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Artificial Intelligence and Smart Systems (ICAIS), International Conference on

作者： Dejan Rivaldo Bongestu Yappiter Harco Leslie Hendric Spits Warnars School of Information Systems Bina Nusantara University Jakarta Indonesia Binus Graduate Program Doctor of Computer Science Bina Nusantara Univerisity Jakarta Indonesia

ISBN: (数字)9781728195377

ISBN: (纸本)9781728195384

This paper discusses the possibility of a better smart city implementation with the Jakarta Information App. Our App will be a one-stop go platform where people could access new information regarding the city live and instantaneously, the information contained is not just from an average news report, but people from social media or communities can also contribute in giving up to date news 24/7. In order to create this app, some processes are done to dive deeper into Jakarta's core infrastructure, the way of living, and the society behind the city. Jakarta Information App's goals are to connect the people everywhere at any time or place; it is not just an average social media app, its main objective is to be some hub for the city, it is an a2-way connected dots, the city with the people and also the reverse. The proposed system has been modeled with a use case diagram to design the business process and using the class diagram to model the database model diagram. The user interface has been designed as a means of communication between the user and the system.

关键词： Smart cities Social networking (online) Databases User interfaces Mobile applications Artificial intelligence Business

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Systematic literature review: Accelerate the rice production for global food security

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AIP Conference Proceedings 2023年第1期2594卷

作者： N. Dominic T. W. Cenggoro B. Pardamean Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480

By 2050, about 70% of extra food production is needed to feed the world's population. As a majority staple food, the expansion of rice production should be accelerated. This systematic literature review aims to discover the factors that influence rice yields through a methodology that is partitioned into four main stages, i.e., query entry into multiple database sources, article title filtering, abstract filtering, and final article selection. The results show that genetics, irrigation system management, and farmers’ long-evolved local knowledge or experiences are the three big factors that elevate the rice production rates. Nevertheless, global warming is a serious challenge that should be deeply considered due to its great impact on reducing rice yields by up to 14.5%. Thus, the development of genetically modified rice varieties needs to be escalated while still maintaining other exogenous factors. This study contributes to providing a broader perspective for decision-makers and other relevant experts to accelerate rice production to achieve global food security.

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Improved LSTM hyperparameters alongside sentiment walk-forward validation for time series prediction

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Journal of Open Innovation: Technology, Market, and Complexity 2025年第1期11卷

作者： Wahyuddin, Eko Putra Caraka, Rezzy Eko Kurniawan, Robert Caesarendra, Wahyu Gio, Prana Ugiana Pardamean, Bens Department of Statistical Computing Politeknik Statistika STIS Jakarta 13330 Indonesia Statistics Indonesia (BPS) Jl. Dr Sutomo 6-8 Jakarta Indonesia School of Economics and Business Telkom University Bandung 40257 Indonesia Research Center for Data and Information Sciences Research Organization for Electronics and Informatics National Research and Innovation Agency (BRIN) Bandung 40135 Indonesia Faculty of Integrated Technologies Universiti Brunei Darussalam Gadong BE1410 Brunei Darussalam Department of Mathematics Universitas Sumatera Utara Medan 20155 Indonesia Bioinformatics and Data Science Research Centre Bina Nusantara University DKI Jakarta 11480 Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Program Bina Nusantara University DKI Jakarta 11480 Indonesia

This study aims to address the common issue of biased estimation errors in time series modeling by analyzing the error in locating ideal hyperparameters and defining appropriate validation methods. Specifically, it focuses on predicting the stock price of Bank Rakyat Indonesia using a combination of historical stock prices, technical indicators, exchange rates, and news sentiment data, while determining the optimal variables for deep learning models. Employing a deep learning-based Long-Short Term Memory (LSTM) model, the study optimizes hyperparameters alongside walk-forward validation for time series prediction. It explores different combinations of variables and adapts the sliding window approach to the context of the data. The results highlight the importance of optimizing hyperparameters and utilizing walk-forward validation for accurate time series prediction. The model incorporating historical stock prices and sentiment scores outperforms others, achieving an RMSE of 96.61 and MAE of 86.97. Incorporating sentiment scores reduces RMSE by 39.55 % compared to models using only historical stock prices, while adding technical indicators does not yield improvement. This study contributes to the field by addressing the issue of biased estimation errors in time series modeling, offering insights into the optimization of hyperparameters and validation methods for accurate predictions. It also underscores the significance of incorporating sentiment analysis alongside historical stock prices for improved forecasting accuracy. © 2024 The Authors

关键词： LSTM Sentiment analysis Stock price prediction Time series modeling Validation methods

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Modeling the relationship between public transportation and traffic conditions in urban areas: A system dynamics approach

Modeling the relationship between public transportation and ...

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International Conference on Physics and Mathematics for Biological science 2019, ICOPAMBS 2019

作者： Sardjono, W. Selviyanti, E. Perdana, W.G. Information Systems Management Department BINUS Graduate Program Master of Information Systems Management Bina Nusantara University Jakarta Indonesia Health Department Politeknik Negeri Jember Jember Jawa Timur68124 Indonesia Post Graduate Program of Environmental Science School of Environmental Science University of Indonesia Jakarta11480 Indonesia

The goals of the paper were to describe were and find the relations between numbers of available public transportation and traffic congestion and other variables that can reduce traffic congestion in Jakarta. The data that used in the simulation were provided by DKI Jakarta Provincial Statistics Agency from view years ago. To analyze the problem, System Dynamics are used to simulate the condition in the future using the models created based on relations between several variables. The results of the analysis shows that numbers of available public transportation cannot reduce traffic congestion if the numbers of private transportation weren't decreased. It can be concluded that government must force their citizen to reduce the number of private transportation by increasing the inflation supported by increasing numbers of available public transportation to accommodate deficit in transportation while building new roads to accommodate transportation growth in the future. © Published under licence by IOP Publishing Ltd.

关键词： Traffic congestion

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A simple student appraisal evaluation model based on multi-stage rule fuzzy logic

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AIP Conference Proceedings 2023年第1期2896卷

作者： Ditdit Nugeraha Utama Siti Sumiyati Irmawan Rahyadi Norhaslinda Zainal Abidin Norazura Ahmad Aida Mauziah Benjamin Wan Laailatul Hanim Binti Mat Desa Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Communication Department BINUS Graduate Program - Master of Strategic Marketing Communication Bina Nusantara University Jakarta Indonesia 11480 Institute of Strategic Industrial Decision Modelling School of Quantitative Sciences Universiti Utara Malaysia 06010 Sintok Kedah Malaysia Decision Science Department School of Quantitative Sciences Universiti Utara Malaysia 06010 Sintok Kedah Malaysia

An evaluating process that involves the multi parameters and rules is complex and complicated. Such complexity shows that the problem is a semi-unstructured problem. Thus, the problem faced is possibly solved by proposing a new intelligentdecision model to get the quantitative decision. Here, the experimental research was conducted by methodically operating the conception of multi-stage rule-based fuzzy logic. The experimental research is a Python programming language experiment and it is one implementation of the multi-stage rule-based fuzzy logic in solving the problem of a simple case for evaluating student performance. The evaluation model was designed thru an object-oriented approach and was conclusively able to show the result of100 dummy students’ performance values.

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Mapping of Smart Economy Research Themes: A Nine-Year Review 8

Mapping of Smart Economy Research Themes: A Nine-Year Review

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8th International Conference on ICT for Smart Society, ICISS 2021

作者： Purnomo, Agung Dian Sano, Albert Verasius Nindito, Hendro Madyatmadja, Evaristus Didik Sianipar, Corinthias P. M. Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Graduate School of Global Environmental Studies Kyoto University Department of Global Ecology Kyoto606-8502 Japan

ISBN: (纸本)9781665416979

Research on the smart economy as a part of a smart city continues to develop but is limited to one country and/or one field. From a bibliometric review, this study aims to visually study mapping and research trends in the field of the smart economy on an international scale. This study used bibliometric techniques with secondary data from Scopus. Analyze and visualize data using the VOSViewer program and the analyze search results function on Scopus. This study analyzed 125 scientific documents published from 2011 to 2020. According to the research, the Peter the Great St. Petersburg Polytechnic University, Russia, and Mboup, G. had the most active individual scientists and in smart economy research. computer science and Advances in 21st Century Human Settlements were the most studied and disseminated outlet of smart economy research. There was one category map of collaborative researchers from around the world. Based on the identification of a collection of knowledge generated from nine years of publication, this research proposes a grouping of smart economy research themes: Economy, Application of smart cities, Smart technology, Smart cities character, Economy of urban, Education and Smart environment, abbreviated as EASSEES research themes. © 2021 IEEE.

关键词： Mapping

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Application for sugarcane plantation: Manpower and transportation planning

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AIP Conference Proceedings 2023年第1期2594卷

作者： H. G. Mawandha D. Sudigyo T. Suparyanto B. Pardamean Department of Agrotechnology Institute of Agriculture STIPER Yogyakarta Indonesia 55281 Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

Sugarcane plantations in Indonesia are still managed in a labor-intensive manner, especially plantation-owned by farmers. Labor intensive means that every stage of work in sugarcane plantation management still uses manpower. One of the jobs in sugarcane plantations that requires a lot of labor is sugar cane harvesting. Trend changing in the workforce gender would affect the quantity and quality of jobs, which is determined by the workforce's capacity and the workload of the work performed. The result of this research was a sugarcane agricultural calculator that made it simple for farmers to measure manpower and transportation requirements in estimating harvest costs. Manpower and transportation of harvested sugarcane commodities were estimated through the workload approach, namely, crop production and manpower's ability to carry a load. These two components helped sugarcane farmers to determine manpower and transportation during the harvest. The final yield produced by the projected harvest labor cost would be known immediately.

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AI-Based Ripeness Grading for Oil Palm Fresh Fruit Bunch in Smart Crane Grabber 3

AI-Based Ripeness Grading for Oil Palm Fresh Fruit Bunch in ...

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3rd International Conference on Eco Engineering Development, ICEED 2019

作者： Harsawardana Rahutomo, Reza Mahesworo, Bharuno Cenggoro, Tjeng Wawan Budiarto, Arif Suparyanto, Teddy Surya Atmaja, Don Bosco Samoedro, Bayu Pardamean, Bens Institut Pertanian STIPER Yogyakarta55281 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Mechatronics and AI Research and Development Center Biotechnic Innovation Yogyakarta55281 Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia

Indonesia is one of the biggest palm oil exporters in the world. For Indonesia to stay competitive in thepalm oil industry, the harvesting and evacuating process in its oil palm plantation need to be optimized. This research introduces machinerycalled as Smart Crane Grabber. This machinery can be used for automatic harvesting and evacuation process of oil palm fresh fruit bunch. To enable automation, Smart Crane Grabber is equipped with an Artificial Intelligencesystem for automatic ripeness sorting. TheArtificial Intelligence system developed for Smart Crane Grabber achieves 71.34% accuracy by using only 400 images as preliminary training data. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Palm oil

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Low Resolution Face Recognition Using Generative Adversarial Network (GAN)

Research Square

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Research Square 2020年

作者： Martin, Howard Suharjito Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University - Anggrek Campus Jakarta11480 Indonesia Department Computer Science BINUS Online Learning Bina Nusantara University Jakarta11480 Indonesia

Face recognition has a lot of use on smartphone authentication, finding people, etc. Nowadays, face recognition with a constrained environment has achieved very good performance on accuracy. However, the accuracy of existing face recognition methods will gradually decrease when using a dataset with an unconstrained environment. Face image with an unconstrained environment is usually taken from a surveillance camera. In general, surveillance cameras will be placed on the corner of a room or even on the street. So, the image resolution will be low. Low-resolution image will cause the face very hard to be recognized and the accuracy will eventually decrease. That is the main reason why increasing the accuracy of the Low-Resolution Face Recognition (LRFR) problem is still challenging. This research aimed to solve the Low-Resolution Face Recognition (LRFR) problem. The datasets are YouTube Faces Database (YTF) and Labelled Faces in The Wild (LFW). In this research, face image resolution would be decreased using bicubic linear and became the low-resolution image data. Then super resolution methods as the preprocessing step would increase the image resolution. Super resolution methods used in this research are Super resolution GAN (SRGAN) [1] and Enhanced Super resolution GAN (ESRGAN) [2]. These methods would be compared to reach a better accuracy on solving LRFR problem. After increased the image resolution, the image would be recognized using FaceNet. This research concluded that using super resolution as the preprocessing step for LRFR problem has achieved a higher accuracy compared to [3]. The highest accuracy achieved by using ESRGAN as the preprocessing and FaceNet for face recognition with accuracy of 98.96 % and Validation rate 96.757 %. © 2020, CC BY.

关键词： Face recognition

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Application of "face Recognition" Technology for Class Room Electronic Attendance Management System 7

Application of "face Recognition" Technology for Class Room ...

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7th International Conference on ICT for Smart Society, ICISS 2020

作者： Chandra Prabowo, Harjanto Fransditya M., M. Feisal Meyliana Gunawan, Michael Andrew Gaol, Ford Lumban Winanti Universitas Bina Nusantara Mobile Application and Technology Jakarta Indonesia Bina Nusantara University BINUS Graduate Program - Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia Universitas Bina Nusantara Cyber Security Jakarta Indonesia

ISBN: (纸本)9781665404228

The attendance management system is a system that needed for learning activity in a University. In some University, the attendance management system has been used tapping system which using NFC technology. Actually, that attendance management system is effective for managing each of attendance information. However, until now we can still see many cheats for this attendance system. For example, leave their cards to their classmates and tell them to tap for them. For that, one of the many effective solutions to resolve that problem is to add face recognition technology in the current attendance system. In our experiment, we know that to add face recognition to the current attendance management system surely need a camera and also face dataset for the system. At the beginning, we need at least 9 images with different emotions and face positions to let the system recognizes one's face. To make this system more accurate at recognizing one's face, we would update the face dataset in every face recognizing process. © 2020 IEEE.

关键词： Face recognition

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