bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analisis Wacana Kritis Theo Van Leeuwen Pada Ebook Sejarah Penggusuran di Jakarta Era Tahun 1970-1980: Tempo Publishing
Authors: Ariani Zeni Ayu , Ernanda Ernanda , Putri Aprilia Kartika 
Published: October 2023

This study aims to find out how the forms of inclusion and exclusion strategies contained in the news ebook History of Evictions in Jakarta in the 1970-1980 era: Tempo Publishing. This research used a qualitative approach with a descriptive literature review model. Researchers download ebooks, and purchase ebooks contained in the Google Play Book application. The data in this study are words, phrases, news sentences published by Tempo publishing. Researchers found as many as 69 exclusion and inclusion data. The exclusion strategy aims to see how actors are excluded from the text of the conversation. The exclusion strategy contained 36 data. The data is divided into 28 passivation process data and 8 nominalization process data. Then forms of inclusion strategy which aims to see how actors are included in the text of the conversation, found as many as 33 data. The data is divided into 2 nomination process data, 9 categorization data, 5 objectivation data, 3 determination data, 6 indetermination data, and 8 association data. From the results of the study it can be concluded that there are more constructions that obscure actors in events, compared to constructions that highlight actors. Topics that eliminate or obscure actors are about evictions and discrimination against marginalized people, while topics that give rise to actors are about the suffering of marginalized people.
Abstrak
Penelitian ini bertujuan untuk mengetahui bagaimana bentuk strategi inklusi dan eksklusi yang terdapat dalam ebook berita Sejarah Penggusuran di Jakarta era tahun 1970-1980:Tempo Publishing. Penelitian ini menggunakan pendekatan kualitatif dengan model kajian studi pustaka yang bersifat deskriptif. Peneliti mengunduh ebook, dan melakukan pembelian ebook yang terdapat pada aplikasi google play book. Data dalam penelitian ini adalah kata, frasa, kalimat berita yang diterbitkan oleh Tempo publishing. Peneliti menemukan sebanyak 69 data eksklusi dan inklusi. Strategi eksklusi bertujuan untuk melihat bagaimana aktor dikeluarkan dari teks pembicaraan. Strategi eksklusi terdapat 36 data. Data tersebut terbagi menjadi 28 data proses pasivasi dan 8 data proses nominalisasi. Kemudian bentuk-bentuk strategi inklusi yang bertujuan untuk melihat bagaimana aktor dimasukkan dalam teks pembicaraan, ditemukan sebanyak 33 data. Data tersebut terbagi menjadi 2 data proses nominasi, 9 data kategorisasi, 5 data objektivasi, 3 data determinasi, 6 data indeterminasi, dan 8 data asosiasi. Dari hasil penelitian dapat disimpulkan bahwa terdapat lebih banyak kontruksi yang mengaburkan aktor dalam peristiwa, dibandingkan konstruksi yang menonjolkan aktor. Topik-topik yang menghilangkan atau mengaburkan aktor adalah mengenai penggusuran dan diskriminasi pada kaum marginal, sedangkan untuk topik-topik yang memunculkan aktor adalah mengenai penderitaan pada kaum marginal.
Pabrikasi Bolus 3D berbahan Polylactic Acid untuk Terapi Radiasi pada Pasien Kanker Payudara
Authors: Yuliandari Annisa , Oktamuliani Sri , Harmadi  , Pratama Andra 
Published: October 2023

Kanker payudara merupakan salah satu jenis kanker yang menempati urutan pertama sebagai penyumbang kematian akibat kanker di Indonesia. Pengobatan kanker payudara pada beberapa kasus belum mendapat dosis permukaan yang maksimal, sehingga dilakukan penelitian yang bertujuan untuk membuat bolus 3D setara dengan jaringan payudara manusia dan dapat meningkatkan dosis. Penelitian ini menggunakan Polylactic Acid (PLA) sebagai bahan utama pembuatan bolus. Bolus dicetak menggunakan printer 3D dengan variasi permukaan persentase material pengisi (infill) yaitu (20, 40, 60, 80, 100) %. Hasil pabrikasi bolus 3D dianalisis menggunakan metode analisis deskriptif berdasarkan hasil pengukuran nilai Relative Electron Density (RED) dan dosis serap menggunakan LINAC 15 MeV pada payudara manekin. Hasil penelitian menunjukkan bahwa bolus 3D berbahan PLA memberikan keseragaman dari segi ketebalan. Bolus dengan persentase infill 20% memiliki nilai RED yang paling mendekati RED payudara yaitu 0,99 dan mampu menyerap radiasi sebesar 1,98 Gy lebih optimal, jika dibandingkan dengan bolus komersial. Hal ini menunjukkan bahwa bolus 3D berbahan PLA dapat menjadi bolus alternatif saat pengobatan kanker psayudara menggunakan radioterapi dengan elektron.
Formulasi Lulur Serbuk Daun Suruhan (Peperomia pellucida L. Kunth)
Authors: Tarigan Christine , Marliati Nolis , Siregar Ika Pranita 
Published: October 2023

Seiring perkembangan teknologi kosmetik lulur bisa ditambahkan dengan bahan-bahan alami dalam bentuk ekstrak, penggunaan bahan-bahan alami dikarenakan hasilnya lebih aman untuk kulit dan praktis dalam pemakaiannya serta meningkatkan manfaat dari kosmetik lulur itu sendiri. Tumbuhan sirih cina (Peperomia pellucida L.) mengandung senyawa alkaloid, flavonoid, saponin, tanin dan triterpenoid yang berpotensi menghambat pertumbuhan bakteri. Tujuan penelitian untuk membuat sediaan lulur krim menggunakan ekstrak daun suruhan (Peperomia pellucida L. Kunth) sebagai zat aktif dengan variasi konsentrasi 3%, 5% dan 7%. Penelitian dilakukan secara eksperimental dengan desain Rancangan Acak Lengkap (RAL). Hasil penelitian menunjukkan lulur krim ekstrak daun suruhan pada semua konsentrasi memenuhi persyaratan uji sifat fisik sediaan yang baik meliputi organoleptis, homogenitas, pH, daya sebar dan daya lekat serta uji hedonik meliputi kesan saat pemakaian dan setelah pemakaian. Uji hedonik lulur dengan 3%,5%,7% ekstrak daun suruhan mununjukkan 47%,55%,65% responden memberikan pendapat bahwa sampel lulur bertekstur agak licin dan ada butirannya dengan nilai α < 0,05. Sampel lulur krim dengan penambahan 7% daun suruhan memiliki mutu fisik yang paling baik dan persentase uji hedonik tertinggi. Uji organoleptik dan fisika serta uji kimia, karakteristik lulur ekstrak daun suruhan memenuhi standar SNI 16-4399-1996 sebagai syarat mutu pelembab kulit sehingga lulur krim yang dihasilkan menyehatkan kulit.
Fitokimia Minyak Trikatu yang Diproduksi dengan Variasi Suhu dan Waktu Digesti secara GC-MS (Gas Chromatography Mass Spectrometry)
Authors: Pramitha Dewa Ayu Ika , Wibawa Agung Ari Chandra , Yuda Putu Era Sandhi Kusuma 
Published: October 2023

Kasa adalah kondisi klinis yang didefinisikan dengan jelas seperti batuk, dan patofisiologisnya terkait erat dengan mekanisme refleks batuk dalam pengobatan modern. Trikatu adalah ramuan yang mengandung tiga bahan herbal dengan rasa pedas, yaitu maricha (black papper), Peepli (long pepper), dan Sunthi (Ginger). Komposisi dari Trikatu terbukti efektif dalam pengobatan Kasa. Perawatan khas dalam mengatasi gejala bronkitis akut, seperti pneumonia dan asma, terbukti tidak efektif, dan Badan Pengawas Obat dan Makanan Amerika Serikat menyarankan untuk tidak menggunakan obat batuk dan pilek pada anak di bawah enam tahun. Pengobatan alternatif perlu dilakukan. Oleh karena itu, pada penelitian ini formula sediaan Trikatu ditransformasikan ke dalam pengobatan Kasa berupa minyak herbal menggunakan VCO, rimpang jahe merah (Zingiber officinale Roxb.), buah kering cabai jawa (Piper retrofractum), dan buah kering merica hitam (Piper nigrum Linn). Formula minyak Trikatu menggunakan metode digesti dengan variasi suhu dan waktu. Tujuan dari penelitian ini adalah untuk mengetahui kandungan senyawa minyak Trikatu terbentuk akibat variasi suhu dan waktu digesti dengan GC-MS. Senyawa bioaktif utama yang dihasilkan pada minyak Trikatu dengan variasi suhu dan waktu digesti yaitu octanoic acid, n-decanoic acid, caryophyllene, α-curcumene, dodecanoic acid, zingerone, tetradecanoic acid, n-hexadecanoic acid, α-Monolaurin, oleic acid, dan piperine. Hasil penelitian menunjukkan bahwa suhu dan waktu digesti berpengaruh terhadap keberadaan senyawa dalam pembuatan minyak Trikatu. Semakin lama waktu digesti yang digunakan dalam pembuatan minyak Trikatu, maka kandungan asam lemak tak jenuh dan jenuh akan semakin meningkat.
Integrasi Framework Balanced Scorecard dan COBIT 2019 dalam Pengelolaan Help Desk pada Sistem Informasi Desk Layanan
Authors: Safitri Adila , Nugraheni Dinar Mutiara Kusumo , Warsito Budi 
Published: October 2023

Sistem Informasi Desk Layanan (SIDELA) adalah aplikasi yang digunakan untuk pengelolaan pengaduan dan pengajuan mengenai layanan TI yang terdapat pada Diskominfo. Pengelolaan SIDELA masih mengalami permasalahan seperti pelaksanaan audit belum dilaksanakan, sehingga belum bisa melihat capaian dari SIDELA. Tujuan penelitian untuk mengevaluasi kapabilitas sistem tata kelola teknologi informasi menggunakan framework COBIT 2019. Metode yang digunakan adalah menggunakan framework COBIT 2019. Terdapat lima tahap dalam penelitian ini yaitu tahap perencanaan, tahap ruang lingkup, tahap pengumpulan data, tahap anlisis, dan tahap penyimpulan hasil. Pengumpulan data dilakukan dengan cara ,wawancara, dan kuesioner. Berdasarkan hasil pemetaan, dipilih 6 domain yaitu DSS01, DSS02, DSS03, DSS04, DSS05, dan DSS06. nilai target level kapabilitas yang diharapkan pada seluruh domain yaitu mencapai Level 4 (Predictable Process). Domain DSS01 memiliki gap sebanyak 4 level, DSS02 memiliki gap sebanyak 1 level, DSS03 memiliki gap sebanyak 1 level, DSS04 memiliki gap sebanyak 1 level, DSS05 memiliki gap sebanyak 4 level, dan DSS06 memiliki gap sebanyak 0 level. Hasil yang didapatkan pada penelitian ini dalam menggunakan kerangka kerja BSC sudah memenuhi target yang diharapkan, Namun secara COBIT 2019 masih kurang, dikarenakan masih terdapat nilai kesenjangan berdasarkan level kapabilitas. Pada penelitian selanjutnya dapat menggunakan metode pengukuran tingkat kapabilitas yang lain.
Research on two-way intelligent self-service system of electric power business hall applying data compression algorithm
Authors: Zhou Baowei , Lin Yongxiang , Cao Sheng , Su Hongbang , Qi Xiaoxuan , Zhang Yaling 
Published: October 2023

Abstract
This paper applies a data compression algorithm to designing a two-way intelligent self-service system for an electric power business hall and proposes a multiwavelet embedded zero-tree coding method and compression of electric power data. Based on the multiwavelet transform, a multiwavelet threshold power data compression algorithm is proposed, and the decomposition reconstruction comparison of the multiwavelet transform, and the implementation process of the compression algorithm are discussed. The implementation effect of the electric power intelligent business hall is discussed through the evaluation analysis of the service before and after the intelligent business hall. The results show that the platform operation effect score of the electric power intelligent service management platform project of company H is 0.8723. This paper's platform design and implementation provide useful research references for improving the service quality and efficiency of the electric power business hall.
A study on the integration of Confucian aesthetics into the curriculum thinking of universities based on multiple data chain networks
Authors: Huang Yimei 
Published: October 2023

Abstract
This paper uses multivariate data chain incremental control to distribute Confucian aesthetic thought data information through a Poisson process to evaluate the initial data set according to changing business volume change dynamics. A time-slot teaching distribution algorithm is employed to transform the time-slot teaching problem using a slow additive incremental approach to increase the amount of Confucian aesthetics information access. The results show that the average error of teaching Civics under the multi-data chain network is 9.7 ns, and 69% of students think that college Civics incorporates many Confucian aesthetic ideas. The good integration of Confucian aesthetic thought with college curriculum Civics has certain practical significance for tapping Confucian thought and can open up new paths for college ideological and political education work.
An investigation into the optimal allocation of resources for China's universities to participate in global education governance based on queuing theory
Authors: Wu Xian , Xu Hui , Zhu Bowen , Wang Hao 
Published: October 2023

Abstract
Queuing theory is used to classify the regularity of educational resource allocation by hierarchy in this paper. The Poisson distribution is used to label the resource queue interval parameters to obtain the expected value of individual queues. The average delay of each class of packets can be reasonably predicted by concatenating individual resources using the Lagrange multiplier algorithm. The load balancing algorithm in each queueing series calculates the average arrival rate of task requests to achieve an optimal model design. The results show that, under the guidance of queuing theory, the coefficient of variance in the participation of Chinese university students in global education governance is reduced by 0.25% on average, and the average of comprehensive efficiency reaches about 1.01%, which realizes the optimal and reasonable allocation of resources.
Research on the expression and creativity of traditional ethnic cultural elements in clothing design based on the fusion of multi-source and multi-objective statistical information
Authors: Ma Yun , Zhang Lei 
Published: October 2023

Abstract
The use of multi-source, multi-objective statistical information fusion is utilized in this paper to identify garment design targets, and the correlation is judged based on garment data. Some parameters are pre-set to generate linear garment descriptions for multi-source, multi-objective information fusion and find the adaptability of ethnic elements under random coefficients using element information relationships. The clothing width vector of the radial basis function is calculated by clustering ethnic culture element data using centroid information. The results show that the innovation rate of ethnic elements of Miao batik reaches the highest 0.57, the average adaptation value in the garment design is increased by 4.92%, and the ethnic-cultural elements are embodied 280 times, which indicates that the proposed method can promote the traditional excellent culture.
Optimization of cross-cultural communication model for ethnic minorities based on self-similarity and comparative learning
Authors: Qi Zhongfang 
Published: October 2023

Abstract
The super-resolution algorithm of self-similarity is utilized in this paper to construct an image training set based on the multi-scale self-similarity of images and reconstruct the super-resolution of images. The visual question-and-answer method of contrast learning ensures full coverage of key targets, which makes the optimization of mutual information more reliable and stable to construct a cross-cultural communication model for ethnic minorities. The results show that compared with the cross-modal audio-video instance discrimination model, the accuracy of TOP1 at the visual clip level is 3.04% higher, and the accuracy of TOP5 at the video level is 2.62% higher for the model designed in this paper. This paper's design model can enhance the ability of cross-cultural communication among ethnic minorities, as indicated.
Study on the aesthetic evaluation method of applying symmetry analysis in industrial product styling design
Authors: Wen Jianqiang , Bai Qiong 
Published: October 2023

Abstract
The evaluation of product styling design is transformed into a complex nonlinear solution problem by symmetry analysis in this paper. The equilibrium matrix decomposition evaluation system calculates the stored matrix singular values in product styling design and proves that symmetry can be obtained from the stress matrix row vector. The regression algorithm is used to process multiple industrial product design objectives, and each design element in product styling is coded to obtain the fitness evaluation of individual industrial products. It is found that the satisfaction score in product styling design is 97.4, the weight index of logo novelty element is up to 7, and the regression coefficient of plane shape is 0.269, to improve the scientific and feasibility of aesthetic evaluation of industrial product styling design.
A theoretical and practical study on the components of intelligent physical education courses in colleges and universities based on Bayesian non-parametric model
Authors: Wei Na 
Published: October 2023

Abstract
This paper performs feature extraction based on the Bayesian nonparametric model for smart sports courses to analyze the Gaussian process principle for composing random variables. The probability distribution of the parameters is estimated based on the known data set, given the input data vector to decompose the likelihood function. To calculate the posterior probabilities of the parameters, the kernel function features are analyzed to give the expressions of eigenvalues and eigenvectors, and data normalization is performed. According to the results, the experimental group had higher sports test scores than the control group, and the third test score of high-speed running reached 9 points. Therefore, colleges and universities should focus on cultivating students' innovative thinking abilities and helping them master sports knowledge and skills to achieve their educational goals.
A study on pronunciation assessment of English learners based on temporal classification algorithm
Authors: Wang Lina 
Published: October 2023

Abstract
This paper utilizes a time-series classification algorithm to classify samples, and the selected datasets are utilized to calculate the distance of time-series samples. The information gain is calculated using the information obtained, and the information entropy is determined collectively for the node datasets to generate time series features. The convolution operation is used to obtain the formal representation of the time series classification, and the extracted English pronunciation features are adaptively matched. The evaluation results were determined using a multilayer wavelet feature scale transformation method, and English learners achieved scores of 6 and above in all three tests using the time-series classification algorithm. To master standard English pronunciation, English learners should use the temporal classification algorithm.
Research on Language Evolution and Language Diversity Based on Chinese Speech Pitch Deviation Features
Authors: Lang Juanjuan 
Published: October 2023

Abstract
This paper constructs a Chinese speech evaluation system based on the characteristics of the vocal mechanism of Chinese speech and uses the detection framework of statistical speech recognition to realize the automatic detection function of pronunciation bias. Assuming that the amplitude spectra of speech and noise obey the generalized Gamma distribution and Gaussian distribution, respectively, the MMSE estimator of the logarithmic spectrum of the speech signal is derived. The speech presence probability under the generalized Gamma speech model is derived as a correction to the MMSE estimation based on language evolution and diversity features. The correct recognition rate of the proposed algorithm reaches 64%, which indicates that the proposed algorithm can effectively suppress the interference of convolutional noise on the speech signal features and improve the subjective perceptual quality of diverse languages.
Extraction and analysis of factors influencing college students’ mental health based on deep learning model
Authors: Yang Weimin 
Published: October 2023

Abstract
This paper analyzes the factors that affect the mental health of college students, and the focus of this analysis is on emotional-emotional factors. The extroverted presentation of emotional affects is used as visual information to study the mental health status of college students. Based on the advantages of long and short memory neural networks based on deep learning models in processing two-dimensional images, a computer vision task is used to perform visual recognition, target detection, and expression image classification of college students’ facial expressions. The use of video facial expression recognition with multi-feature fusion is utilized to effectively identify the facial expression machine of college students in both laboratory-controlled and outdoor environments. The mental health status of college students was analyzed in terms of facial expression recognition and feature extraction. The recognition rate for general features was 80.3%, 89.3% for six specific facial emotions, and 84.4% for LBP features.
Research on Innovative Reform of Vocal Music Teaching Mode in Colleges and Universities Based on Network Vocal Music Teaching Model
Authors: Guan Qingzhen 
Published: October 2023

Abstract
Improving timbre recognition and Internet technology have created new avenues for developing vocal teaching models in colleges and universities. In this paper, several people propose a timbre-based Internet vocal teaching model based on the cross-classification vocal teaching model. The timbre is extracted and divided into training and test data, dimensionality reduction and classification processes to form the general process of timbre recognition. A GMM-HMM timbre recognition model is proposed by describing the observed timbre probabilities using GMM so that the observed timbre states of HMM are continuous. The SVM classification algorithm is employed to categorize the identified timbres and determine the specific distribution of incorrect timbres. In the vocal teaching test, the Mayer inversion coefficient achieved a higher RPA when the number of candidate pitches was less than 4. If the number of candidate pitches exceeds 5, the amplitude-free weighting method will increase slowly.
An investigation of the fusion path of multiple singing styles in American vocal singing by incorporating Markov chain prediction model
Authors: Liu Na 
Published: October 2023

Abstract
In this paper, by analyzing the four American vocal singing styles, the vocal semantics beyond the semantics of the four vocal singing styles are constructed by using the common knowledge map, and the heavy semantic fusion mechanism is established based on the pre-training model of the knowledge map to obtain the contextual semantic features, and the relational classification model MSF-RC is realized. To predict the degree of fusion of the three vocal singing styles, the classical gray theory and To predict the degree of fusion of the three vocal singing styles, the Markov chain prediction is completed for the residual numerical sequences with large volatility. After testing, the accuracy of this algorithm is 0.88, the recall is 0.92, the F-Score is 0.88, and the MAPE value between the actual values of American singing and ethnic singing fusion and the prediction results corrected by the fusion Markov chain model is 1%, which has high prediction accuracy.
Numerical analysis-oriented Kruskal algorithm for the analysis and integration of effective components of university music pedagogy
Authors: Li Yuan 
Published: October 2023

Abstract
This paper constructs a collection of effective teaching methods based on the improved K-Means clustering algorithm for clustering and dividing effective components of music teaching in colleges and universities. By analyzing the personalized content recommendation system, we can construct a recommendation system based on teaching content using information retrieval and filtering techniques. The collaborative filtering recommendation algorithm is used to ensure the accurate placement of teaching content. The Kruskal algorithm is used to find the minimum spanning tree of teaching effective components, and the K-means clustering principle is applied to the division of music teaching effective components, and the cluster of effective teaching components is divided by the clustering algorithm. According to the findings, mind-body integration and the teaching goal of valuing creativity were classified as effective teaching components in music. Personal aesthetics had a 0.6 influence on musical creativity, and a free environment had a 0.3 influence.