bluuebunny/crossref_metadata_2025 huggingface dataset:
Analisis Pengaruh Harga, Kualitas Produk dan Kualitas Pelayanan Terhadap Kepuasan Konsumen (Studi Kasus Ayam Geprek Dower Pekanbaru)
Authors: Pane Arya Duta Permana
Published: May 2024

Abstrak
Bisnis kuliner merupakan salah satu sektor industri yang memiliki tingkat persaingan yang cukup besar yang muncul seiring dengan adanya ide yang kreatif dan inovatif yang membuat konsep pemasaran lebih berkembang dan tepat sasaran. Tujuan dari penelitian ini adalah untuk mengetahui seberapa besar pengaruh harga, kualitas produk dan kuallitas pelayanan terhadap kepuasan konsumen di Ayam Geprek Dower Pekanbaru. Metode penelitian yang digunakan yaitu kuantitatif. Data yang digunakan pada penelitian ini adalah data primer yang diperoleh dari kuesioner. Sampel penelitian ini adalah konsumen Ayam Geprek Dower yang berjumlah 100 responden. Teknik analisis menggunakan analisis linier beganda. Variabel penelitian ini terdiri dari variabel bebas yaitu harga, kualitas produk, dan kualitas pelayanan dan variabel terikat yaitu kepuasan konsumen pada Ayam Geprek Dower Pekanbaru. Hasil penelitian menujukkan bahwa harga, kualitas produk dan kualitas pelayanan berpengaruh positif dan signifikan terhadap kepuasan konsumen secara simultan. Pengujian secara parsial menghasilkan: harga berpengaruh signifikan terhadap kepuasan konsumen ditunjukkan dengan nilai thitung 1990 dan ttabel 1.985. kualitas produk berpengaruh signifikan terhadap kepuasan konsumen ditunjukkan dengan nilai thitung 2.306 dan ttabel 1.985. kualitas pelayanan berpengaruh secara signifikan terhadap kepuasan konsumen ditunjukkan dengan nilai thitung 3.452 dan ttabel1.985
Kata Kunci : Harga, Kualitas Produk, Kualitas Pelayanan, Kepuasan Konsumen
The Influence of Marketing Mix on Purchase Intention with Customer Attitude as a Mediating Variable (A Case Study of a New Men's Fashion Retail Business in Surabaya)
Authors: Rizky Suci Sukmajaya , Aprianingsih Atik
Published: May 2024

Indonesia's textile and apparel industry is experiencing a significant demand, with an anticipated GDP increase of 2022. Surabaya, a major city in Indonesia, is well-positioned to capitalize on this opportunity by establishing a retail business catering to the lower-middle-class segment of the men's fashion industry. This study aims to help entrepreneurs in Surabaya identify factors influencing their decision to establish a retail business in the men's fashion sector using the SEM-PLS method. The research investigates the purchase intentions of men of productive age from the lower-middle-class demographic and the potential marketing mix strategies for businesses in the Surabaya men's fashion sector. Findings from 230 respondents showed that product, place, and promotion variables significantly influence customer attitude, which in turn influences purchase intention. However, price does not significantly influence customer attitude. The study suggests that price, product, and promotion variables can be partially mediated by customer attitude, while the place variable can be fully mediated.
The Influence Of Product Quality, And Brand Images On Purchasing Decisions Through The Role Of Purchase Intention As An Intervening Variable As An Intervening Variable (Case Study On Purchasing An Iphone Brand Smartphone In Yogyakarta)
Authors: Lukitaningsih Ambar , Cahya Agus Dwi , Iskandar Mizan
Published: May 2024

This research is quantitative research, which was conducted to test the influence of product quality, brand image, and purchase intention as intervening variables on purchasing decisions. The data in this research was collected through a questionnaire using Google Form with respondents who were owners, users, or who had purchased an iPhone brand smartphone in Yogyakarta, with a total of 115 respondents. Testing in this research uses multiple linear regression analysis tests. The results of this research show that product quality has a significant effect on purchasing decisions, brand image has no effect on purchasing decisions, purchase intention has an effect on purchasing decisions. Simultaneously, the variables product quality, brand image, and purchase intention influence purchasing decisions.
Performance Evaluation Of Programs And Activities In The Aspect Of Information And Communication Technology With A Logic Model Approach
Authors: Haloho Selvy Elida , Wijayanti Nanda Ayu
Published: May 2024

This study was conducted to evaluate the performance of programs and activities in the ICT aspect in order to determine the logical relationship between information and performance indicators that have been determined in the strategic planning documents of the Kutai Kartanegara Regency Government and Diskominfo, as well as the outcome sequence chart in accordance with the evaluation results in order to improve the performance of these programs and activities. This research is a qualitative study using a case study-based evaluation process. Primary data used is obtained from semi-structured interviews with respondents in the ICT and E-Governement Sectors. Analysis of program and activity performance data will use a logic model approach. The results showed that performance information already has a logical relationship, but its implementation cannot support the achievement of Diskominfo's KPI performance. Furthermore, there are still inconsistencies between the performance indicators that have been determined and those listed in the performance appraisal document. The recommended outcome sequence chart has been prepared in accordance with indicators related to the ICT aspect of SPBE. Diskominfo needs to reformulate information and performance indicators to be in line with the strategic planning that has been set. This research is expected to contribute to improving the performance of existing programs and activities in the Regional Government.
Perceptions and Attitudes of Indonesian Generation Z towards Debt
Authors: Astuti Penitaliasih Dwi , Faturohman Taufik
Published: May 2024

This research aims to understand the relationship between the demographic profile of Generation Z in Indonesia and their perceptions and behavior towards debt. Data collection was carried out through an online survey of 400 respondents in the period July to September 2023. Analysis of the data that had been collected was carried out using descriptive statistics, and continued using the Kruksal Wallis and Mann Whitney U Test to see more deeply whether there were statistically significant differences. between two or more independent variables. The results of this study found that there were significant differences in the influence of gender and income on their perceptions and behavior toward debt. Apart from that, there is no significant difference between level of education and employment and perceptions and behavior towards debt.
The Effect of Marketing Mix on Purchase Intention in the Home Appliance Industry in West Java
Authors: Sari Dyah Puspita , Belgiawan Prawira Fajarindra
Published: May 2024

The purpose of this research is to discover what factors influence someone's decision to purchase home equipment. In this study, a discussion was held about the effect of the 4P marketing mix elements on purchase intention. The product, the price, the place, and the promotion are the four marketing aspects that will be discussed in this paper. The respondents in this study were 234 people who met the requirements of being of productive age, living in West Java, and having a fixed income. SEM-PLS was used to analyze the data, and the results revealed that just three variables from the marketing mix affected customer purchase intention in the home appliances industry. Product, price, and promotion are the variables that influence purchase intention; however, place has no effect. The company can pay attention to these three variables while designing strategies to improve market competition.
Comparative Analysis Of Machine Learning And Deep Learning Models Integrated With Altman Z-Score For Financial Distress Prediction In Companies Listed On The Indonesia Stock Exchange (IDX)
Authors: Irvan Fadly Muhammad
Published: May 2024

Financial distress is a condition in which a company experiences a decline in its financial situation, which is typically temporary. However, financial distress can worsen if not promptly addressed, leading to bankruptcy. Early identification of potential financial distress in a company is crucial for stakeholders such as investors, creditors, and regulators. In practice, predicting financial distress in a company is not an easy task. One of the methods commonly used to identify early symptoms of financial distress is the method introduced by Altman in 1986. Altman's research model, known as the Z-Score, determines a value based on standard calculations of financial ratios to indicate the likelihood of a company experiencing bankruptcy. The use of artificial intelligence, such as deep learning, can enhance the scope of research on the analysis and prediction of financial distress. This study aims to conduct a comparative analysis of machine learning models, such as the K-Nearest Neighbor Classifier and Random Forest Classifier, and deep learning models, such as Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN). This analysis is carried out to evaluate the success rate of the proposed deep learning models in predicting financial distress in companies operating in Indonesia. Based on the conducted research, the K-Nearest Neighbor Classifier algorithm achieved an accuracy of 77.42% during testing and 88.89% during validation, the Random Forest Classifier algorithm achieved an accuracy of 87.09% during testing and 95.24% during validation, the CNN model achieved an accuracy of 95.16% during testing and 96.83% during validation, and the RNN model achieved an accuracy of 93.55% during testing and 96.83% during validation. Based on these results, the deep learning method has a higher average success rate than machine learning models in predicting financial distress.
FAKTOR – FAKTOR YANG BERHUBUNGAN DENGAN KEJADIAN DIARE PADA BALITA DI RT/007 RW/008 DESA AIR DINGIN KECAMATAN BUKIT RAYA PEKANBARU
Authors: Heni Heriyeni  , Rizki Natia Wiji
Published: May 2024

In Indonesia, diarrheal disease is one of the causes of death in infants. Diarrhea is one of the most common diseases affecting children worldwide. The aim of the study was to determine the factors associated with the incidence of diarrhea in toddlers at RT007 RW008 Airdinding Village, Bukit Raya District, Pekanbaru in 2024. This research method used an analytical survey approach with a cross sectional design. The population in this study were all babies who visited the Simpang Tiga Health Center as many as 126 toddlers. Sampling was carried out by Probability Sampling with a total of 95 samples. Primary data collection using a questionnaire. Univariate analysis described the frequency distribution of each variable while bivariate analysis used the Chi-Square test. The results of univariate analysis showed a history of non-exclusive breastfeeding 51.6%, 65.3% less knowledge of mothers, 57.9% personal hygiene and 67.4% history of diarrhea and the results of bivariate analysis showed that there were three variables of history of exclusive breastfeeding with p value = 0.0016, mother's knowledge p = 0.000 and maternal personal hygiene with p = 0.000 means that Ho is rejected and Ha is accepted. It is suggested that health workers at the Simpang Tiga Health Center provide promotions that should be focused on eliminating various inaccurate assumptions about diarrhea. Diarrhea prevention promotion materials should include the influence of the environment and breastfeeding on the occurrence of diarrhea with the process of activities being carried out in an integrated manner with the planning of other programs.
PENERAPAN AROMATERAPI MAWAR TERHADAP PENGURANGAN RASA NYERI PERSALINAN PADA NY P DI PUSKESMAS TANJUNG BALAI KARIMUN
Authors: Maryati Maryati , Utami Risqi , Fahnawal T. Marzila
Published: May 2024

Labor pain needs to get good treatment and not cause complications that can interfere with labor. Aromatherapy is a complementary therapy that is able to treat pain and infection because it is an analgesic, anti-inflammatory and antimicrobial (Muchtaridi, 2015). Objective To provide midwifery care to mothers giving birth on an ongoing basis, with management of midwifery care in accordance with midwifery service standards. Midwifery care that is applied is the application of rose aromatherapy to reduce labor pain. Methods The type of research used in the preparation of the practice report was a descriptive study, conducted at the Tanjung Balai Karimun Health Center in March 2023. The results of midwifery care related to the application of rose aromatherapy to midwifery care for mothers in labor to reduce labor pain have been carried out Conclusion Evaluation of the care provided shows that giving rose aromatherapy can help reduce pain in labor
PENERAPAN AROMATERAPI SEREH TERHADAP KECEMASAN MENGHADAPI PERSALINAN PADA NY D DI PUSKESMAS TANJUNG BALAI KARIMUN
Authors: Nilma  , Mariyana  , Roza Nova
Published: May 2024

Anxiety about childbirth is felt by all pregnant women before delivery. Essential oils in labor can improve coping strategies in birthing mothers. The main role of essential oils during labor and delivery is to help relieve pain, stress and anxiety. The aim is to provide midwifery care for mothers in a comprehensive and sustainable manner, with management of midwifery care in accordance with midwifery service standards. Midwifery care that is applied is the application of citronella aromatherapy to anxiety in facing childbirth. The practice report preparation method is descriptive research with the case study method conducted at the Tanjung Balai Karimun Health Center in February 2023. The subject used in this case study with midwifery care management was Mrs. D. Results and Conclusions Evaluation of the care provided related to the application of lemongrass aromatherapy to the anxiety of facing childbirth there is a reduction in the anxiety that the mother feels
PENGARUH PEER GROUP SUPPORT TERHADAP SELF CARE KLIEN HIPERTENSI
Authors: Mi’mah Nihayatun , Asyrofi Ahmad , Arisdiani Triana , Ardiyanti Yulia
Published: May 2024

Hypertension is still a health problem that is quite high from all reported non-communicable diseases. Hypertension will cause complications such as heart disease, stroke, kidney failure if hypertensive patients have poor self-care. Complications can be prevented by doing good self care to improve the patient's quality of life. One of the interventions that can be used to improve self-care is peer group support. The measuring instrument uses a Self Care Management Behavior Questionnaire which is valid and reliable. The research design used Quasi Experimental with the Nonequivalent Control Group Design method pretest-posttest. The sample used was hypertensive clients who took prolanis at the Patebon 02 health center with a total of 30 respondents as a peer group support group and 30 respondents as a control group. The sampling technique used was total sampling. Statistical test using Wilcoxon and Chi Square. The results of the study obtained a p value of 0.0001 (p <0.05), which means that there is an influence of peer group support on self care of hypertensive clients.
HUBUNGAN STATUS GIZI DENGAN KEJADIAN HIPERTENSI PADA LANSIA DI WILAYAH KERJA PUSKESMAS KALIWUNGU KABUPATEN KENDAL
Authors: Saharani Ifaresa , Kusuma Triya Ulva , Moviana Radiati
Published: May 2024

Hypertension is still the highest degenerative disease in Indonesia, which has experienced a high increase in cases compared to previous years. Nutritional status is one of the risk factors that influence the incidence of hypertension. This study aims to determine the relationship between nutritional status and the incidence of hypertension in the elderly in the working area of ​​the Kaliwungu Public Health Center, Kendal Regency. The research method used was a cross-sectional study design and used primary data in the form of nutritional status and blood pressure of the elderly in the working area of ​​the Kaliwungu Health Center, Kendal Regency. Nutritional status was obtained by measuring body weight and height, while hypertension status was obtained by measuring systolic blood pressure in the elderly. The number of research samples is 108 respondents, the analysis used is the Gamma correlation statistical test with a confidence level of 95%. The results of this study showed that some of the respondents were elderly with obesity nutritional status (BMI => 27) as much as 26.9% and elderly people who had stage I hypertension, namely as many as 32.4%. The results of the nutritional status gamma test with the incidence of hypertension in the elderly in the working area of ​​the Kaliwungu Public Health Center, Kendal Regency, were p = 0.164 (p <0.05). It can be concluded that the relationship between nutritional status and the incidence of hypertension has a positive direction, although there is no significant relationship. This insignificant relationship is probably due to the fact that most of the respondents have normal nutritional status (50%), but as many as 62.9% of respondents have stage I hypertension. Nutritional status is not always related to the incidence of hypertension, there are other factors that can also influence it concurrent with hypertension. The conclusion in this study is that nutritional status has no relationship with the incidence of hypertension in the elderly in the working area of ​​the Kaliwungu Health Center, Kendal Regency.
Exploring Knowledge, Attitudes and Practices Regarding Single-Use Plastics in Lahore Workspaces
Authors: Ayub Fizzah , Haider Naqvi Syeda Laiba , Zahra Naqvi Syeda Hamayal , Afzal Aiman , Akram Rizwana , Jaweriya Jaweriya , `Shahzad Muhammad
Published: May 2024

Plastics are solid, low-price and have become a vital part of our daily life. The plastic industry is growing continuously over the decades to satisfy the needs of growing population. About 40% of the plastics produced worldwide are single use plastic and their disposal is a significant hazard to the human health and environment. The current study focuses on the knowledge, attitude and practices of people towards plastic usage at different workplaces in Lahore. To investigate behavior and perception of plastic consumption an online survey was conducted from March to August 2021. Results suggested that people have good knowledge about the impacts of plastic on public as well as environmental health 90% of respondents knew plastic takes thousands of years to degrade, 91.5% of them knew plastic is hazardous for environment, they (87.8 %) agreed that plastic threatens aquatic life but they usually don’t practice it and show negligent attitude towards the use of plastic and its products. Like 54.8 % respondents use plastic bag to carry their lunch box and 32.5 % of them take tea/coffee in disposable plastic cup at their workplace. Similarly, 86.3 % people knew that heating plastic lunch box in microwave oven makes food cancerous but still majority (36.8 %) of them directly microwave their plastic lunch box. Hence, combination of sound policies and awareness may help to address the major environmental problem and may also help to reduce environmental pressure posed due to plastic pollution.
Morphology and phylogeny of four new species within Polycephalomycetaceae (Hypocreales) parasitising Ophiocordyceps species
Authors: Liu Zuoheng , Tang Dexiang , Lu Yingling , Zhu Juye , Luo Lijun , Sun Tao , Yu Hong
Published: May 2024

Species of the family Polycephalomycetaceae grow on insects or entomopathogenic fungi and are distributed from tropical to subtropical regions. This study proposed four new species of hyperparasitic fungi from China based on six molecular markers (ITS, SSU, LSU, TEF-1α, RPB1 and RPB2) phylogenetic analyses and morphological characteristics. The four new species, i.e. Pleurocordyceps litangensis, Polycephalomyces jinghongensis, Po. multiperitheciatae and Po. myrmecophilus, were described and illustrated. Pl. litangensis, exhibiting a hyperparasitic lifestyle on Ophiocordyceps sinensis, differed from Pleurocordyceps other species in producing subulate β-phialides and ovoid or elliptic α-conidia. Po. jinghongensis was distinct from Polycephalomyces other species, being parasitic on Ophiocordyceps sp., as producing oval or long oval-shaped α-conidia and columns of β-conidia. Po. multiperitheciatae differed from Polycephalomyces other species as having synnemata with fertile head, linear β-conidia and parasitic on Ophiocordyceps multiperitheciata. Po. myrmecophilus was distinct from Polycephalomyces other species, being parasitic on the fungus Ophiocordyceps acroasca, as producing round or ovoid α-conidia and elliptical β-conidia without synnemata from the colonies. These four species were clearly distinguished from other species in the family Polycephalomycetaceae by phylogenetic and morphological characteristics. The morphological features were discussed and compared to relevant species in the present paper.
Assessing knowledge, perceptions, and readiness of telemedicine recipients: A cross-sectional study
Authors: Hamdan Iman , Alkhader Enas
Published: May 2024

Objectives: The current study aimed to assess the knowledge and perceptions of telemedicine recipients. Secondly, to evaluate their readiness towards adopting telemedicine in clinical settings.

Methods: A cross-sectional survey study was conducted in Jordan and designed to show the demographics of participants. The questionnaire was piloted for validity and reliability to achieve the aim of the study, and a collective of 420 participants were recruited.

Findings: Multiple regression analysis conducted showed that telemedicine services were significant at a level of α ≤ 0.05. Whereas the Pearson’s correlation of the dependent and independent variables was also significant at a level of α ≤ 0.05 as a function of age, working status, and income.

Conclusions: Regardless of the fact that participants showed a limited knowledge of telemedicine services, most of the participants expressed positive perceptions towards telemedicine services and its adoption in the clinical settings.
Similar looking sisters: A new sibling species in the Pristimantis danae group from the southwestern Amazon basin (Anura, Strabomantidae)
Authors: Köhler Jörn , Glaw Frank , Aguilar-Puntriano César , Castroviejo-Fisher Santiago , Chaparro Juan C. , De la Riva Ignacio , Gagliardi-Urrutia Giussepe , Gutiérrez Roberto , Vences Miguel , Padial José M.
Published: May 2024

We describe a new frog species that is the sibling of Pristimantis reichlei. These two sister species inhabit the Amazonian lowlands and adjacent foothills of the Andes, from central Bolivia to central Peru. Pristimantis reichlei occurs from central Bolivia to southern Peru (Alto Purús National Park), while the new species occurs from northern Bolivia (Departamento Pando) to Panguana in central Peru (Departamento Huánuco), at elevations between 220 and 470 m a.s.l. In spite of their morphological crypsis, these siblings occur in syntopy without evidence of interbreeding (in the Alto Purús area) and are recovered as reciprocally monophyletic. Their uncorrected pairwise genetic distances in the 16S rRNA gene range from 9.5–13.5%, and their advertisement calls differ in both qualitative and quantitative traits. Moreover, our study found uncorrected pairwise distances within the new species of up to 5.0% and up to 9.3% within P. reichlei. We therefore cannot rule out the possible existence of hybrids or additional species-level lineages hidden in this complex. Furthermore, we found another potential pair of sibling species composed of P. danae and an unnamed lineage, with divergences of 9.4% in the 16S gene, whose in-depth analysis and taxonomic treatment are pending future revision. With the new nominal species, the Pristimantis danae species group now includes 20 species, distributed across the upper Amazon basin and in the eastern Andes, from western Brazil to Bolivia and Peru. Our study, together with an increasing number of other studies, indicates that sibling species are far from being rare among Amazonian amphibians and that species resolution remains low even for groups that have received considerable attention in recent years.
Envisaging Dynamics of Entrepreneurship in View of Modern-Day Innovation and Advancements
Authors: Raghunath K. Madhu Kishore , Patro Chandra Sekhar
Published: May 2024

Digital technologies are changing the essence and extent of entrepreneurship. A distinctive characteristic of digitization is its ability to automate tasks that demand a lot of human labour. Contemporary innovations in artificial intelligence (AI) are making it possible for computers to perform activities that would typically need human intellect, such as processing vast unstructured data sets using sophisticated, adaptive algorithms. This has prompted entrepreneurs to consider the generativity of AI, indicating that the technology may represent a fundamental innovation to the instruments that they develop with, in addition to a way to achieve cost and productivity gains. Thus, the purpose of the chapter is to assess the influence of AI determinants on entrepreneurial effectiveness, identify the key strategies for successful digital transformation, benefits and challenges of AI on entrepreneurship.
AI-Enabled Industrial Applications
Authors: Kamalapuram Khaja Baseer , Joseph Maria Joseph B. , Abhishek  , Jahir Pasha Jahir
Published: May 2024

The project's objective is to provide an explanation of AI-enabled industrial applications and how they can benefit businesses. One of the primary factors that contribute to a movement closer to the fourth industrial revolution is AI. Automation has the potential to enhance economic growth worldwide by streamlining tasks and improving human performance. Additionally, it can aid in decision-making and facilitate interconnected supply chains by providing real-time data from various sources, allowing for total optimization and transparency that might not be possible with the most effective methods currently in use. On a larger scale, AI may completely replace human workers. Artificial intelligence can be used to link the real and virtual worlds in a loop. In this project overview, the authors talk about how AI and human workers can work together to automate a wide range of tasks and the challenges we'll face while developing and investing in these solutions.
Shattering the Glass Ceiling of Women Entrepreneurship in the Digital Retail Landscape
Authors: Mishra Pallavi , Mukherjee Tanushri
Published: May 2024

With its unprecedented ability to harness collective intelligence Web 2.0 has ushered possibilities in digital entrepreneurship. Digital entrepreneurship has occupied an indispensable place in the business industry as it has a dynamic approach to engross customers on online platforms and to promote their products and services. Over the years, access to digital technology has played a major role in empowering women to do business.The famous women entrepreneurs of Nykaa, Zivame, Limeroad and Sugar Cosmetics have paved a way for entrepreneurial development that features each kind of new digital business, and an analysis of how those traits determine the success factors of women entrepreneurship. In the panorama of entrepreneurship, the function of women has been evolving step by step over the years. One place wherein their effect has been specifically noteworthy is virtual media entrepreneurship. This chapter delves into the arena of girls' entrepreneurs within the virtual media area, brands like Nykaa, Zivame, Limeroad and SUGAR Cosmetics.
A Wikipedia Narration of the GameStop Short Squeeze
Authors: Vasileiou Evangelos , Hadad Elroi , Chalkiadaki Aikaterini
Published: May 2024

This paper examines the usefulness of Wikipedia pageviews as indicator of the performance of stock prices. We examine the GameStop (GME) case, which drew the investors' and scholars' attention in 2021 due to the Short Squeeze (SSQ), and its skyrocketing price increase since 2021. We use the daily number of pageviews of Wikipedia pages for COVID-19, GME, and SSQ as explanatory variables for the period 31/12/2018-30/3/2022. The results show strong statistical evidence that increased number of Wikipedia pageviews for COVID-19, which represents the fear of the pandemic, has a negative impact on the GME performance. Moreover, the findings show that the increased interest in information regarding the short squeeze, as expressed by the increased number of pageviews of the relative Wikipedia page, is positively linked with the GME price. This approach holds the potential to yield benefits not only for entrepreneurs within the finance sector but also across various other fields. It serves as a valuable proxy for gauging the demand for goods, services, and/or overall interest in a market.
Potential of Business Intelligence and Analytics on the Performance of Tourism and Hospitality Companies
Authors: Amiri Mahsa , Ramos Célia M. Q.
Published: May 2024

Nowadays, making the right business decisions is crucial for companies. With the enhancements in connectivity, data accessibility has been expanding rapidly. Information is meaningful, data and business intelligence (BI) turn data into information to support the decisions of persons or companies with the purpose of efficiency and effectiveness increasing. However, selecting the right BI system which can be adopted perfectly by a business is an important issue which still needs further studies. The given study comprises the literature review which focuses on BI and analytics, and it continues to study the structure of a BI system and the effects such systems may cause. The findings contribute to a better comprehension of BI and more efficient feedback from BI systems by choosing the right ones. The future collaboration between BI and artificial intelligence (AI), also BI and sustainability goals, are further given topics in this study
Development of an Intelligent System for Stock Market Prediction Using Enhanced Deep Learning Technique With Banking Data
Authors: Manjunatha B. , Revathi V. , Kavin Balasubramanian Prabhu , Seng Gan Hong
Published: May 2024

The future may be unknown and uncertain, but there are still opportunities to make money by anticipating it. The request of AI and ML to stock market prediction is one such opportunity. Artificial intelligence may be used to generate accurate forecasts before investing, even in a dynamic environment like the stock market. The stock market's data is typically not stationary, and its properties are often uncorrelated. The stock market patterns that are traditionally predicted by several STIs may be inaccurate. To study the features of the stock market using STIs and to make profitable trading decisions, a model has been developed. This study presents an enhanced bidirectional gated recurrent neural network (EBGRNN) for detecting stock price trends using STIs. HDFC, Yes Bank, and SBI, three of the most well-known banks, have had their dataset evaluated. It is a real-time snapshot of the national stock exchange (NSE) of India's stock market. The datasets included business days from 11/17/2008 to 11/15/2018.
Ensembled Time Series Deep Learning Framework for Stock Market Prediction
Authors: Balagourouchetty Lakshmipriya , Singh Nidhi , Jayalakshmy S.
Published: May 2024

Prediction and analysis of Stock Market plays a very important and crucial role in today's economic growth. Understanding the pattern of these financial activity and predicting its transformation and development are the most challenging areas of research in financial sectors and academic sectors. This paper explores the competency of sequential learning elements viz. long short-term memory (LSTM), bidirectional long short-term memory (BiLSTM) and gated recurrent unit (GRU) with different depths and combinations in forecasting the share market trend from the Nifty50 dataset. The experimental assessment elucidates that the ensemble prediction model built using BiLSTM-LSTM and BiLSTM-GRU by the virtue of integrating the merits of BiLSTM and LSTM/GRU layers demonstrate a better performance closer to reality with least error.
A Smart Innovative Pre-Trained Model-Based QDM for Weed Detection in Soybean Fields
Authors: Gunapriya B. , Thirumalraj Arunadevi , Anusuya V. S. , Kavin Balasubramanian Prabhu , Seng Gan Hong
Published: May 2024

Precision farming that takes advantage of the internet of things infrastructure now includes weed identification as a core component. Weeds now account for 45 percent of crop losses in farming because of competition with crops. This figure can be lowered with effective weed detecting technology. One of the most important areas of AI, known as deep learning (DL), is revolutionizing weed discovery for site-specific weed management (SSWM). In the past half a decade, DL methods have been used with both ground- and air-based technology for weed documentation in still images and in real time. According to the latest findings in DL-based weed detection, developing methods that aid precision weeding technologies in making informed decisions is a priority. Over the past five years, deep learning algorithms have been successfully incorporated into both ground-based and aerial-based systems for the purpose of weed identification in both still picture and real-time scenarios.
Cloud Computing Adoption for Small and Medium Enterprises in Mechanical Engineering
Authors: Sekhar K. C. , Ranganathan L. , Bathrinath S. , Premnath D. , Yuvasri B. , Boopathi Sampath
Published: May 2024

This chapter delves into the adoption of cloud computing in small and medium-sized enterprises (SMEs) in mechanical engineering, highlighting its transformative potential. It discusses the benefits of cloud infrastructure, such as improved operational efficiency and innovation, but also addresses security and privacy challenges. The chapter provides strategies to mitigate these risks and emphasizes the importance of tailoring cloud solutions to meet the unique needs of SMEs. It also discusses the future of cloud technology, focusing on emerging trends and innovations. It also examines regulatory compliance and adherence strategies for a secure and compliant cloud integration journey. The chapter concludes with a comprehensive roadmap for SMEs in mechanical engineering, offering practical strategies, lessons learned, and a forward-looking perspective on the ever-evolving intersection of cloud computing and mechanical engineering.
Sugarcane Disease Detection Using Data Augmentation
Authors: Verma Abhishek , Singh Jagrati
Published: May 2024

Sugarcane is an important crop for the Indian economy, providing employment opportunities for millions of farmers. Nevertheless, the cultivation of sugarcane faces challenges from pests and diverse diseases. The detection and segmentation of plant diseases using deep learning have shown promising results in simple environments with abundant data. However, in complex environments with limited samples, the performance of existing models suffers. This study introduces an innovative method that addresses the challenges of complex environments and sample scarcity, aiming to enhance disease recognition accuracy. The highest accuracy showcased by model is 98% on testing data. Comparative study was done on the same dataset by employing various ML algorithms and achieved the highest accuracy of 70%. An Android app has been created to serve as the user interface for this model. This app enables farmers to either take pictures using their phone's camera or choose images from their gallery.
AI-Enabled Data Processing for Real-World Applications of IoT
Authors: Santhanagopalan Suresh , Ramachandran Murali , Pappu Rajan A.
Published: May 2024

This is a digitally inclined era. The government support across all the countries in the globe and its associated initiatives on this IoT are commendable. In this chapter, the authors studied the research papers related to big data, IoT, and AI. The research papers were fetched from the Scopus database using Boolean operators (AND, OR) with the keywords, “IoT”, “Big Data”, “H IoT”, and “AI”. The chapter is presented in two parts. The first part is about the synthesis of the major papers related to this study. The second part is about the leverage of AI in various sectors like healthcare, education, finance, smart cities, energy, telecommunication, and agriculture. After studying from the vast literature, it shows that that IoT, big data, and ML are indispensable in the years to come. In this chapter, the authors call for government, industries, and academicians to collaborate together for conferences, seminars, and joint projects to digitalize all the premises and bring a data driven decisions.
Python Programming for Geospatial Applications
Authors: Das Deepthi , Natarajan Arul Kumar
Published: May 2024

Geospatial solutions represent a pivotal toolset for analyzing, interpreting, and visualizing spatial data across diverse domains, facilitating informed decision-making and fostering innovation. This book chapter provides a comprehensive overview of geospatial solutions, emphasizing their critical role in addressing spatially explicit challenges and driving efficiency, productivity, and innovation across various sectors. Furthermore, it explores the integration of Python programming in geospatial applications, highlighting its versatility and extensive ecosystem of libraries and tools tailored for spatial data analysis and visualization. The fundamentals of web mapping are discussed in depth, elucidating spatial representation, technologies, and tools commonly employed in web mapping applications. Also, the chapter explores Python's role in retrieving geospatial data with Python, visualization methods, and interactive web mapping.
Exploring Vector and Raster Data Formats for Geospatial Visualization With Python
Authors: M. Marsel Sonu , Das Deepthi , Natarajan Arul Kumar , A. Manimaran
Published: May 2024

The chapter uses Python to explore vector and raster data formats within geospatial visualization. It highlights their pivotal role across diverse environmental science, urban planning, and natural resource management domains. A nuanced comprehension of these formats is deemed essential for proficient geospatial visualization in Python, as they facilitate the storage and manipulation of spatial data. Vector data formats accurately represent points, lines, and polygons within a coordinate system. In contrast, raster data formats are tailored to depict continuous surfaces or grids of data. An array of libraries and tools are outlined for exploring and visualizing these geospatial data formats in Python, each serving distinct functionalities ranging from data manipulation to visualization. The chapter systematically introduces the concept of geospatial visualization, elucidates the disparities and application scenarios of vector and raster data formats, and subsequently elucidates various Python libraries and tools conducive to geospatial data manipulation and visualization.
Welcome to the 12th ICTHIC!
Authors: Anna Falanga, Benjamin Brenner, Alok A. Khorana Guest Editors:
Published: May 2024

Dear Colleagues,
We are pleased to present this volume of the Proceedings and the Abstracts of the 12th International Conference on Thrombosis and Hemostasis Issues in Cancer (ICTHIC) being held in Bergamo, Italy, May 17-19, 2024.
Cancer-associated thrombosis – which includes both venous and arterial events in its clinical manifestations and involves cancer biology, hemostatic proteins, platelets and many other players in its subclinical terrain – is an old problem. Yet it makes its way into the newest of new themes in cancer medicine, including new paradigms of treatment which continue to be complicated by this very old effect [...]
Surface carcass treatment with olive mill wastewater polyphenolic extract against Salmonella enteritidis and Listeria monocytogenes: in vitro and in situ assessment
Authors: Altissimi Caterina , Roila Rossana , Primavilla Sara , Branciari Raffaella , Valiani Andrea , Ranucci David
Published: May 2024

In recent years, there has been an increased interest in substances that could inhibit or reduce microbial growth in food products. Olive oil industry by-products, due to bioactive compounds with potential antimicrobial properties such as polyphenols, could be used in carcass treatment to enhance hygienic and quality traits. The assessment of the antimicrobial efficacy of bioactive molecules against pathogens should be determined with in vitro and in situ models since it is not possible to evaluate it directly on carcasses at the slaughterhouse. This study aimed to evaluate the effect of an olive mill wastewater polyphenolic extract against Salmonella enteritidis and Listeria monocytogenes, simulating carcass surfaces using bovine dermis samples that were experimentally contaminated with the selected pathogens. The minimum inhibitory concentration and minimum bactericidal concentration were first determined for S. enteritidis and L. monocytogenes. In situ bactericidal activity assessment was performed using 20 cm2 derma samples contaminated with 5 Log CFU/20 cm2 of S. enteritidis and L. monocytogenes in separate trials. Treatment with the polyphenolic extract was not effective for either microorganism. In order to establish the bacteriostatic activity of the polyphenolic extract, suspensions of about 2 Log CFU/20 cm2 of S. enteritidis and L. monocytogenes were used. Polyphenolic extract treatment was not effective against Salmonella, while for Listeria it allowed microbial growth to delay (around 1 Log CFU/cm2 difference at 3, 7, and 14 days between treated and control groups). Further investigations are needed to evaluate the application of polyphenolic compounds on carcass surfaces and their effects on sensory traits.
Public support to low-carbon innovation: Grants for all?
Authors: Ruester Sophia , Olmos Luis
Published: May 2024

This article is devoted to the financing of innovation activities targeting low-carbon technologies. Its aim is to guide European energy policy makers in the design and implementation of public support policies given the inevitable constraints on funding. We focus on pre-deployment innovation, namely research, development and demonstration activities that belong to the early, highly risky stages of the innovation chain and, thus, need direct public support.
STUDY ON LITERACY NUMERACY TOWARDS STUDENTS’ LOGIC MATHEMATICS: A LITERATURE REVIEW
Authors: Pratiwi Septia Ayu , Nofikusumawati Peni Nur Robiah , Prabowo Anggit
Published: May 2024

Numeracy literacy and mathematical logical thinking have a significant relationship in mathematics learning. Therefore, the study of this literacy examines the relationship between literacy, numeracy, and the development of students' logical thinking in the domain of mathematics education. This research aims to delineate the impact of numeracy literacy and logical thinking in shaping students' abilities to understand and apply logical principles in the context of mathematics, given the fundamental importance of literacy and numeracy skills. In this study, a literature review is employed to examine the relationship between literacy, numeracy, and logical thinking in the context of mathematics. The methodology used involves data collection, review processes, and in-depth analysis of scholarly articles sourced from Google Scholar, JSTOR, and PubMed. A total of 105 articles were analysed and categorized into the contexts of literacy, numeracy, and logical thinking in the context of mathematics. The research findings indicate the complexity of the interrelationship between literacy, numeracy, and logical thinking in mathematics education. This research contributes to offering insights into numeracy literacy and logical thinking for educators, researchers, and policymakers interested in enhancing the quality of mathematics education.
An Investigation of the Prevalence & Reporting of Mild Traumatic Brain Injury in a Survey of British Female Basketball Players
Authors:   , Hall Layla
Published: May 2024

Objective: The current study sought to investigate the prevalence of reporting of mild Traumatic Brain Injury (mTBI) and its symptoms in female basketball athletes. It also sought to evaluate the attitudes and knowledge surrounding mild traumatic brain injury (mTBI) in the same sample. Method: Participants (N = 34) from the three highest leagues in Great Britain (Women’s British basketball league: 24.91±4.28 years old, National basketball league division one: 22.06±4.14 years old, National basketball league division two: 22.33±2.73 years old) were recruited. Each participant completed a novel survey assessing the prevalence of mTBI, the reporting habits of mTBI, and the educational history regarding mTBI. Results: Within the sample 52.94% answered they had received a suspected mTBI in their careers, with 35.29% being formally diagnosed with a mTBI. The mean number diagnosed was 2.21±1.90. Athletes were more likely to report a mTBI during a training session than they were in a competition/game (t=0.07, P>0.05) also more likely (t=0.06, P>0.05) to report a mTBI during game play to a teammate than they were to a member of their coaching staff. 41.18% answered yes to if they had ever experienced any mTBI symptoms and continued to play, and 32.35% of the samples answered yes to having not reported mTBI to continue playing in a game or practice. Conclusions: In conclusion, female basketball players within the UK are at risk of sustaining mTBI during their careers, and further to this, these athletes do not report all mTBI suffered from. This supports the current findings in previous research as to the negative culture of underreporting of mTBI in athletic populations.
Mathematical modelling as a field of research: advances in the ecological analysis
Authors: Barquero Berta
Published: May 2024

This paper focuses on the recent evolution of the field of mathematical modelling research and how different research questions have been formulated and addressed by international theoretical frameworks. This paper focuses on the “epistemological”, “economic” and “ecological” dimensions of these different theoretical approaches to mathematical modelling. We will see that the ecological issue is still largely absent from many approaches. This will allow us, in a second step, to show some tools of the anthropological theory of the didactic (ATD) such as the study and research paths (SRP) that we have been proposed to facilitate the design, implementation and analysis of modelling practices in different school levels and in teacher education.

Este artículo se centra en la evolución reciente del campo de la investigación en modelización matemática y en cómo se han formulado y abordado diferentes problemas de investigación en los distintos enfoques teóricos en el ámbito internacional. Nos centramos más concretamente en cómo los distintos enfoques teóricos a la modelización matemática abordan las dimensiones “epistemológica”, “económica” y “ecológica”. Mostraremos cómo la problemática ecológica sigue estando bastante ausente en muchos de estos enfoques. Esto nos permitirá, en la segunda parte, mostrar algunas herramientas de la teoría antropológico de lo didáctico (TAD), como los recorridos de estudio e investigación (REI) que han sido propuestos para facilitar el diseño, implementación y análisis de prácticas de modelización en distintos niveles escolares y en la formación de profesores.

Cet article s’intéresse à l’évolution récente du domaine de recherche sur la modélisation mathématique et la manière dont différentes questions de recherche ont été formulées et abordées par des cadres théoriques internationaux. Ce travail se focalise plus particulièrement sur les dimensions « épistémologique », « économique » et « écologique » de ces différentes approches théoriques de la modélisation mathématique. Nous verrons que la problématique écologique est encore en grande partie absente de nombreuses approches. Ceci permettra, dans un second temps, de montrer certains outils de la théorie anthologique du didactique (TAD) comme les parcours d’étude et de recherche (PER) que nous avons proposés pour faciliter la conception, la mise en œuvre et l’analyse des pratiques de modélisation dans différents niveaux scolaires et dans la formation des enseignants.