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3rd International Conference on Modeling, Simulation, Optimization and Algorithm, ICMSOA 2021

作者： Wijaya, A.H. Andhini, T.M.W. Rahmadi, Y.P. Warnars, H.L.H.S. Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta Indonesia

Through this pandemic, the world has experienced two major crises, health crisis, and economic crisis. It would be dangerous for us to continue with our "normal"daily lives. We have been forced to stay at home, and some have been dismissed from their jobs;even street vendors are forced to close. The primary purpose of this paper is to represent our solution idea on the troubles regarding COVID-19 to help and support people by providing them all the information and services needed about the COVID-19, such as the high-risk COVID-19 area, statistical growth, safety tips, online swab test booking, etc. through a mobile-based application. In this paper, we designed a model with the use case and class diagrams and implemented using Android Studio. © Published under licence by IOP Publishing Ltd.

关键词： COVID-19

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Detection of Narcotics Money Laundering in Suspicious Financial Transactions Using Convolutional Extreme Gradient Boosting (ConvXGB)

Detection of Narcotics Money Laundering in Suspicious Financ...

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Intelligent Cybernetics Technology & Applications (ICICyTA), International Conference on

作者： Leonardus Verrell Sayoga Kinantra Winarno Antoni Wibowo Computer Science Department Binus Graduate Program – Master of Computer Science School of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331506490

ISBN: (纸本)9798331506506

With the development of narcotics problems that continue to increase, the Indonesian Government responds through the Badan Narkotika Nasional (BNN) with data showing the condition of narcotics tends to grow every year and is followed by the number of assets of money laundering (ML) crimes against narcotics cases. One of the banks in Indonesia as a reporting party for suspicious financial transactions (SFT) has obstacles in detecting narcotics ML due to complex and rarely found patterns. Some previous studies conducted experiments using Convolutional Neural Network (CNN), Extreme Gradient Boosting (XGBoost), and even a combination of both into Convolutional Extreme Gradient Boosting (ConvXGB), and improved model performance in several datasets. This paper designs a model using the ConvXGB algorithm by adopting the CNN architecture, LeNet-5, by applying several convolution layers and pooling layers as a baseline model for feature learning, and the XGBoost as feature classification. Three phases of research are the preprocessing phase by collecting data, transforming data, balancing data with a hybrid sampling technique, splitting data, and scaling data, followed by the implementation phase by creating a ConvXGB model, training and testing the model, then finally the evaluation phase by analyzing results and hyperparameter tuning. The dataset used is SFT from the bank during 2023. This ConvXGB has three convolution layers, a pooling layer, and a flattened layer. The performance test results are the accuracy value and F1-Score value of 99.11% each after hyperparameter tuning. By performing a hybrid model, the model performance results are better.

关键词： Training Representation learning Analytical models Convolution Government Boosting Data models Convolutional neural networks Tuning Testing

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Analyzing Patterns of Violence Against Women in Pernambuco Using Self-Organizing Maps and Apriori Algorithm

Analyzing Patterns of Violence Against Women in Pernambuco U...

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Latin America Congress on Computational Intelligence (LA-CCI)

作者： Brenda Barros Alves Da Silva Rodolfo Moreira Pereira Cleyton M. de Oliveira Rodrigues Roberta Andrade de Araújo Fagundes Graduate Program in Computer Engineering Polytechnic School of Pernambuco POLI/UPE Recife Brazil

ISBN: (数字)9798350374575

ISBN: (纸本)9798350374582

This study investigates significant patterns of violence against women in Pernambuco using Self-Organizing Maps (SOM) and the Apriori algorithm. The methodology includes trend analysis, clustering, and association rule mining, utilizing data from the Ministério da Mulher covering 2015 to 2021. The exploratory data analysis identified demographic, temporal, and spatial trends in violence. SOM was employed for dimensionality reduction and clustering, revealing three clusters representing 5.24%, 19.68%, and 75.08% of the dataset, respectively. The Apriori algorithm was applied to yearly subsets of each cluster to uncover relevant association patterns. Our findings highlight key characteristics and temporal dynamics of violence, supporting the development of targeted interventions and support systems.

关键词： Self-organizing feature maps Surveys Pandemics Heuristic algorithms Soft sensors Clustering algorithms Psychology Data collection Market research Real-time systems

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Automatic essay exam scoring system: a systematic literature review

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Procedia computer science 2023年 216卷 531-538页

作者： Meilia Nur Indah Susanti Arief Ramadhan Harco Leslie Hendric Spit Warnars Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta 11480 Indonesia.

Currently, Indonesia and the whole world are being hit by the Covid-19 pandemic which has an impact on various fields of life. It affects all sectors, including the education sector. The government through the Ministry of Education and Culture makes a policy in education in terms of the learning process. Teaching and learning activities that were initially carried out face to face become distance learning which was carried out at home. In this study, a systematic literature review is conducted on automatic assessment of essay answers. Various previous studies discuss the essay answer scoring system that has been developed using various methods. We synthesize the results to enrich our understanding of the automated essay exam scoring system. The expected result of this research is that it can contribute to further research related to the automated essay exam scoring system, especially in terms of considering methods and dataset forms.

关键词： assessment automatic essay scoring system systematic review

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Sentiment Analysis of User Review on Indonesian Food and Beverage Group using Machine Learning Techniques

Sentiment Analysis of User Review on Indonesian Food and Bev...

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2022 IEEE Creative Communication and Innovative Technology, ICCIT 2022

作者： Yanfi, Yanfi Heryadi, Yaya Lukas, Lukas Suparta, Wayan Arifin, Yulyani Bina Nusantara University Binus Graduate Program Computer Science School of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Jakarta12930 Indonesia Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Department of Electrical Engineering Yogyakarta55281 Indonesia

ISBN: (纸本)9781665468763

A vast number of technologies based on Artificial Intelligence (AI) have proliferated into various application domains. As part of its objectives to develop agents which can behave and think like humans, some branches of AI have focused on developing various algorithms that can learn from input data without explicitly being programmed. In the food industry, notably in restaurants, smartphone technology is typically used to collect data from customers efficiently such as orders or feedback toward the services provided. The use of smartphones by some restaurants is motivated by their convenience and efficiency. Furthermore, various promotions, discounts, and membership benefits offered by cellular service providers have attracted the use of smartphones as devices for improving restaurant services to their customers. This study aimed to conduct a sentiment analysis related to multi-brand restaurants in Indonesia based on customer feedback. The data retrieved from the Google Play Store consists of 756 reviews from Boga, Champs, Hangry, Ismaya, Kulo, and Union groups. In this study, TF-IDF was used as a vectorizer to represent customer feedback as numeric vectors. The polarity sentiment of customer feedback was recognized using classifier models based on machine learning such as Logistic Regression, Naive Bayes (NB), Random Forest, and Support Vector Machine (SVM) as the classifier. The empirical results showed that SVM has the best accuracy of 93.10 % average accuracy followed by Logistic Regression with 92.41 %, Random Forest with 84.14 % average accuracy, and Naive Bayes with 76.55 % average accuracy. © 2022 IEEE.

关键词： Sentiment analysis

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Cloud-Native Mobile Application Applied for Law and Regulations Harmonization 3

Cloud-Native Mobile Application Applied for Law and Regulati...

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3rd International Conference on Intelligent Cybernetics Technology and Applications, ICICyTA 2023

作者： Al Qausar, Muhammad Juan Heryadi, Yaya Lukas, Lukas Suparta, Wayan Sonata, Ilvico Doctor of Computer Science Bina Nusantara University Binus Graduate Program Computer Science Department Jakarta Indonesia Jakarta Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta Indonesia

ISBN: (纸本)9798350394559

Navigating the complex legal and regulatory landscape requires a sophisticated platform that is not only comprehensive but also user-friendly and enables seamless analysis and document comparison in the legal realm. To address this challenging requirement, this research is dedicated to the user experience (UX) design of state-of the-art cloud-native mobile applications specifically designed for legal and regulatory harmonization. The methodology used is based on design thinking principles and takes advantage of the benefits of cloud computing. These include, but are not limited to, scalability, reliability, and security. The result is a solution that is not only powerful but also cost-effective. The core of this application follows a user-centered design philosophy and involves potential users closely in the design process. A comprehensive evaluation is performed using the System Usability Scale (SUS) methodology to measure the effectiveness and usability of the application. The results of this comprehensive approach are convincing. The application has an impressive 95.5% usage rate, indicating strong user engagement. Furthermore, user satisfaction ratings are particularly high and transformative impact of this application in a complex environment of legal harmonization. Through its innovative design, seamless functionality, and user-centric approach, this application has proven to be not only a technical solution, but also a catalyst for positive change in the legal and regulatory harmonization process. © 2023 IEEE.

关键词： Cost effectiveness

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Interpretable Machine Learning for Multi-Class Crop Yield Prediction 3

Interpretable Machine Learning for Multi-Class Crop Yield Pr...

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3rd International Conference on Intelligent Cybernetics Technology and Applications, ICICyTA 2023

作者： Nurcahyo, Aldian Heryadi, Yaya Lukas Suparta, Wayan Sonata, Ilvico Bina Nusantara University Compuer Science Binus Graduate Program Jakarta Indonesia Jakarta Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta Indonesia Doctor of Computer Science Bina Nusantara University Binus Graduate Program Compuer Science Departement Jakarta Indonesia

ISBN: (纸本)9798350394559

Crop Yield Analysis and Prediction is a fast-expanding discipline that is critical for optimizing agricultural methods. A lack of trustworthy data is one of the challenges in estimating crop yields. We develop predictive models for 22 different fruits and vegetables data. The goals of this study are to create accurate and interpretable crop recommendation models. We used multiple machine learning (ML) models for multi-class crop production prediction to fulfill our research goal. We thoroughly examined the influence of climate and nutrient factors on crop yield, considering their complex interactions. To improve the dataset, augmented data techniques were applied. Configuring the parameters and fine-tuning the hyperparameters is our technique to increase the model performance. Furthermore, we employ explainable artificial intelligence (XAI) techniques and interpretability tools like Shapley Additive exPlanations (SHAP) to improve the interpretability of our prediction model. Our findings reveal that the XGBoost model has the best performance model with 99.86% accuracy, followed by SVM Poly Kernel with 99.32% and Random Forest with 98.82%. Feature selection and analysis are emphasized, particularly in regional agricultural contexts. This study contributes to the creation of accurate and interpretable crop recommendation models while also addressing the issue of untrustworthy data, providing useful insights for optimizing agricultural practices. © 2023 IEEE.

关键词： Forecasting

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Social Media as the Most Effective Means of Business Promotion Today with Using Social Media Advertising Technology 7th

Social Media as the Most Effective Means of Business Promoti...

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7th International Conference on Inventive Systems and Control, ICISC 2023

作者： Saputra, Aldo Tannaris, Ingwen Hubert, Kelby Gaol, Ford Lumban Matsuo, Tokuro Information Systems Department Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program—Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (纸本)9789819916238

Indonesia has the largest number of people that are active in social media and Indonesia is a country with the most social media users in the world. Social media in general is used to socialize (relate, both, personally, in groups and so on) between users. The users of social media in Indonesia already has reached 160 million in January 2020. and this number of social media users in Indonesia increased up to 12 million (8.1%) from April 2019 to January 2020. Firstly, social media was used by users to connect with each other through community. However, now social media is not only used as a means of virtual community for interaction but is also used as a channel for doing business. There are still many people who do not realize that social media has the advantage of being a very efficient and effective business, and many company that still confused about to choose which social media platform that suitable with their business promotion. Therefore, we want to show and tell them one of the advantages of social media in the field of promotion. Based on the surveys, there are four most popular social media in Indonesia such as YouTube, WhatsApp, Facebook, and Instagram. However, there still very few studies can be found to understand that social media is effective or not for business promotion. For this reason, this article will examine the advantages that social media have that can support business promotion. This article will utilize the questioners method to assess the important factors of social media users such as user satisfaction factors in using social media and what social media are often used by user to promote their business. The research result is expected to provide valuable guidance for user to understand about function social media for business promotion. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Economic and social effects

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Investigating the Impact on Data Recovery in computer Forensics

Investigating the Impact on Data Recovery in Computer Forens...

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Cryptography, Informatics, and Cybersecurity (ICoCICs), IEEE International Conference on

作者： Semi Yulianto Benfano Soewito Computer Science Department Graduate Program Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department Graduate Program. Master of Computer Science Bina Nusantara University Jakarta Indonesia

Defragmentation can potentially be employed as a tactic by perpetrators to conceal, misrepresent, or eliminate digital evidence. This study explores the effects of minor defragmentation, a potential method to conceal digital evidence, on recovering file system data in digital forensics. Our investigation sought to determine the influence of minor defragmentation on the effectiveness of data recovery and to identify methods that can augment the success rate post-defragmentation. We limited the scope of this study to defragmentation in Hard Disk Drives (HDDs), solid-state drives (SSDs), and USB drives. A mixed-method approach employs a literature review, case studies, and controlled experiments. Comparative analysis was used as the main data analysis technique to investigate its impact. Preliminary findings suggest that minor defragmentation hampers data recovery; however, certain strategies can augment success rates. These results can significantly influence the development of data recovery policies, particularly those of digital forensic analysts and law enforcement. The primary objective of this study is to bolster the efficiency and dependability of file system data recovery post-defragmentation while upholding ethical and legal standards.

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Into 3D-Reconstructed Apparel over Virtual Try-On with Virtual Reality

Into 3D-Reconstructed Apparel over Virtual Try-On with Virtu...

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2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Doungtap, Surasachai Petchhan, Jirayu Phanichraksaphong, Varinya Wang, Jenq-Haur International Graduate Program of Electrical Engineering and Computer Science Taiwan National Taiwan University of Science & Technology Dept. of Electrical Engineering Taiwan National Taipei University of Technology Department of Computer Science and Information Engineering Taiwan

ISBN: (纸本)9798350324174

Virtualization technologies are still growing bigger and faster. Despite the greatness of its advancement, the costume industry is still very accessible when it comes to real trials. Off-the-shelf stuff are inadequate details for the desired individual to assess its in-depth utility for each garment trying on for a second, including custom stuff are much harder to try out right away. To this end, 2D image-based 3D reconstruction inclusive of touchable-virtualized space is accessible easier to stuff details for mans' decision making in purchasing. We establish the overall end-to-end pipeline from reconstruction until visualization for one instance to be triable on its stuff for a moment. As an expectation, our proposed approach can bring objects into the experimental area and use them immediately without any obstacle. © 2023 IEEE.

关键词： Virtual reality

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