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Proceedings of the 2022 6th International Conference on Software and e-Business

作者： Rogel Angelo Rebualos Yogi Tri Prasetyo Irene Dyah Ayuwati Satria Fadil Persada School of Industrial Engineering and Engineering Management Mapua University Philippines and School of Graduate Studies Mapua University Philippines School of Industrial Engineering and Engineering Management Mapua University Philippines and International Program in Engineering for Bachelor Yuan Ze University Taiwan Department of Information Systems Institut Teknologi Telkom Surabaya Indonesia Entrepreneurship Department BINUS Business School Undergraduate Program Indonesia

ISBN: (纸本)9798400700095

Online games display a unique market with a promising economy; hence many developer companies are exploring and have been utilizing this technology because of good possibility in recent years. This study aimed to determine the composition of online game attribute that is most preferred by customers using a Conjoint Analysis Approach. This study utilized different attributes such as graphics, player-to-player interaction, character creation freedom, game accessibility, monetization, storyline, and business model. An orthogonal design of conjoint analysis was utilized to assess customer preference for online games. A survey was proposed to a community of online game players and segmented among their gender, age, and income. The results showed that business model was the most considered attribute while accessibility and monetization were the least preferred. The findings of this study could be beneficial to both technology corporations developing products that fit their target customers and customers making most of their investment.

关键词： market segmentation preference conjoint online games

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Use of Conjoint Analysis Filipino Consumer Preference on Attributes of Fixed Line Internet Service Providers 22

Use of Conjoint Analysis Filipino Consumer Preference on Att...

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Proceedings of the 2022 6th International Conference on Software and e-Business

作者： Justine Kyle Chan Nattakit Yuduang Yogi Tri Prasetyo Irene Dyah Ayuwati Satria Fadil Persada School of Industrial Engineering and Engineering Management Mapua University Philippines and School of Graduate Studies Mapua University Philippines School of Industrial Engineering and Engineering Management Mapua University Philippines and International Program in Engineering for Bachelor Yuan Ze University Taiwan Department of Information Systems Institut Teknologi Telkom Surabaya Indonesia Entrepreneurship Department BINUS Business School Undergraduate Program Indonesia

ISBN: (纸本)9798400700095

Internet has evolved from a basic communication medium into wide networks of communication networks where it has become integrated in people's daily lives. Not only that, because of the recent pandemic, the demand for internet has been rapidly increasing. With the integration of internet to our day to day interactions, choosing a provider that is inclined with consumers preference and usage should be the basis. This study aims to determine the Filipino consumer preference on choosing Fixed line internet service providers using Conjoint analysis. The method uses survey questionnaires that is disseminated across the regions of the Philippines. The data gathered from the survey are analyzed using SPSS. The result shows that out of all the attributes considered internet speed is the top priority of the consumers followed by pricing and brand. Overall, this study is beneficial in developing market strategies for companies in the telecommunications industry.

关键词： Internet Service Provider Internet ISP Conjoint Analysis Attributes

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Energy Absorption Analysis on Crash-Module Shape and Configuration of Medium-Speed Train 1

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5th International Conference on Mechanical engineering, ICOME 2021

作者： Syaifudin, Achmad Windharto, Agus Setiawan, Andri Farid, Abdul Rochman Department of Mechanical Engineering Institut Teknologi Sepuluh Nopember Surabaya Indonesia Department of Industrial Design Institut Teknologi Sepuluh Nopember Surabaya Indonesia Graduate Program of Supply Chain Management Institut Teknologi Sepuluh Nopember Surabaya Indonesia Surabaya Indonesia

ISBN: (数字)9789811915819

ISBN: (纸本)9789811915802

Trains as a means of mass transportation should protect passengers against potential accidents. To reduce the risk of train accidents due to collisions, train manufacturers should implement a passive safety system. The passive safety system could be in the form of an impact-absorbing module that is used to absorb impact energy during a collision and to minimize the damage of vehicle structures in the passenger area. This study uses a module with a circular, hexagonal, and square cross-sectional shape mounted on the front end of the medium-speed train. Finite element simulations were carried out based on the standards of SNI 8826 and EN 15227. The materials used are aluminum 6005A, mild steel AISI 1018, and glass laminated with polyvinyl butyral (PVB), which are defined as bilinear elastic–plastic for the material properties and as Johnson–Cook model for the material behaviors. The numerical simulation indicated that the module with a circular cross-section has good energy kinetic absorption and fulfills the safety requirement according to the standards for the collision under speed of 45 km/h. Besides, the square cross-section can be used as a protective frame due to lower axial deformation. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Crashworthiness

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Predicting Factors Influencing the Actual Use of E-learning Platform Among Medical Students in the Philippines

Predicting Factors Influencing the Actual Use of E-learning ...

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IEEE International Conference on industrial engineering and engineering management

作者： Omar Paolo Benito Yogi Tri Prasetyo Ralph Andre C. Roque Fernan Patrick Flores Maela Madel L. Cahigas Reny Nadlifatin Irene Dyah Ayuwati International Bachelor Program in Engineering Yuan Ze University Taoyuan Taiwan Department of Industrial Engineering and Management Yuan Ze University Taoyuan Taiwan School of Industrial Engineering and Engineering Management Mapúa University Manila Philippines School of Graduate Studies Mapúa University Manila Philippines Department of Information Systems Institut Teknologi Sepuluh Nopember Surabaya Indonesia Rectorate University of Surabaya Surabaya Indonesia

ISBN: (数字)9798350386097

ISBN: (纸本)9798350386103

This study aimed to examine the factors influencing the acceptance of eLearning platforms in medical education during the COVID-19 pandemic in the Philippines, using the latent variables from the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) and two additional variables derived from relevant literature. A total of $\mathbf{3 6 0}$ medical students participated by completing an online survey comprising 40 questions. The analysis, conducted using stepwise multiple linear regression, revealed that Performance Expectancy (PE), Habit (HB), and Instructor Characteristics (IC) were significant predictors of Actual Use (AU) with an accuracy of 54.22%. Higher levels of PE, HB, and IC were found to positively influence the acceptance and utilization of medical eLearning platforms. The findings from this study can provide valuable insights for the Commission on Higher Education in the Philippines, aiding in the enhancement of eLearning platforms for medical education. Although this research primarily focused on UTAUT2 and two additional variables-Learning Value and Instructor Characteristicsthe results offer substantial implications for the broader development f eLearning platforms in the medical field.

关键词： COVID-19 Surveys Gold Technological innovation Electronic learning Accuracy Pandemics Education Linear regression industrial engineering

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Performance Assessment of Food Logistics Service Under SERVQUAL Model Using Analytic Hierarchy Process Approach

Performance Assessment of Food Logistics Service Under SERVQ...

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IEEE International Conference on industrial engineering and engineering management

作者： Poonyawat Kusonwattana Yogi Tri Prasetyo Jui-Hao Liao Omar Paolo Benito Michael Nayat Young Nattakit Yuduang Thanatorn Chuenyindee Satria Fadil Persada School of Industrial Engineering and Engineering Management Mapúa University Manila Philippines School of Graduate Studies Mapúa University Manila Philippines International Bachelor Program in Engineering Yuan Ze University Chung-Li Taiwan Department of Industrial Engineering and Management Yuan Ze University Chung-Li Taiwan Logistics and Supply Chain Management Program Faculty of Business Administration Suvarnabhumi Institute of Technology Samut Prakan Thailand Department of Industrial Engineering and Aviation Management Navaminda Kasatriyadhiraj Royal Air Force Academy Bangkok Thailand Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta Indonesia

The food supply chain at present is important to the human and there have a lot of transportation modes to distribute food from manufacturer to customer also business to business. The customers there need fresh food and the providers always find the best way in logistics that send their food to customers with the best quality and fresh, that is why the cold chain of logistics is popular and needs to improve more for the customers. However, there is no clear way to improve the performance and assessment of food logistics service, the aim of this study focused on service quality of food logistics and identify a set of service quality dimensions that developed from the SERVQUAL model for measuring their logistics process after that researcher prioritized the dimensions and sub-dimensions by Analytic Hierarchy Process (AHP) and finalize the local weight and global weight from AHP result. Finally, this research has shown the providers and the customers were prioritized for punctuality in food logistics service. It should be concern and improvement about punctuality in a food logistics service at the same time, the worst dimension of the provider's perspective is tangible and the customer perspective is empathy, that they did not pay attention it should be improved later.

关键词：

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US Army Aviation air movement operations assignment, utilization and routing

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Journal of Defense Analytics and Logistics 2023年第1期7卷 2-28页

作者： Nelson, Russell King, Russell McConnell, Brandon M. Thoney-Barletta, Kristin Operations Research Graduate Program North Carolina State University Raleigh NC United States Department of Industrial and Systems Engineering North Carolina State University Raleigh NC United States Center for Additive Manufacturing and Logistics North Carolina State University Raleigh NC United States Department of Textile and Apparel Technology and Management North Carolina State University at Raleigh Raleigh NC United States

Purpose: The purpose of this study was to create an air movement operations planning model to rapidly generate air mission request (AMR) assignment and routing courses of action (COA) in order to minimize unsupported AMRs, aircraft utilization and routing cost. Design/methodology/approach: In this paper, the US Army Aviation air movement operations planning problem is modeled as a mixed integer linear program (MILP) as an extension of the dial-a-ride problem (DARP). The paper also introduces a heuristic as an extension of a single-vehicle DARP demand insertion algorithm to generate feasible solutions in a tactically useful time period. Findings: The MILP model generates optimal solutions for small problems (low numbers of AMRs and small helicopter fleets). The heuristic generates near-optimal feasible solutions for problems of various sizes (up to 100 AMRs and 10 helicopter team fleet size) in near real time. Research limitations/implications: Due to the inability of the MILP to produce optimal solutions for mid- and large-sized problems, this research is limited in commenting on the heuristic solution quality beyond the numerical experimentation. Additionally, the authors make several simplifying assumptions to generalize the average performance and capabilities of aircraft throughout a flight. Originality/value: This research is the first to solve the US Army Aviation air movement operations planning problem via a single formulation that incorporates multiple refuel nodes, minimization of unsupported demand by priority level, demand time windows, aircraft team utilization penalties, aircraft team time windows and maximum duration and passenger ride time limits. © 2022, In accordance with section 105 of the US Copyright Act, this work has been produced by a US government employee and shall be considered a public domain work, as copyright protection is not available.

关键词： Aircraft Demand priority Dial-a-ride problem Helicopter routing Heuristic Military aviation Multiple refuel nodes Vehicle utilization

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Solving Container Stowage Problem using Particle Swarm Optimization Algorithm with Multiple Social Learning Structures 2021

Solving Container Stowage Problem using Particle Swarm Optim...

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3rd International Conference on management Science and industrial engineering, MSIE 2021

作者： Perwira Redi, A.A.N. Perwira Dwi Lasmana, Ina Layli Rachmawati, Nur Tri Prasetyo, Yogi Budiono, Doni Jewpanya, Parida Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia Department of Logistics Engineering Universitas Pertamina Jakarta Indonesia School of Industrial Engineering and Engineering Management Mapúa University Manila Philippines Department of Technology Management Institut Teknologi Sepuluh Nopember Surabaya Indonesia PT Jakarta International Container Terminal Jakarta Department of Industrial Engineering Rajamangala University of Technology Lanna Tak Tak Thailand

ISBN: (纸本)9781450388887

The growth of international trade resulted in the raising of the total containers transported annually. In Indonesia, the number of container throughput has reached 12.85 million TEUs in 2018. In providing fast and efficient port services, container terminals (CT) constantly face complex problems on its everyday operation, one of the operational level problems occurred at CT is Container Stowage Problem (CSP). CSP is an NP-Hard Problem, therefore metaheuristic algorithm is used to solve the problem. This study proposed the use of Global, Local, and Neighborhood - Particle Swarm Optimization (GLN-PSO) algorithm to solve CSP. The basic idea of GLN-PSO is emphasize on the particle movement that considers multiple social learning structures. GLN-PSO algorithm is a development of the PSO algorithm that has been used in previous studies and is proven to outperform Bee Swarm algorithm. In this study, GLN-PSO is used to solve two types of data, namely small instances (consist of 5-27 containers) and medium instances (consist of 100-140 containers). The result showed that for small instances, GLN-PSO can outperform the PSO algorithm in terms of objective function value by 0.72% and in terms of computational time by 0,172 seconds. For medium instances, GLN-PSO has not been able to outperform the PSO algorithm by producing a gap of 27% for the objective function and 8,2 seconds for computational time © 2021 ACM.

关键词： International trade

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Two-phase cost-sensitive-learning-based framework on customer-side quality inspection for TFT-LCD industry

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Journal of Intelligent Manufacturing 2024年

作者： Shih, Ming-Sung Chen, James C. Chen, Tzu-Li Hsu, Ching-Lan International Intercollegiate Ph.D. Program National Tsing Hua University Hsinchu30013 Taiwan Department of Industrial Engineering and Engineering Management National Tsing Hua University Hsinchu30013 Taiwan Graduate Institute of Intelligent Manufacturing Technology National Taiwan University of Science and Technology Taipei106335 Taiwan

The Covid-19 outbreak in 2020 boosted the stay-at-home economy, causing a surge in electronics industry demand, especially benefiting the LCD panel sector. However, as the pandemic situation improved, countries revised policies, leading to the gradual discontinuation of remote work arrangements in various industries. This resulted in declining dividends for the stay-at-home economy. The decreased demand created intense competition within the TFT-LCD industry, urging panel companies to prioritize product quality enhancement to meet customer expectations. Panel quality inspection heavily relied on manual labor, causing varying inspection levels due to subjective judgments. Understanding and aligning with customer expectations regarding product quality inspections became imperative. Identifying defective products during inspection led to additional costs for the companies. Balancing customer product quality requirements and re-inspection costs became crucial for optimal benefits. This study addresses the binary classification problem of customer-side quality inspection through cost-sensitive learning. The predictive model considers panel process yield, production history, customer feedback, inspection capacity constraints, and cost minimization to predict panel quality as accepted or defective. To tackle the highly imbalanced data, a two-phase cost-sensitive-learning-based framework is proposed, combining data preprocessing methods and models, while considering re-inspection capacity constraints and costs to enhance accuracy. The model’s evaluation uses key performance indicators like AUC and G-mean. Actual inspection cost and defective parts per million (DPPM) are calculated based on the company’s practical assessment. Two products are used for experimentation to validate the proposed model, demonstrating over 50% reduction in inspection cost and over 10% improvement in DPPM. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Spr

关键词： Inspection

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Mean-variance and Safety-first Portfolio Selection Strategy for High-volume/Highvalue Traded Stocks in Philippine Stock Exchange (PSE)

Mean-variance and Safety-first Portfolio Selection Strategy ...

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IEEE International Conference on industrial engineering and engineering management

作者： T. C. De Guzman M. N. Young Y. T. Prasetyo S. F. Persada R. Nadilfatin School of Graduate Studies Mapua University Manila Philippines School of Industrial Engineering and Engineering Management Mapua University Manila Philippines Department of Industrial Engineering and Management Yuan Ze University Taoyuan City Taiwan International Bachelor Program in Engineering Yuan Ze University Taoyuan City Taiwan Entrepreneurship Business Creation Business School Binus University West Jakarta Indonesia Department of Information Systems Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (数字)9798350386097

ISBN: (纸本)9798350386103

This research evaluates the effectiveness of Mean-Variance (MV) and Safety-First (SF) portfolio selection strategies for high-volume/high-value traded stocks on the Philippine Stock Exchange (PSE). Analyzing data from 288 stocks over 7,670 trading days (30 years), we estimated stock returns, assigned probability weights, and conducted optimization models. The results show that the Mean-Variance (MV0.5) strategy achieved the best balance between risk and return, boasting the highest mean and cumulative returns with moderate volatility. The Safety-First (SF) strategy, however, yielded negative cumulative returns, indicating potential issues. The Market strategy had the lowest mean return but also the least risk, appealing to risk-averse investors. The Portfolio Mean-Variance (PMV) strategy provided a reasonable balance of returns and risk. Statistical analysis revealed that only the MV0.5 strategy outperformed market returns. These findings offer crucial insights into risk assessment and portfolio management for investors evaluating these strategies against market performance.

关键词： Statistical analysis Optimization models Oils Safety Risk management Stock markets Portfolios Standards Monitoring Investment

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Graph Convolution-Based Recurrent Encoder-Decoder for Anomaly Diagnoses in Multivariate Time-Series Data

SSRN

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SSRN 2024年

作者： Kim, Yejin Lee, Taek-Ho Jeon, Daeseong Park, HyeRim Lee, Changyong Kim, Suhyeon Lee, Junghye Department of Industrial Engineering Ulsan National Institute of Science and Technology Ulsan44919 Korea Republic of Technology Management Economics and Policy Program Institute of Engineering Research Seoul National University Seoul08826 Korea Republic of Department of Management Engineering Ulsan National Institute of Science and Technology Ulsan44919 Korea Republic of Technology Management Economics and Policy Program Seoul National University Seoul08826 Korea Republic of Department of Public Administraion Korea University Seoul02841 Korea Republic of Graduate school of Data Science Kyungpook National University Daegu41566 Korea Republic of Technology Management Economics and Policy Program & Graduate School of Engineering Practice Seoul National University Seoul08826 Korea Republic of

Detecting anomalies in multivariate time-series data is an important task in various real-world industries, but doing so is non-trivial because both the temporal dependency within the time series and correlations between multiple time series must be considered. Previous studies have only addressed one issue, resulting in limited performance. To address this, we propose a graph convolution-based recurrent encoder-decoder, called GC-RED. The model incorporates intra-dependencies and inter-correlations using a graph-construction process and an encoding-decoding process that encodes the graph with an attention-enhanced graph convolutional LSTM and then restores it. Anomaly detection and root cause identification are performed based on the reconstruction error. Considering that anomalies with various durations can occur in actual situations, the model includes a vanilla model reflecting single scales and a model reflecting multiple scales. The feasibility and usefulness of GC-RED are demonstrated by intensive experiments on several benchmark and real-world datasets with comparisons to other competitive methods. © 2024, The Authors. All rights reserved.

关键词： Anomaly detection

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