Evaluation of Service Quality Through ITIL V3 Framework in the Service Design Domain (Case Study: Lazada Application)

In the era of globalization and business digitalization, improving the quality of customer service is a crucial aspect for company success. Companies that are able to provide optimal and responsive service tend to maintain customer satisfaction and compete effectively in an increasingly tight market. Therefore, the use of the Information Technology Infrastructure Library (ITIL) framework is a strong foundation for managing and improving service quality. This research focuses on analyzing service quality in the ITIL V3 Service Design domain, by applying this framework to a significant e-commerce application, namely Lazada. Lazada, as a leading platform in Southeast Asia, has been an example of providing superior customer experience through its services. This research explains the role of ITIL in managing service quality, with an emphasis on the Service Design domain. This study uses a combination of methods, including literature study, questionnaire survey of Lazada users, and observation of application infrastructure. The analysis results show that Lazada has reached a high level of maturity in ITIL V3 Domain Service Design, with all subdomains reaching maturity level 4. However, there is room for improvement, especially in information security. The conclusion shows that Lazada can continue to maintain customer satisfaction and competitiveness in a competitive market by continuing to improve service quality, especially in aspects found through gap analysis

Investigation into Data Mining for Analysis and Optimization of Direct Maintenance Costs in Civil Aircraft Operations

Civil aircraft maintenance cost is an important indicator to measure the maintainability and economy of civil aircraft, and it accounts for a considerable proportion of aircraft operating costs. Data mining technology can unearth potentially high-value data from massive aircraft operating data. In this paper, aiming at the problem that there are very few actual aircraft maintenance data that can be effectively used in the development stage of civil aircraft, the research on the direct maintenance cost analysis and optimization method of civil aircraft based on data mining is carried out. The theoretical basis of direct maintenance cost analysis based on data mining is studied, the factors affecting the direct maintenance cost of civil aircraft are analyzed based on data mining, and the DMC analysis method is established. On the basis of the above research, the direct maintenance cost analysis model of civil aircraft was established and optimized to achieve the goal of reducing direct maintenance costs. It is of great significance for reducing aircraft life cycle costs and improving aircraft market competitiveness

Chord Recognition in Music Using a Robust Pitch Class Profile (PCP) Feature and Support Vector Machines (SVM)

Music is the most direct and effective means to express emotion, and the effective identification of music works can help us better understand the works and realize the correct interpretation of music. This paper takes robust PCP feature and SVM as the research object. Firstly, the related concepts of terms and a large number of robust CFO description chord spectrum methods used in audio analysis are introduced. Secondly, it expounds the correlation between SVM and speech tonality, designs the system of music chord recognition, tests the performance of the system, and focuses on the test in the direction of recognition rate. Finally, the test results show that the system greatly improves the recognition of music chords with the support of robustness feature optimization and SVM pattern

Factors Affecting Security Information Systems : Information Security, Threats and Cyber Attack, Physical Security, and Information Technology

Information systems are very important to support various organizational and individual activities. Therefore, information system security is an important issue in today's digital era, where it is very important to pay attention to the protection of sensitive data and information. This research aims to identify and analyze factors that influence information system security. These factors include information system security, cyber threats and attacks, physical security, and information technology. Each factor is thoroughly analyzed to understand its impact on information system security. The results of this research will help improve our understanding of the factors that influence information system security. These findings can be used as a basis for creating effective security policies in protecting the information assets owned by the organization. By understanding these things, organizations can optimize their security efforts against the ever-evolving security threats in today's digital world

Exploring Transformer Life Forecasting through an In-Depth Analysis Utilizing the Random Forest Algorithm in Research and Development

Accurately assessing the life and operating status of transformers has important guiding significance for the formulation of maintenance strategies for power grid companies, and at the same time plays a key role in the risk management of power grid companies. However, the traditional methods for predicting the remaining life of the equipment have the problems of insufficient accuracy or long data training time. In order to achieve a more accurate assessment of the life and status of the transformer, a random forest-based transformer life prediction method is constructed in this paper. Relying on the theory of big data analysis, by mining and analyzing the accumulated data of massive transformers, the life prediction model of the transformer is established and the characteristic parameters affecting the life of the transformer are extracted to predict the life of the transformer. The experimental data research demonstrates that the model can be accurate and effective Predicting the life of transformers has higher prediction accuracy than traditional methods, providing method references for asset management and risk management of power grid companies

The Research and Application of Adjustable Drive Improve Oil Recovery Technology in Ansai Low Permeable Fracture Reservoir

In order to solve the serious problem that the injected water channeling is serious and water flooding effect is getting worse in Ansai low permeability fractured reservoir. Developed the gelling movable gel profile control displacement-agent RD which Can control the gel time and the strength. Select out the surfactant XSY-1 that can reduce water interfacial tension to ultra-low and can significantly improve oil displacement efficiency. Designed five group profiling experiments on parallel cores, optimized movable frozen rubber slug of surfactant slug best combination of 0.2 of the PV profile control agent add 0.40 PV surfactant, compared with the water flooding ways to enhance oil recovery of 22.5％ . Adjustable drive combined with technology is the effective way to improve the Ansai low permeability fractured reservoir water flooding effect

Study on the Ideological and Political Practice Teaching of College Students Based on the Internet + Technology

At present, although the ideological and political courses in Colleges anduniversities include practical teaching, there are many problems in practical teaching. Therefore, the reform of College Students' Ideological and political practice teachingmode has become a key research issue. Through the practical teaching mode, wecanenhance the attraction of Ideological and political course, which will improvetheteaching effect. This paper first analysis the importance of practical teachingintheideological and political course. Then, this paper puts forward some problems inpractical teaching. Finally, some suggestions are put forward

Research on Data Fusion Algorithm of Intelligent Building Based on Internet of Things Technology

In an era of sustained economic growth and rising living standards, the demand for housing continues to increase significantly, driving the development of the construction industry and the inevitable transformation of architectural digitization as a prevailing trend. This circumstance has generated limitless economic opportunities across various construction-related sectors, including building materials, technology, and related services. Simultaneously, the evolving Internet of Things (IoT) technology has paved the way for the digitization of buildings, revolutionizing the entire process of architectural design, construction, and management. Architectural digitization enables real-time monitoring, in-depth data analysis, and the optimization of building efficiencies, encompassing energy management, temperature control, and lighting systems. In the current landscape, architectural digitization has given rise to smart buildings that can effectively control nearly all aspects, from temperature and lighting to security systems and comfort. Furthermore, IoT technology has facilitated addressing sustainability challenges by enabling more efficient and sustainable energy management—an essential aspect of the journey toward environmentally friendly buildings. Nevertheless, on the path to fully interconnected digital buildings, there are challenges that must be addressed, such as data security and user privacy, both of which require special attention. Looking forward, research directions include the development of more sophisticated digital integration algorithms, enhanced data security, and the integration of artificial intelligence into building management. The future of architectural digitization holds great promise, with the potential to create more efficient, secure, and environmentally friendly buildings. To achieve these goals, it is essential to strengthen cross-sector collaboration, receive government support, and emphasize research and innovation in the field of architectural digitization

Analysis of Information Technology Service Management Using ITIL V3 Domain Service Operation at Company XYZ

The rapid development of information technology and excellent technology services have become the aspiration for everyone, organizations, institutions, and universities to support their activities, facilitate their tasks, and streamline their business processes. An enterprise organization needs to adapt to the current information technology trends. Managing IT services is a centralized method focusing on consumers' perspective of IT services towards a company's business. XYZ Company has implemented information technology specifically designed for users to manage service activities and process company administrative data. Service Operation is a lifecycle phase covering all day-to-day operations of IT service management. Based on research results on 3 processes, namely Event Management, Request Fulfillment, and Problem Management, there is a need to enhance the hardware, software, and infrastructure requirements to adequately meet the needs of XYZ Company for more effective work. Additionally, the need for implementing Standard Operating Procedures (SOP) and appropriate modules for employees is crucial to enhance their efficiency in utilizing information technology

Comparison of Three Time Series Forecasting Methods on Linear Regression, Exponential Smoothing and Weighted Moving Average

The purpose of this study is to compare the 3 forecasting methods Linear Regression, Exponential Smoothing and Weighted Moving Average based on the smallest error value or close to zero. From the results of this study, the Linear Regression method was obtained as the correct method with a predicted value of 502 students, the smallest error value was MAD 27.83, MSE 1152.1 MAPE 8.1%. The Tracking Signal value moves between 1 and -1, the movement is within the control limits of the tracking signal standard deviation distribution 4 and -4, meaning that the method is correct. The Moving Range value moves between 68 and -46, this value is within the MR control limits of 117.83 and -117.83, this result shows that this means that this method has been tested for truth and can be accepted as well. Thus, indicating that the Linear Regression method as a forecasting method is appropriate and acceptable as a basis for future decision making. The level of accuracy of the error and the value in control shows that there is a time series data relationship between the x variable, namely time, and the variable y, namely actual data. In addition, it produces trending data movement patterns, meaning that data movements experience a significant increase over a long period of time or for 7 periods