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8th International Conference on information Management and Technology, ICIMTech 2023

作者： Sardjono, Wahyu Kristin, Desi Maya Putra, Gustian Rama Binus Graduate Program - Master of Information Systems Management Bina Nusantara University Information Systems Management Department Jakarta11480 Indonesia School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Pakuan University Computer Science Study Program Faculty of Mathematics & Natural Sciences Bogor Indonesia

ISBN: (纸本)9798350326093

Companies or organizations usually use key performance indicators (KPI) as indicators to determine their performance. The company's performance achievements are reflected in the set indicators that will describe the overall performance, as well as higher education institutions can also set key performance indicators, to see their performance achievements. The use of e-learning as a tool to support teaching and learning processes to be more effective and efficient is an example of which performance needs to be measured. This article discusses how the process of developing key performance indicators is carried out through the stages of designing questionnaires and distributing questionnaires to students, data is processed using the method of factor analysis to obtain the main indicators determining performance and the method of regression analysis is also used to build performance models. obtain KPI determinants, and then develop KPI models. The results show that there are indicators of sharing knowledge, managing knowledge, understanding knowledge, and utilization knowledge as performance measurement indicators. © 2023 IEEE.

关键词： Regression analysis

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The Impact of Recommendation System Provided Based on Online Learning Readiness in the MOOC Environment 24

The Impact of Recommendation System Provided Based on Online...

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24th International Arab Conference on information Technology, ACIT 2023

作者： Murad, Dina Fitria Toha, Mohamad Mayatopani, Hendra Dewi, Meta Amalya Leandros, Riyan Murad, Silvia Ayunda Heryadi, Yaya Wijanarko, Bambang Dwi Bina Nusantara University Information Systems Department Binus Online Learning Jakarta Indonesia Universitas Terbuka Jakarta Indonesia Pradita University Department of Information System Tangerang Indonesia Bina Nusantara University Computer Science Department Binus Graduate Program Doctor of Computer Science Jakarta Indonesia Bina Nusantara University School of Computer Science Jakarta Indonesia

ISBN: (纸本)9798350384307

MOOCs are one of the developments or impacts of e-learning or online learning. Massive Open Online Course (MOOC) is one of the choices for students to increase their knowledge through non-formal channels. Our research aims to determine the level of readiness of students regarding MOOC learning and opportunities for utilizing recommendation systems in students' decision-making regarding selecting MOOCs that suit their interests and needs. We conducted a survey regarding the constraints and needs of learner readiness through 5 aspects, namely 1) technical aspect, (2) social aspect, (3) communication aspect, (4) lecture readiness aspect, and (5) online discussion. The results of this research show that the main challenges that MOOC participants may face in a MOOC environment are Technical Aspects (28.25%), Social Aspects (21.47%), and Communication Aspects (18.93%). Meanwhile, the greatest strength of online learning in the MOOC environment is the social aspect (21%), the most influential and continued with technical and other aspects. Meanwhile, the lecture readiness aspect is quite good, and the online discussion aspect is the biggest aspect that influences the success of MOOC learning. Other results of this research indicate the importance of a recommendation system for MOOC students to make it easier for students to choose the right MOOC according to their interests and needs. © 2023 IEEE.

关键词： MOOC personalization Recommendation system student competency Technology Enhanced Learning

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Mobilizing Health and Work: Investigating the Role of Mobile Instant Messaging (MIM) as a Community Medium for Health information Acquisition among Thai Low-Income Workers 23

Mobilizing Health and Work: Investigating the Role of Mobile...

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8th International Conference on Sustainable information engineering and Technology, SIET 2023

作者： Jarupreechachan, Weerachaya Surasak, Thattapon Kitchat, Kotcharat Trakunsathitman, Phanthika Department of Computer Engineering Kasetsart University Kamphaengsaen Nakhon Pathom73140 Thailand Department of Computer and Information Science King Mongkut's University of Technology North Bangkok Bangkok10800 Thailand Department of Computer Science and Information Engineering National Central University Taoyuan320 Taiwan Graduate School of Business Siam University Bangkok10160 Thailand

ISBN: (纸本)9798400708503

In recent years, the number of Thai low-income workers has kept growing, especially workers who work abroad, however, improving their life by connecting them with the government via the MIM (Mobile Instant Messaging) community platform has still not yet been studied. Previously studies were limited to the aspect of the worker's life in healthcare services. This study had two aims. First, could anonymity help engage Thai low-income workers to seek health information or work-related information from the government through the MIM community platform Second, how the MIM community platform helps improve their quality of life in perceiving information. We conducted the survey through questionnaires and interviews focusing on health information and work-related information perceptiveness of workers after being introduced to the MIM community platform (also known as LINE Open Chat). The preliminary results showed that the MIM community, on the user's side, gives a sense of security due to its anonymity feature and sense of trust for real-Time responses along with the sense of belonging from the MIM community model. On managerial contribution, the MIM is cheaper and more convenient for the government to manage. We also included group size suggestion, which is limited based on the purpose of information perceptiveness, to reduce information overload and confusion. © 2023 Owner/Author.

关键词： Message passing

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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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Tabu search for solving multiple-vehicle bike sharing system routing problem with real port distribution

Tabu search for solving multiple-vehicle bike sharing system...

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2022 International Conference on Electrical, computer, Communications and Mechatronics engineering, ICECCME 2022

作者： Tsushima, Honami Sviridova, Nina Ikeguchi, Tohru Department of Information and Computer Technology Graduate School of Engineering Tokyo University of Science Katsushika-ku Tokyo Japan Department of Information and Computer Technology Faculty of Engineering Tokyo University of Science Katsushika-ku Tokyo Japan

ISBN: (数字)9781665470957

ISBN: (纸本)9781665470957

The bicycle sharing system (BSS) is one of the eco-friendly transportation systems introduced in major cities world-wide. However, BSS faces one crucial challenge: an imbalance of bicycles among the ports, because users are free to rent and return bicycles freely. It is necessary to restore the bicycles among the ports using vehicles to overcome this issue. We have already proposed search strategies for finding the tours of the vehicles in a reasonable time frame. In our previously proposed method, we used the tabu search which harnesses executing two local searches: the CROSS-exchange and the Or-opt. In the numerical experiment, we used instances with uniformly distributed ports to evaluate the performance of our previous method;however, real BSS ports are not uniformly distributed. Thus, in this paper, we use instances with real port distributions from four BSSs (Boston, Washington D.C., New York, Chicago) to investigate whether our method is effective for non-randomly distributed ports of larger-size instances (200 ports). From the numerical experiments, our proposed method is also effective for instances based on real BSS port locations. © 2022 IEEE.

关键词： Tabu search

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PROPOSAL ON DISTRIBUTED MQTT BROKERS ARCHITECTURE 22

PROPOSAL ON DISTRIBUTED MQTT BROKERS ARCHITECTURE

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22nd International Conference on e-Society 2024, ES 2024 and 20th International Conference on Mobile Learning 2024, ML 2024

作者： Kosaka, Kazuhiro Mitsuuchi, Masaki Yokotani, Tetsuya Ishibashi, Koichi The Graduate School of Electrical Engineering and Electronics Kanazawa Institute of Technology Ishikawa Nonoichi Japan Department of Electrical and Electronic Engineering College of Engineering Kanazawa Institute of Technology Ishikawa Nonoichi Japan Department of Information and Computer Science College of Engineering Kanazawa Institute of Technology Ishikawa Hakusan Japan

Message Queue Telemetry Transport (MQTT) is a popular communication protocol for IoT, in which Publishers and Subscribers communicate through a single broker. Therefore, a distributed broker is necessary to accommodate multiple Publishers and Subscribers at multiple locations. Previous studies have used a method in which multiple brokers are connected in a ring to share information. However, in this method, the processing delay time increases as the number of brokers and Hops increases. In this study, we propose a direct connection method between distributed brokers that reduces the processing delay time. We also use an Analytic Hierarchy Process (AHP) to determine the communication protocol used to connect brokers. Next, partial prototyping was performed to estimate the latency. © 2024 International Conferences e-Society 2024 and Mobile Learning 2024. All rights reserved.

关键词： DDS Distributed Brokers IoT MQTT

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Integer programming Approaches to an Issue of Scheduling for a Truck-Drone Last-Mile Delivery System with Parcel Pickup Service 13

Integer Programming Approaches to an Issue of Scheduling for...

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Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on Advanced Intelligent Systems, SCIS and ISIS 2024

作者： Yamada, Kotaro Karuno, Yoshiyuki Iima, Hitoshi Graduate School of Science and Technology Kyoto Institute of Technology Mechanodesign Program Kyoto Japan Kyoto Institute of Technology Faculty of Mechanical Engineering Kyoto Japan Kyoto Institute of Technology Faculty of Information and Human Sciences Kyoto Japan

ISBN: (纸本)9798350373332

In this paper, we consider a scheduling issue for parcel delivery and pickup services by a truck-drone last-mile delivery system. We are given a single carrier truck and multiple identical drones to serve a finite set of customers. The single carrier truck plays the role of a mobile depot for the drones, and it visits several stops in a given order of them. The given order of stops constitutes a fixed truck route, and the carrier truck is allowed to launch (resp., to retrieve) a drone to (resp., from) a customer at a stop. For each sortie of a drone, the launching stop and the retrieving stop must be the same. The load capacity of a drone is limited to one, and for a sortie of a drone at a stop, there are three options: (i) only deliver a parcel to a customer, (ii) only pick up a parcel from a customer, and (iii) deliver a parcel to a customer, and then pick up a parcel from a customer. The scheduling problem asks to find an assignment of customers to drones with sortie options and a choice of a truck stop for each sortie in the assignment. The objective is to minimize the total duration of the carrier truck over all the stops, which is equivalent to minimizing the makespan. In this paper, we first propose an extended integer program for the case with both delivery and pickup services from an existing one for the case with delivery service only. We also conduct numerical experiments to demonstrate the solution quality of the proposed integer program by utilizing an integer programming solver, and report the results. © 2024 IEEE.

关键词： Integer programming

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Deep Learning for Multivariate Prediction of Building Energy Performance of Residential Buildings

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computers, Materials & Continua 2023年第6期75卷 5947-5964页

作者： Ibrahim Aliyu Tai-Won Um Sang-Joon Lee Chang Gyoon Lim Jinsul Kim Department of ICT Convergence System Engineering Chonnam National UniversityGwangju61186Korea Graduate School of Data Science Chonnam National UniversityGwangju61186Korea Interdisciplinary Program of Digital Future Convergence Service Chonnam National UniversityGwangju61186Korea Department of Computer Engineering Chonnam National UniversityYeosu59626Korea

In the quest to minimize energy waste,the energy performance of buildings(EPB)has been a focus because building appliances,such as heating,ventilation,and air conditioning,consume the highest ***,effective design and planning for estimating heating load(HL)and cooling load(CL)for energy saving have become *** this vein,efforts have been made to predict the HL and CL using a univariate ***,this approach necessitates two models for learning HL and CL,requiring more computational ***,the one-dimensional(1D)convolutional neural network(CNN)has gained popularity due to its nominal computa-tional complexity,high performance,and low-cost hardware *** this paper,we formulate the prediction as a multivariate regression problem in which the HL and CL are simultaneously predicted using the 1D *** the building shape characteristics,one kernel size is adopted to create the receptive fields of the 1D CNN to extract the feature maps,a dense layer to interpret the maps,and an output layer with two neurons to predict the two real-valued responses,HL and *** the 1D data are not affected by excessive parameters,the pooling layer is not applied in this ***,the use of pooling has been questioned by recent *** performance of the proposed model displays a comparative advantage over existing models in terms of the mean squared error(MSE).Thus,the proposed model is effective for EPB prediction because it reduces computational time and significantly lowers the MSE.

关键词： Artificial intelligence(AI) convolutional neural network(CNN) cooling load deep learning energy energy load energy building performance heating load prediction

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Dealing with Imbalanced Classes in Bot-IoT Dataset

arXiv

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arXiv 2024年

作者： Atuhurra, Jesse Kasahara, Shoji Sasabe, Masahiro Zhang, YuanYu Hara, Takanori Program of Information Science and Engineering Graduate School of Science and Technology Nara Institute of Science and Technology Japan Division of Information Science Xidian University China

With the rapidly spreading usage of internet of things (IoT) devices, a network intrusion detection system (NIDS) has an important role to detect and protect various types of attacks in the IoT network. To evaluate the robustness of the NIDS in the IoT network, the existing work proposed a realistic botnet dataset in the IoT network (Bot-IoT dataset) and applied it to machine learning based anomaly detection. This dataset contains imbalanced normal and attack packets because the number of normal packets is much smaller than that of attack ones. The nature of imbalanced data may make it difficult to identify the minority class correctly. In this thesis, to address the class imbalance problem in the Bot-IoT dataset, we propose a binary classification method with synthetic minority over-sampling techniques (SMOTE). The proposed classifier aims at detecting the attack packets and overcoming the class imbalance problem with the help of SMOTE algorithm. Through numerical results, we demonstrate the fundamental characteristics of the proposed classifier and the impact of imbalanced data on the classifiers' performance. Copyright © 2024, The Authors. All rights reserved.

关键词： Internet of things

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An Evaluation of Number of Pixels Change Rate (NPCR) in Symetric Cryptography Based on Data Encryption Standard (DES)

An Evaluation of Number of Pixels Change Rate (NPCR) in Syme...

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

作者： Naufal, Muhammad Rizky Sari, Christy Atika Rachmawanto, Eko Hari Handoko, Lekso Budi Isinkaye, Folasade Olubusola Al-Dayyeni, Wisam Subhi Talib University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia Ekiti State University Department of Computer Science Ekiti Nigeria Ada University School of Information Technologies and Engineering Baku Azerbaijan

ISBN: (纸本)9798350339215

Data Encryption Standard (DES) is a symmetric encryption algorithm that uses a single key to encrypt and decrypt information. In addition, the cipher text will be hidden inside an image using Stepic. DES Encryption use symmetric encryption to encrypt and decryption to decrypt. It will secure the symmetric encryption and maintain the speed of the encryption and decryption. The result of this study is the lowest error that we got as the Mean Square Error (MSE) is 0.00% and is inversely proportional with the Peak Signal to Noise Ratio (PSNR) and Avalanche with 79.36% and 34.91% in order that is not stable for result of Avalanche Effect (AVA). 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 43.47% for UACI and 99.87% for the NPCR. © 2023 IEEE.

关键词： Pixels

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