bluuebunny/crossref_metadata_2025 huggingface dataset:
Handwritten digit recognition based on deep learning techniques
Authors: Zhang Xinshen
Published: February 2024

The identification of handwritten digits in images recognition and machine learning is a prominent research area. In order to create a handwritten digit recognition model for this investigation, deep learning is introduced. The proposed approach integrates Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), and EfficientNetB0, three separate deep learning models. Specifically, the CNN model utilizes pooling layers and data augmentation techniques to enhance its classification ability, the RNN model takes advantage of its ability to process sequential data, and the EfficientNetB0 model benefits from a deeper and more complex network structure. These models are trained and evaluated using the Modified National Institute of Standards and Technology (MNIST) dataset. The experimental results demonstrate the efficacy of the proposed approach: the CNN model attains a remarkable accuracy of 98.9% on the test set, thereby showcasing its exceptional classification performance. Similarly, the RNN model achieves an accuracy of 96.7%, underscoring its suitability for analyzing sequential data. Furthermore, the EfficientNetB0 model attains an accuracy of 98.1%, thereby elucidating the benefits of the deeper network architecture. The models constructed in this study have significant real-world implications, such as improved object recognition systems, medical diagnostics, and autonomous driving. The EfficientNetB0 model produced an accuracy of 98.1% with its complex network architecture when applied to recognise handwritten digits.
An angle of arrival estimation method for intelligent metasurface using machine learning
Authors: Peng Yang
Published: February 2024

Today, techniques for altering electromagnetic waves and the data they transport are increasingly crucial. These techniques have become increasingly important in several communication technologies, such as intelligent metasurface, with the rise and development of next-generation wireless communication systems. Since those technologies call for locating devices, angle of arrival (AoA) analysis becomes a crucial area for research. The AoA can now be shown in various ways, and some subspace methods have already achieved great precision. However, the extensive calculation required by those techniques is one of their key shortcomings. The author developed a novel radio frequency (RF) switching circuit design in this research and applied a novel machine-learning method to signal AoA. In single-wave settings, it was discovered that the proposed machine learning method performed satisfactorily with an average difference of 0.6 degrees.
Sarcasm detection methods based on machine learning and deep learning
Authors: Zhang ZhiYu
Published: February 2024

Sarcasm is an expression of emotion, which often expresses criticism and disgust in a positive tone, and we see it everywhere on social networking platforms. Because of this nature, sarcasm can be challenging to process in Natural Language Processing (NLP) Systems. Failing to detect sarcasm correctly can negatively affect the results of natural language processing tasks such as text correct and sentiment analysis. In recent years, there are more and more studies on sarcasm detection, and the research methods are diverse. According to the survey, the methods based on machine learning (ML) and deep learning (DL) account for the majority. Therefore, this paper mainly summarizes the literature on sarcasm detection based on ML and DL methods in recent years. This paper first introduces the application of sarcasm, then expounds the general architecture of sarcasm detection and makes a distinction between machine learning and deep learning. Then the author investigates the relevant literature and compares the results. Finally, the challenges and research directions in this field are summarized. The purpose of this paper is to facilitate the follow-up research of sarcasm detection.
Text emotional analysis in Natural Language Processing
Authors: Lin Shangyue
Published: February 2024

Natural Language Processing (NLP) is an important research direction in the field of artificial intelligence, aimed at enabling computers to understand and process human natural language. Emotional analysis refers to the use of computer technology to automatically recognize and classify the emotional tendencies expressed in text, such as positive, negative, or neutral. This technology can be applied to fields such as social media analysis, public opinion monitoring, market research, etc. The goal is to enable computers to understand and interpret emotional information in text like humans. Text sentiment analysis, as a key task of NLP, aims to identify and classify emotional tendencies expressed in text. This article will delve into the field of text sentiment analysis in natural language processing, focusing on the role and application of standard sentiment dictionaries and corpora in sentiment analysis. Reviewing relevant research conclusions, providing reference and inspiration for achieving more accurate and comprehensive text sentiment analysis through research and exploration.
Probing RSA's weak spots: Dissecting timing attacks and Euclidean method exploitations
Authors: Tan Siwei , Tong Siyuan
Published: February 2024

The RSA encryption system, a cornerstone of numerous cryptographic frameworks, has long enjoyed a reputation for robustness. However, its strength is inherently tethered to the meticulous selection and management of its foundational prime numbers, p and q. This study delves into a nuanced vulnerability that surfaces when p and q assume particularly large values. Within this context, we illuminate how the Euclidean method can be weaponized to swiftly decipher RSA-encrypted messages, unveiling the original plaintext with surprising efficiency. Intriguingly, our analysis also uncovers that harnessing parallel computation for the Euclidean method expedites decryption exponentially, accentuating this vulnerability. Such revelations cast a spotlight on a delicate balancing act between computational prowess and cryptographic fortitude. The insights gleaned from our research emphasize the paramount importance of judicious prime selection in the RSA framework. They also caution about the unforeseen pitfalls that might lurk behind algorithmic enhancements in cryptographic contexts. Through this investigation, we aspire to catalyse a critical re-evaluation of RSA's real-world deployments and champion a more circumspect, continually adaptive approach to designing cryptographic systems.
Exploring techniques and overcoming hurdles in generative AI
Authors: Bai Jinjie
Published: February 2024

The realm of artificial intelligence has witnessed significant advancements, with generative models standing at the forefront of this progress. Generative Artificial Intelligence concerns the development of algorithms and models equipped to generate novel content - be it images, text, or music. This paper delves into the primary techniques underpinning generative AI, including Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and autoregressive models like Transformers. These methodologies have enabled a myriad of applications, from synthesizing images to facilitating data augmentation and style transfer. While the results from generative models have been profoundly impressive, they are not devoid of challenges. The surge in their capabilities has brought forth issues related to ethics, inherent biases, scalability, and the quest for more stable training methods. This paper aims to provide an insightful exploration of the pivotal methods defining generative AI while shedding light on the prevailing challenges and ethical implications intertwined with its growth.
Construct a garbage recognition model using automatic machine learning based on EasyDL
Authors: Qi Jiaxuan
Published: February 2024

In modern times, machine learning has become an indispensable part of various industries. As the amount of data increases, reducing the time cost of manual annotation is crucial. AutoML emerges as a solution that effectively automates labor-intensive tasks like image annotation. In this article, we use Tencent's EasyDL to develop a garbage recognition function. The garbage recognition model completed through EasyDL achieved an average of over 90% in terms of accuracy and F1 score. This indicates that autoML can greatly reduce manual participation while ensuring a certain level of accuracy.
Machine translation of classical Chinese based on unigram segmentation transformer framework
Authors: Ju Zhuonan , Xin Yixuan , Ye Mingda
Published: February 2024

In the translation work of Chinese ancient books, traditional manual translation is difficult and inefficient. As an important field of natural language processing, machine translation is expected to solve this problem. Due to the rapid development of NLP technology, prior works mainly follow the pipeline of Transformer when dealing with the machine translation task, which can extract the high-quality feature representation with its self-attention mechanism. The great success of Transformer has inspired the direction of our ancient text translation work. In this paper, we screen the Unigram word division by exploring and comparing, and propose a solution for the translation of ancient literary texts. Specifically, we adopt the evaluation of BLEU value and achieve the BLEU values of 43.4 and 40.03 for short and long sentences respectively. When compared with the results of Baidu Translation, our BLEU values increase by 8.12 and 5.18. Additionally, our translation results are more in line with the original text than Baidu Translation, demonstrating the potential and advantage of the model in bridging the ancient and modern Chinese era rift.
Analysis of Naive Bayesian and Back Propagation algorithms in iris classification
Authors: Yu Chengyang
Published: February 2024

An efficient taxonomy of irises can provide botanists with valuable tools. Machine learning algorithms can effectively improve the performance of iris classification models because they can automatically analyze and summarize data. To this end, this paper introduces Naive Bayesian (NB) and Back Propagation (BP) to build classification models. When creating the NB model, the petal and sepal data from the iris dataset are used sequentially as classification criteria to classify the data. When constructing the BP model, the author sets different iterations and outputs the loss function and accuracy of the BP model under different iterations. The study finds that the NB model has higher classification accuracy when using petal length and petal width as classification criteria, which is 17% higher than the classification accuracy using sepal length and sepal width. Therefore, the NB model is more suitable for classifying independent data. By studying the use of the BP algorithm to classify iris flowers, the automatic classification of iris flowers can be realized and the accuracy of classification can be improved. Compared with the traditional NB algorithm, the BP algorithm can better mine the hidden patterns and information in the iris data and make effective classifications. This study provides new insights and discoveries for the taxonomic study of Iris plants.
Prediction of diabetes progress based on machine learning approach
Authors: Han Yiteng , Li Qixuan , Lou Jinghui , Zhang Jingrui
Published: February 2024

Uropathy is a serious chronic disease whose prevalence is increasing at an alarming rate. Early detection and prediction of diabetes in women is important because of the increased risk of diabetes-related complications during pregnancy. This study introduces machine learning models to assess the likelihood of diabetes in women. The importance of studying characteristics and improving prediction accuracy to understand the nuances of categorization. Specifically, for data preprocessing, experiments are conducted to solve the problem of missing values and outliers by replacing the zero values of certain features with the median values of the corresponding features. This step reduces the impact of less reliable data on model performance. As recognition models, Gaussian Naive Bayes (GNB), Support Vector Machine (SVM), and Random Forest (RF) are built. Performance analysis is performed along with a careful exploration of the hyperparameter space. Scores for Receiver Operating Characteristic - Area Under the Curve (ROC-AUC) are used to compare various models. Different features affect the classification to different degrees. The experimental findings indicate that the modified random forest model demonstrates superior prediction accuracy and robustness. These findings can assist physicians in predicting a patient's risk of developing diabetes earlier.
Design and development of 2D game 'Adventurous spirit'
Authors: Liu Jianshuo
Published: February 2024

In the present world, 2D games continue to be a significant component of the gaming industry. This article aims to discuss the process of designing and developing the 2D game "Adventurous spirit," while analyzing its essential elements and Unreal Engine technology. We will introduce the principles of game design, the intentions and purposes behind designing the game, the development process, as well as the tools and techniques employed. This 2D game is developed using the currently popular Unreal Engine, showcasing the final game outcome. Through the presentation in this report, readers will gain insights into the fundamental knowledge and practical experiences of 2D game design and development, along with some technical aspects and operations related to Unreal Engine development. Additionally, the genre of this game is a 2D side-scrolling game, where players enhance character abilities and levels through defeating monsters, and they can explore by selecting different characters.
The development and diverse applications of temperature sensors in different temperature environments
Authors: Cai Xinlin
Published: February 2024

This paper provides an in-depth study of the origins and trends of temperature sensors and their applications in high, low, and ambient temperature environments. Temperature sensors are crucial in industrial automation, healthcare, environmental monitoring, and other fields. This paper reviews the history of temperature sensors, from early measurement methods to advanced technologies. The use cases of temperature sensors in high-temperature environments are analyzed, emphasizing their role in ensuring equipment safety in industrial production and energy development. In low-temperature environments, temperature sensors find applications in scientific research and medical equipment, providing reliable temperature monitoring solutions. In room temperature environments, temperature sensors play a vital role in indoor temperature control and IoT applications. Three examples of temperature sensors, LM35, DS18B20, and DHT22, in different environments are introduced in detail. An in-depth analysis of the advantages and disadvantages of these sensors is provided, along with their specific uses in practical applications. This paper offers a comprehensive examination of temperature sensors, their historical development, and their diverse applications in various temperature environments. The analysis and presentation of specific sensor examples contribute to a deeper understanding of temperature sensing technology and its practical implications.
Enhancing multiplication efficiency: Harnessing Booth algorithm and Wallace tree synergy for 32-bit signed multipliers
Authors: Chen Panpan
Published: February 2024

This paper focuses on exploring performance optimization strategies for 32-bit signed multipliers in the realm of digital computation. The ingenious combination of the Booth algorithm and the Wallace tree takes center stage as the core of this research. Through a thorough analysis of this combined technique, the paper unveils its multifaceted advantages in multiplication operations. The unique contribution of the Booth algorithm is elaborately discussed, which involves streamlining the multiplication process by reducing the number of addition operations. Subsequently, the exceptional performance of the Wallace tree in accelerating the merging of partial products is highlighted. Through the synergistic interplay of these two techniques, the efficiency of multiplication operations is significantly enhanced, particularly suited for domains necessitating high-speed arithmetic computations, such as graphics processing and digital signal processing. The paper delves further into the significance of optimizing resource utilization, particularly in the field of integrated circuit design. By minimizing addition operations and optimizing parallel processing, the complexity of hardware implementation is reduced, leading to a notable decrease in resource requirements. This advantage proves invaluable in modern integrated circuit design, aiding designers in striking an optimal balance between spatial efficiency and power consumption.
Sentiment analysis of hotel comments based on LSTM and GRU
Authors: Xu Zeyu
Published: February 2024

Sentiment analysis, which tries to examine the emotional information in the provided text data, has always been a popular topic in the community of natural language processing. Sentiment analysis is currently used in many different contexts, including e-commerce platforms, social media platforms, public opinion platforms, and chatbots. These applications are crucial to the advancement of society and the domestic economy. However, due to the personalization of text data, especially comments, and the presence of acronyms, it is a challenging problem to obtain accurate sentiment information from large and complex unstructured text data. This study presents a comparative examination of various text sentiment analysis approaches, including LSTM, CNN, and GRU. These methods are employed to evaluate their respective performance on sentiment analysis tasks, specifically using a dataset of hotel reviews for training the models. The method presented in this research has been extensively validated through numerous experimental results, affirming its efficacy and its potential to offer novel perspectives for the practical implementation of sentiment analysis.
The distinguish between cats and dogs based on Detectron2 for automatic feeding
Authors: Shi Zijing
Published: February 2024

With the rapid growth of urbanization, the problem of stray animals on the streets is particularly prominent, especially the shortage of food for cats and dogs. This study introduces an automatic feeding system based on the Detectron2 deep learning framework, aiming to accurately identify and provide suitable food for these stray animals. Through training using Detectron2 with a large amount of image data, the system shows extremely high recognition accuracy in single-object images. When dealing with multi-object images, Detectron2 can generate independent recognition frames for each target and make corresponding feeding decisions. Despite the outstanding performance of the model, its potential uncertainties and errors still need to be considered. This research not only offers a practical solution to meet the basic needs of stray animals but also provides a new perspective for urban management and animal welfare. By combining technology with social responsibility, this innovative solution opens up a new path for solving the stray animal problem in cities, with broad application prospects and profound social significance.
Research on unsupervised image retrieval methods based on contrastive learning
Authors: Liu Hanhong
Published: February 2024

In the convergence of fashion and artificial intelligence (AI), significant strides have been made in areas such as clothing recognition, retrieval, and classification, enabled by advanced AI technologies and expansive annotated datasets. As the AI in Fashion market continues to surge, the future of the fashion industry promises to be redefined by intelligent, efficient, and more accessible solutions. Image retrieval, one of the important parts in AI, has experienced remarkable growth, empowered by advanced algorithms and vast annotated datasets, making it a crucial component in various domains such as digital libraries, online marketing. Therefore, this report mainly provides an extensive review of image retrieval methods and the emerging paradigm of contrastive learning, underscoring their relevance and applications in the realm of artificial intelligence. This paper primarily reviews the technologies in the amalgamation of the image retrieval field and contrastive learning. It elucidates the history and progression of image retrieval, offers a methodical analysis of the two primary approachestext-based image retrieval and content-based image retrievaland examines how contrastive learning is employed in image retrieval systems.
Chebyshev filter and Butterworth filters: Comparison and applications in different cases
Authors: Li Zhiqi
Published: February 2024

This study focuses on the filter selection problem in signal processing and wireless communication applications. Specifically, addressed two different filter selection problems: the Chebyshev filter and the Butterworth filter. Using MATLAB, in order to design and model these two types of filters. The performance, frequency response, transition band width, filter order, design complexity and target application of Chebyshev filter and Butterworth filter under different parameters are analyzed and compared. The selection of the two filters under different conditions and the reasons for choosing them are discussed. The Chebyshev filter is suited for applications that call for a high frequency response, and Chebyshev filters provide a steeper roll-down slope, which can suppress high-frequency noise and interference signals, according to the test results, it is widely used in communication systems. On the other hand, the Butterworth filter is more suitable for applications that require a flat passband and a wide stopband, such as audio systems.
Enhancing ASIC chip performance through integrated algorithm optimization
Authors: Xiao Shuying
Published: February 2024

As a crucial arithmetic logic unit, the multiplier plays a significant role in digital signal processing. However, multiplication operations often require a large number of calculations and logic gates, leading to increased circuit complexity and power consumption. To enhance the performance and efficiency of multipliers, this paper presents an optimization analysis based on the Wallace Tree and Booth algorithms. The Wallace Tree algorithm decomposes multiplication operations into multiple stages and employs both separate operations and bit-level parallelism to accelerate multiplication, achieving efficient parallel multiplication computations and reducing both latency and area complexity of multiplication. On the other hand, the Booth algorithm is an optimization method for signed binary multiplication. By introducing the concept of Booth encoding, it transforms signed multiplication into unsigned multiplication, thereby reducing the number of multiplication operations. This paper analyses the application and research progress of the Wallace Tree and Booth algorithms in the field of multiplier optimization to improve computational speed and reduce power consumption of multipliers.
Verbs of thought in 21st century literatura: Dante Medina
Authors: Ruiz Llamas Sandra
Published: February 2024

El lenguaje coloquial aumenta con expresiones, en su mayoría verbos de pensamiento. ¿Por qué pasó esto? Es precisamente el estudio de nuestro análisis: en los últimos dos siglos la pragmatización de las expresiones ha crecido desmesuradamente. En la literatura del siglo XXI, vemos cómo en América Latina se rompe una forma de decir las cosas con verdadero sentido semántico. En la literatura, los verbos que expresan procesos mentales representan nuevas realidades, sin que el vocabulario previamente existente sea minoritario. Los verbos de pensamiento más relevantes son adivinar, creer, idear, considerar, decidir, saber, recordar, preguntarse, darse cuenta, perdonar, entre otros. Nuestro análisis va dirigido a cuál es el uso actual que se consideraría correcto. Este estudio incluye los neologismos —verbos de pensamiento modernos— y el adecuado tratamiento del uso en el escritor mexicano Dante Medina. ¿Cómo y por qué el estudio de la pragmática en la literatura? La pragmática literaria probablemente utiliza el “adverbio de verosimilitud”, comunicación lingüísticamente correcta para designar las acciones como deben ser, es cuando entra la corriente filológica, y la representación de las incógnitas poéticas empieza a interesar con el uso de verbos de pensamiento. Aludimos en este estudio a que, junto a la semántica y la sintaxis, la pragmática conforma una cuadrilla que nos lleva a analizar la teoría semiótica de Medina aplicada al lenguaje de su literatura y verbos. Aprovechamos la pragmática Moderna que ofrece economía en el lenguaje: es lógica y precisa, para definir las distintas funciones que la semántica y la sintaxis tienen en los verbos del pensamiento para manifestar significados verdaderos.
Analisis Implementasi Pengukuran Kinerja Rumah Sakit Umum Daerah Asy-Syifa Sumbawa Barat dengan Menggunakan Metode Balance Scorecard
Authors: Nurman Amril , Umar Umar , Fahlia Fahlia
Published: February 2024

Tujuan penelitian ini adalah untuk menganalisi penerapan menggunakan metode balance Scorecard di RSUD Asy Syifa Sumbawa Barat. Jenis Penelitian penelitian menggunakan metode penelitian kuantitatif Deskriftif dengan sequential explanatory design melalui pendekatan sistem yaitu input, proses dan outcome pelayanan kesehatan di rumah sakit dengan pengisian kuisione, dan obyek penelitian adalah RSUD Asy Syifa Sumbawa Barat. Hasil penelitian hasil pengukuran mengan metode banlance scorecard melalui pada 4 perspektif didapati hasil yaitu 1) perspektif keuangan dengan menggunakan Value For Money yang terdiri atas: rasio ekonomi, rasio efisiensi dan rasio efektivitas  secara  umum  RSUD  Asy-Syifa’  Sumbawa  Barat  telah  ekonomis, artinya realisasi pengeluaran lebih kecil dari anggaran yang telah dibuat, 2) perspektif pelanggan menunjukkan hasil yang baik dengan yang dinilai melalui tingkat kepuasan pelayanan yang diberikan mencapai 88% termasuk dalam kategori puas, 3) perspektif bisnis internal menunjukkan keseluruhan proses bisnis berjalan baik dimana jumlah pengguna jasa terus meningkat yang dilihat dari BOR berada pada standar yaitu 72,34% dan TOI 1,88 walaupun untuk BTO melebih standard yaitu 53,82% yang artinya kebutuhan akan rawat inap terus meningkat 4) hasil analisis perspektif pembelajaran dan pertumbuhan menunjukkan hasil perhitungan secara keseluruhan sikap karyawan rumah sakit didapati kategori sangat puas menggunakan Multiatribut Attitude Model  (MAM) menghasilkan nilai sebesar 393,05. Sehingga diharapkan rumah sakit terus menjaga mutu pelayanan diikuti dengan evaluasi kinerja secara berkala untuk tahun-tahun kedepan, agar kinerjanya semakin baik.
К механизму образования спиртов при газофазном термическом окислении этилена
Authors: Эвинян М. А. , Давтян А. Г. , Арсентьев С. Д.
Published: February 2024

Изучен механизм образовании этанола при взаимодействии гидроксиэтильного и этоксильного радикалов с формальдегидом. Гибридным методом теории функционала плотности B3LYP/6-31+G(d,p) исследована поверхность потенциальной энергии системы C2H5OH+HCO на которой, для реакции образования этанола, локализованы переходные состояния и структуры, соответствующие пред- и пост-реакционным комплексам. Рассчитаны энергетические параметры реакций образовании этанола и формильного радикала.
Ուսումնասիրվել է հիդրօքսիէթիլ և էթօքսի ռադիկալների ֆորմալդեհիդի հետ փոխազդեցության ընթացքում էթանոլի առաջացման մեխանիզմը։ C2H5OH+HCO համակարգի պոտենցիալ էներգիայի մակերևույթի (ՊԵՄ) ուսումնասիրության համար կիրառվել ե խտության ֆունկցիոնալի տեսության հիբրիդային B3LYP/6-31+G(d,p) մեթոդը։ ՊԷՄ-ի վրա տեղայնացվել են էթանոլի առաջացման ռեակցիայի անցումային վիճակները, նախա- և հետռեակցիոն կոմպլեքսները: Հաշվարկվել են էթանոլի և ֆորմիլ ռադիկալի առաջացման ռեակցիաների էներգետիկ պարամետրերը։ Ցույց է տրվել, որ հիդրօքսիէթիլ և էթօքսիլ ռադիկալները ֆորմալդեհդի հետ փոխազդեցության ժամանակ էթանոլի առաջացման ռեակցիաների ջերմային էֆեկտները մոտավորապես հավասար են։
The mechanism of ethanol formation during the interaction of hydroxyethyl and ethoxy radicals with formaldehyde has been studied. The hybrid density functional theory method B3LYP/6-31+G(d,p) was used to study the potential energy surface of the C2H5OH+HCO system on which, for the reaction of ethanol formation, transition states and structures corresponding to pre- and post-reaction complexes are localized. The energy parameters of the reactions for the formation of ethanol and formyl radical were calculated. It has been shown that the thermal effects of the reactions of ethanol formation during the interaction of hydroxyethyl and ethoxyl radicals with for-maldehyde are approximately equal.
PROFITABILITAS DAN SOLVABILITAS PADA KINERJA KEUANGAN BANK SYARIAH
Authors: Hayani Wulan Martha , Sutra Dewi Aminar
Published: February 2024

This study aims to examine the extent to which profitability and solvency ratios affect financial performance. This research is a quantitative research method using data in the form of financial statements of the Islamic banking sector at the Financial Services Authority for the period 2017 –2021. This study used a purposive sampling method. The results of the study show that the influence of the profitability ratio on the performance of the Islamic banking financial sector at the Financial Services Authority during the 2017 – 2021 period has no significant effect. Although the results in this study are not significant it does not mean that companies can ignore the Profitability ratio. Often conditions of high profit will be a consideration for investors in these companies in making investment decisions and creditors in loan decisions. Meanwhile, the solvency ratio of the Islamic banking sector at the Financial Services Authority during the 2017-2021 period as a whole is said to be in good condition and has a positive effect on financial performance. In this study, the data analysis method used was descriptive statisrics using the stata 14 program
ANALISIS MODEL AISDALSLove : HIERARKI EFEK RESPONS KONSUMEN TERHADAP LOGO HALAL BARU INDONESIA
Authors: Wahyudi Hijrah , Mardiyati Mardiyati
Published: February 2024

This study aims to analyze the hierarchical effect of consumer responses to Indonesia's new halal logo using the AISDALSLove model. The data analysis technique used was the Total Category Rating (TCR) with a total of 200 respondents who were taken using a purposive sampling technique. The results showed that the variable awareness has the highest rating rate of 84.30%, while the variable desire and like has the lowest rating rate of 80.10%. This shows that consumers have high awareness of Indonesia's new halal logo and the importance of halal certification in food and beverage products. However, the level of consumer desire and preference in buying products containing the new Indonesian halal logo still needs to be improved. Thus, food and beverage companies need to continue to improve the quality of their halal products and strengthen marketing and education campaigns regarding the new Indonesian halal logo to increase the level of consumer desire and preference in buying halal products. This research is expected to contribute to the food and beverage industry in increasing consumer confidence in local halal products.
KOMPARASI PENDAPATAN USAHATANI PADI BERDASARKAN PENGGUNAAN BENIH DI KECAMATAN SUNGAI KAKAP KABUPATEN KUBURAYA
Authors: Ekawati  , Darmawan Reiza , Rizieq Rahmatullah , Sugiardi Sigit
Published: February 2024

This study aims to compare rice farming income between those using certified and non-certified seeds. The results of this study can provide an overview of the income farmers will obtain if they use certified seeds. The research was conducted in Sungai Kakap village, Sungai Kakap sub-district, Kubu Raya Regency. Most rice is produced in this area, so it was chosen as the research location. The research sample consisted of 30 farmers consisting of 22 farmers using non-certified seeds and eight farmers using certified seeds. The research data is processed so that RC Ratio can be obtained and continued with the different tests between income. The results showed that the income from rice farming with certified seeds was higher than non-certified seeds. However, the value of the RC ratio for farms with non-certified seeds is higher. The t-test results concluded that there is a significant difference between farm income using certified and non-certified seeds statistically. Finding certified seeds that will increase production and save costs is advisable. The four farmers are also advised to be able to use certified seeds in their farming business
ANALISIS LAPORAN KEUANGAN PT KERETA API INDONESIA (PERSERO) PERIODE 2020–2021 UNTUK MENGUKUR KINERJA KEUANGAN BERDASARKAN RASIO LIKUIDITAS
Authors: Maura Azhari Dhea , Samri Juliati Nasution Yenny
Published: February 2024

Analysis is used to assess the company's financial performance using its financial reports from different reporting periods. The general public, investors, shareholders and management can all benefit from financial company reports while making decisions and growing their own assets. This study will use financial measures based on liquidity ratios which include current ratios, quick ratios, and cash ratios to show the financial performance of the company PT Kereta Api Indonesia (Persero). The company's financial statements, which include an income statement and balance sheet for 2020-2021, are the subject of research. In this research data analysis used descriptive analysis using financial ratio analysis. Liquidity ratio consisting of current ratio (Current Ratio), quick ratio (Quick Ratio), and cash ratio (Cash Ratio) which is the basis for the results of financial ratio analysis
PENGARUH GREEN PRODUCT KNOWLEDGE TERHADAP PURCHASE INTENTION MELALUI GREEN TRUST DAN GREEN ATITTUDE
Authors: Ardiansyah
Published: February 2024

The aim of this research is to test the influence of green product knowledge on purchase intention with green trust and green attitude as mediating variables. This research is explanatory research which aims to test and explain the causal relationship between research variables through hypothesis testing. The approach taken in this research is a quantitative research approach. The data used is primary data. The purposive sampling method was used as a sample determination technique. The process of obtaining data is carried out by means of a survey in the form of a questionnaire. In this study, researchers used 100 respondents who were consumers of LED lights. This research uses Structural Equation Modeling (SEM) to test the hypothesis. The findings of this research are as follows. Green product knowledge, green trust and green attitude have a positive influence on purchase intention. Apart from that, green trust and green attitude are unable to mediate the relationship between green product knowledge and purchase intention.
GENDER DIFFERENCES IN SLEEP DURING AGING: A NARRATIVE REVIEW
Authors: Iroldi Grazielle Ferreira , Grazziano Pedro , Guiesi Pedro Henrique Machado , Alves Élen dos Santos , Orlandi Ariene Angelini dos Santos , Inouye Keika
Published: February 2024

Sleep is a fundamental biological need for rest, maintenance and restoration of physical and mental well-being. Irregular sleep causes changes in the circadian cycle and can lead to changes in physiological processes. Furthermore, it is different between men and women. Therefore, the objective of this research is to carry out a narrative review on the topics, sleep, aging and the difference between sleep in relation to gender. The literature points out that there are differences in sleep between women and men. Women present complaints regarding sleep, such as insomnia, due to the physiological and cyclical variation of their organism. Men, on the other hand, report more problems with their sleep due to respiratory problems, such as apnea, and excessive daytime sleepiness. There are few studies on the topic nowadays, so it would be interesting to study more about the impact of these differences during aging
COVID-19 AND THE RELATIONSHIP WITH ENVIRONMENTAL FACTORS: A SCOPE REVIEW
Authors: Capeleto Silkiane Machado , Da Silva Cristhiane Almeida Leite , Pinto Júnior Osvaldo Borges , De Oliveira Igor Rian Bonelli , Shimoya-Bittencourt Walkiria
Published: February 2024

Objective: Conduct a scoping review to map the scientific evidence on the existing relationship between the transmission and spread of COVID-19 with environmental, climatic and seasonality factors. Methodology: Review studies published in PubMed, Embase, Web of Science, SCOPUS and Virtual Health Library Portal (VHL). 33 studies were included in the review, most from China, followed by Brazil and the United States of America. Results: The most studied factors were temperature, climate and humidity, wind, air quality, precipitation with the transmission of the SARS-Cov-2 virus in the year 2020. The attribution of the positive relationship or not, obtained in the studies regarding influence of climatic environmental factors and seasonality on the transmission or dissemination of SARS-CoV2 are controversial both for the increase or reduction of cases, due to the divergence of results regarding the studied variables, design and location. Conclusion: This study did not find enough evidence to support the hypothesis that higher temperatures will reduce COVID-19 transmission. The significant and valid impact of air pollution and climate change on the transmission of COVID-19 must be considered, with strong implications for preventive strategies for new pandemics.
PENGARUH KOMPETENSI DAN BUDAYA ORGANISASI TERHADAP KINERJA PEGAWAI DENGAN KEPUASAN KERJA SEBAGAI VARIABEL INTERVENING
Authors: Lestariningsih Suprihatin , Widhiastuti Susanti
Published: February 2024

Permasalahan dalam sebuah organisasi yakni kompeten dari sumber daya manusia dengan peran dan tugas untuk mendukung organisasi mencapai tujuannya. Sebuah organisasi, macam bentuknya yang tetap dibutuhkannya individu yang memiliki ragam potensi dalam mendukung kinerja yang diharapkan. Salah satunya perguruan tinggi, yang menjadi organisasi yang bergantung pada kinerja sumber daya manusianya yang menjadi bagian, termasuk pegawai yang memiliki peran, tugas, dan tanggungjawab dalam mewujudkan tujuan pendidikan nasional, yaitu mencerdaskan kehidupan bangsa, meningkatkan kualitas manusia Indonesia, yang meliputi kualitas iman dan takwa, akhlak mulia, dan penguasaan ilmu pengetahuan, teknologi, dan seni, serta mewujudkan masyarakat Indonesia yang maju, adil, makmur, dan beradab. Faktor-faktor yang mempengaruhi kinerja karyawan adalah kompetensi dan budaya organisasi terhadap kinerja karyawan pada suatu organisasi atau institusi. Pendekatan yang akan dilakukan dalam penelitian ini adalah pendekatan analisis kuantitatif berdasarkan informasi statistika. Hasil dalam penlitian ini adalah pengaruh langsung kompetensi dan budaya organisasi terhadap kinerja pegawai lebih dominan bila dibandingkan dengan pengaruh tidak langsung kompetensi dan budaya organisasi terhadap kinerja pegawai melalui kepuasan kerja.
Upaya Pencegahan Stunting Melalui Kegiatan Sosialisasi Dan Makanan Sehat Kepada Masyarakat Di Desa Pakis Kecamatan Panti Kabupaten Jember Oleh KKN Kolaboratif 154 Jember
Authors: Al Fauzi Fatih , Akbar Hidayatullah Gumanti  , Kholid Muayyanah  , Nadiyah Choirun Nisah  , Mohammad Fajar Ramadhan  , Ayu Ning Tiyas  , Sri Yulistiani  , Adistya Maharani  , Rina Wulandari  , Daniel Jireh Rampisela  , Sukartiningsih  , Karimatul Azizah  , Afita Khoirun Nisa  , Prafilia Hilyatul Faizah  , Putri Maulidya Achsani  , Wahida Rohmatullah  , Eka Efit Fitrianingsih
Published: February 2024

Stunting merupakan salah satu permasalahan yang serius di Desa Pakis Kecamatan Pakis. Mahasiswa KKNK 154 berupaya untuk mengurangi angka stunting di Desa Pakis dengan menggunakan sosialisasi, penyuluhan dan demo makanan sehat untuk anak-anak dan ibu hamil. Metode yang digunakan yaitu dengan mengumpulkan data kesehatan di desa Pakis, menetapkan sasaran sosialisasi kemudian melakukan sosialisasi dan membuat produk makanan sehat (puding jagung) untuk mengurangi angka stunting. Hasil yang didapat selama pengabdian KKN di Desa Pakis yaitu banyak masyarakat yang antusias mengikuti sosialisasi, banyaknya ibu hamil yang mendapat informasi dan perduli terhadap stunting. Selain itu banyak anak kecil yang mulai melakukan gaya hidup sehat dan memakan makanan sehat. Tingginya angka stunting di Desa Pakis dapat dikurangi dengan rutin memberikan sosialisasi, pengarahan dan demo makanan sehat bagi ibu hamil dan anak-anak untuk mengurangi resiko terjadinya stunting sekaligus mengurangi angka stunting.
Pengenalan Healthy Food Sebagai Upaya Meningkatkan Produk Makanan Sehat Dalam Kewirausahaan
Authors: Wulandari P Aulia , G Pratidina Febi , Arditya M , Virginia Nanda , Brammastha RS Righty , Muktiarni Muktiarni
Published: February 2024

Kegiatan penyuluhan ini dilatar belakangi oleh kurangnya kesadaran remaja untuk mengkonsumsi healthy food. Padahal masa remaja merupakan masa pertumbuhan dan perkembangan yang sangat pesat baik secara fisik, psikis, dan kognitif. Healthy food merupakan salah satu faktor penting dalam proses pertumbuhan dan perkembangan remaja. Akan tetapi, kini remaja lebih banyak mengkonsumsi junk food dibandingkan healthy food, yang dimana dapat memberikan pengaruh negatif terhadap pertumbuhan mereka karena kebanyakan junk food tidak sehat jika dikonsumsi berlebihan. Kebiasaan mengkonsumsi junk food berpengaruh terhadap kegiatan kewirausahaan di SMA yang dimana siswa/i kerap menjual makanan atau minuman yang dianggap kurang sehat seperti mie pedas, makanan kemasan, dan minuman yang mengandung banyak gula. Oleh karena itu dilakukan penyuluhan mengenai healthy food yang diharapkan kedepannya dapat diterapkan dalam kegiatan kewirausahaan tingkat SMA. Metode yang digunakan saat melakukan penyuluhan yaitu metode ceramah, quiz dan demo masak healthy food. Ceramah dilakukan dengan media PowerPoint dan Quiz dilakukan dengan platform Quiziz. Berdasarkan penyuluhan yang telah dilakukan diketahui bahwa sebagian besar siswa/i belum mengenal lebih mendalam mengenai healthy food dan belum mengkonsumsi healthy food kehidupan sehari-hari. Setelah diberikan pematerian siswa/i mulai memahami mengenai healthy food dan siswa/i dapat menjawab pertanyaan quiz yang diberikan dengan hasil yang cukup memuaskan
Effective Promotion: Pemanfaatan Media Sosial Pada Pengembangan UMKM Kuliner Kolyaki di Desa Kedungboto
Authors: Amalijah Eva , Wahyuddin Zida , Ardiansah Helmi
Published: February 2024

Kuliner memiliki peran yang sangat penting bagi Ekonomi dan Pariwisata. Dan juga penggunaan sosial media sebagai media promosi juga berkembang sangat massif. Hasil dari pengabdian masyarakat yang dilakukan di Desa Kedungboto untuk mempromosikan Kuliner Kolyaki dengan memanfaatkan media sosial dipaparkan dalam artikel ini. Salah satu kuliner yang sedang dikembangkan desa ini adalah takoyaki dengan isian kol sawah yang disebut kolyaki. Tujuan penelitian ini adalah untuk meningkatkan ekonomi desa dengan menggunakan media sosial sebagai alat promosi. Selama pengabdian, warag desa Kedungboto telah mendapatkan pelatihan digital marketing untuk meningkatkan penggunaan media sosial. Dalam konteks ini, warga desa Kedungboto menerima pelatihan digital marketing yang mencakup pengenalan sosial media dan pemanfaatan media sosial sebagai media promosi. Selain itu, Pre-test dan Post-test dilakukan untuk mengevaluasi pengetahuan dan kemampuan Warga desa Kedungboto dalam promosi digital. Penelitian menunjukkan bahwa pemanfaatan media sosial dapat membantu pertumbuhan ekonomi desa, meningkatkan ekonomi pengusaha UMKM dan popularitas produk Kolyaki.
Peningkatan Produksi ASI Ibu Menyusui dengan Penyuluhan Pola Makan Seimbang dan Penurunan Tingkat Stress di Bogorejo, Magetan
Authors: Sebtalesy Cintika Yorinda , Anisia Dian , Mulyati Sesaria Betty
Published: February 2024

Menyusui secara eksklusif selama 6 bulan pertama kelahiran bayi tanpa memberikan tambahan makanan padat atau cairan selain Air Susu Ibu (ASI) bermanfaat bagi banyak segi kehidupan. Produksi ASI yang lancar diperlukan untuk proses tersebut. Makanan dan ketenangan jiwa merupakan salah satu faktor yang dapat mempengaruhi produksi ASI tersebut selain dipengaruhi oleh faktor hormon prolaktin dan oksitosin. Kandungan ASI terdiri dari berbagai macam jenis gizi yang sangat khusus dan sempurna sesuai yang dibutuhkan oleh bayi. Tujuh dari sepuluh ibu di Bogorejo  memiliki pengetahuan yang kurang mengenai  pola makan untuk ibu menyusui dan belum mengetahui mengenai pengelolaan stres. Kegiatan penyuluhan ini bertujuan untuk meningkatkan pengetahuan ibu menyusui khususnya mengenai pola makan dan pengelolan stres sehingga dapat meningkatkan produksi ASI. Kegiatan ini menggunakan metode penyuluhan dan diberikan evaluasi pengetahuan berupa pre-test dan post test dengan jumlah peserta 17 responden ibu menyusui bayi usia 0-12 bulan. Dari kegiatan penyuluhan ini diperoleh hasil adanya peningkatan pengetahuan pada ibu menyusui bayi usia 0-12 bulan dilihat dari perbandingan hasil pre-test dan post test.
Code Switching in English Teacher Instruction: A study of the Teacher Language in English Classroom and Its Implications for Indonesian Students Language Education
Authors: Abdul Gani Hastini , Nabilah Nur Izzah  , Jamiluddin
Published: February 2024

Teaching English in Indonesia is not the same as teaching English in a country where English is the native language. The teacher should make sure the students understand the explanation or instruction from the teacher. In the foreign language classroom, code switching is naturally occurring to make the teaching learning process run smoothly. Therefore, this study aimed to explain the function of code switching, students perceptions of the teacher’s code switching, and the effect of teacher’s code switching practices on students’ understanding in the teaching learning process. It was conducted at SMAN 9 Palu by using descriptive qualitative as the method. The researcher used observation, questionnaire and interview to get the data. The results of the study showed that first, there were three functions of code switching used by the teacher proposed by Sert (2005), those are topic switch, affective function, and repetitive function. Second, most of the students had positive perceptions about students' understanding and students' feelings during learning with code switching used by the teacher. Third, code switching used by the teacher in teaching learning English process provides a positive effect in providing a positive learning environment, and facilitating students with low level of second language proficiency

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Keywords: Code switching, English classroom, teacher instruction