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9th International Conference on information Management and Technology, ICIMTech 2024

作者： Sutedja, Indrajani Handayani, Lutfi Maryuni Hendry Faisal, Mohammad Reza School of Information Sytems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Midwifery Study Program Binawan University Faculty of Nursing and Midwifery Jakarta13630 Indonesia Satya Wacana Christian University Faculty of Information Technology Salatiga50711 Indonesia FMIPA Lambung Mangkurat University Department of Computer Science Banjarmasin70123 Indonesia

ISBN: (纸本)9798350390025

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. © 2024 IEEE.

关键词： Artificial Intelligent Indonesian information System Stunting stunting stunting chatbot and bibliometric stunting prevention VOS Viewer

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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 AI-Based Support Vector Machine Algorithm for Fraud Detection in Digital Payment systems

Implementation of AI-Based Support Vector Machine Algorithm ...

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International Seminar on Research of information Technology and Intelligent systems (ISRITI)

作者： Edy Prayitno Rikie Kartadie Uning Lestari Munengsih Sari Bunga Accounting Information Systems Faculty of Information Technology Universitas Teknologi Digital Indonesia Yogyakarta Indonesia Computer Engineering Study Program Faculty of Information Technology Universitas Teknologi Digital Indonesia Yogyakarta Indonesia Informatics Study Program Faculty of Science and Information Technology Universitas Akprind Indonesia Yogyakarta Indonesia Department of Computer Engineering Smart City Information Systems Politeknik Negeri Indramayu Indramayu Indonesia

ISBN: (数字)9798331519643

ISBN: (纸本)9798331519650

The increasing use of digital payment systems has led to a rise in fraudulent activities, presenting a significant challenge in ensuring secure transactions. This research focuses on implementing the Support Vector Machine (SVM) algorithm with a Radial Basis Function (RBF) kernel to detect fraud in digital payment systems. One of the main challenges addressed in this study is the severe class imbalance in the dataset, where fraudulent transactions account for only 0.17% of total transactions. To overcome this, the SMOTE (Synthetic Minority Over-sampling Technique) method was applied to balance the dataset, allowing the model to better recognize fraudulent patterns. The results indicate that the SVM model achieved an accuracy of 99.93%, with a precision of 86.23% and a recall of 75.51%. These results demonstrate that SVM, combined with SMOTE and RBF kernel, is highly effective in detecting fraudulent transactions while minimizing false positives. This research provides a strong foundation for improving fraud detection models in the context of digital payment systems, offering enhanced security and trust for users. Further research could explore hybrid models and real-time data analysis to improve performance.

关键词： Support vector machines Seminars Adaptation models Accuracy Data models Real-time systems Fraud Security Kernel Intelligent systems

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The Impact Perceived Desirability, Propensity to Act, and Perceived Feasibility towards Technoprenurial Commitment Based on A Entreprenurial Event Theory 6

The Impact Perceived Desirability, Propensity to Act, and Pe...

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6th International Conference on Cybernetics and Intelligent System, ICORIS 2024

作者： Rumangkit, Stefanus Irianto, Aloysius Bagas Pradipta Hadi, Antonius Satria Management Department BINUS Business School Bina Nusantara University Jakarta Indonesia Information System Department Faculty of Engineering Atma Jaya University Yogyakarta Indonesia Study Program of Entrepreneurship Faculty of Economy University of Widya Mataram Yogyakarta Indonesia

ISBN: (纸本)9798331539603

Technopreneurship represent a form of entrepreneurship that emphasizes entrepreneurial skills and technology. Studies on technopreneurship have been conducted, but research investigating antecedents of technopreneurship based on the entrepreneurial event model (EEM), is still limited. Most research on technopreneurship is dominated by the use of the theory of planned behavior (TPB). Therefore, this study aims to investigate the driving factors in EEM, namely perceived desirability, propensity to act, and perceived feasibility to technopreneurship intention. In addition, another purpose of this study is to explore technopreneurship intention towards technopreneurship commitment. To achieve this goal, the study used quantitative research design, primary data sources, and data collection methods using questionnaires. The sample in this study amounted to 240, with the sampling method using purposive sampling. Reliability, validity, and hypothesis testing using Smart-PLS software version 3. The results showed that perceived desirability affects technoprenurial intention, propensity to act affects technoprenurial intention, perceived feasibility affects technoprenurial intention, and technoprenurial intention affects technopreneurial commitment. © 2024 IEEE.

关键词： Entrepreneurship Intention Entreprenurial Event Model Technopreneurship

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In-Depth Examination of Student Attrition in Higher Education Through Decision Tree, Random Forest, and XGBoost Algorithms

In-Depth Examination of Student Attrition in Higher Educatio...

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International Conference on Electrical engineering, Computer Science and Informatics (EECSI)

作者： Clement Aurelio Johan Setiawan Faculty of Engineering and Informatics Information Systems Study Universitas Multimedia Nusantara Tangerang Indonesia

ISBN: (数字)9798350355314

ISBN: (纸本)9798350355321

Customer Customer churn, a critical metric for businesses reliant on customer loyalty, involves the loss of customers from a company. This study examines churn among college and university students, leading to financial losses, decreased accreditation, and diminished reputations for educational institutions, ultimately reducing their appeal to prospective students. To identify factors contributing to student churn and classify students as likely to churn or not, this research utilizes Decision Tree, Random Forest, and XGBoost algorithms. These classification algorithms, with XGBoost and Random Forest enhancing Decision Trees through boosting and bagging techniques, respectively, are well-suited for the task. The data was sourced from the Academic information Bureau and processed before model development. The model with the best performance will predict student churn on new, unseen data. Findings indicate varying performance metrics for each model, including accuracy, precision, recall, and F1-score. The XGBoost model excelled, achieving an accuracy of 98%, precision of 99%, recall of 96%, and an F1-score of 97%, significantly improving over the base Decision Tree model across all metrics. Notably, all models showed better performance in predicting the majority class (not churn) compared to the minority class (churn).

关键词： Measurement Accuracy Computational modeling Predictive models Approximation algorithms Prediction algorithms Data models Classification algorithms Decision trees Random forests

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Machine Learning-Based Prediction of Corrosion Inhibition Efficiency of Expired Pharmaceuticals: Model Development and Application

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Journal of Bio- and Tribo-Corrosion 2025年第1期11卷 1-12页

作者： Putra, Dzaki Asari Surya Ardyansyah, Nibras Bahy Putranto, Nicholaus Verdhy Trisnapradika, Gustina Alfa Akrom, Muhamad Rustad, Supriadi Dipojono, Hermawan Kresno Maezono, Ryo Faculty of Computer Science Study Program in Informatics Engineering Universitas Dian Nuswantoro Semarang50131 Indonesia Research Center for Materials Informatics Faculty of Computer Science Universitas Dian Nuswantoro Semarang50131 Indonesia Quantum and Nano Technologies Research Group Faculty of Industrial Technology Institut Teknologi Bandung Bandung40132 Indonesia School of Information Science Japan Advanced Institute of Science and Technology Ishikawa923-1292 Japan

Corrosion poses a significant challenge in industries due to material degradation and high maintenance costs, making effective inhibitors essential. Recent studies suggest expired pharmaceuticals as alternative corrosion inhibitors, but identifying the most efficient compounds can be time-consuming. This study applies machine learning models, particularly Gradient Boosting Regressor (GBR), to predict corrosion inhibition efficiency (CIE). The developed model is integrated into a web-based application, enabling real-time, accurate CIE predictions. Results show GBR as the more precise model for predicting CIE, with low error rates. The streamlit-based web application offers a user-friendly platform, facilitating quick identification of suitable inhibitors. It is flexible, supporting analysis beyond corrosion inhibitors, and significantly enhances the efficiency of the evaluation process. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Adversarial machine learning

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New Media as a Tools to Improve Creative Thinking: A Systematic Literature Review 7

New Media as a Tools to Improve Creative Thinking: A Systema...

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7th International Conference on information Technology, information systems and Electrical engineering, ICITISEE 2023

作者： Hermawan, Hellik Mahardika, Fajar Darmayanti, Irma Sumantri, R. Bagus Bambang Saputra, Dhanar Intan Surya Aminuddin, Afrig Universitas Amikom Purwokerto Faculty of Computer Science Department of Informatics Jawa Tengah Banyumas Indonesia Institut Teknologi Dan Sains Nahdlatul Computer Technology Study Program Faculty of Science and Technology Ulama Pekalongan Indonesia Universitas Amikom Purwokerto Faculty of Computer Science Department of Information Technology Jawa Tengah Banyumas Indonesia Universitas Harapan Information Systems Study Program Faculty of Science and Technology Bangsa Indonesia Universitas Amikom Yogyakarta Faculty of Computer Science Sleman Indonesia

ISBN: (纸本)9798350382266

This systematic literature review (SLR) study aims to analyze the role of New Media as a Tool to Improve Creative Thinking, with relevant articles from 2018 to 2023 taken from reputable international journals. It uses three research questions (RQ) to explore New Media's relevance in stimulating creativity. The results indicate that interactive platforms such as social media and online collaboration tools positively influence creative thinking skills. Interaction through New Media allows individuals to share ideas, discuss, and be exposed to various points of view, all of which stimulate creative thinking. In addition, New Media also facilitates the creative process of solving problems and generating original ideas. The immersive experiences offered by this technology can enhance the exploration of ideas and increase the ability to think out-of-the-box. While New Media offers great potential to enhance creativity, there are also potential risks, such as false information, media addiction, and privacy concerns. Therefore, awareness of the wise use of New Media needs to be increased, especially in education and everyday life. Overall, this literature review provides in-depth insight into the role of New Media in enhancing creative thinking skills and driving innovation. With the right approach, New Media can be an effective tool in stimulating creative thinking and encouraging the creation of original ideas beneficial for future social and technological developments. © 2023 IEEE.

关键词： Creative Thinking New Media Original Ideas Systematic Literature Review The Effect of Using New Media

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Early Detection and Classification of Melanoma Based on Android MobileNet V2 Convolutional Neural Network

Early Detection and Classification of Melanoma Based on Andr...

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

作者： Prabandari, Jasmine Iswarini Dyah Sari, Christy Atika Rachmawanto, Eko Hari Irawan, Candra Altamer, Bilal R. 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 Mosul University Presidency University of Mosul Mosul Iraq National University of Science and Technology Department of Computer Science DhiQar Iraq

ISBN: (纸本)9798350339215

Melanoma is a malignant form of cancer that affects the skin and has a particularly high mortality rate, so it requires early detection to increase the level of safety for users. Diagnosis and detection of skin cancer are usually done through manual screening and visual inspection. This process requires a long time, has high complexity, is subjective, and is prone to errors. CNN is one of the algorithms with advantages in accurate classification. In this research, early detection and classification of melanoma cancer were carried out based on two classes, namely benign and malignant using the Convolutional Neural Network method. Our proposed method yields an accuracy of 81.11% for the validation data. The accuracy results obtained can be improved by using more datasets and increasing the number of layers used. This study uses the CNN method using MobileNet V2 architecture to detect melanoma skin cancer. The class used is benign and malignant. © 2023 IEEE.

关键词： Convolutional neural networks

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Placement of information systems as a strategic tool for achieving company objectives 7

Placement of information systems as a strategic tool for ach...

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7th information systems International Conference, ISICO 2023

作者： Sardjono, Wahyu Perdana, Widhilaga Gia Cholidin, Achmad Salim, Guntur Information Systems Management Department BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta11480 Indonesia Post Graduate Program of Management Science State University of Jakarta Jl. R.Mangun Muka Raya No.11 Jakarta Timur Jakarta13220 Indonesia Law Study Program Faculty of Law University of Muhammadiyah Jakarta Indonesia Post Graduate Program Faculty of Economic Science University of Trisakti Jl. Kyai Tapa No. 1 Grogol Jakarta11440 Indonesia

The information system is a strategic tool for the goals but is considered not optimal because there are indications that long-term target strategies have not been achieved. it is necessary to identify the factors that influence this success so that a model can be built that describes the achievement of the company's strategic objectives. The research was conducted with a quantitative approach through an analysis of data using factor analysis and regression analysis. The results of the study show three factors that influence strategic goals in companies, namely Leadership & Organizational, Goals Visualization, and Enterprise-wide Awareness. © 2023 The Authors. Published by Elsevier B.V.

关键词： Factor analysis

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Procedural Low-Poly Buildings using L-System for Turn-based Tactic Game ***

Procedural Low-Poly Buildings using L-System for Turn-based ...

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

作者： Augusta Steven Benedict Umi Rosyidah Ardiawan Bagus Harisa Hanny Haryanto Study Program in Information Engineering Faculty of Computer Science Universitas Dian Nuswantoro Semarang Indonesia

ISBN: (数字)9798350366648

ISBN: (纸本)9798350366655

One of the critical visual components in video game creation is 3D asset prototypes, which also require significant effort. A procedural model using the L-system method for making low-poly buildings can address this issue. This model produces low-poly buildings based on simple parameters input by the user. The model receives input in the form of axioms, which are then processed according to predetermined L-system rules. After the building is formed, it is saved as a prefab in Unity so that it can be reused and modified by the user. The proposed method is implemented to our turn-based tactic *** and provided as a Unity package (add-on). Experimental results show that the buildings generated by the model have a minimalistic yet functional benefits.

关键词： Seminars Visualization Video games Three-dimensional displays Shape Buildings Prototypes Games Rendering (computer graphics) Generators

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