bluuebunny/crossref_metadata_2025 huggingface dataset:
Unveiling the powerhouses of AI: A comprehensive study of GPU, FPGA, and ASIC accelerators
Authors: Shi Yicheng
Published: March 2024

In the ever-evolving realm of technology, Artificial Intelligence (AI) has ushered in a transformative era, reshaping our interactions with digital systems, and expanding the horizons of machine capabilities. At the core of this AI revolution are specialized hardware entities known as AI accelerators. These accelerators, including Graphics Processing Units (GPUs), Field-Programmable Gate Arrays (FPGAs), and Application-Specific Integrated Circuits (ASICs), play a pivotal role in advancing AI applications across diverse domains. This paper delves into these accelerators, offering an in-depth exploration of their unique attributes and application domains. GPUs, initially designed for graphics, have evolved into versatile tools, thanks to their parallel computing prowess and efficient memory utilization. FPGAs, with reconfigurability and low latency, prove valuable in aerospace and neural network implementations, though they come with cost and expertise challenges. ASICs, engineered for specific functions, excel in performance and power efficiency for mass production but require significant time and resources for development. Furthermore, this paper presents practical application analyses, showcasing how these accelerators are effectively deployed in real-world scenarios. With this comprehensive exploration, readers gain a deeper understanding of AI accelerators and their transformative impact on the AI landscape.
Based on social network analysis: Whether international trade network changed before and after the outbreak of the COVID-19 pandemic?
Authors: Jin H R
Published: March 2024

Since the outbreak of COVID-19 pandemic, the international trade has been facing a severe impact. Based on the social network analysis method, this research models the world trade network during the six years from 2017 to 2022. The world trade network is made into a weighted directed adjacency matrix based on the data published by UN Comtrade database. The matrix also refers to the gravity model. With visualized data and images, this research makes a quantitative study on the impact of the COVID-19 pandemic on the world trade network from the perspective of network analysis, centrality analysis and clustering coefficient. Apart from that, this research focuses on the international trade pattern and how it changes under the impact of the pandemic. According to this research, although the world trade network has not been deeply affected by the disease, there are some concealed tendency has been discovered, which may profoundly change the world pattern in the future.
Applying ensemble learning to multiple stock price predictions: A comparative study
Authors: Ye Shenghua
Published: March 2024

Predicting stock prices has been a perennial challenge and topic of interest for financial analysts, investors, and researchers alike. This holds true especially for influential tech companies that significantly impact the stock market landscape like Google and Tesla. While numerous models and methods have been applied to forecast stock prices globally, there remains a gap in a comparative, in-depth evaluation using Support Vector Regression (SVR), Recurrent Neural Network (RNN), Long Short-Term Memory network (LSTM), and XGBoost models for predicting prices of prominent tech stocks. This paper aims to bridge this gap, presenting a comprehensive model comparison for stock price forecasting. A series of datasets, inclusive of Google's stock prices and Tesla stock price, form the backbone of the analysis. Among the evaluated models, our preliminary findings indicate that LSTM and XGBoost demonstrate superior predictive capabilities, capturing intricate market dynamics with high precision. Further, the paper delves into the underlying factors and patterns driving stock prices, gleaning insights from the models' predictions. Through this research, this paper offers valuable benchmarks and insights for the best model for research in the field of stock price predictions and some evaluation of different features in the field of stock price predictions.
Design of music recommendation system based on EDA and K-means cluster analysis
Authors: Chen Pengbo , Dong Liyan , Liu Yuanning
Published: March 2024

This paper describes the construction and analysis of a music recommendation system, through visual and exploratory analysis of the open source dataset of music recommendation system in the UCL database, exploring the relationship between music popularity and music acoustic properties, using the K-means clustering algorithm for clustering analysis of genres and songs, and finally building a music recommendation system that can, based on the user input of music data, to match the ten music songs that best meet the listener's taste. The analyses in this paper show that there is a certain correlation between music popularity and the indicators of sound, danceability, energy, instrumentality, liveliness, loudness, language, rhythm, mood, duration and tone. The indicators of energy, liveliness, loudness and tempo are positively correlated with the popularity of music, while the indicators of mood and duration are negatively correlated with the popularity of music. In addition, this paper uses K-means clustering algorithm to cluster analysis of genres and songs, and shows the similarity and difference between different genres and songs through visualisation, which provides important data support for the construction of music recommendation system. Finally, this paper establishes a music recommendation system based on K-means clustering algorithm, which can match the ten music songs that best meet the listener's taste according to the music data input by the user. The system is intelligent and personalised, and can recommend music works that are more in line with the user's taste based on the user's preferences and historical listening records. The results of this paper provide useful reference and support for the algorithms and models of the music recommendation system, which can be further researched in depth in the future to improve its intelligence and personalisation level and provide users with better music services.
DCGAN-based data augmentation for improving CNN performance in meningioma classification
Authors: Chen Muye
Published: March 2024

Using Magnetic Resonance Imaging (MRI) to scan the brain and using the image to identify whether the patient has a brain tumor or not is the common way doctors use it today. However, as this may potentially add to the workload of healthcare professionals, it becomes crucial to explore methods for automating image identification. One effective algorithm for this purpose is the utilization of a Convolutional Neural Network (CNN) network. However, when applying a CNN network to discern whether an individual has meningioma or not, it becomes evident that the available data may be limited. Meningioma is relatively uncommon, and not all associated images have been made accessible for analysis. The shortage of original samples makes it hard to train the CNN network and has relatively low accuracy. In this case, this study tries to use DCGAN to generate more images based on the original sample. By comparing the accuracy and f1 score of the CNN network, this study finds that implementing images has improved the performance of the CNN network. By implementing the images, the DCGAN generates, the accuracy for the same CNN network to identify whether the images have meningioma or not is increased from 93.53 percent to 97.75 percent. The f1 score also increased from about 0.9187 to about 0.9738.
Enhanced DeblurGAN: An advanced combinatorial model for motion blur removal in low-light photography
Authors: Zhuang Hong
Published: March 2024

This article aims to address the challenge of eliminating low-light motion blur, a problem that lacks effective solutions, despite being crucial in various application scenarios. For instance, it can help in the identification of moving individuals or license plates during nocturnal surveillance, filming running videos after dark, and managing animals in rural areas at night. These examples represent commonplace and significant scenarios. These are all important domains, but few approaches are effective at handling such specific cases simultaneously. This paper utilizes a fusion model to increase the brightness of an image while preserving the photographic details. The motion blur is subsequently eliminated from the brightness-enhanced image. This results in the enhancement of image details and the removal of motion blur. Comparing the model proposed in this paper with the commonly used Deblur model, it becomes apparent that the new model effectively enhances brightness in low-light motion blur while preserving image details and reducing much of the blur. This implies that the model is more versatile, as it can be used not only for images but also for low-light videos.
Revolutionizing comic coloring: Federated learning-based neural network for efficiency and privacy
Authors: Tian Lunshuo
Published: March 2024

The conventional method of coloring comics can be quite arduous and time-consuming, particularly within the realm of animation, where each frame necessitates individual coloring. Over the past few years, the advent of deep learning technology has introduced fresh prospects for comic coloring. Nonetheless, it's worth noting that deep learning typically demands a substantial volume of data to effectively train models, giving rise to legitimate concerns regarding data privacy. This study proposes an innovative approach that applies federated learning to comic coloring to improve efficiency and address privacy issues. In this research, an existing neural network European Conference on Computer Vision (ECCV16) model was employed using federated learning to partition and train the model on segmented databases. To better quantify the color differences between the original images and the colored images, this study designed a custom loss function. Experimental results demonstrate that this approach has been effective in comic coloring, demonstrating the feasibility of applying federated learning to the task of comic coloring.
Explore the causes and prevention strategies of stroke
Authors: Meng Fantian
Published: March 2024

This research paper will include information and an introduction to stroke, and the prediction of stroke factors based on the research. It is important to let people do some common factor of prediction strategies for stroke since it is a sudden cause of death. It will list several typical types of strokes. This paper will also show the cause and reason that affect a stroke. It will also include its death rate and people may have a higher chance to get one. In the second part, there will be different analyses of its symptoms. The research will compare each result and get their common factor. Using data visualization and graphs to clearly show the difference, will show which habit will cause a higher risk of stroke. It will further lead to their age and diet structures. In the end, it will show the prevention of common strokes, giving more advice and strategies to face the stroke, and giving more direct instructions to the people who are never aware of it.
Comparison of different machine learning models: Linear model, forest and SVM
Authors: Liu Xinran
Published: March 2024

Over the past century, machine learning has developed rapidly with the fast evolution of AI. As high-performance computing (HPC) has popularized over the past few decades, huge differences have been made in the field of machine learning, from expert systems to deep learning algorithms nowadays. This study summarizes some well-known models and compares three of the current popular machine learning models: the Linear Model, the Forest Model, and the Supporting Vector Machine (SVM), which aims to give and clearer view of those models in several aspects. Forest and SVM are more powerful in performance than the Linear Model due to their ability to deal with more types and more complex relationships and patterns. However, Forest and SVM have a higher complexity than the Linear Model and are less interpretable. Through the comparison of the three models, the basic model and algorithms will be better understood, the appropriate model will be selected faster when solving the problem, saving training time and space, and effectively saving resources and costs.
A neural network model for predicting price changes of the exchange rate EUR/USD
Authors: Deng Chuxuan , Hu Yuzhi , Peng Cheng
Published: March 2024

With the rapid development of the global economy, economic exchanges and cooperation between countries have become increasingly frequent, and the importance of the foreign exchange market has become increasingly prominent. As a link between international trade, foreign exchange plays a crucial role in formulating relevant financial policies and the risk management of multinational enterprises. However, accurately predicting foreign exchange changes is very challenging because the foreign exchange market is characterized by non-linear and dynamic changes and exchange rate fluctuations are also affected by historical data. The analysis method based on time series has always been an effective solution for studying exchange rate issues, and the model trained by the deep learning model based on time series data can further simulate and predict the exchange rate. Therefore, this article uses the BP neural network algorithm based on the time series model to predict the price change of the exchange rate EUR/USD. This article first uses the historical exchange rate data of the euro against the US dollar as a training set and performs data preprocessing. Secondly, the activation function and learning rate of the model are tuned, and the performance of the model is compared by evaluating indicators to improve prediction accuracy. The final experimental results show that the neural network model is highly accurate and predictive in predicting EUR/USD exchange rate price changes.
A user study on regulating upset emotion in workplace through HELMO
Authors: Xu Qi
Published: March 2024

The rising prevalence of emotional distress resulting from mental health pressures constitutes a paramount issue within the context of a rapidly evolving work environment. The detrimental consequences experienced by those affected by this phenomenon are of considerable magnitude. In order to address these issues, it is possible to design relevant applications that can assist individuals in identifying workplace disputes and devising effective strategies to alleviate emotional strain. Previous research has predominantly focused on investigating the potential of robots to exert a positive influence on conflict dynamics within a team-based problem-solving context through their ability to address interpersonal violations post-conflict. Consequently, there is a limited understanding regarding the specific criteria via which robots may contribute to conflict resolution. This study encompasses user research, analysis of essential elements, and the proposal of a high-fidelity prototype named HELMO. This prototype provides a range of daily functions that can assist individuals in recognizing conflicts and mitigating the danger of experiencing negative emotions. The findings indicate that individuals have a high demand for detecting conflicts and releasing emotional pressure in many subject matters. The mental health application known as HELMO shows promise in addressing the difficulties associated with emotional discomfort that may arise during or following workplace confrontations.
Calculation and numerical modeling of the effect of heat and mass transfer on the properties of pile foundations in seasonally freezing soils
Authors: Mussakhanova Saltanat , Sarsembayeva Assel , Zhussupbekov Askar , Collins Philip
Published: March 2024

The phenomenon of heat and mass transfer in seasonally freezing soils has a significant impact on the condition of pile foundations. Building structures constructed in such soils experience extremely negative consequences: frost heave, vibration dynamics, moisture mass transfer and soil weakening during the thawing. Seasonally freezing soils occupy most of the territory of Kazakhstan, and in most regions the depth of soil freezing exceeds 1.5 m, there are settlements where the index reaches 1.97 m (Semiyarka, East Kazakhstan region) and in the north of the country - 2.74 m (Arshaly, Akmola region). Arrangement of foundation bases below the frost depth leads to increased construction costs, requires additional costs for thermal insulation, ventilation, other materials and structures, and, in addition, does not always lead to a full levelling of the negative impact of heat and mass transfer on the term and conditions of operation of buildings, structures, railways and roads. Therefore, the efforts of engineers and specialists in the field of thermal physics are aimed at finding effective ways to solve the problems of deformation and destruction of foundations in seasonally freezing soils. In the article an attempt is made to reveal the character of heat and mass transfer influence on pile foundations in seasonally freezing soils on the basis of a thermomechanical model.
Comprehensive Evaluation of the Development Level of Rural Logistics in China from the Perspective of Rural Revitalization
Authors: Shi Yuhong , Yang Mengju
Published: March 2024

Taking the perspective of rural revitalization, this study constructs an index system for the development level of rural logistics. Based on data from the year 2021, the entropy method is employed to calculate scores for each index, thus providing a comprehensive evaluation of the current status of rural logistics development in China. The results indicate that the overall level of rural logistics development in China is on an upward trend with robust developmental momentum. However, challenges such as supply and demand imbalances, unfavorable conditions, slowing speed, and inappropriate structure exist. The spatial layout of rural logistics development exhibits a decreasing trend from the southeast coastal areas to the central, northern, and western regions. It is suggested that enhancing rural economic levels, improving rural infrastructure, addressing imbalances in rural logistics supply and demand, and promoting rural informatization are the main strategies for developing rural logistics in China.
Study on Wind Speed Distribution Law of Mine Roadway Section under Different Conditions
Authors: Sun Rui
Published: March 2024

Ventilation is the cornerstone of coal mine safety production, and accurate monitoring of ventilation parameters is the basic guarantee for ventilation technology decision-making. Aiming at the problem that the accuracy of wind speed monitoring in coal mine roadway is difficult to meet the needs of decision-making, this paper studies the position relationship between the average wind speed line and the roadway wall surface by combining theoretical calculation and numerical simulation, and simulates the wind speed distribution law of typical roadway section. The main factors affecting the distribution of wind speed in roadway section include roadway section shape, section size, support form, wind speed, facilities and equipment status, etc. The expression of the position relationship between the average wind speed line of the rectangular and semi-circular arch roadway section and the roadway wall surface is y=elna-1.5. Through 25 groups of model simulation, the wind speed distribution law of different types of roadway sections under different conditions is obtained: the wind speed contour is basically parallel to the roadway wall. The wind speed gradient near the roadway wall is large, and the wind speed gradient in the middle of the roadway is small. The thickness of the boundary layer decreases with the increase of wind speed.
Based on an Overview of Crack Detection
Authors: Wei Jinglong
Published: March 2024

This Crack detection, as an important part of concrete structural health monitoring, aims to reflect the stress state and damage degree of the structure. Traditional concrete crack detection mainly relies on manual visual identification, which has low detection efficiency and accuracy. In addition, manual visual detection has problems such as being greatly affected by lighting conditions, being unable to cover overhead locations such as bridge towers and high piers, and being highly subjective. In recent years, in order to solve the above problems, researchers at home and abroad have developed concrete crack detection equipment based on digital image technology, such as inspection vehicles equipped with high-resolution cameras, unmanned aerial vehicles, crawling robots, and so on. Meanwhile, efficient and accurate crack detection algorithms are the basis for realizing accurate crack identification. How to balance the detection speed and accuracy has been the focus of academic attention. This paper reviews the research progress of concrete crack detection equipment based on digital image technology at home and abroad in recent years, including camera platform, calibration method, preprocessing, traditional and deep learning algorithms, crack feature extraction, image stitching, and 3D representation and monitoring of cracks. In addition, the deficiencies in the research are summarized.
The Application Status and Energy Saving Analysis of Heat Pump Technology Under Dual Carbon Target
Authors: Cao Shuanghua , Guo Pengyuan , Wang Yichun
Published: March 2024

This paper introduces the significance of energy conservation and the current situation of energy utilization in China, and focuses on the development prospect of heat pump technology. Since the proposal of carbon peaking and carbon neutrality has made higher requirements for carbon emission reduction in different industries, the energy structure in China will make important adjustments accordingly. The research focuses on the way to reduce carbon emission in conventional industries and making full use of renewable energy. Among different energy saving and emission reduction technologies, heat pump technology has been widely used in civil, industrial and agricultural areas due to its remarkable performance of energy saving and emission reduction. There are many kinds of heat pump technology, but there are great differences in specific applications. How to make effective use of heat pump technology has become an important direction of our current development. It is a problem we must solve to study the current situation of heat pump technology and then realize energy saving.
Summary of the Influence of Image Subject Ratio on Design Evaluation
Authors: Wu Yankun
Published: March 2024

With the rapid development of the information age, images and animations have become the mainstream way of product display at present. At the same time, the development of image processing and technology makes the rapid processing of images become a reality. Through image processing, the proportion of the image subject to the whole image is calculated, and the image sample and its proportion are obtained. A more accurate psychological model of users' needs is obtained by using the joint experiment of eye movement and EEG, and the influence of image subject ratio on users' information transmission is determined. The purpose of this study is to provide reference and suggestions for product design publicity pictures, and to help designers design products that meet users' emotional demands from a user-centered perspective.
Research Status and Outlook on High Temperature Performance of Fiber Concrete
Authors: Wu Yuhao , Miao Yuhan , Lv Dong , Guo Mingzhe , Wang Xinming
Published: March 2024

Fiber concrete is a novel composite material that has widespread use in the construction industry. However, high-temperature environments can cause severe damage to concrete structures. Therefore, it is essential to study the refractory properties and microscopic changes of fiber concrete under such conditions. This paper reviews the current research status of steel fiber concrete, polypropylene fiber concrete, and hybrid fiber concrete, which are commonly used in practical engineering, and summarizes their respective roles in concrete by combining theory and practice. The review also looks forward to future research directions and development trends to provide a reference for related research. Studies have demonstrated that adding a suitable amount of fibers can significantly enhance the high-temperature performance of concrete. However, different fiber types have varying effects on concrete. The high-temperature performance of fiber concrete is also influenced by various factors, including concrete mix ratio, fiber type, and admixture. Future research should focus on investigating the mechanism and microscopic changes in the high-temperature performance of fiber concrete, developing new fiber materials, optimizing concrete mixing ratios, and exploring the application of fiber concrete in practical engineering.
Measures Taken by Lecturers in Teaching Language Skills to Large EFL Classes Online at Some Universities in Vietnam
Authors: Tran Thi Thanh Huong , Ngo Huy Tu
Published: March 2024

In EFL online teaching, large-sized classes are of major concern, and different teachers have taken various measures to facilitate and enable better learning outcomes. This study investigated the measures used by lecturers at some universities in Vietnam to teach language skills to large EFL classes online. The sample size was 60 respondents from different age groups, university settings, and IT competence levels. The research found that most teachers often preferred teaching receptive skills (i.e. reading and listening) as they were more graphic and more easily handled. Accordingly, more audio-visual measures were reported to be effective. Activities that allowed students to prepare and get ready were also more favorable. Presentations, role-plays, interviews and flipped classes were counted among the most frequently used activities. Besides, class short assignments on less academic tasks were more prevailing because they did not apply challenges and pressure on learners. Respondents revealed that they had to perform a lot of technical skills and combine several digital means of teaching, managing, monitoring and assessing their classes. It was recommended from this study that more training on handling blended classes and support efforts should be given to teachers of large classes as well as more innovative language activities and pedagogical measures should be designed to improve teaching and learning quality in such a circumstance.
Automatic App Review Using Android Application
Authors:   B. Tech Student, Dept of Computer science and Engineering, M.G.R EDUCATIONAL AND RESEARCH INSTITUTE, Maduravoyal,  Chennai-95, Tamil Nadu, India
Published: March 2024

DeepMatcher comes with a tool that connects usage data from app analytics to error reports in the monitored data. DeepMatcher uses advanced techniques to automate this process, enabling developers to quickly spot bugs and dynamically improve bug reporting. In this Paper we have got Simple Mail Transfer protocol (SMTP) which can send and receive Mail to concerned app developers for the improvement in app experience. As our abstract aims to make a standalone app that can make the user give feedback directly to developer so that the app satisfies the user as NLP required in DeepMatcher to report the SMTP used is simplified and make the developer easily rectify the issue with regards to this research we propose DeepMatcher, a tool to automate bug detection and enhance bug reporting in app development .We contrast our solution to an alternative, SMTP (Simple Mail Transfer Protocol), featuring distinct advantages. Whilst DeepMatcher illustrates automation, SMTP provides user-to-developer direct and immediate communication channels, simplifying feedback submission and bug reports. This direct approach provides timely and detailed feedback, faster bug resolution and higher app quality resulting in improved user satisfaction. Keywords— SMTP, CoRe, Standalone, Feedback, Developer, Generated
FAKTOR -FAKTOR PENYEBAB GAGALNYA PEMBERIAN ASI EKSLUSIF
Authors: Zahra Tamela , Puspitasari Yeviza
Published: March 2024

Latar Belakang: Pemberian ASI Eksklusif yang gagal dan tidak optimal dapat berdampak pada pertumbuhan dan perkembangan anak di masa yang akan datang. Kegagalan ini juga dapat meningkatkan angka kematian dan kesakitan ibu dan anak. Tujuan: Untuk mengetahui faktor-faktor yang menyebabkan gagalnya pemberian ASI Eksklusif. Metode: Penelitian kuantitatif menggunakan metode survey analitik dengan pendekatan Cross Sectional, variabel independen yaitu pengetahuan, umur, budaya dan Dukungan Keluarga dan variabel dependen yaitu kegagalan dalam pemberian ASI esklusif. Populasi dalam penelitian ini  adalah seluruh ibu yang memiliki anak usia 6-12 bulan dan sampel dalam penelitian ini berjumlah 95 responden. Penggumpulan data dilakukan dengan cara wawancara menggunakan kuesioner. Analisa data univarit dan bivariat menggunakan software SPSS. Hasil: Diketahui dari hasil analisa data melali uji statistik chi-square didapatkan adanya hubungan antara Pengetahuan (pvalue=0,00), Umur (p value=0,004), Budaya (p value=0,014) dan Dukungan Keluarga (p value=0,012). Kesimpulan: Pengetahuan mengenai ASI ekslusif, peran serta keluarga adalah kunci utama keberhasilan pemberian ASI eksklusif, meningkatkan pengetahuan ibu dan keluarga mengenai ASI eksklusif dan melibatkan keluarga serta suami dapat meningkatkan angka keberhasilan ASI eksklusif.
SMALL CLAIM COURT PROCEDURES IN UPHOLDING THE PRINCIPLES OF SIMPLE, FAST, AND LOW COST COURTS IN INDONESIAN CIVIL PROCEDURE LAW
Authors: Hariwijaya Ramadian Putra , Adnyana I Gusti Ngurah
Published: March 2024

This legal research aims to explore important aspects concerning the settlement of simple lawsuits and the legal considerations made by judges in establishing the settlement of such cases. The research adopts a Normative Juridical method, which involves analyzing issues through library research, summarizing and interpreting legal doctrine opinions. The conclusions drawn from the research and discussions are as follows: Firstly, there are specific requirements for settling simple lawsuits that differ from those of regular civil proceedings. The time period and value of the object involved in simple lawsuits are distinct from ordinary civil lawsuits. Secondly, in determining the settlement of a simple claim, judges carefully consider the evidence presented by the Plaintiff, including documentary evidence and credible witnesses, ensuring that the lawsuit satisfies the elements outlined in PERMA number 4 of 2019.
EXPLORING THE POTENTIAL OF HYPERLOCAL MEDIA: BENEFITS, CHALLENGES, AND FUTURE DIRECTIONS
Authors: Jati Rocky Prasetyo
Published: March 2024

Hyperlocal media is an increasingly important player in the media landscape, providing communities with targeted and relevant information. This conceptual paper aimed to explore the potential of hyperlocal media as a solution for community media in the digital era. The study analyzed the benefits of hyperlocal media for communities and discussed the key challenges and opportunities facing these media outlets. The analysis revealed that hyperlocal media could foster civic engagement, cultural preservation, public discourse, and community connection. However, the study also emphasized the need to address the sustainability of these media outlets and the importance of exploring innovative technologies and strategies to support their growth and development. This study sheds light on the significance of hyperlocal media in creating more substantial, more connected communities and highlights the need for further research in this area.
THE INFLUENCE OF BUSINESS STRATEGY AND ORGANIZATIONAL CULTURE ON MANAGEMENT ACCOUNTING INFORMATION SYSTEMS
Authors: Marlina Ressy , Hertati Lesi , Putri Andini Utari
Published: March 2024

This study aims to determine the effect of Business Strategy and Organizational Culture on Management Accounting Information Systems for Employees of CV. Srijaya City of Palembang. The selected sample is 40 respondents. The research data was obtained from a questionnaire (primary data). The analysis technique used is multiple linear regression method. The results of data analysis with the help of SPSS 26 showed that the results of the partial hypothesis test (t-test) on business strategy have no significant effect on the management accounting information system. Meanwhile, organizational culture has a significant effect on management accounting information systems. Likewise, the results of the simultaneous test (f-test) based on the coefficient of termination proves that the variables of business strategy and organizational culture simultaneously have a positive and significant effect on the management accounting information system.
IHRM: A BLIBIOMETRIC ANALYSIS
Authors: Pramita Cindy
Published: March 2024

The globalization of business has created a need for companies to develop effective international human resource management practices. IHRM is a critical area of research in the field of human resource management, as it encompasses issues related to the management of people in a global context. Given the complexity of managing human resources across national borders, it is important to understand the factors that influence IHRM practices and their impact on organizational outcomes. This research aims to investigate the interrelationships between IHRM and other related topics, such as global and domestic hiring practices. The data used consists of 100 articles indexed by Scopus for the period of 2018-2023. This research method employs bibliometric analysis using the VOSviewer software. The results of the analysis were visualized through co-authorship, co-occurrence, and co-citation, namely the most frequently identified article citations from the 10 highest citation groups. It shows that IHRM commitment is related to other issues such as cultural divergence, IHRM strategy, HRM practices convergence, expatriates, and global HR hiring. This review aims to serve as a reference for future research on IHRM strategy and other relevant variables.
THE INFLUENCE OF THE VESPA SPEEDING INDONESIA YOUTUBE CHANNEL ON SUBSCRIBER LIFESTYLE
Authors: Maulana Rifki , Agustiningrum Henny , Puspadarmaja Nyoman
Published: March 2024

The development of technology has resulted in social media becoming an online tool that allows individuals and groups to share digital content. Among the various forms of social media, vlogs (video blogs) and YouTube stand out as platforms that offer information through a combination of images, sound, video, and text. YouTube, in particular, is widely used by people for informational purposes and features diverse channels spanning various topics, including music, travel, culinary arts, and automotive enthusiasts. Piaggio's Vespa, known as a legendary brand, is one of many brands that offer Vespa products. As a pioneer in the automotive industry, Vespa chose to launch a YouTube Channel called Vespa Ngebut Indonesia, dedicated to Vespa riders in Indonesia. This study aims to examine the influence of the Vespa Speeding Indonesia Channel on the lifestyle of its viewers, particularly young adults, and how this influence drives them to purchase a Vespa. The study focuses on the age group that watches and subscribes to the Vespa Speeding Indonesia Channel the most. Data was collected from 100 participants through a questionnaire distributed via Google Forms, and statistical analysis using a Likert scale was employed to analyze the data. The research utilized an explanatory quantitative analysis approach based on the SOR theory. The findings of this study indicate that the Vespa Speeding Indonesia Channel has a significant impact on the lifestyle of its subscribers.
ADDRESSING THE MANAGEMENT OF AREAS AND SLUMS IN MOJOKERTO IN ACCORDANCE WITH THE SDG'S FRAMEWORK
Authors: Julkarnain Donny Setyaelvanda , Bisri Mohammad , Khusaini Moh. , Wijaya Andy Fefta
Published: March 2024

This study aims to analyze the existing conditions of handling areas and slums in Mojokerto in accordance with the SDG's framework, and determine the dominant factors that influence the handling of areas and slums in the region. The research method used is Mix Method. The results of the analysis show that the existing condition of slum areas in Kedungmaling Village, Sooko Sub-district, Mojokerto District falls into the Moderate Slum category. However, there are no factors that can be included in the logistic equation model in multivariate analysis with logistic regression on the analysis parameters for safe and resilient cities/settlements. In the context of the SDG's framework, the handling of slum areas and settlements in Mojokerto needs to be evaluated by taking into account the dimensions of sustainable development compiled in the SDG's concept, as well as the indicators used to measure (Sustainable Cities and Communities) in the SDG's. Thus, a strategy for handling slum areas and settlements in Mojokerto can be developed. Thus, strategies for handling slum areas and settlements can be developed that are more in line with the principles of sustainable development included in the SDG's.
THE EFFECT OF PERCEIVED TRUST AND PERCEIVED ENJOYMENT ON REPURCHASE INTENTION
Authors: Mulia Nana Tri , Adlina Hafiza
Published: March 2024

One of the e-commerce that has been well known by some Indonesians is Tokopedia. Tokopedia is ranked as the first most trusted e-commerce and as the most visited e-commerce in 2022. The domination of using Tokopedia compared to other e-commerce has led to various perceptions provided by Tokopedia so that it attracts users to repurchase. The purpose of this study was to determine the effect of perceived trust and perceived enjoyment on repurchase intention of Tokopedia users in Medan City. This research was conducted using quantitative techniques with a research sample of 100 respondents who are Tokopedia users in Medan City. The analysis techniques used include instrument tests, classical assumption tests, multiple linear regression analysis and hypothesis testing. The results of this study show that Perceived Trust has a significant positive effect on Repurchase Intention with a sig value of 0.000 <0.05 and Perceived Enjoyment has a significant positive effect on Repurchase Intention with a sig value of 0.019 <0.05. In simultaneous testing, the Perceived Trust and Perceived Enjoyment variables simultaneously have a positive effect on Repurchase Intention with an influence level of 61.3%.
THE INFLUENCE OF YOUTUBE CONTENT ON MOBILE LEGENDS ON THE INTEREST IN E-SPORTS TOURNAMENTS AMONG ADOLESCENTS IN JAGAKARSA, SOUTH JAKARTA
Authors: Gusrialdi Joko , Kau Suni Eugenius
Published: March 2024

Today's technology is getting more advanced and sophisticated with smartphones that can be applied easily anytime and anywhere. Having a smartphone makes it easier to get trending information. There are several examples of social media applications that are in great demand, such as Instagram, WhatsApp, Line, Twitter, YouTube, and others. Most people in the world use YouTube to share their videos or just enjoy various video clips. This study aims to describe interest in participating in E-sports tournaments after watching YouTube mobile legends content. Knowing the influence of YouTube mobile legends content on interest in E-sports tournaments in Jagakarsa youth, South Jakarta. The method used in this research is quantitative by involving teenagers in Jagakarsa, South Jakarta who play mobile legends games and are active in the mobile legends community. The data collection process uses a questionnaire that is distributed via the Google Form link and then processed using a simple linear analysis technique. The results of the study show that Youtube Mobile Legends content has a significant influence on adolescents in Jagakarsa, South Jakarta. It can be concluded that Mobile Legends content has a positive and significant influence on interest in tournaments among young people in Jagakarsa, South Jakarta. Obtaining these results is dominantly influenced by the Cognitive effect dimension as the highest measure of variable X (Influence of Mobile Legends Content) with the indicator: Motivated to Play the Mobile Legends Game.
JOB DEMANDS – JOB RESOURCE: SYSTEMATIC LYTERATURE REVIEW
Authors: Prilatama Aris , Pramita Cindy , Sopiah
Published: March 2024

This systematic literature review aims to summarize various studies on the relationship between job demands and job resources. This research utilized the SLR (Systematic Literature Review) method. Journals were obtained from Publish or Perish by selecting Scopus sources. The keywords used were "job demands" and "job resources" and after conducting the search from Publish or Perish, a total of 200 records were filtered within the years 2018-2023. Subsequently, these records were verified, resulting in 30 articles that met the criteria. The results indicate that job demands can deplete physical, psychological, and cognitive resources, which can have negative consequences for employees. In contrast, job resources can fulfill basic psychological needs, increase employee engagement, and foster creativity.
THE EFFECT OF INTEREST RATES ON THE DEMAND FOR MULTIPURPOSE LOAN (KSG) AT PT. BANK PERKREDITAN RAKYAT HASAMITRA DAYA MAKASSAR CITY BRANCH
Authors: Ngabe Joyti Devi Adnyaswari , Widhi Kurniawan Agung , Nurman  , Anwar  , Mustika Amin Andi
Published: March 2024

Banks play a crucial role as financial institutions by collecting and distributing public funds to support national development. Conventional banks primarily generate income through interest charged on loans provided to borrowers. This study aimed to investigate the impact of interest rates on the demand for multipurpose loan (KSG) at PT. Bank Perkreditan Rakyat Hasamitra Daya, Makassar City Branch. The variables considered in this study are interest rates and the demand for multipurpose loans. The population for this study consists of all interest rate data and credit request reports for multipurpose loans at PT. Bank Perkreditan Rakyat Hasamitra Daya, Makassar City Branch. The sample includes interest rate data and credit request reports for multipurpose loan at PT Bank Perkreditan Rakyat Hasamitra Daya, Makassar City Branch, from 2015 to 2022, covering each quarter. The data collection techniques employed in this study are documentation and interviews. The analysis used to determine the relationship between the independent variables and the dependent variable includes simple linear regression, classical assumption tests, and hypothesis testing. The results of the regression equation for the impact of interest rates on the demand for multipurpose loans are as follows: Y = 17,337,852 - 75,073 X. Based on these findings, interest rates do not exhibit a significant effect on the demand for multipurpose loans. The influence of interest rates on the demand for multi-purpose credit at PT. Bank Perkreditan Rakyat Hasamitra Daya, Makassar City Branch, accounts for 38.4%. The remaining 61.6% is influenced by other factors not examined in this study.
THE EFFECT OF APPLICATION OF AUDIT DIGITALIZATION ON AUDITOR PERFORMANCE WITH PROFESSIONAL ETHICS AS A MODERATION VARIABLE
Authors: Astuti Dewi Saptantinah Puji , Rohmah Uliya
Published: March 2024

In recent years, digitalization has transformed various aspects of business operations, including the field of auditing. The integration of digital technologies in audit processes has the potential to enhance efficiency, accuracy, and overall performance. As organizations increasingly adopt digital audit practices, it becomes essential to examine the impact of digitalization on auditor performance. The objective of this research is to assess the impact of digitalization audits on auditor performance. The study focuses on a public accounting firm located in Central Java, comprising a total of 24 individuals. Primary data was collected for this research. The population considered was the entire group of auditors working in public accounting offices in Central Java. Purposive sampling method was employed, resulting in a sample size of 60 auditors. Data was collected through questionnaires distributed directly to auditors in the public accounting offices in Central Java. Multiple linear regression analysis was used to analyze the data. The data analysis techniques included classic assumption testing, multiple linear analysis, t-test, F-test, coefficient determination (R2), and regression analysis with a moderating variable. The results of the research indicate that audit digitization has a significantly positive influence on auditor performance. However, professional ethics was found to have no moderating effect on the influence of audit digitization on auditor performance in public accounting firms in Central Java.
DEVELOPMENT OF THE RENDANG INDUSTRIAL INNOVATION SYSTEM IN PAYAKUMBUH CITY
Authors: Musthafa Imelfina , Tan Firwan
Published: March 2024

This research aims to examine efforts to develop an innovation system for the rendang industry in Payakumbuh City. The methodology used in this research is interviews with related parties regarding efforts to develop an innovation system for the rendang industry in Payakumbuh City. The results obtained are that there are various efforts to develop an innovation system for the rendang industry in Payakumbuh City, namely: the establishment of a rendang industrial center, rebranding of Payakumbuh City, the establishment of UPTD P3R, the establishment of the "IKOSERO" cooperative, the establishment of the School of Randang,collaboration and partnerships, technology implementation, marketing, HR training and development, as well as licensing and standardization. Government policy to provide support to the rendang industry in Payakumbuh is very necessary so that rendang in Payakumbuh City is able to have competitiveness in the national market and Payakumbuh rendang can enter the international market and become a food that is in demand by people throughout the world.
E-COMMERCE UTILIZATION EFFORTS ENTREPRENEURS IN INDONESIA
Authors: Meilisa Meilisa , Bachtiar Nasri , Taifur Werry Danar , Ridwan Endrizal
Published: March 2024

To increase competitive advantage and expand markets, digitalization brings new trends with technological innovation in the form of e-commerce. Using Sakernas data for 2021, the research intends to analyze the impact of using e-commerce on business actors between two groups, namely business actors using e-commerce and those without using e-commerce for their business. The selected sample in the research was business actors who did not yet have permits for their business activities, namely 36,703. The e-commerce category is: product promotion with internet coverage, and sales carried out through marketplaces (Tokopedia, Bukalapak, Olx, etc). The results show that business actors who utilize e-commerce have higher income than business actors without using e-commerce in their business, which is influenced by human capital (education), digital skills (use of computers and smartphones), socio-demographics (age, gender), with the Propensity Score Matching (PSM) method.