bluuebunny/crossref_metadata_2025_split huggingface dataset:
Simulasi Monte Carlo Dalam Meramalkan Pola Permintaan Tanaman Hias Melalui Usaha Rumahan di Tengah Pandemi Covid 19
Authors: Syata Ilham , Nurman Try Azisah , Adnan Airien Nabilla Baroqah 
Published: October 2023

ABSTRAK, Penelitian ini membahas mengenai peramalan permintaan tanaman hias dengan menggunakan Simulasi Monte Carlo. Metode Monte Carlo ialah metode analisis numerik yang melibatkan pengambilan sampel eksperimen random number. Salah satu model simulasi yang paling dikenal pada pengendalian persediaan adalah simulasi Monte Carlo. Penelitian ini bertujuan untuk mengetahui hasil peramalan permintaan tanaman hias (kaktus) selama 100 hari ke depan pada usaha rumahan Yuliah Kaktus di tengah pandemi covid 19 dengan menggunakan Simulasi Monte Carlo. Pengumpulan data dilakukan dengan teknik observasi dan wawancara dengan pemilik usaha rumahan Yuliah kaktus dengan mengambil sampel data yang sudah ada pada bulan Juli 2020-Februari 2022. Berdasarkan hasil penelitian yang diperoleh didapatkan hasil simulasi permintaan tanaman hias kaktus untuk 100 hari kedepan sebesar 76 kaktus dengan nilai MSE sebesar 2,06.
Perhitungan Korelasi dan Regresi dalam Penentuan Koefisien Muai Volume Beberapa Minyak Nabati
Authors: Endaryono  , Nurfidiah Dwitiyanti  
Published: October 2023

Dalam peneilitian ini dilakukan proses perhitungan penentuan nilai koefisien muai ruang beberapa minyak nabati dengan perhitungan teori korelasi dan regresi. Data yang digunakan data sekunder yang bersumber dari International Journal of Food Properties, Shreya N. Sahasrabudhe, dkk, tahun 2017. Dalam data sekunder terdapat nilai densitas beberapa minyak nabati yang memiliki massa 69,67 gram pada rentang suhu mulai 220C sampai 2000C. Dari data densitas dihitung perubahan volume setiap perubahan temperatur. Selanjutnya dilakukan perhitungan korelasi dan regresi. Berdasarkan hasil perhitungan didapatkan nilai koefisien muai volume beberapa minyak nabati yaitu minyak jagung (corn oil) adalah 7,5978 x 10-4/0C, minyak zaitun (olive oil) 7,4997 x 10-4/0C, dan minyak kedelai (soyben oil) sebesar 7,4785 x 10-4/0C. Sebagai bahan perbandingan, hasil percobaan yang dilakukan Meta Yantidewi tahun 2018 di Laboratorium Elektronika Dasar dan Instrumentasi Jurusan Fisika, FMIPA Unesa bahwa nilai koefisien valume minyak nabati sebesar (7,2 ± 0,2) x 10-4/0C.
ANALISIS REGRESI LOGISTIK BINER UNTUK MENGIDENTIFIKASI FAKTOR-FAKTOR YANG MEMPENGARUHI INDEKS PRESTASI KUMULATIF MAHASISWA MATEMATIKA UNIVERSITAS ISLAM NEGERI ALAUDDIN MAKASSAR
Authors: Andi Mariani  , Sauddin Adnan , Adiatma  , Nufus Husnatun 
Published: October 2023

Penelitian ini membahas tentang faktor yang memberikan pengaruh terhadap capaian Indeks Prestasi Kumulatif (IPK) Mahasiswa prodi matematika. Penelitian dilakukan menggunakan metode observasi (kuisioner). Metode penentuan sampel yang digunakan adalah Proporsional Stratified Random Sampling. Hasil penelitian menunjukkan bahwa dari beberapa faktor yang diikutkan dalam penelitian ini yaitu faktor motivasi belajar, sarana dan prasarana belajar, kinerja pengajar dan lingkungan keluarga , diketahui hanya faktor motivasi belajar yang memberikan pengaruh signifikan terhadap capaian IPK mahasiswa dengan nilai odds ratio sebesar 1,102 kali dan ketepatan klasifikasi model regresi logistik biner sebesar 70%.
IMPLEMENTASI METODE REGRESI LOGISTIK BINER PADA KEAKURATAN KLASIFIKASI JENIS MUSIK K-POP DAN WESTERN PADA SPOTIFY
Authors: Imron M. , Putroue Keumala Intan  
Published: October 2023

Musik yang didengar memiliki keunikan sendiri yang dapat menjadi suatu karakteristik, dimana dapat dengan adanya karakteristik tersebut lagu dapat dikelompokkan berdasarkan jenis lagu yang sama. Bersarkan data dari spotify penyanyi dikelompokkan oleh variabel Dancebility, Energy, Acousticness, Tempo dan beberapa variabel lain. Memanfaatkan variabel tersebut dilakukan penelitian bertujuan untuk melihat keakuratan klasifikasi jenis musik dimana musik yang akan di label adalah (1 = K-Pop) dan (0 = Western). Klasifikasi dilakukan dengan menggunakan regresi logistik biner. Data penelitian displit dengan proporsi perbandingan 80:20 kemudian diolah menggunakan metode regresi logistik biner, model yang terbentuk dapat menghasilkan akurasi klasifikasi 79.04% untuk data training, dan 79.69% untuk data testing.
Comparing the Performance Characteristics and Commonalities of Chinese Modern and Contemporary Literature in Different Cultural Contexts by Combining Text Mining Techniques
Authors: Zhang Xianghui 
Published: October 2023

Abstract
This paper first investigates the expressive features and developmental commonalities of Chinese modern and contemporary literary works, explains the paradoxical nature, and there are dilemmas in the expressive features by reviewing the data, and proposes the nationalized literary model and the cosmopolitan literary model, aiming to promote the development of Chinese modern and contemporary literature. Then, based on text mining techniques, atomic cuts are performed in the lowest fifth layer using Hidden Markov Models, and rough Chinese word splitting is performed using the n-shortest path method to find out the most likely n ambiguous word splitting results and text clustering analysis based on HMM-LDA topic models is performed on top of the splitting results. The results show that the HMM-LDA text recognition model is more accurate than the HMM text recognition model in terms of recall and accuracy of entity recognition in five categories of Chinese modern and contemporary literature: poetry, prose, drama, novel, and picture. Through this study, people gain a deeper understanding of modern and contemporary literature, gain some insight, and establish a foundation for promoting modern and contemporary literature.
Research on the design of computer network security defense system applying cloud computing technology
Authors: Wang Jian 
Published: October 2023

Abstract
In this paper, we first study cloud computing technology and build a computer network security defense system based on cloud computing technology. Secondly, to better analyze the network generated by cloud computing, the corresponding network topology is established according to the characteristics of the cloud computing network, and the complete network topology is generated through four steps. Then, the avalanche effect under the cloud computing network attack and its propagation are studied. Simulated tests are used to evaluate the performance of the network security defense system security. According to the results, the test group's network security defense rate is 89.2% when the intensity of network intrusion behavior is the highest. The defense effectiveness of all eight regions in the security domain test is above 90%, which is excellent.
Optimality of analysing smart tourism destination management based on media convergence algorithms
Authors: Xiong Keke 
Published: October 2023

Abstract
This paper uses a local path fusion method of medium to simulate the angular deviation between the end direction of the trajectory and the target direction according to a specific evaluation function. The media fusion algorithm is guided to achieve global optimality of the path by fusing global path planning information and avoiding local dynamic obstacles. The smart tourism and tourism management systems are fused to balance the intensity loss constraint weights and perform Gaussian filtering to derive the tourism management situation. By decomposing the highest level of tourism information and normalizing the pixel intensity values and tourism characteristic information, it was found that the smart tourism penetration rate increased by 3.6%, the total tourism revenue increased by 88.87% over the previous year, and the working variance of tourism project effectiveness was 62.430.
Research on Microteaching Mode of College English Courses Based on Regression Network Models
Authors: Nie Wei 
Published: October 2023

Abstract
This paper determines the solution vector of ELT proficiency constraint covariates using the correlation fusion approach, the proficiency prediction control objective function is constructed, and the education process’ quantitative recursive properties are discovered. The K-means algorithm is employed to obtain the predicted values of the resource limitation vector for ELT competence assessment, obtain the similarity of the distribution of teaching resources, combine linear regression grouping and integrate the ranking parameters for ELT competence assessment, obtain the characteristics of the data probability density, and finish evaluating the teaching model. The results show that the maximum utilization value reaches 99.03% by assessing English teaching ability through the K-means algorithm and linear regression, which indicates that the reasonable use of mobile Internet can enhance students’ English teaching level and ensure the efficiency of teaching resources utilization.
Visual Analysis of the Evolution of Traditional Chinese Ethnic Clothing Design Styles Based on Big Data and Artificial Intelligence
Authors: Dong Xuyi , Fu Jufen 
Published: October 2023

Abstract
This paper adopts the combination of big data and artificial intelligence to process the data on the evolution of Chinese traditional ethnic clothing design styles by using an ant colony algorithm and storing the processed data in a large database. According to the probability analysis, there are 618 data results obtained, and these related literature data were analyzed by word frequency analysis and clustering to calculate the relationship between the data and complete the data visualization analysis. According to the clustering analysis of 618 data, there were 21 abnormal data sets compared to the actual value of 22. Only one data set had a difference. The comprehensive analysis result is more satisfactory and has a reference value for analyzing the evolution of Chinese traditional ethnic clothing design style.
Teaching design of Chinese contemporary stylized watercolor based on quadratic exponential smoothing model
Authors: Song Xiangdong , Xu Yating 
Published: October 2023

Abstract
This paper is based on the exponential smoothing model to enhance the abilities of watercolor students and achieve their stylized watercolor creation. Firstly, the system is structured from the predicted value of the smoothing index. The sum of weights is calculated for each coefficient, and the quadratic, exponential smoothing model is modified. The design of the watercolor teaching system based on the quadratic, exponential model was completed after analyzing the components of the teaching model. Finally, a comparison experiment was conducted to verify that the overall performance of students was improved, and the final test score of painting reached 69%, which was significantly improved relative to that of the control class. The students in the experimental class were also tested for their T-values, and the test results were all below the significance level. It indicates that after the systematic teaching designed in this paper, the watercolor students' watercolor skill ability, personal stylization, and watercolor creation ability have a positive enhancement effect.
Application of AR technology in the study of controlled structure in basketball training
Authors: Liu Chaobao 
Published: October 2023

Abstract
To calculate the standard deviation of each attribute in the training control data, the normalized results of the standard deviation coefficient vector of basketball sports metrics are used as weights. Lagrange’s equation is used to analyze the behavioral trajectories of both players to enhance the offensive and defensive transitions of individual players. The weights used to calculate the standard deviation of each attribute of the training control data are based on the normalized results of the standard deviation coefficient vector of basketball sports metrics. It was found that the compression efficiency in the basketball sports teaching video with AR technology was 98.65%, the dominance ratio of offense-defense transition was 1.089, and the variance estimation of the disturbance term was 0.4621. Scientific training with AR technology can adjust training ideas, theories, and methods in real-time to realize the sports ideas of winning the standard and nurturing people.
Research on risk prediction and prevention and control measures of economic management of engineering construction based on econometric model
Authors: Yang Jingsi , Li Zhenhai , Yang Ge 
Published: October 2023

Abstract
To provide construction units with comprehensive and accurate information to assist in decision-making, this paper utilizes econometric models to use the Internet for management monitoring and engineering construction schedule scheduling. The parametric linearity constraint test method is set up, production function examples are established for engineering tests, and statistics are approximated to obey degrees of freedom and cardinal distribution. To obtain the inverse of the estimated information matrix, the least squares method is employed to maximize the engineering construction expression. The engineering economic management error value is found to be the lowest value of 0.84, the maximum value of elasticity coefficient is 0.379, and the minimum value of covariance is 0.185. To fully improve the risk prediction capability of engineering construction, econometric modeling techniques must be integrated.
Research on the reform of university education pedagogy based on deep learning model in the context of information era
Authors: Yu Dan 
Published: October 2023

Abstract
In this paper, the minimization loss function optimization deep learning algorithm is used to achieve educational pedagogical reform in the context of the information technology era by continuously optimizing the loss function to reach local minima. A feature weight threshold is used to calculate the weights of each output feature, and a weighted average pooling is performed for each one-dimensional vector to produce multiple lengths of nearest neighbor samples. The deep learning model increased the scoring frequency of key values in the reform of higher education pedagogy by about 0.18, with an accuracy rate of 0.91 and an increase of lecture board words by more than 95%. To promote the smooth promotion of college education curriculum reform, the deep learning model recommends promoting the reform of college education pedagogy.
Research on the manifestation of university network Civics teaching based on adaptive network
Authors: Lv Xin 
Published: October 2023

Abstract
This paper proposes an adaptive learning model for the interrelationship between civic education and college students’ career planning. Secondly, a competency point tracking model is constructed based on a neural network algorithm to explore the relationship between student behavior and competency points and how a certain student behavior affects competency points. Then, the Civics teaching platform for the college network was designed for college Civics teaching needs. Finally, the platform performance was tested, and the impact of the platform application was analyzed. The study showed that when the number of online users reached 5000, the transaction success rate remained at 100%, the average CPU usage rate was 56%, and the response time did not exceed 10 s. The average grade of Civics students has gone up by more than 10 points.
Dimensional structure, scale development and impact effect testing of platform-based human resource management
Authors: Zhang Miao , Zhang Jingdan , Liu Yixin 
Published: October 2023

Abstract
This paper first constructs an analytical model of platform-based human resource management, where the series of independent variables and the series of dependent variables are grayed out by multiplying each variable by its whiteness at different time series points. The Cholesky method is employed to solve for the regression parameters, and the original dependent variable series and its predicted value series are gathered to calculate the error estimates. Finally, the model was used to analyze the dimensional structure and test the effect of platform-based HRM. =0.31, p0.001, the perception of continuous platform-based HRM was significantly and positively related to job performance, as demonstrated by the results. The perception of continuous platformed HRM is significantly and positively related to psychological capital β=0.54, p<0.001. This paper provides a theoretical guide for HRM in platformed companies and a conceptual model and measurement tools for studying platformed HRM.
Construction of a Digital Shared Management Platform for Enterprise Finance in the Information Age
Authors: Liang Shujing 
Published: October 2023

Abstract
Based on the construction objectives of the enterprise financial sharing management platform, this paper focuses on the design concept and implementation process of each system module based on the overall system design under the framework of the financial sharing platform. The BP neural network algorithm is used to evaluate the financial information risk, the particle swarm optimization algorithm is used to optimize the database, the big data visualization technology is used for digitizing the financial information, and the metadata sharing technology is used to transfer the financial sharing data, to complete the financial information sharing. Through testing the platform, it is concluded that the real-time packet loss rate of financial sharing data is kept below 20%, and the average response time of multi-user clicks is within 2S. Therefore, the sharing function, the function of each module, and the performance of the platform in this paper can meet the needs of enterprises.
Management, organization, coordination and prognosis of precast beams during construction
Authors: Ma Weini 
Published: October 2023

Abstract
In this paper, we propose a method for monitoring the construction quality and progress of assembled buildings based on point cloud model feature extraction to achieve accurate identification and rapid detection of construction process information because of the existing problems in precast beam construction data collection and processing, combined with 3D laser scanning technology. Soil excavation and filling calculations are performed to determine the site design elevation before the main structure construction starts, the prefabricated components are simulated to be assembled and viewed for assembly errors during the construction process, and the verticality and flatness of the prefabricated beams are inspected after the construction is completed in combination with least squares. The construction quality problems and delays in construction progress were also corrected and adjusted to ensure a smooth construction process. After the main bridge was constructed, it was measured to have a damping ratio of around 0.011, which means it can dissipate external energy input.
Research on the development strategy of integration of Chinese traditional culture and tourism development oriented to a matrix model
Authors: Zhu Fengbo , Sha Liang 
Published: October 2023

Abstract
Based on its evolutionary history, this paper explores the different manifestations of traditional culture in tourism development. The matrix decomposition of the spatial elements of tourism development is used to study the coupling relationship between tourism space and traditional culture. Finally, the evaluation index system of the tourism development degree is constructed, and the two-dimensional matrix model is used to realize the integration measurement of traditional culture inheritance and tourism development. In the empirical study, the evaluation index of cultural industry development in Liaoning province increased year by year from 2011 to 2020, reaching a stage peak of 0.623189 in 2015, and the coupling degree of the culture and tourism industry in Liaoning province was greater than 0.92. The measurement model established in this study effectively promotes the integrated development of traditional culture tourism.
Application of SLAM in bolt tightening monitoring process based on intelligent data algorithm analysis
Authors: Wang Tengfei , Deng Hongjian , Wang Feng , Lu Donghao , Xiang Qin 
Published: October 2023

Abstract
In this paper, firstly, according to the requirements of static monitoring of bolt tightening quality, the bolt tightening process can be divided into four stages: snug, elastic deformation, yielding and plastic deformation, and the SLAM technology is applied to bolt monitoring modeling and building engineering modeling. Next, the pre-tightening force for the bolt is measured using the waveform expansion method, and the bolt tightening index can be determined. Then, all the collected bolt data are randomly combined into two categories of loosening and tightening to form a training data set, and the improved intelligent data algorithm is used to train and predict them. The results show a linear correlation between tightening degree x |τ
ɛ| and preload force change ΔF under 0.31kN and 0.22kN loading gradients, and the linear correlation coefficient of the fitted curve is greater than 0.9215. The results of the data analysis verify the correctness of the theoretical analysis.
Research on Cultural Confidence of Contemporary College Students and Its Cultivation Based on BSO Algorithm
Authors: Chen Hua 
Published: October 2023

Abstract
The first topic covered in this paper is the development of cultural confidence among college students within the context of the Internet, including its manifestations, characteristics, and value implications. Secondly, elite guidance is used to carry out adaptive parameter optimization of the BSO algorithm, and then horizontal and dynamic cultural communication strategies are proposed. Finally, an examination is conducted on college students' current state of cultural self-confidence. The results show that the average knowledge of cultural confidence of different majors is 0.0477, 0.3097, 0.4492 and 0.1935, respectively, and 882 college students indicate that they are very familiar with the knowledge of social core values. It follows that to foster college students’ cultural confidence, society and families must work with colleges and universities to encourage students to identify with and have confidence in Chinese culture.
Evaluation and Analysis of the Effectiveness of University Innovation and Entrepreneurship Courses Based on Data Analysis Technology
Authors: Zhu Zhiwei 
Published: October 2023

Abstract
An innovation and entrepreneurship education model centered around Timmons’ entrepreneurial process is suggested in this study after an initial analysis of applied bachelor universities, innovation and entrepreneurship education, and innovation and entrepreneurship courses. Second, a neural network with BP and an artificial neural network is used to build an assessment system for the efficiency of school innovation and entrepreneurship courses. Finally, examples were used to quantitatively study data on the approval of innovation and entrepreneurship classes and students’ graduation selections. The findings reveal that satisfaction with the innovation and entrepreneurship course may be successfully assessed using data analysis techniques because there is just a variance of 0.037 between the input assessment, with the lowest average score of 4.938 and the multidimensional experience assessment, with the highest average score of 4.975.