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Articles 20041 - 20070 of 63167

Full-Text Articles in Computer Sciences

Deep Fingerprint Matching From Contactless To Contact Fingerprints For Increased Interoperability, Alexander James Wilson Jan 2021

Deep Fingerprint Matching From Contactless To Contact Fingerprints For Increased Interoperability, Alexander James Wilson

Graduate Theses, Dissertations, and Problem Reports (ETD)

Contactless fingerprint matching is a common form of biometric security today. Most smartphones and associated apps now let users opt into using this form of biometric security. However, it’s difficult to match a finger-photo to a fingerprint because of perspective distortion occurring at the edges of the finger-photo, so direct matching using conventional methods will not be as accurate due to a lack of sufficient matching minutiae points. To address this issue, we propose a deep model, Perspective Distortion Rectification Model (PDRM), to estimate the fingerprint correspondence for finger-photo images in order to recover more minutiae points. Not only do …

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Topic Modeling And Cultural Nature Of Citations, Marie Coraline Dumaz Jan 2021

Topic Modeling And Cultural Nature Of Citations, Marie Coraline Dumaz

Graduate Theses, Dissertations, and Problem Reports (ETD)

Ever since the beginning of research journals, the number of academic publications has been increasing steadily. Nowadays, especially, with the new importance of online open-access journals and databases, research papers are more easily available to read and share. It also becomes harder to keep up with novelties and grasp an idea of the general impact of a given researcher, institution, journal, or field. For this reason, different bibliometric indicators are now routinely used to classify and evaluate the impact or significance of individual researchers, conferences, journals, or entire scientific communities. In this thesis, we provide tools to study trends in …

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Plant Species Identification In The Wild Based On Images Of Organs, Meghana Kovur Jan 2021

Plant Species Identification In The Wild Based On Images Of Organs, Meghana Kovur

Graduate Theses, Dissertations, and Problem Reports (ETD)

Image-based plant species identification in the wild is a difficult problem for several reasons. First, the input data is subject to a very high degree of variability because it is captured under fully unconstrained conditions. The same plant species may look very different in different images, while different species can often appear very similar, challenging even the recognition skills of human experts in the field. The large intra-class and small inter-class image variability makes this a fine-grained visual classification problem. One way to cope with this variability and to reduce image background noise is to predict species based on the …

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Ensemble Encoder-Decoder Models For Predicting Land Transformation, Pariya Pourmohammadi Jan 2021

Ensemble Encoder-Decoder Models For Predicting Land Transformation, Pariya Pourmohammadi

Graduate Theses, Dissertations, and Problem Reports (ETD)

In studying dynamic and complex processes which are influenced by a system of inter-connected driving variables, it is crucial to apply models that can learn the complexity of the interactions. Land transformation is one of such complex processes, prediction of which can help to mitigate severe climate situations and improve the resiliency of communities. In this study, a multi-spectral set of data cubes is used to capture various characteristics of a geographic region. Based on the data cube, a feature space is constructed using socio-economic attributes, terrain characteristics, and landscape traits of the study region. Two-dimensional and three-dimensional convolutional neural …

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Association Of Incident Cancer To Low-Value Care And Healthcare Cost Burden Among Elderly Medicare Beneficiaries, Chibuzo Iloabuchi Jan 2021

Association Of Incident Cancer To Low-Value Care And Healthcare Cost Burden Among Elderly Medicare Beneficiaries, Chibuzo Iloabuchi

Graduate Theses, Dissertations, and Problem Reports (ETD)

In the United States (US), 25% of healthcare spending is considered wasteful because it is spent reimbursing low-value care. Low-value care is the utilization of healthcare services, medical tests, and procedures that have unclear or no clinical benefit to patients but still exposes them to risk. World-wide, low-value care imposes a significant economic burden on patients, payers, governments, and society. Cancer care among older adults > 65 years is one of the biggest drivers of healthcare expenditure in the US and accounts for nearly 40% of all spending, and low-value care among cancer patients is prevalent and contributes to the financial …

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Analysis And Classification Of Software Fault-Proneness And Vulnerabilities, Mohammad Jamil Ahmad Jan 2021

Analysis And Classification Of Software Fault-Proneness And Vulnerabilities, Mohammad Jamil Ahmad

Graduate Theses, Dissertations, and Problem Reports (ETD)

Software bugs are expensive to fix and can lead to catastrophic consequences. Therefore, their analysis and the use of machine learning for prediction are of the utmost importance. Many prediction models have been proposed and different factors affecting the prediction performance have been extensively studied. This work addresses four topics in two areas in software engineering: software fault-proneness prediction and analysis and classification of security-related bug reports. The first topic focuses on the effect of the learning approach (i.e., the way software fault-proneness prediction models are trained and tested) on the performance of software fault-proneness prediction which lacks extensive research …

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Software Engineering In Australasia, Sherlock A. Licorish, Christoph Treude, John Grundy, Kelly Blincoe, Stephen Macdonell, Chakkrit Tantithamthavorn, Li Li, Jean-Guy Schneider Jan 2021

Software Engineering In Australasia, Sherlock A. Licorish, Christoph Treude, John Grundy, Kelly Blincoe, Stephen Macdonell, Chakkrit Tantithamthavorn, Li Li, Jean-Guy Schneider

Research Collection School Of Computing and Information Systems

Six months ago an important call was made for researchers globally to provide insights into the way Software Engineering is done in their region. Heeding this call, we hereby outline the position Software Engineering in Australasia (New Zealand and Australia). This article first considers the software development methods, practices and tools that are popular in the Australasian software engineering community. We then briefly review the particular strengths of software engineering researchers in Australasia. Finally, we make an open call for collaborators by reflecting on our current position and identifying future opportunities.

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A Data-Driven Method For Online Monitoring Tube Wall Thinning Process In Dynamic Noisy Environment, Chen Zhang, Jun Long Lim, Ouyang Liu, Aayush Madan, Yongwei Zhu, Shili Xiang, Kai Wu, Rebecca Yen-Ni Wong, Jiliang Eugene Phua, Karan M. Sabnani, Keng Boon Siah, Wenyu Jiang, Yixin Wang, Emily Jianzhong Hao, Hoi, Steven C. H. Jan 2021

A Data-Driven Method For Online Monitoring Tube Wall Thinning Process In Dynamic Noisy Environment, Chen Zhang, Jun Long Lim, Ouyang Liu, Aayush Madan, Yongwei Zhu, Shili Xiang, Kai Wu, Rebecca Yen-Ni Wong, Jiliang Eugene Phua, Karan M. Sabnani, Keng Boon Siah, Wenyu Jiang, Yixin Wang, Emily Jianzhong Hao, Hoi, Steven C. H.

Research Collection School Of Computing and Information Systems

Tube internal erosion, which corresponds to its wall thinning process, is one of the major safety concerns for tubes. Many sensing technologies have been developed to detect a tube wall thinning process. Among them, fiber Bragg grating (FBG) sensors are the most popular ones due to their precise measurement properties. Most of the current works focus on how to design different types of FBG sensors according to certain physical laws and only test their sensors in controlled laboratory conditions. However, in practice, an industrial system usually suffers from harsh and dynamic environmental conditions, and FBG signals are affected by many …

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Peer-To-Peer Trade And The Economy Of Distributed Pv In China, Peiyun Song, Yiou Zhou, Jiahai Yuan Jan 2021

Peer-To-Peer Trade And The Economy Of Distributed Pv In China, Peiyun Song, Yiou Zhou, Jiahai Yuan

Research Collection School Of Computing and Information Systems

With the deepening of power market reform, distributed power generation is gaining momentum. This paper tests the distributed photovoltaic (DPV) economy under different business models by taking three provinces to stand for typical resource zones. The Internal return rate (IRR) is used to measure the economy, while the improved levelized cost of electricity (LCOE) is used to model the generation cost. Three business modes, namely pure producer (all generation sold to the grid), prosumer (self-use and the rest sold to the grid), and peer-to-peer trade (P2P, all generation traded via the grid) are studied. Results show that peer-to-peer trade is …

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Attribute-Aware Pedestrian Detection In A Crowd, Jialiang Zhang, Lixiang Lin, Jianke Zhu, Yang Li, Yun-Chen Chen, Yao Hu, Steven C. H. Hoi Jan 2021

Attribute-Aware Pedestrian Detection In A Crowd, Jialiang Zhang, Lixiang Lin, Jianke Zhu, Yang Li, Yun-Chen Chen, Yao Hu, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Pedestrian detection is an initial step to perform outdoor scene analysis, which plays an essential role in many real-world applications. Although having enjoyed the merits of deep learning frameworks from the generic object detectors, pedestrian detection is still a very challenging task due to heavy occlusions, and highly crowded group. Generally, the conventional detectors are unable to differentiate individuals from each other effectively under such a dense environment. To tackle this critical problem, we propose an attribute-aware pedestrian detector to explicitly model people's semantic attributes in a high-level feature detection fashion. Besides the typical semantic features, center position, target's scale, …

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Can We Trust Your Explanations? Sanity Checks For Interpreters In Android Malware Analysis, Min Fan, Wenying Wei, Xiaofei Xie, Yang Liu, Xiaohong Guan, Ting Liu Jan 2021

Can We Trust Your Explanations? Sanity Checks For Interpreters In Android Malware Analysis, Min Fan, Wenying Wei, Xiaofei Xie, Yang Liu, Xiaohong Guan, Ting Liu

Research Collection School Of Computing and Information Systems

With the rapid growth of Android malware, many machine learning-based malware analysis approaches are proposed to mitigate the severe phenomenon. However, such classifiers are opaque, non-intuitive, and difficult for analysts to understand the inner decision reason. For this reason, a variety of explanation approaches are proposed to interpret predictions by providing important features. Unfortunately, the explanation results obtained in the malware analysis domain cannot achieve a consensus in general, which makes the analysts confused about whether they can trust such results. In this work, we propose principled guidelines to assess the quality of five explanation approaches by designing three critical …

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Fakespotter: A Simple Yet Robust Baseline For Spotting Ai-Synthesized Fake Faces, Run Wang, Felix Juefei-Xu, Lei Ma, Xiaofei Xie, Yihao Huang, Jian Wang, Yang Liu Jan 2021

Fakespotter: A Simple Yet Robust Baseline For Spotting Ai-Synthesized Fake Faces, Run Wang, Felix Juefei-Xu, Lei Ma, Xiaofei Xie, Yihao Huang, Jian Wang, Yang Liu

Research Collection School Of Computing and Information Systems

In recent years, generative adversarial networks (GANs) and its variants have achieved unprecedented success in image synthesis. They are widely adopted in synthesizing facial images which brings potential security concerns to humans as the fakes spread and fuel the misinformation. However, robust detectors of these AI-synthesized fake faces are still in their infancy and are not ready to fully tackle this emerging challenge. In this work, we propose a novel approach, named FakeSpotter, based on monitoring neuron behaviors to spot AIsynthesized fake faces. The studies on neuron coverage and interactions have successfully shown that they can be served as testing …

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Performance-Based Iadl Evaluation Of Older Adults With Cognitive Impairment Within A Smart Home: A Feasibility Study, Iris Rawtaer, Khalid Abdul Jabbar, Xiao Liu, Thit Thit Htat Ying, Anh Thuy Giang, Philip Lin Kiat Yap, Rachel Chin Yee Cheong, Hwee-Pink Tan, Pius Lee Wei Qi, Shiou Liang Wee, Tze Pin Ng Jan 2021

Performance-Based Iadl Evaluation Of Older Adults With Cognitive Impairment Within A Smart Home: A Feasibility Study, Iris Rawtaer, Khalid Abdul Jabbar, Xiao Liu, Thit Thit Htat Ying, Anh Thuy Giang, Philip Lin Kiat Yap, Rachel Chin Yee Cheong, Hwee-Pink Tan, Pius Lee Wei Qi, Shiou Liang Wee, Tze Pin Ng

Research Collection School Of Computing and Information Systems

Introduction Mild cognitive impairment (MCI) is characterized by subtle deficits that functional assessment via informant-report measures may not detect. Sensors can potentially detect deficits in everyday functioning in MCI. This study aims to establish feasibility and acceptability of using sensors in a smart home for performance-based assessments of two instrumental activities of daily living (IADLs). Methods Thirty-five older adults (>65 years) performed two IADL tasks in a smart home laboratory equipped with sensors and a web camera. Participants' cognitive states were determined using published criteria including measures of global cognition and comprehensive neuropsychological test batteries. Selected subtasks of the …

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Unsupervised Representation Learning By Predicting Random Distances, Hu Wang, Guansong Pang, Chunhua Shen, Congbo Ma Jan 2021

Unsupervised Representation Learning By Predicting Random Distances, Hu Wang, Guansong Pang, Chunhua Shen, Congbo Ma

Research Collection School Of Computing and Information Systems

Deep neural networks have gained great success in a broad range of tasks due to its remarkable capability to learn semantically rich features from high-dimensional data. However, they often require large-scale labelled data to successfully learn such features, which significantly hinders their adaption in unsupervised learning tasks, such as anomaly detection and clustering, and limits their applications to critical domains where obtaining massive labelled data is prohibitively expensive. To enable unsupervised learning on those domains, in this work we propose to learn features without using any labelled data by training neural networks to predict data distances in a randomly projected …

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Who Am I?: Towards Social Self-Awareness For Intelligent Agents, Budhitama Subagdja, Han Yi Tay, Ah-Hwee Tan Jan 2021

Who Am I?: Towards Social Self-Awareness For Intelligent Agents, Budhitama Subagdja, Han Yi Tay, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Most of today’s AI technologies are geared towards mastering specific tasks performance through learning from a huge volume of data. However, less attention has still been given to make the AI understand its own purposes or be responsible socially. In this paper, a new model of agent is presented with the capacity to represent itself as a distinct individual with identity, a mind of its own, unique experiences, and social lives. In this way, the agent can interact with its surroundings and other agents seamlessly and meaningfully. A practical framework for developing an agent architecture with this model of self …

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The Value Of Humanization In Customer Service, Yang Gao, Huaxia Rui, Shujing Sun Jan 2021

The Value Of Humanization In Customer Service, Yang Gao, Huaxia Rui, Shujing Sun

Research Collection School Of Computing and Information Systems

As algorithm-based agents become increasingly capable of handling customer service queries, customers are often uncertain whether they are served by humans or algorithms, and managers are left to question the value of human agents once the technology matures. The current paper studies this question by quantifying the impact of customers' enhanced perception of being served by human agents on customer service interactions. Our identification strategy hinges on the abrupt implementation by Southwest Airlines of a signature policy, which requires the inclusion of an agent's first name in responses on Twitter, thereby making the agent more humanized in the eyes of …

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Chronic Customers Or Increased Awareness? The Dynamics Of Social Media Customer Service, Shujing Sun, Yang Gao, Huaxia Rui Jan 2021

Chronic Customers Or Increased Awareness? The Dynamics Of Social Media Customer Service, Shujing Sun, Yang Gao, Huaxia Rui

Research Collection School Of Computing and Information Systems

Despite that social media has become a promising alternative to traditional call centers, managers hesitate to fully harness its power because they worry that active service intervention may encourage excessive use of the channel by disgruntled customers. This paper sheds light on such a concern by examining the dynamics between brand-level customer complaints and service interventions on social media. Using details of customer-brand interactions of 40 airlines on Twitter, we find that more service interventions indeed cause more customer complaints, accounting for the online customer population and service quality. However, the increased complaints are primarily driven by the awareness enhancement …

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Anticipating And Adapting To The Future Impacts Of Climate Change On The Health, Security And Welfare Of Low Elevation Coastal Zone (Lecz) Communities In Southeastern Usa, Thomas Allen, Joshua Behr, Anamaria Bukvic, Ryan S.D. Calder, Kiki Caruson, Charles Connor, Christopher D'Elia, David Dismukes, Robin Ersing, Rima Franklin, Jesse Goldstein, Jonathon Goodall, Scott Hemmerling, Jennifer Irish, Steven Lazarus, Derek Loftis, Mark Luther, Leigh Mccallister, Karen Mcglathery, Molly Mitchell, William Moore, Charles Reid Nichols, Karinna Nunez, Matthew Reidenbach, Julie Shortridge, Robert Weisberg, Robert Weiss, Lynn Donelson Wright, Meng Xia, Kehui Xu, Donald Young, Gary Zarillo, Julie C. Zinnert Jan 2021

Anticipating And Adapting To The Future Impacts Of Climate Change On The Health, Security And Welfare Of Low Elevation Coastal Zone (Lecz) Communities In Southeastern Usa, Thomas Allen, Joshua Behr, Anamaria Bukvic, Ryan S.D. Calder, Kiki Caruson, Charles Connor, Christopher D'Elia, David Dismukes, Robin Ersing, Rima Franklin, Jesse Goldstein, Jonathon Goodall, Scott Hemmerling, Jennifer Irish, Steven Lazarus, Derek Loftis, Mark Luther, Leigh Mccallister, Karen Mcglathery, Molly Mitchell, William Moore, Charles Reid Nichols, Karinna Nunez, Matthew Reidenbach, Julie Shortridge, Robert Weisberg, Robert Weiss, Lynn Donelson Wright, Meng Xia, Kehui Xu, Donald Young, Gary Zarillo, Julie C. Zinnert

Political Science & Geography Faculty Publications

Low elevation coastal zones (LECZ) are extensive throughout the southeastern United States. LECZ communities are threatened by inundation from sea level rise, storm surge, wetland degradation, land subsidence, and hydrological flooding. Communication among scientists, stakeholders, policy makers and minority and poor residents must improve. We must predict processes spanning the ecological, physical, social, and health sciences. Communities need to address linkages of (1) human and socioeconomic vulnerabilities; (2) public health and safety; (3) economic concerns; (4) land loss; (5) wetland threats; and (6) coastal inundation. Essential capabilities must include a network to assemble and distribute data and model code to …

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Coordination, Adaptation, And Complexity In Decision Fusion, Weiqiang Dong Dec 2020

Coordination, Adaptation, And Complexity In Decision Fusion, Weiqiang Dong

Dissertations

A parallel decentralized binary decision fusion architecture employs a bank of local detectors (LDs) that access a commonly-observed phenomenon. The system makes a binary decision about the phenomenon, accepting one of two hypotheses (H0 (“absent”) or H1 (“present”)). The k 1 LD uses a local decision rule to compress its local observations yk into a binary local decision uk; uk = 0 if the k 1 LD accepts H0 and uk = 1 if it accepts H1. The k 1 LD sends its decision uk over a noiseless dedicated channel to a Data Fusion Center (DFC). The DFC combines the …

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Drone-Assisted Emergency Communications, Di Wu Dec 2020

Drone-Assisted Emergency Communications, Di Wu

Dissertations

Drone-mounted base stations (DBSs) have been proposed to extend coverage and improve communications between mobile users (MUs) and their corresponding macro base stations (MBSs). Different from the base stations on the ground, DBSs can flexibly fly over and close to MUs to establish a better vantage for communications. Thus, the pathloss between a DBS and an MU can be much smaller than that between the MU and MBS. In addition, by hovering in the air, the DBS can likely establish a Line-of-Sight link to the MBS. DBSs can be leveraged to recover communications in a large natural disaster struck area …

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A Deep Machine Learning Approach For Predicting Freeway Work Zone Delay Using Big Data, Abdullah Shabarek Dec 2020

A Deep Machine Learning Approach For Predicting Freeway Work Zone Delay Using Big Data, Abdullah Shabarek

Dissertations

The introduction of deep learning and big data analytics may significantly elevate the performance of traffic speed prediction. Work zones become one of the most critical factors causing congestion impact, which reduces the mobility as well as traffic safety. A comprehensive literature review on existing work zone delay prediction models (i.e., parametric, simulation and non-parametric models) is conducted in this research. The research shows the limitations of each model. Moreover, most previous modeling approaches did not consider user delay for connected freeways when predicting traffic speed under work zone conditions. This research proposes Deep Artificial Neural Network (Deep ANN) and …

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Supporting User Interaction And Social Relationship Formation In A Collaborative Online Shopping Context, Yu Xu Dec 2020

Supporting User Interaction And Social Relationship Formation In A Collaborative Online Shopping Context, Yu Xu

Dissertations

The combination of online shopping and social media allow people with similar shopping interests and experiences to share, comment, and discuss about shopping from anywhere and at any time, which also leads to the emergence of online shopping communities. Today, more people turn to online platforms to share their opinions about products, solicit various opinions from their friends, family members, and other customers, and have fun through interactions with others with similar interests. This dissertation explores how collaborative online shopping presents itself as a context and platform for users' interpersonal interactions and social relationship formation through a series of studies. …

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Performance Optimization Of Big Data Computing Workflows For Batch And Stream Data Processing In Multi-Clouds, Huiyan Cao Dec 2020

Performance Optimization Of Big Data Computing Workflows For Batch And Stream Data Processing In Multi-Clouds, Huiyan Cao

Dissertations

Workflow techniques have been widely used as a major computing solution in many science domains. With the rapid deployment of cloud infrastructures around the globe and the economic benefits of cloud-based computing and storage services, an increasing number of scientific workflows have migrated or are in active transition to clouds. As the scale of scientific applications continues to grow, it is now common to deploy various data- and network-intensive computing workflows such as serial computing workflows, MapReduce/Spark-based workflows, and Storm-based stream data processing workflows in multi-cloud environments, where inter-cloud data transfer oftentimes plays a significant role in both workflow performance …

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Inexact Tensor Methods And Their Application To Stochastic Convex Optimization, Artem Agafonov, Dmitry Kamzolov, Pavel Dvurechensky, Alexander Gasnikov, Martin Takac Dec 2020

Inexact Tensor Methods And Their Application To Stochastic Convex Optimization, Artem Agafonov, Dmitry Kamzolov, Pavel Dvurechensky, Alexander Gasnikov, Martin Takac

Machine Learning Faculty Publications

We propose general non-accelerated and accelerated tensor methods under inexact information on the derivatives of the objective, analyze their convergence rate. Further, we provide conditions for the inexactness in each derivative that is sufficient for each algorithm to achieve a desired accuracy. As a corollary, we propose stochastic tensor methods for convex optimization and obtain sufficient mini-batch sizes for each derivative. © 2020, CC BY.

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Semantic, Integrated Keyword Search Over Structured And Loosely Structured Databases, Xinge Lu Dec 2020

Semantic, Integrated Keyword Search Over Structured And Loosely Structured Databases, Xinge Lu

Dissertations

Keyword search has been seen in recent years as an attractive way for querying data with some form of structure. Indeed, it allows simple users to extract information from databases without mastering a complex structured query language and without having knowledge of the schema of the data. It also allows for integrated search of heterogeneous data sources. However, as keyword queries are ambiguous and not expressive enough, keyword search cannot scale satisfactorily on big datasets and the answers are, in general, of low accuracy. Therefore, flat keyword search alone cannot efficiently return high quality results on large data with structure. …

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Countering Internet Packet Classifiers To Improve User Online Privacy, Sina Fathi-Kazerooni Dec 2020

Countering Internet Packet Classifiers To Improve User Online Privacy, Sina Fathi-Kazerooni

Dissertations

Internet traffic classification or packet classification is the act of classifying packets using the extracted statistical data from the transmitted packets on a computer network. Internet traffic classification is an essential tool for Internet service providers to manage network traffic, provide users with the intended quality of service (QoS), and perform surveillance. QoS measures prioritize a network's traffic type over other traffic based on preset criteria; for instance, it gives higher priority or bandwidth to video traffic over website browsing traffic. Internet packet classification methods are also used for automated intrusion detection. They analyze incoming traffic patterns and identify malicious …

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Pengembangan Sistem Informasi Pemasaran Produk Pertanian Berbasis Website, Veronika Asri Tandirerung, Syahrul Syahrul, Achmad Padil Dec 2020

Pengembangan Sistem Informasi Pemasaran Produk Pertanian Berbasis Website, Veronika Asri Tandirerung, Syahrul Syahrul, Achmad Padil

Elinvo (Electronics, Informatics, and Vocational Education)

Pengembangan sistem informasi pemasaran produk pertanian (SIPTANI) dibutuhkan untuk membantu para petani dalam memasarkan produk-produk pertanian khususnya di era pandemic Covid-19. Penelitian ini merupakan penelitian pengembangan sistem dengan model pengembangan prototype dengan studi kelayakan menggunakan standar ISO 9126. Data penelitian diperoleh dari hasil observasi dan pengisian kuesioner oleh responden. Hasil pengujian aplikasi diperoleh dengan menganalisis aspek-aspek pada functional suitability, usability, compatibility, dan portability. Pada aspek functional suitability berada pada kategori layak diterima. Pada aspek usability, kategori sangat setuju memiliki dengan persentase 90%, sehingga aplikasi dinyatakan layak dan ditanggapi baik oleh pengguna. Pada aspek compatibility, sistem pemasaran pertanian ini dapat …

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Penggunaan Analytical Hierarchy Process (Ahp) Pada Penentuan Prioritas Supplier Food Chemical Di Pt. Garuda Hidrotive Internasional, Nehemia Hadiwijaya, Jenie Sundari Dec 2020

Penggunaan Analytical Hierarchy Process (Ahp) Pada Penentuan Prioritas Supplier Food Chemical Di Pt. Garuda Hidrotive Internasional, Nehemia Hadiwijaya, Jenie Sundari

Elinvo (Electronics, Informatics, and Vocational Education)

Abstract-Supplier selection is one of the important things in purchasing activities for companies. Supplier selection is a multi-criteria problem which includes quantitative and qualitative factors. One method that can be used for supplier selection is the AHP (Analytical Hierarchy Process) method. The problems that will be discussed in this study are: (1) how is the order of priority criteria and sub-criteria in the selection of suppliers at PT Garuda Hidrotive International? (2) which supplier / supplier should PT Garuda Hidrotive International choose based on the AHP method? The sampling technique uses judgment sampling because the AHP method requires dependence on …

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Penerapan Model Utaut 2 Untuk Mengetahui Faktor-Faktor Yang Memengaruhi Penggunaan Siortu, Nur Azmi Ainul Bashir Dec 2020

Penerapan Model Utaut 2 Untuk Mengetahui Faktor-Faktor Yang Memengaruhi Penggunaan Siortu, Nur Azmi Ainul Bashir

Elinvo (Electronics, Informatics, and Vocational Education)

Layanan sistem informasi akademik untuk orang tua (SIORTU) telah banyak diterapkan di kampus-kampus, salah satunya adalah Universitas Islam Indonesia (UII). Nama resmi SIORTU UII yaitu UNISYS untuk orang tua. Belum banyak orang tua atau wali mahasiswa yang menggunakan SIORTU. Tercatat hanya 7.361 akun SIORTU yang aktif pada rentang April 2018 s.d Maret 2019. Jumlah tersebut hanya 36.68% dari jumlah akun yang disediakan untuk orang tua mahasiswa angkatan 2015-2018 yaitu 20.068 akun. Penelitian ini merupakan pengembangan penelitian yang telah dilakukan sebelumnya. Penelitian ini merupakan penelitian kuantitatif. Data yang dianalisis diperoleh dari data penelitian yang dikembangkan. Tujuan penelitian ini adalah mengetahui pengaruh …

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Optimalisasi Media Penyimpanan Pada Sistem Inventori Stok Barang Untuk Pt. Multi Usaha Sejahtera Jaya Menggunakan Metode Goldbach Codes, Angga Debby Frayudha, Siti Purwanti Dec 2020

Optimalisasi Media Penyimpanan Pada Sistem Inventori Stok Barang Untuk Pt. Multi Usaha Sejahtera Jaya Menggunakan Metode Goldbach Codes, Angga Debby Frayudha, Siti Purwanti

Elinvo (Electronics, Informatics, and Vocational Education)

Pengelolaan data secara konvensional, baik manual pada buku maupun penggunaan aplikasi pengolah data (kata atau angka) dinilai masih memiliki keterbatasan terutama dalam hal keterjangkauan akses dan pengelolaan. Sistem informasi inventori mampu menyajikan pengelolaan data berupa informasi-informasi yang dibutuhkan untuk produktivitas tempat usaha sesuai karakteristik pengguna informasi pada tempat usaha tersebut. Lebih lanjut untuk proses transmisi data yang lebih baik, diperlukan optimalisasi media penyimpanan melalui teknik kompresi data tertentu. Salah satu algoritma kompresi data teks yang memiliki keunggulan pada optimalisasi ukuran hasil kompresi adalah Goldbach Codes. Artikel ini mendeskripsikan pengembangan sistem pengelolaan inventori dengan kemampuan dapat menyimpan maupun mengubah data stok …

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