检索结果-内蒙古大学图书馆

International Conference on Information Management and Technology (ICIMTech)

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

Relationship with customers is one of the most crucial factors in business continuity and development. Many current businesses have started delving into Customer Relationship Management (CRM) to establish and maintain their sales and customer relationships. This research was conducted on one retail company that implements CRM but experiencing a gap in their unit sales performance between their targeted sales and the realization. This study aims to analyze the gaps causing factors using Factor Analysis Method, constructing a suitable regression model, and proposing the company's necessary strategy. The research was conducted quantitatively using a questionnaire from 264 respondents. The result of this study showed that there are five causing factors which are CRM Reliability, Underutilization of CRM, CRM Capability, CRM Unpreparedness, and Customer Relation Quality, as well as forming a regression model of the company's CRM performance.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Development of Key Performance Indicators in e-Learning Implementation in Higher Education Institutions

Development of Key Performance Indicators in e-Learning Impl...

引用

International Conference on Information Management and Technology (ICIMTech)

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.

关键词：

来源：评论

学校读者我要写书评

暂无评论

The Smart Analysis of Performing Scalable Inference for Big Data Analytics

The Smart Analysis of Performing Scalable Inference for Big ...

引用

2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Bhandarkar, Vishakha D. Rongali, Aruna Sri Shamout, Mohamed Dawood Pund, Sachin Nama, Gigih Forda Patil, Shrishailappa Yeshwantrao Chavan College of Engineering Applied Mathematics and Humanities India University of the Cumberlands Graduate Doctoral Information Technology Information Technology Emphasis/Information Technology United States College of Business Administration University of Sharjah Department of Management Sharjah United Arab Emirates Shri Ramdeobaba College of Engineering and Management Department of Industrial Engineering Maharashtra Nagpur India Doctoral Program of Environtmental Science University of Lampung Department of Informatics Bandar Lampung Indonesia Vishwakarma Institute of Technology Computer Engineering Pune India

ISBN: (纸本)9798350357769

This paper examines the reproducibility of massive information analytics under particular factors. The paper proposes the 'performing Scalable Inference' technique to cope with scalability troubles and to exploit current big statistics platforms for efficient computing and statistics garage of the statistics. In particular, the paper describes how to perform leak-free, parallelizable visible analytics over massive datasets using present extensive records analytics frameworks such as Apache Flink. This method presents an automated manner to execute analytics that preserves reproducibility and the ability to make adjustments without re-running the entire technique. The paper also demonstrates how these analytics may help several real-world use instances, explore affected person cohorts for studies, and develop stratified patient cohorts for hospital therapy. In the end, the paper observes how the proposed method may be exercised within the real world. Actively scalable inference for massive information analytics is pivotal in optimizing decision-making and allocation of assets. Typically, such inferences are made based on information accumulated from numerous sources, databases, unstructured data, and different digital sources. So one can ensure scalability, a complete cloud-primarily based platform has to be hired. This solution will permit the ***, deploying the essential records series and evaluation algorithms are prime here. It could permit the platform to recognize the styles inside the statistics and discover any ability correlations or traits. Additionally, predictive analytics and system mastering strategies may be incorporated to provide insights into the results of the information. In the long run, by leveraging those techniques, the platform can draw efficient inferences and appropriately compare situations in an agile and green way.. © 2023 IEEE.

关键词： adjustments an a lytics automated preserves statistics

来源：评论

学校读者我要写书评

暂无评论

Air Quality Prediction Based on Air Pollution Emissions in the City Environment Using XGBoost with SMOTE

Air Quality Prediction Based on Air Pollution Emissions in t...

引用

International Conference of computer science and Information Technology

作者： Adli A Nababan Sutarman Muhammad Zarlis Erna B Nababan Department of Computer Science Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Department of Mathematics Faculty of Mathematics and Natural Sciences Universitas Sumatera Utara Medan Indonesia Department of Information Systems Management BINUS Graduate Program-Master of Information Systems Management Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9798350399080

Air pollution makes it worse in populated regions. Indonesia's major cities are also impacted by air pollution. Due to rising traffic, material consumption by vehicles, industrial growth, land burning, and garbage collection, air quality has altered significantly. Accurate measurement and classification of air quality are required. Results of accurate classification aid in forming governmental regulations. To reach the criteria for livable air quality, we intend to manage controls. Some of the characteristics of air pollution include particulate (PM10) or PM25, sulfides (in the form of SO2), carbon monoxide (CO), ozone (O3), and nitrites (NO2). Using the XGBoost algorithm and synthetic minority oversampling (SMOTE) methods based on the Air Pollution Standard Index (ISPU) category, this study seeks to uncover factors that affect air quality. XGBoost, an ensemble machine learning approach built on a decision tree and applying a gradient reinforcement framework, is the classification algorithm in use. Air quality categorization has been tested and shown to work with the XGBoost algorithm. The dataset used in this study is air quality in 2021 which was collected by the Jakarta Environmental Ministry The proposed classification model will be evaluated using the Repeated k-fold cross-validation method for objective results. The results of the study prove that SMOTE and XGBoost have better performance than using only the XGBoost method in predicting air quality, where the overall accuracy value of SMOTE with XGBoost is 99.60%, The overall precision value is 99.60%, the overall recall value is 99.60% and the overall f1-score is 99.60% and the overall ROC AUC value is 99.96%. The overall SMOTE method with the proposed XGBoost has given better performance in air pollution prediction.

关键词： Machine learning algorithms Urban areas Air pollution Prediction algorithms Particle measurements Regulation Classification algorithms

来源：评论

学校读者我要写书评

暂无评论

Dynamic programming Algorithm using Furniture Industry 0/1 Knapsack Problem

Dynamic Programming Algorithm using Furniture Industry 0/1 K...

引用

International Conference on Cybernetics and Intelligent System (ICORIS)

作者： Mietha Anditta Natashya Amartya Laurens Spits Warnars Harco Leslie Hendric Spits Warnars Arief Ramadhan Teddy Siswanto Teddy Mantoro Nurulhuda Noordin Computer Science Departement School of Computer Science Bina Nusantara University Jakarta Indonesia Information Systems Departement School of Information Systems Bina Nusantara University Jakarta Indonesia Computer Science Departement BINUS Graduate Program - Computer Science Bina Nusantara University Jakarta Indonesia PJJ Informatika Telkom University Bandung Indonesia Information Systems Department Trisakti University Jakarta Indonesia Faculty of Engineering and Technology Sampoerna University Jakarta Indonesia School of Computing Sciences College of Computing Informatics and Mathematics Universiti Teknologi MARA Selangor Malaysia

Dynamic programming is a fundamental algorithm that can be found in our daily lives easily. One of the dynamic programming algorithm implementations consists of solving the 0/1 knapsack problem. A 0/1 knapsack problem can be seen from industrial production cost. It is prevalent that a production cost has to be as efficient as possible, but the expectation is to get the proceeds of the products higher. Thus, the dynamic programming algorithm can be implemented to solve the diverse knapsack problem, one of which is the 0/1 knapsack problem, which would be the main focus of this paper. The implementation was implemented using C language. This paper was created as an early implementation algorithm using a Dynamic program algorithm applied to an Automatic Identification System (AIS) dataset.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Deep learning performance in sentiment analysis 4

Deep learning performance in sentiment analysis

引用

4th International Conference on Electrical, Telecommunication and computer Engineering, ELTICOM 2020

作者： Manalu, Boy Utomo Tulus Efendi, Syahril Graduate Program of Computer Science Universitas Sumatera Utara Medan Indonesia Universitas Sumatera Utara Department of Mathematics Medan Indonesia Universitas Sumatera Utara Department of Computer Science Medan Indonesia

ISBN: (纸本)9781728188706

A problem of sentiment analysis is the text representation, that encodes text into a continuous vector by arranging projections from semantics to the points in high dimensional space. Deep learning methods have been widely used to solve various sentiment analysis problems. To improve the performance of deep learning in sentiment analysis requires a good method of text representation to be used as an embedding layer. In this study, we analyzed deep learning with the Recurrent Neural Network (RNN) method with Long Short-Term Memory (LSTM) variants in sentiment classification. We compare the performance of the LSTM network with Word2Vec to the network without Word2Vec as word embedding. Sentiment data used is derived from user-provided reviews of the applications in Google Play. The training process involves the Dropout layer and Early Stopping points to prevent overfitting. The results showed that the LSTM network using a word embedding Word2Vec is better than without Word2Vec. LSTM with Word2Vec 300 words dimension got a low error value of 0.3287 with an accuracy of 86.76%. While the LSTM testing results without Word2Vec get the lowest error of 0.3751 with an accuracy of 84.14%. © 2020 IEEE.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

Bounding the sum of the largest signless Laplacian eigenvalues of a graph

arXiv

引用

arXiv 2022年

作者： Abiad, Aida de Lima, Leonardo Kalantarzadeh, Sina Mohammadi, Mona Oliveira, Carla Department of Mathematics and Computer Science Eindhoven University of Technology Netherlands Department of Mathematics: Analysis Logic and Discrete Mathematics Ghent University Belgium Department of Mathematics and Data Science Vrije Universiteit Brussel Belgium Graduate Program in Mathematics Federal University of Parana Curitiba Brazil Sharif University of Technology Iran Department of Mathematical National School of Statistical Sciences Rio de Janeiro Brazil

关键词： Eigenvalues and eigenfunctions

来源：评论

学校读者我要写书评

暂无评论

More Efficient Identifiability Verification in ODE Models by Reducing Non-Identifiability

arXiv

引用

arXiv 2022年

作者： Ilmer, Ilia Ovchinnikov, Alexey Soto, Pedro Pogudin, Gleb Program in Computer Science Graduate Center CUNY New YorkNY United States Program in Mathematics CUNY Queens College New YorkNY United States LIX CNRS École Polytechnique Institute Polytechnique de Paris Paris France

Structural global parameter identifiability indicates whether one can determine a parameter’s value from given inputs and outputs in the absence of noise. If a given model has parameters for which there may be infinitely many values, such parameters are called non-identifiable. We present a procedure for accelerating a global identifiability query by eliminating algebraically independent non-identifiable parameters. Our proposed approach significantly improves performance across different computer algebra frameworks. © 2022, CC BY-SA.

关键词： Algebra

来源：评论

学校读者我要写书评

暂无评论

Compression for qubit clocks

arXiv

引用

arXiv 2022年

作者： Yang, Yuxiang Chiribella, Giulio Hayashi, Masahito Department of Computer Science The University of Hong Kong Hong Kong Department of Computer Science The University of Oxford United Kingdom Canadian Institute for Advanced Research CIFAR Program in Quantum Information Science Canada Graduate School of Mathematics Nagoya University Japan Centre for Quantum Technologies National University of Singapore Singapore

Two-level (qubit) clock systems are often used to perform precise measurement of time. In this work, we propose a compression protocol for n identically prepared states of qubit clocks. The protocol faithfully encodes the states into (1/2) log n qubits and (1/2) log n classical bits and works even in the presence of noise. If the purity of the clock states is fixed, (1/2) log n qubits are sufficient. We also prove that this protocol requires the minimum amount of total memory among all protocols with vanishing error in the large n limit. Copyright © 2022, The Authors. All rights reserved.

关键词： Quantum optics

来源：评论

学校读者我要写书评

暂无评论

Implementing the Haversine Formula for Detecting Societal Issues and Delivering Relevant Preaching Content

Implementing the Haversine Formula for Detecting Societal Is...

引用

International Conference on Electrical Engineering and Informatics (ICon EEI)

作者： Rahmad Kurniawan Fatayat Tisha Melia Evfi Mahdiyah Abdul Somad Batubara Imam Ghozali Ilyas Husti Department of Computer Science Faculty of Mathematics and Natural Sciences Universitas Riau Pekanbaru Indonesia Bandar Seri Begawan Brunei Darussalam Universiti Islam Sultan Sharif Ali Brunei Darussalam Sekolah Tinggi Agama Islam Negeri (STAIN) Bengkalis Bengkalis Indonesia Graduate Program Universitas Islam Negeri Sultan Syarif Kasim Riau Pekanbaru Indonesia

ISBN: (数字)9798331540791

ISBN: (纸本)9798331540807

The effectiveness of Islamic preaching is often hindered by the need for localized data on societal issues, which leads to lectures that may not address the community’s specific needs. This study seeks to bridge this gap by developing a system that provides relevant preaching outlines tailored to issues detected within a 1 km radius of a mosque. The system incorporates data from 185 mosques and is enhanced by integrating societal issues as a feature. The Haversine formula was employed for precise distance calculations to identify nearby issues accurately. Blackbox testing verified that the system functions correctly. In addition, response time experiments showed an average time of 0.17 seconds. This result highlights the system's overall efficiency in delivering quick responses. Furthermore, a user acceptance test involving eight Islamic preachers revealed high satisfaction with the system’s ease of understanding, as indicated by a mean score of 4.75. These findings suggest that the system effectively supports preachers in delivering contextually relevant preaching and enhances the impact of their preaching efforts by aligning them with the specific concerns of the communities. This innovative approach marks a significant step forward in using geospatial intelligence for religious outreach, with future developments planned to integrate AI to generate dynamic content for various Islamic occasions.

关键词： Electrical engineering Bridges Closed box Geospatial analysis Time factors Artificial intelligence Informatics Testing

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：