwin Destiano, Ravel Salim, Jennifer Margarita, Vania Hartono, Hendry Hebrard, Marylise Bina Nusantara University School of Information System Information Systems Department Jakarta11480 Indonesia Bina Nusantara University BINUS Business School Undergraduate Program Management Department Jakarta11480 Indonesia Institut des Usages Enterprise Law Program Study Montpellier France

ISBN: (纸本)9781665449373

Mobile Food Ordering Application (MFOAs) has driven growth during the COVID-19 pandemic in Indonesia. The research goals were to examining variables of mobile payment continuance intention on MFOAs during this phenomenon. Authors chose PLS-SEM as study research with a judgment sampling approach for gaining data and Smart PLS version 3.0 as a statistical tool. The research model is developed based on ECM and TAM by integrating security and trust as an extended variable. The study result is based on 400 respondents from October - November 2020 who are active using non-bank mobile payment in Jabodetabek area and city of Bandung. Data was collected using purposive sampling and use Smart PLS as a tool for the research SEM model. In this research, all five variables indicate a significant impact on the Continuance Intention variable through trust. The Ease of Use variable has the most considerable influence on usefulness than the other variables. The Usefulness variable also has a significant impact on continuance intention through satisfaction. © 2021 IEEE.

关键词： COVID-19

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