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1st International Conference on Advanced Information Scientific Development, ICAISD 2020

作者： Pujiastuti, Lise Wahyudi, Mochamad Solikhun STMIK Antar Bangsa Information System Study Program Banten Indonesia Universitas Bina Sarana Informatika Faculty of Technical and Informatics Information Technology Study Program DKI Jakarta Indonesia AMIK Tunas Bangsa Pematangsiantar Informatics Management Study Program North Sumatra Indonesia

Bank is a business entity whose activities are collecting funds from the public in the form ofdeposits and channeling them to the public in the form of loans or other forms to improve the livesof many people. This study aims to classify the feasibility data of prospective borrowers with the perceptron algorithm using quantum computing to facilitate the bank in determining the prospective debtor. The results of this study are an analysis of the feasibility of prospective borrowers usingthe perceptron algorithm with quantum computing. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Neural networks

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Emergency Position Reporting System for Border and Inland Areas with APRS Communication Mode

Emergency Position Reporting System for Border and Inland Ar...

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IEEE International Conference on Aerospace Electronics and Remote Sensing Technology (ICARES)

作者： Dananjaya Ariateja Ria Aprilliyani Herwin Melyanus Hutapea Edy Sulistyadi Muhammad Yasir Zain Amelia Chandra Pratiwi Faculty of Defense Science and Technology Universitas Pertahanan Republik Indonesia Bogor Indonesia National Defense Development Institute Universitas Pertahanan Republik Indonesia Bogor Indonesia Faculty of Engineering Universitas Madura Informatics Study Program Madura Indonesia

ISBN: (数字)9798331542016

ISBN: (纸本)9798331542023

Border and Inland areas are often faced with communication problems due to limited infrastructure and extreme geographical conditions. This research has produced three APRS-based communication system devices in border and inland areas that can be used to report emergency positions, namely Tracker, Digipeater, and Internet Gateway (IGate). Two APRS testing scenarios were conducted, namely sending beacons from Tracker and Ground Station, and sending beacons from Tracker, Digipeater, and Ground Station. The first scenario test results recorded a maximum distance of 2.36 kilometers (straight line) for sending and receiving information. Meanwhile, the second scenario test results can send and receive information with a maximum distance of 4.21 kilometers (straight line). This result confirms that the range of sending information signals using the digipeater device can expand the range of receiving information up to two times. Based on these results, the second scenario between Tracker, Digipeater, and Ground Station is more effectively used to increase communication coverage in border and inland areas.

关键词： Meters Logic gates Aerospace electronics Internet Reliability Remote sensing Testing

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Event log analytics to correlate the academic achievements of students using low-cost high-utility sequential pattern algorithm

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AIP Conference Proceedings 2024年第1期2867卷

作者： Ridho Gunawan Informatics Study Program Sanata Dharma University Yogyakarta Indonesia

During the Covid-19 pandemic, almost all learning is done online through learning management system. All activities carried out in the learning management system are recorded in the event log. Only looking for the sequence of activities carried out by the learner is not an enough analysis of the event log. It is also necessary to see whether the activities carried out are effective. Analysis of event logs can be used to improve the quality of the learning process. The method used to get an effective event log activity is to develop a sequential pattern method, which is to find a sequence of activities that is low-cost while getting high utility. Low cost means that students use as little time as possible to complete an activity, while high utility means that students get maximum value learning outcomes. Learning outcomes can be in the form of quizzes or assignments. Measurement of the effectiveness of the pattern obtained is in terms of looking at the correlation between cost and utility of the pattern formed. This method is applied to analyse the event log obtained from the Moodle learning management system for one course. The experimental results show learning patterns in which they show effective patterns and can obtain patterns that can improve learning optimization. Searching for low-cost high-utility patterns in the event log of the learning management system is one effective way to improve learning performance.

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Optimizing Indoor Vertical Farming with DDPG Reinforcement Learning: Enhancing Control of Nutrient Levels, Climate Conditions, and Plant Health

Optimizing Indoor Vertical Farming with DDPG Reinforcement L...

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International Conference on Technology, informatics, Management, Engineering, and Environment (TIME-E)

作者： Albert Good Fried Panggabean Rahmat Romadhon Ramot Lubis Endra Joelianto Doctoral Program in Engineering Physics Institut Teknologi Bandung Bandung Indonesia Faculty of Informatics and Electrical Engineering Institut Teknologi Del Toba Indonesia Engineering Physics Study Program Institut Teknologi Bandung Bandung Indonesia Instrumentation Control and Automation Research Group Institut Teknologi Bandung Bandung Indonesia

ISBN: (数字)9798350364750

ISBN: (纸本)9798350364767

In indoor vertical farming systems, managing dynamic and complex environments poses significant challenges. Traditional control strategies often fall short in adapting to rapid changes in critical parameters such as nutrient levels, climate conditions, and plant health indicators. To address these challenges, this paper presents a novel approach for optimizing indoor vertical farming using Deep Deterministic Policy Gradient (DDPG), a reinforcement learning algorithm well-suited for environments with continuous action spaces. Our study focused on the control and monitoring of key parameters, including nutrient levels (pH and EC), climate conditions (temperature, humidity, light, and CO2 levels), and plant health indicators (biomass accumulation and leaf size structure). By defining a comprehensive state and action space, we simulated an indoor farming environment and trained the DDPG model to maximize crop yield and health.

关键词： Smart agriculture Precision agriculture Reinforcement learning Humidity Aerospace electronics Nutrients Temperature control informatics Monitoring Farming

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Mapping and Visualization of Artificial Intelligence for Digital Economy Research: A Bibliometric Approach 4

Mapping and Visualization of Artificial Intelligence for Dig...

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4th IEEE International Conference of Computer Science and Information Technology, ICOSNIKOM 2022

作者： Maulana, Fairuz Iqbal Purnomo, Agung Pramono, Andi Arifin, Mohammad Nazir School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Binus Business School Undergraduate Program Bina Nusantara University Entrepreneurship Department Jakarta11480 Indonesia School of Design Bina Nusantara University Interior Design Department Jakarta11480 Indonesia Informatics Engineering Study Program University of Madura Pamekasan Indonesia

ISBN: (纸本)9798350399073

Artificial Intelligence (AI) seems to be a disruptive technology that defines and reshapes the economy, more efficient industrial processes, new business models, and the service sector, becoming the development of different practices than before. The literature shows that it will be included in all fields and people's lives, as is the case in the digital economy. Artificial Intelligence for Digital Economy has not been studied significantly. This study uses bibliometric analysis to graphically map scientific publications and research trends in the Artificial Intelligence for Digital Economy sector around the world in the last ten years. The Scopus database was used to collect metadata information for this study, and VOSViewer was used to demonstrate bibliometric network mapping. We use an article selection procedure starting with the searched keywords and year constraints and then exporting the database to a RIS file format. Over the last ten years, we retrieved 540 scientific publications published between 2012 and 2021 from the Scopus database. From the data obtained, researchers at the Russian Federation have the most published papers indexed by Scopus among the most productive countries (N=131), the most productive authors are Petrenko, S.A. (N=4), and the most subject area is Computer Science (N=246). We also use VOSViewer to map the Network Theme. This study recommends incorporating research subjects Artificial Intelligence for Digital Economy: Thing, Education, Platform, Global Economy, abbreviated as TEPGE research theme. © 2022 IEEE.

关键词： Mapping

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Deep Learning for Cyber Security: Deephoax Detection

Deep Learning for Cyber Security: Deephoax Detection

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Advanced Innovations in Smart Cities (ICAISC), International Conference on

作者： SY. Yuliani Yakub Rivo Juicer Wowor David Agustriawan Irmawati Dinar Ajeng Kristiyanti P.M. Winarno Rosilah Hassan Roshayu Mohamad Randy Zahran Razzaq Department of Informatics Universitas Multimedia Nusantara Tangerang Indonesia Information System Study Program Universitas Multimedia Nusantara Tangerang Indonesia Center for Cyber Security (CYBER) Universiti Kebangsaan Malaysia Selangor Malaysia College of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia Department of Informatics UIN Sultan Maulana Hasanuddin Banten Indonesia

ISBN: (数字)9798331506995

ISBN: (纸本)9798331507008

The increasing prevalence of deep hoaxes, such as fake news and phishing schemes, poses a significant threat to cybersecurity, undermining trust and spreading misinformation. In Indonesia, surveys indicate that more than 60% of people exposed to hoax news believe that it is true, emphasizing the urgent need for robust detection methods. Traditional cybersecurity approaches often struggle to keep pace with the growing scale and sophistication of these attacks. To address this challenge, this research investigates the use of deep learning techniques, specifically focusing on text-based hoax detection in the Indonesian language. The study fine-tunes IndoBERT, a pretrained deep learning model optimized for Indonesian text, to enhance the accuracy and scalability of hoax detection. The IndoBERT model was trained on a balanced dataset of 29,552 articles, comprising both hoax and real news content, collected from the Mafindo API and Kaggle's Indonesia News Dataset. The model was fine-tuned using supervised learning and evaluated using several key metrics, including accuracy, F1-score, precision, and recall. The results demonstrate that IndoBERT outperforms existing state-of-the-art approaches, achieving an accuracy of 98.51%, an F1-score of 98.44%, and a precision of 98.23% on the test set. These results highlight the effectiveness of IndoBERT for hoax detection, which offers a scalable solution to improve cybersecurity defenses against deceptive content. This research contributes to the integration of advanced deep learning models into cybersecurity systems, addressing the evolving landscape of cyber threats.

关键词： Deep learning Measurement Training Surveys Adaptation models Technological innovation Accuracy Computer security Fake news Videos

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Application of the local antimagic total labeling of graphs to optimise scheduling system for an expatriate assignment 3

Application of the local antimagic total labeling of graphs ...

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3rd International Conference on Combinatorics, Graph Theory, and Network Topology, ICCGANT 2019

作者： Utami, W. Wijaya, K. Slamin Department of Management Universitas Jember Indonesia Study Program of Informatics Universitas Jember Indonesia

An expatriate assignment at the branch company in other country must be optimised due to the short term duty. Accuracy calculation is needed to optimise the expatriate assignment including its scheduling system. There are many ways and methods to optimise the scheduling system. One of the methods is making use of graph theory instruments such as local antimagic total labeling. The local antimagic total labeling of a graph is a map from the set of vertices and edges of the graph to the set of positive integers from 1 to the number of vertices and edges such that the weight of two adjacent vertices are different. The vertex weight is calculated by adding the labels of the vertex and all edges incident to it. In this paper, this labeling is applied to optimise the scheduling system for the expatriate assignment. This system can be modelled by a graph where the assignments are represented by vertices and connection between the assignments are represented by edges. The represented graph is then labelled by the local antimagic total labeling in order to obtain the minimum number of different vertex weights. The such number is equivalent to the optimal time allocated for the expatriate assignment. © Published under licence by IOP Publishing Ltd.

关键词： Scheduling

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Improvement of E-Nose Sensor Signal Using MVA, FFT, DWT Methods on Pineapple Fruit Maturity

Improvement of E-Nose Sensor Signal Using MVA, FFT, DWT Meth...

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International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE)

作者： Mhd Arief Hasan Riyanarto Sarno M. Syauqi Hanif Ardani Informatics Department Intitut Teknologi Sepuluh Nopember Surabaya Indonesia Informatic Engineering Study Program Universitas Lancang Kuning Pekanbaru Indonesia

In this study, we built an Electronic Nose to detect pineapple ripeness. We designed a prototype E-Nose using a wooden crate. Inside the box, we built the E-Nose using 9 MQ sensor circuits connected to the Arduino Microcontroller. In the crate, we put an object, namely a pineapple with three levels of ripeness (ripe, half ripe, and unripe), each weighing 1kg placed in three different positions (5cm, 20cm, and 35cm) from the position of the sensor array (E-nose). We converted the signal output results into ppm units. We compared the value of each fruit signal based on the level of ripeness and distance using E-Nose. We used several signal processing methods (wavelets) for signal processing. Then, we improved the signal generated using wavelet. The wavelet methods used are Moving Average, Fast Fourier Transform (FFT), and Discrete Wavelet Transform (DWT). The contribution of this research is to see the influence of the signal valuegenerated from the sensor (MQ Sensor) to the position (distance) of the object (fruit) and its influence on the level of maturity (fruit). Then signalgenerated from the sensor we make improvements with the mva, fft, and dwt methods.

关键词： Electrical engineering Microcontrollers Fast Fourier transforms Array signal processing Prototypes Electronic noses Discrete wavelet transforms

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Design of IOT based facial recognition door access control locker services at tourist attractions in Bali 2

Design of IOT based facial recognition door access control l...

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2nd International Conference on Vocational Education and Technology, IConVET 2019

作者： Widiartha, K.K. Ekayana, A.A.G. Study Program of Informatics Engineering STMIK STIKOM Indonesia Denpasar-Bali80225 Indonesia

Safety and comfort are things that everyone wants to get on a trip. Every tourist who wants a vacation to one of the tourist destinations will prioritize these two things. Leisure in travel is influenced by the availability of supporting facilities. From accommodation, restaurants to facilities provided by tourism actors in each tourism object. One problem is the lack of facilities in attractions such as luggage storage (lockers), many tourists in enjoying tourism objects carrying luggage such as backpacks;groceries to backpacks for tourists are classified as backpackers. Of course this will disrupt the comfort of traveling. In the research conducted, researchers wanted to design a system of goods storage services as a form of supporting industry 4.0 in the tourism environment. By designing an image of the storage media of goods by implementing access control for doors in each locker based on image processing supported by a microcontroller. The method used that focuses on facial recognition as image input using the PCA (Principal Component Analysis) method, which can measure the Euclidean distance in an object's face image. The design as a blueprint makes it easier to develop the next item of storage media (lockers).The results of this study indicate that the facial recognition method used is able to extract facial features and be recalibrated to activate the locker that is owned by the face object. © 2020 IOP Publishing Ltd. All rights reserved.

关键词： Principal component analysis

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On the Dominant Local Metric Dimension of Corona Product Graphs

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IAENG International Journal of Applied Mathematics 2022年第4期52卷 1页

作者： Umilasari, Reni Susilowati, Liliek Slamin Prabhu, Savari Mathematics Department Airlangga University Indonesia Study Program of Informatics Jember University Indonesia Mathematics Department Rajalakshmi Engineering College Tamil Nadu Chennai602105 India

A nontrivial connected graph T which one of the vertex is v, v is said to distinguish two vertex u;t if the distance between v and u is different from v to t, where u,t (Formula Presented) V (T). Metric dimension is one topic in graph theory that uses the concept of distance. Combining the definition of the local metric dimension and dominating set, there is a new term, we called it dominant local metric dimension and symbolized as Ddiml(T). An ordered subset Wl = {w1,w2,…,wn}(Formula Presented)V (T) is called a dominant local resolving set of T if Wl is a local resolving set as well as a dominating set of T. The goal of this paper’s research is to determine precise values of dominant local metric dimension for the corona product graphs. n copies of the graphs P1,P2,…,Pn of P are made to constructed the corona of any two graph T and P. After that, we link the i-th vertex of T to the vertices of Pi, where n is an order of graph T. T corona P is symbolized by T(Formula Presented)P. © 2022,IAENG International Journal of Applied Mathematics. All Rights Reserved.

关键词： Graph theory

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