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

作者： Purnama Alamsyah, Doni Morika, Doni Siswanto, Boby Othman, Norfaridatul Akmaliah Binus Business School Bina Nusantara University Entrepreneurship Department Jakarta11480 Indonesia School of Design Bina Nusantara University Design Interior Study Program Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Computer Science Study Program Jakarta11480 Indonesia Universiti Teknikal Malaysia Melaka Faculty of Technology Management and Technopreneurship Department of Technology Management Melaka76100 Malaysia

ISBN: (纸本)9798350389654

The Learning Management System (LMS) is a component of the Smart Campus and is implemented with e-learning. E-learning can be effective if it gives satisfaction to the user and improves academic performance. Therefore, it is important to evaluate online learning users to support learning outcomes. The purpose of this study is to examine the relationship model of individual performance with support for user satisfaction and flexibility in an e-learning environment. This study was carried out using a survey to 615 e-learning users. Users are among the universities students in the city of Bandung (Indonesia). Data were collected quantitatively through questionnaires distributed online. Data processing is done with SmartPLS, where there are two model tests, namely the PLS Algorithm and Bootstrapping. Results of this study model test found that user satisfaction can be increased by information quality from e-learning. Online learning has perceived flexibility that is assessed by users and can increase user satisfaction and individual performance. It was found that user satisfaction was able to support the individual performance achievements of students as e-learning users. The results from this study provide valuable insights into the role of user satisfaction as a mediator in controlling individual student performance, highlighting the significance of integrating Smart Campus solutions. © 2024 IEEE.

关键词： Individual Performance Information Quality Perceived Flexibility User Satisfaction

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The Contribution of Assessment Platform Technology to Promote Teacher's Work in Schools 6

The Contribution of Assessment Platform Technology to Promot...

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6th International Conference on Interactive Digital Media, ICIDM 2020

作者： Zamahsari, Gamal Kusuma Putikadyanto, Agus Purnomo Ahmad Maulana, Fairuz Iqbal Bina Nusantara University Faculty of Economics and Communication Communication Science Department Jakarta11480 Indonesia Institute of Islamic Religion Madura Indonesian Language Education Study Program Pamekasan69371 Indonesia Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781728149288

This study examines the efficiency of summative assessment in schools utilizing the *** assessment platform. The objectives of this study were (1) to describe staff efficiency on summative assessment using *** in schools, and (2) to describe the time efficiency on summative assessment using *** in schools. This study uses a qualitative design. The location of this research is Junior High School 3 Malang. Data were collected through observation, document study, and interviews. Interviews were conducted with the vice-principal of the curriculum field. Investigation of validity data used triangulation, with additional interviews to the curriculum team and teachers at the school. Summative assessments using the *** platform show the more efficient in terms of staff's work as much as 17% compared to conventional summative assessment and a time efficiency of 44% compared to conventional assessments. The use of technology saves time from the planning, processing, and reporting stages of the assessment. The greatest efficiency is in the summative assessment processing stage because the costs of correcting or scanning student work, changing grades, and analyzing question items are not done manually. The use of technology with the *** platform for summative assessment in schools can be an alternative solution to promote teacher work. © 2020 IEEE.

关键词： Curricula

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IndoBERT Based Data Augmentation for Indonesian Text Classification

IndoBERT Based Data Augmentation for Indonesian Text Classif...

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Information Technology Research and Innovation (ICITRI), International Conference on

作者： Fuad Muftie Muhammad Haris Computer Science Study Program Universitas Nusa Mandiri Jakarta Indonesia

Text data augmentation has been able to improve the performance of models or algorithms for text classification and sentiment analysis. In major cases, rule-based augmentation techniques can be easily applied to various languages such as Indonesia language. However, language model-based augmentation techniques rarely investigated for Indonesian language data. Therefore, this paper presents a text data processing model for Indonesian language, which has limited data, to perform text preprocessing and data augmentation techniques by selectively inserting words based on IndoBERT. This IndoBERT-based augmentation is able to generate data that still retains meaning and sentiment similar to the original data. The testing of this Twitter text dataset yielded results showing that the proposed augmentation technique was able to increase accuracy and outperform the Random Insert augmentation technique.

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Optimization of hyper parameter bandwidth on naïve Bayes kernel density estimation for the breast cancer classification 2

Optimization of hyper parameter bandwidth on naïve Bayes ke...

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2nd International Conference on Information and Communications Technology, ICOIACT 2019

作者： Sasongko, Theopilus Bayu Arifin, Oki Al Fatta, Hanif Information Technology Department Faculty of Computer Science Universitas Amikom Yogyakarta Yogyakarta Indonesia Management of Informatics Study Program Economy and Business Departement Politeknik Negeri Lampung Lampung Indonesia

ISBN: (纸本)9781728116556

Cancer is viewed as the most harmful disease in the world. One of the most deadly cancer diseases attacking the women is breast cancer. In this paper, used Naïve Bayes classifier Kernel Density Estimation in breast cancer Wisconsin dataset take from UCI data repository. Naïve Bayes with Kernel Density Estimation was used as it could enable the Naïve Bayes to process the quantitative data. However, the performance of KDE (kernel density estimation) highly depends upon the size of the bandwidth parameter used to control the curve. The problem an accurate choice of parameter bandwidth (h) using trial and error technique requires a long process. A large bandwidth (h) will over-smooth the density and mask the structure in the data, a small bandwidth (h) will yield a density estimate that is spiky and very hard to interpret. The aim of this research is to compare the optimization of grid search parameter with the genetic algorithm to determine the bandwidth parameter (h) on the Naïve Bayes Kernel Density Estimator algorithm. The parameters used to compare the two optimization methods included accuracy, AUC (Area under Curve), and computation time. The experiment results on the test of the significance value on the comparison of grid search and algorithm in determination of the bandwidth parameter (h) naïve Bayes kernel density used Mann-Whitney Test. The result of the significance ranking showed that mean rank of the genetic algorithm accuracy was 489.95 better than the mean value of the rank of grid search accuracy at only 189.05, mean rank of AUC genetic algorithm was 491.82 better than mean rank of AUC grid search only at 187.18. The mean rank of computation time grid search was 243.37 faster than mean rank of computation time genetic algorithm at 435.63. © 2019 IEEE

关键词： Classification (of information)

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Convolutional Neural Network Analysis on Handwriting Patterns and Its Relationship to Personality: A Systematical Review

Convolutional Neural Network Analysis on Handwriting Pattern...

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International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS)

作者： Zaid Romegar Mair Widya Cholil Evi Yulianti Dona Marcelina Theresiawati Ika Nurlaili Isnainiyah Informatics Study Program Computer and Natural Science Faculty Indo Global Mandiri University Indonesia Informatics Study Program Computer Science Faculty Universitas Pembangunan Nasional Jakarta Indonesia Information System Study Program Computer and Natural Science Faculty Indo Global Mandiri University Indonesia

It can be argued that the Convolutional Neural Network (CNN) used in this research is an efficient algorithm for classifying images based on the end prediction of the path taken. In every plot that is made, there is a similar process for achieving a prediction of the final result. The implementation for each of these procedures follows the steps that are summarized into a flow of analysis stages that can help to develop the application of an algorithm. The initial stage is to take the handwriting from the user which is then pre-processed the image, to eliminate existing noise, and sharpen the contrast, so that the image can be seen clearly. Images will be processed and analyzed using the Convolutional Neural Network model, training will be carried out, with an average training of a dataset of 100 epochs or about 7 to 10 minutes, and labeling on the trained dataset. The accuracy of the training reached 98.89%, as a proportion of the different characteristics of the handwriting sample.

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Citrus Limon L. Ripeness Identification Using Feature Extraction of Mean RGB, HSV, LBP and K-Nearest Neighbor

Citrus Limon L. Ripeness Identification Using Feature Extrac...

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

作者： Priyo Utomo, Ade Cahyo Sari, Christy Atika Rachmawanto, Eko Hari Hadi, Heru Pramono Mostafa, Salama A. Al-Dayyeni, Wisam Subhi Talib University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia University of Dian Nuswantoro Study Program in Information Systems Semarang Indonesia Universiti Tun Hussein Onn Malaysia Faculty of Computer Science and Information Technology Johor Malaysia Ada University School of Information Technologies and Engineering Baku Azerbaijan

ISBN: (纸本)9798350339215

Citrus Limon L. (Lemon) is a type of fruit that is currently widely consumed, because it contains abundant vitamin C, fiber, and antioxidants. This fruit have high potential in the agribusiness sector and is widely cultivated by traditional farmers. However, during harvest time, traditional farmers generally still use manual methods using the human eye in distinguishing the maturity level of lemons which is less efficient because it has a low accuracy. Digital image processing is one solution to this problem. In the research on the classification of lemon maturity levels using digital image processing with the feature extraction method of the Mean RGB, HSV, and LBP methods and the K-Nearest Neighbor classification algorithm in this study, a total of 120 lemon images were used which were divided into 80 training image data and 40 image data. testing. The results of model performance measurements in the form of the highest accuracy level in the Mean RGB method of 100%, the highest accuracy in the HSV method of 98%, and the highest accuracy in the LBP method of 82.5%. © 2023 IEEE.

关键词： Citrus fruits

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Evaluation of E-government services based on social media using structural equation modeling 4

Evaluation of E-government services based on social media us...

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4th International Conference on Information Management and Technology, ICIMTech 2019

作者： Nindito, Hendro Madyatmadja, Evaristus Didik Dian Sano, Albert Verasius Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Computer Science Study Program Bina Nusantara Institute of Creative Technology Malang65126 Indonesia

ISBN: (纸本)9781728133331

Today many local governments have provided aspiration services or social media based complaints about the community to participate in giving aspirations and report problems that occur around the area. To improve the usefulness of this service, we conduct research with the aim of evaluating and identifying the factors that affect the service's application. The impact of this study is that the government can provide services according to the wishes of the community, because the model found can be a reference for the government to increase public trust and satisfaction for users of government services. The influence on the adoption of Aspiration Services is explained by using perceptions of trust, attitudes, and intentions of use that refer to technology acceptance models (TAM). Data processing and analysis in our research using the SEM-PLS method (Structural Equation Model-Partial Least Square). The results in this research will present that services applying technology that gain a positive effect on the awareness of usability and benefit for service users. © 2019 IEEE.

关键词： Least squares approximations

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The Application of AGNES Algorithm to Optimize Knowledge Base for Tourism Chatbot 3

The Application of AGNES Algorithm to Optimize Knowledge Bas...

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3rd International Conference on Information Management and Technology, ICIMTech 2018

作者： Sano, Albert Verasius Dian Imanuel, Tanto Daud Intanadias Calista, Mega Nindito, Hendro Condrobimo, Andreas Raharto Bina Nusantara Institute of Creative Technology Computer Science Study Program Malang65126 Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781538658215

Most tourists have limited time and schedule when they are visiting a particular tourism area. One of the main issues faced by those tourists is that they can not make simple queries to search engines about, for example, which sites or places to visit optimally if we only have one day or two-day visit? Search engines are better and better in replying users' queries with relevant answers. However, search engines are not always able to respond queries suited to users' characteristics such as their styles, personalities, knowledge backgrounds, etc. Also, search engines are not as flexible as chatbots in enabling dialogical-communication-queries. This case study aims to respond aformentioned issue by applying hierarchical cluster analysis on a set of tourism sites around Malang city, Malang regency, and Batu city based on AGNES (Agglomerative Nesting) algorithm. The result, then, is fed into chatbot's knowledge base. This chatbot will assist tourists to get information on which possible sites they have to visit optimally if they are under limited vacancy-Time constraints. © 2018 IEEE.

关键词： Search engines

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Teachers and Mobile Learning Perception: Towards a Conceptual Model of Mobile Learning for Training

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Procedia - Social and Behavioral sciences 2015年 176卷 425-430页

作者： Iin Karmila Yusri Robert Goodwin Carl Mooney School of Computer science Engineering and Mathematics Flinders University Australia Computer and Networking Engineering Study Program Ujung Pandang State of Polytechnic Indonesia

Before designing and implementing a mobile learning system, it is important to ascertain the perception of future users towards mobile learning since their perception will influence their willingness and readiness to use the system. This research investigated the perception of teachers in Indonesia of mobile learning to ascertain their readiness to engage in mobile learning for training. This study conducted a survey with 308 high school teacher respondents. The results show that teachers in Indonesia had positive perception of mobile learning and were looking forward to engage in mobile learning. Financial and device issues were not obstacles for the teachers to participate in a mobile learning environment. Interestingly, the knowledge and readiness for mobile learning of teachers who taught ICT subject was lower than teachers with mathematics, science, and other subjects. Findings obtained from this study are used as a base for designing and developing a mobile learning system for ICT training for teachers in Indonesia.

关键词： teachers mobile learning perception training system

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Artificial Intelligence and Digital Media Industry Through Social Media Based on OpenAI Technology in the Indonesian Presidential Election 2024 10

Artificial Intelligence and Digital Media Industry Through S...

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10th International Conference on Smart Computing and Communication, ICSCC 2024

作者： Pinatih, I Gusti Ayu Agung Dewi Sucitawathi Antari, Ni Putu Bayu Widhi Marijan, Kacung Sakarkar, Gopal Universitas Pendidikan Nasional Public Administration Master's Study Program Denpasar Indonesia Universitas Pendidikan Nasional Public Administration Study Program Denpasar Indonesia Universitas Airlangga Political Department Surabaya Indonesia Dr. Vishwanath Karad MIT World Peace University Department of Computer Science and Applications Pune India

ISBN: (纸本)9798350363104

This research aims to explain the use of social media based on OpenAI technology in the 2024 Presidential Election in Indonesia. The methodology used is based on a descriptive qualitative study with primary and secondary data analysis techniques. Primary data was obtained through interviews with academician in the fields of political marketing and academician in the fields of information technology. Secondary data was obtained through several journal literatures and official websites related to the research topic. The validity of the data is obtained through source triangulation based on interview data from different informants and documentation studies to obtain valid information. This study found that the use of AI-based social media is based on the advantages of OpenAI's more sophisticated technological features, fast and real-time data analysis capabilities, and content visualization capability of image rebranding. © 2024 IEEE.

关键词： Data assimilation

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