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Decision Support System to Determine the Student Achievement Scholarship Recipients Using Fuzzy Multiple Attribute Decision Making (FMADM) with SAW 7

Decision Support System to Determine the Student Achievement...

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7th International Conference on Cyber and IT Service Management, CITSM 2019

作者： Kurniawan, Helmi Swondo, Ashari P. Sari, Eka Purnama Ummi, Khairul Yufrizal Agustin, Fhery Faculty of Engineering and Computer Science Universitas Potensi Utama Medan Indonesia English Education Study Program Universitas Potensi Utama Medan Indonesia Manajement Study Program Universitas Potensi Utama Medan Indonesia

ISBN: (纸本)9781728129099

Higher education is an education unit that organizes higher education. College students are called students, while college educators are called lecturers. Higher education as a place of learning and self-development Students provide facilities to improve student achievement in the form of student achievement scholarships. This scholarship program is expected to stimulate students' interest in learning to be better. In determining scholarship recipients, the student division selects prospective scholarship recipients based on existing criteria. In the selection process, the student division has difficulty choosing the data of prospective recipients. Because each type of scholarship criteria and has different criteria weights. Calculation of the value of weighting criteria requires precision. Based on the problems that occur, the author designed a decision support system to determine the recipients of achievement scholarships using the SAW method. This system can help student affairs to carry out criteria for recipients of achievement scholarships based on administrative data of prospective scholarship recipients in determining criteria for weighting value calculations. With this system, it can minimize errors to determine prospective scholarship recipients who excel. After testing the use of support systems for deciding scholarship decisions using the SAW method, it can be concluded that a decision support system can assist the student's part in carrying out their duties. © 2019 IEEE.

关键词： Decision support systems

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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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Classification of Rupiah Banknote for the Visually Impaired using Convolutional Neural Network with Custom Architecture and RMSProp Optimizer 11

Classification of Rupiah Banknote for the Visually Impaired ...

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11th International Conference on ICT for Smart Society, ICISS 2024

作者： Kurniadi, Dede Rahmi, Murni Lestari Mulyani, Asri Nashrulloh, Muhammad Rikza Septiana, Yosep Tri Julianto, Indri Institut Teknologi Garut Department of Computer Science Garut Indonesia Institut Teknologi Garut Informatics Study Program Garut Indonesia

ISBN: (纸本)9798350389654

Visual impairment is a condition that affects the sense of sight. In Indonesia, around 1.5% of the 4 million people are blind. In their daily activities, the visually impaired rely on their sense of touch to recognize the value of money by feeling the double lines on the right and left sides of the rupiah banknote. However, if the money is in bad condition, they are unable to recognize it, so they have to involve the help of others with the risk of fraud. Research is underway to develop a paper currency detection tool to assist the visually impaired in everyday transactions and reduce the risk of fraud. The research in this paper focuses on creating a classification model for detecting Indonesian rupiah banknotes. The method approach used in this research involves using a custom architecture Convolutional Neural Network model that combines elements from the AlexNet and VGGNet architectures, along with the RMSProp Optimizer. Before training the model, the private dataset that has been collected is augmented to increase the dataset and then split data. Next, the model is trained and tested using a private dataset of 800 images of rupiah banknotes for 2016, 2020, and 2022 emissions years, divided into eight classes of banknotes with denominations of IDR 1000, IDR 2000, IDR 5000, IDR 10,000, IDR 20,000, IDR 50,000, IDR 75,000, and IDR 100,000. Finally, the model's performance is evaluated using loss function, accuracy, precision, recall, and AUC-ROC evaluation metrics. The model evaluation results show a value loss function of 1.28, an accuracy of 95.31 %, a precision of 95.24%, a recall of 93.75%, and an AUC-ROC value of 0.99. This evaluation result indicates that the model is highly effective for use in the rupiah currency nominal detection system for the visually impaired. © 2024 IEEE.

关键词： Convolutional neural networks

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Virtual Exhibition Implementation of POP Display Project in Experimental Print Design Class 22

Virtual Exhibition Implementation of POP Display Project in ...

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6th International Conference on Education and Multimedia Technology, ICEMT 2022

作者： Darisman, Aris Indrawati, Desi Sjaerodji, Yuda Suryasa Visual Communication Design Study Program School of Design Bina Nusantara University Bandung Campus Indonesia Language Center Computer Science Study Program Faculty of Humanities Bina Nusantara University Bandung Campus Indonesia

ISBN: (纸本)9781450396455

Today, Experimental Print Design mainly focuses on the use and manipulation of attractive sales displays and retail floor plans to engage customers and boost sales activity. Furthermore, the aesthetics of retail space enhance functionality, customer loyalty, and brand identity. The studies highlight the teaching methods for effective learning of the course. This study aims to investigate the implementation, challenges, and implications of a virtual exhibition project in Experimental Print Design Class for Visual Communication Design Students. A mixed methods research design was used to collect, analyze, and mix both quantitative and qualitative research and methods to answer the research problems of the implementation and implications of a virtual exhibition project in Experimental Print Design Class. The sample was a class with 16 students in the online class and 4 students in the onsite class for hybrid learning. The findings show three main stages namely preparation, preliminary, final artwork for exhibition as the implementation of the virtual exhibition project in Experimental Print Design class and the challenges of the course were ensuring the right material quality and addressing durability concerns. In addition, virtual exhibition implementation of POP display project in Experimental Print Design class effectively improved students' ability in the aesthetics of retail space, the impression of hierarchy targets such as color, imagery, and words on the display, concept, the idea of the assets that are presented digitally in 2D or/and 3D and examine competitors' design work. In conclusion, based on the implication of the POP display project in the Experimental Print Design class, it was found that there was no significant difference between the online and onsite class as hybrid learning for Virtual Exhibition Project of POP display project in Experimental Print Design class. Thus, it was effective in improving the skill of Visual Merchandising to the online an

关键词： Students

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Feature Learning using Deep Variational Autoencoder for Prediction of Defects in Car Engine

Feature Learning using Deep Variational Autoencoder for Pred...

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2024 International Conference on Information Technology Research and Innovation, ICITRI 2024

作者： Susanto, Nanang Pardede, Hilman Ferdinandus Universitas Nusa Mandiri Computer Science Study Program Jakarta Indonesia National Research and Innovation Agency Indonesia Universitas Nusa Mandiri Computer Science Faculty of Information Technology Jakarta Indonesia

ISBN: (纸本)9798350376210

Machine learning has been employed to automatically detect the defects on car engines in several studies. One of crucial challenges on applying machine learning is on the amount of defect data collected is often large with high dimensional data, making manual detection inefficient and inaccurate. The other problem is on the missing data as oftentimes the collected data are incomplete. In this paper, we employ machine learning frameworks for engine defect detection. It comprises the data pre-processing stage which includes imputing missing value data, then performing feature correlation using the Pearson method, and selecting the features to use. After that, the label encoder and standard scaler are carried out. The experimental process begins with creating a baseline, then continues with improving imbalance data using SMOTE, and feature reconstruction using variational autoencoder (VAE). Afterwards, for classification, we employ convolutional neural networks (CNN). The proposed method achieved precision 99.63%. We collect engine quality dataset of 224,239 data with 90 features from major automobile manufacturing in Indonesia. This showed that SMOTE and Variational Autoencoder dimensional reconstruction method can overcome defect predictions in car engine defect data with data imbalance conditions. This novel methodology distinguished our study from prior methods and shows considerable increases in precision and recall matrix. © 2024 IEEE.

关键词： Convolutional neural networks

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The influence of antecedent factors of is/it utilization towards organizational performance a case study of iain raden fatah palembang

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WSEAS Transactions on computers 2011年第3期10卷 81-92页

作者： Ekawati, Rika Kharlina Hidayanto, Achmad Nizar STMIK MDP Rajawali Road No.14 Palembang 30113 Indonesia Information Technology Magister Study Program Faculty of Computer Science University of Indonesia Salemba Road No.4 Jakarta 10430 Indonesia

Information technology is one thing that is important in supporting the operational success of an organization. In an uncertain environment, information is needed primarily to support the performance of organization in decision-making. Information Systems is an orderly combination of human, hardware, software and communication network of data resources, which collect, modify, and distribute information within an organization to support organizational decision-making and control. But before the IS/IT is implemented, it is worth considering the antecedent factors that may be used as reference to see the history before the IS/IT is implemented, whether antecedent factors of IS/IT implementation has correlation and influence on organizational performance. Antecedent factors consist of six aspects, which are social factors, attitudes, support conditions, system complexity, long-term consequences and habits. This study aims to find empirical evidence that there is correlation and influence between antecedent factors of IS/IT implementation and organizational performance. Using Pearson correlation analysis and Regression analysis for the testing, the results obtained showed that attitude, facilitating conditions and system complexity have correlation with organizational performance. Among these, only attitude and facilitating condition that influence organizational performance.

关键词： Information systems

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Hybrid Encryption Based on Fernet and Rivest Shamir Adleman (RSA)

Hybrid Encryption Based on Fernet and Rivest Shamir Adleman ...

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

作者： Hisbullah, Muhammad Dafi Sari, Christy Atika Rachmawanto, Eko Hari Handoko, Lekso Budi Umam, Chaerul Isinkaye, Folasade University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia Ekiti State University Department of Computer Science Ekiti Nigeria

ISBN: (纸本)9798350339215

RSA is an asymmetric encryption algorithm that uses two different keys, a public key to encrypt the plain text and a private key to decrypt the cipher text. Fernet is a symmetric encryption algorithm that uses a single key to encrypt and decrypt information. This study uses Fernet and RSA which is the combination of symmetric and asymmetric encryption called hybrid encryption. In addition, the cipher text will be hidden inside an image using Stepic. Hybrid Encryption uses asymmetric encryption to encrypt the symmetric encryption secret key, it will secure the symmetric encryption. The result of this study is the lowest error that we got as the MSE is 0.00% and is inversely proportional with the Peak Signal to Noise Ratio (PSNR) and Avalanche (AVA) with 79.00% and 42.34% in order. Inversely proportional to the length of the text that is hidden in the image, the longest text that is hidden, the more changes that we get in the image with the highest Unified Average Changing Intensity (UACI) and Number of Pixels Change Rate (NPCR) with the biggest image size with 46.48% for UACI and 99.86% for the NPCR. © 2023 IEEE.

关键词： Signal to noise ratio

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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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An intelligent applied Fuzzy Logic to prediction the Parts per Million (PPM) as hydroponic nutrition on the based Internet of Things (IoT) 4

An intelligent applied Fuzzy Logic to prediction the Parts p...

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4th International Conference on Informatics and Computing, ICIC 2019

作者： Musa, Purnawarman Sugeru, Herik Mufza, Haya Fadhila Faculty of Computer Science and Information Technology Universitas Gunadarma Indonesia Faculty of Industrial Technology Study Program of Agrotechnology Universitas Gunadarma Indonesia

ISBN: (纸本)9781728122076

Hydroponic plants require regular monitoring of plants that grow well and can even cause plants to die. Because too late in providing nutrition or getting too little or too little food or routine monitoring in the hydroponic system. The innovation proposed in the agricultural sector that we suggest is the process of monitoring hydroponic plants in real-time. This study aims to predict the excess or lack of nutrient content based on the results of routine monitoring and has the analytical ability to determine the prediction of the value of Parts per Million (PPM) to find the nutritional value of plant media. Measurement of nutritional value using Electrical Conductivity (EC) and the potential of Hydrogen (pH) in hydroponic plant media. In this research, using the NFT hydroponic system as the application of fuzzy logic with the Mamdani method to determine the predictions of PPM values in providing nutrients at plants to adjusting the nutritional at each plant (e.g., for water spinach plants are need 1050 until 1400 PPM). The implemented is method Internet of Things (IoT) to remote sensing on measure using a smartphone as the representation of the measurement results on the hydroponic system. © 2019 IEEE.

关键词： Hydroponics

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Advancements in Deep Learning Optimization for Post-Earthquake Building Damage Detection A Systematic Review

Advancements in Deep Learning Optimization for Post-Earthqua...

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2024 International Conference on Advanced Information Scientific Development, ICAISD 2024

作者： Sonang, Sahat Yuhandri, Y. Tajuddin, Muhammad Universitas Putra Indonesia Yptk Information Technology Study Program Padang Indonesia Universitas Bumigora Department of Computer Science Mataram Indonesia

ISBN: (纸本)9798350392036

This study conducts a systematic literature review (SLR) that focuses on optimizing deep-learning techniques for post-earthquake building damage detection. By employing the PRISMA protocol, this review aimed to collect, analyze, and summarize the findings of various studies published between 2014 and 2024. This research identifies and evaluates optimization methods such as hyperparameter tuning, transfer learning, and data augmentation, highlighting their effectiveness and implementation. Challenges such as data quality, computational costs, and model interpretability were also discussed. The findings indicate that while deep learning techniques significantly enhance the accuracy and efficiency of damage detection, further research is required to address existing challenges and improve model robustness in diverse earthquake scenarios. © 2024 IEEE.

关键词： Contrastive Learning

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