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BULLET : Jurnal Multidisiplin Ilmu
Published by CV. Multi Kreasi Media
ISSN : -     EISSN : 28292049     DOI : -
Core Subject : Humanities, Health, Education, Social,
Humanities Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Nursing
- Ilmu Komputer - Kemasyarakatan - Kewirausahaan - Manajemen - Ekonomi - Manajemen - Agama - Ilmu Hukum - Pendidikan - Pertanian - Sastra - Teknik - Dan Bidang Ilmu Lainnya
Arjuna Subject : Umum - Umum
Articles 589 Documents
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Using AI in Healthcare: Improving Fraud Detection and Combining Petroleum and Herbal Medicine Insights Muhammad Ibrar; Muhammad Fahad; Muhammad Umer Qayyum; Ali Husnain
BULLET : Jurnal Multidisiplin Ilmu Vol. 3 No. 4 (2024): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

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Abstract

Artificial Intelligence (AI) is revolutionizing multiple sectors by enhancing efficiency, optimizing processes, and driving innovation. This article explores the transformative impact of AI across four diverse fields: healthcare, herbal medicine, the petroleum sector, and their interdisciplinary synergies. In healthcare, AI's applications include advanced diagnostics, personalized treatment, and improved fraud detection. Insights from the petroleum industry, where AI is used for predictive maintenance, exploration optimization, and safety management, offer valuable strategies for enhancing healthcare operations and fraud detection. Additionally, the integration of AI with herbal medicine promises to validate traditional remedies and personalize patient care by combining modern technology with ancient practices. The article highlights how cross-industry insights can lead to novel solutions and enhanced outcomes across different domains. By examining these interdisciplinary connections, the article underscores the potential of AI to bridge gaps, drive innovation, and create a more integrated approach to solving complex challenges, ultimately benefiting society and advancing the frontiers of technology and knowledge.
The Most Recent Advances and Uses of AI in Cybersecurity Muhammad Ismaeel Khan; Aftab Arif; Ali Raza A Khan
BULLET : Jurnal Multidisiplin Ilmu Vol. 3 No. 4 (2024): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

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The incorporation of modern technology into cybersecurity measures has become imperative due to the growing sophistication and frequency of cyber threats. This review delves into the most recent developments and uses of artificial intelligence (AI) in cybersecurity, emphasizing how it may improve threat detection, automate responses, and give businesses useful insights. The conversation covers the present state of artificial intelligence applications, such as automated threat intelligence, natural language processing, and machine learning, and it uses case studies from a variety of industries, including retail, healthcare, and finance, to demonstrate how effective they are. Important implementation hurdles for AI, such as data privacy difficulties, ethical concerns, and the high rate of false positives, are also covered, highlighting the necessity for enterprises to carefully manage these challenges. In terms of the future, the analysis points to several interesting avenues for AI in cybersecurity, such as enhanced automation, better predictive capabilities, and integration with cutting-edge innovations like quantum computing, block chain, and the Internet of Things (IoT). The review emphasizes how AI has the ability to completely change cybersecurity procedures and emphasizes how crucial it is to solve ethical and practical issues in order to reap the full benefits of this technology. Organizations may improve their cybersecurity posture and effectively respond to a changing threat landscape by implementing AI-driven solutions and cultivating a culture of continuous learning and adaptation.
Harnessing Artificial Intelligence in Healthcare and Petroleum Industries Advances in Fraud Detection and Novel Approaches in Cancer Medicine George Edison
BULLET : Jurnal Multidisiplin Ilmu Vol. 3 No. 4 (2024): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

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Abstract

This review explores the transformative role of artificial intelligence (AI) in enhancing sustainability and operational efficiency in the healthcare and petroleum industries. It highlights the potential of AI technologies to revolutionize patient care through improved diagnostics, personalized medicine, and optimized resource allocation in healthcare, while also addressing critical ethical considerations such as data privacy, algorithmic bias, and accountability. In the petroleum sector, AI applications in resource extraction, predictive maintenance, and emissions monitoring present significant opportunities for reducing environmental impact and increasing operational efficiency. The review emphasizes the necessity of establishing ethical frameworks and regulatory standards to navigate the complexities associated with AI deployment, ensuring that its benefits are distributed equitably across diverse populations. Furthermore, it underscores the importance of collaboration among stakeholders, including policymakers, industry leaders, and ethicists, to promote responsible AI usage that prioritizes sustainability and equity. By harnessing AI's capabilities thoughtfully, both sectors can advance toward a more efficient, equitable, and sustainable future while addressing the pressing challenges of our time.
Pengaruh Arus Kas Operasi Dan Laba Akuntansi Terhadap Tingkat Keuntungan Saham Nurlailatul Laifah, Ika; Adi Rahardjo, Kusuma; Supriadi, Imam; Muchran Noor, Gusti
BULLET : Jurnal Multidisiplin Ilmu Vol. 3 No. 5 (2024): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

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Abstract

This research aims to examine the influence of Operating Cash Flow and Accounting Profit on the level of stock profits because in reality there are several differences between the relationship between each variable and the level of stock profits for consideration by potential investors before investing in shares. This research uses a quantitative approach with secondary data as a source of information. The theory used is signal theory. The independent variables in this research are Operating Cash Flow and Accounting Profit, while the dependent variable in this research is the stock profit rate. The population in this study was 99 companies. This research uses a purposive sampling technique with a sample of 31 companies and produces observation sample data of 93 companies in the period 2020 – 2022. The analysis technique used is Statistical Product and Service Solutions (SPSS) version 25. The results of this research show that Operating Cash Flow has an effect positive effect on stock profit levels, while accounting profits have a negative effect on stock profit levels. Simultaneously, these two independent variables influence the level of stock profits. It is hoped that potential investors and issuers will always pay attention to liquidity as one of the highlights when considering stock investment.
Evaluasi Pelatihan Jarak Jauh Business English I Pada Balai Pendidikan Dan Pelatihan Keuangan Denpasar Dyah Indrawati, Efi; Lestyowati, Jamila
BULLET : Jurnal Multidisiplin Ilmu Vol. 3 No. 5 (2024): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

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Distance Training (PJJ) of Business English I is intended to improve the competence of Ministry of Finance employees to use English in carrying out organizational tasks and functions, especially in conducting business conversations and practicing basic business writing. This study aims to evaluate the effectiveness of PJJ Business English using the Kirkpatrick Evaluation Model Level 1 (Reaction) and Level 2 (Learning). The evaluation is used to obtain the participants’ satisfaction and their skills improvement in English. The research method used is a mixed method. Quantitative data were obtained through participant satisfaction surveys at the Reaction level and pre-post-test results at the Learning level. Qualitative data were collected through in-depth interviews to explore participants' experiences and perceptions of the training. The results showed that participants were satisfied with the training with an average high level of satisfaction. At the Learning level, there was a significant increase in participants' business English skills, such as understanding business terms and written communication skills. These findings indicate that distance training of Business English I is effective in improving participant competence. The implications of the results of this study can be a reference in the development of more structured distance training on business English that is tailored to the needs of participants.
Tingkat Keterampilan Passing Control Futsal Peserta Ekstrakurikuler Sekolah Menengah Kejuruan Negeri 1 Lelea Azhar Saifuddin, Faiz; Zakky Mubarok, Mochamad; Kharisma, Yudhi
BULLET : Jurnal Multidisiplin Ilmu Vol. 3 No. 5 (2024): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

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Abstract

The purpose of this study is to find out Skill Level of Futsal Passing Control Extracurricular Participants futsal Vocational High School 1 Lelea. The research method used in this study is a descriptive research method. The population and samples in this study were 20 students at SMKN 1 Lelea. The sampling technique is using purposive sampling, the research used by this study. Futsal Passing Control Skills Test. The result of this study was passing control with a good category of 9 students 45%.
Analisis Rancangan Tata Letak Fasilitas Toko Roti A Dengan Pendekatan Activity Relationship Chart (ARC), Total Closeness Rating (TCR) Dan Ongkos Material Handling (OMH) Tiara; Perdana, Surya; Atikah
BULLET : Jurnal Multidisiplin Ilmu Vol. 3 No. 5 (2024): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

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Abstract

A's Bakery has an inadequate facility layout, which reduces productivity and service quality. To improve operational efficiency and enhance movement efficiency in the store, the facility layout must be reorganized. All areas and spaces in A Bakery, including the display, cashier, kitchen, toilet, storage, and dining area, are included in the primary data of this research. This research uses the Activity Relationship Scheme (ARC) and Total Closeness Rating (TCR) for data processing. The results of the Total Closeness Rating (TCR) calculation show the order of development priorities, with TCR values of 192 for the display area, 110 for the kitchen, 110 for the cashier, 97 for the dining area, 92 for the warehouse, and 6 for the restroom. Based on distance calculations and material handling costs, it was found that the initial distance results decreased from 1,398.00 to 840.1 and the material handling cost calculation results decreased from 2,255,742.91 to 1,355,543.37, this can make bakery A effective and efficient based on the layout of existing facilities. The result of this calculation forms a layout solution, which includes block templates, suggested alternative layouts, and optimal layouts.
Implications of AI on Cardiovascular Patients’ Routine Monitoring and Telemedicine Arbaz Haider Khan; Hira Zainab; Roman Khan; Hafiz Khawar Hussain
BULLET : Jurnal Multidisiplin Ilmu Vol. 3 No. 5 (2024): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

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Cardiovascular and chronic disease management and treatment are started to incorporate Artificial Intelligence gradually into cardiovascular telemedicine and remote monitoring. Through the use of AI technologies, patients are much benefited, and at the same time, it promotes improvement in patients, examination, and continuous monitoring. Since the use of AI forefront in its role as a monitoring technique, predictive analytics, risk factors and detail personal medication in zone of cardio vascular diseases, this paper dwells on one how cardio vascular care is evolving with experimental use of AI. It also describes the limitation and challenge of AI use, for instance, around data privacy, legal regime and data quality, and AI moral decisions such as the disposition of openness and trust. Nevertheless, the current demands require future development in cardiology –telemedicine with the use of artificial intelligence in prescriptive and predictive cardiology based on precision medicine, machine learning, and genomic as well as electronic health records data. Therefore, the following aspects should be addressed to overcome the present challenges to the effective functioning of AI in the healthcare segment of cybersecurity threats, data connections, and accessibility. Therefore, the paper’s conclusion about the subject AI obversive points to the potential for a full-scale revolution in the sphere of cardiovascular care with regards to the patient’s outcomes and accessibility and effectiveness on the international level under conditions of further regulation as well as technological enhancement.
Leveraging Artificial Intelligence and Big Data: A Comprehensive Examination of Workforce Performance Enhancement, Fraud Detection in the Petroleum and Banking Sectors, Healthcare Innovations, and Ethical Considerations in Information Management Systems Alexandra Harry; Ali Khan
BULLET : Jurnal Multidisiplin Ilmu Vol. 3 No. 5 (2024): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

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Abstract

In a time of swift technology development and growing data quantities, businesses in a variety of industries are realizing how important it is to boost employee performance, increase operational efficiency, and prevent fraud. The impact of employee training and development on productivity, the use of Block chain and artificial intelligence (AI) in healthcare, the application of successful fraud detection techniques in the banking and petroleum industries, and the optimization of SQL databases for big data workloads are the four main topics covered in this thorough analysis. The results highlight how crucial it is to fund staff training initiatives designed to develop competencies and promote an environment of lifelong learning in order to propel organizational success. The combination of Block chain technology with artificial intelligence (AI) has the potential to revolutionize patient-centered care and secure data management in the healthcare industry, improving both operational efficiency and health outcomes. Advanced technologies like machine learning and big data analytics, which offer strong defenses against the growing threat of fraudulent activities, are becoming more and more important in the banking and petroleum industries for detecting fraud. Effective management of big data workloads requires optimizing SQL databases using strategies like indexing, partitioning, and in-memory processing, which guarantees quick access to crucial insights. All of these observations demonstrate how training, technology, and operational strategies are intertwined in negotiating the intricacies of the modern business environment. In addition to strengthening their resilience, organizations that take proactive measures to address these issues will set themselves up for long-term growth and innovation in a setting that is becoming more and more competitive.
ENHANCING DATA PRIVACY AND SECURITY IN MULTI CLOUD ENVIRONMENTS Md Emran Hossain; Md Farhad Kabir; Abdullah Al Noman; Nipa Akter; Zakir Hossain
BULLET : Jurnal Multidisiplin Ilmu Vol. 1 No. 05 (2022): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

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In this study, we present and realize a solution for contributing to the provision of data security and data privacy in a hybrid configuration based Multi Cloud environment. This method combines prevention of independent cloud security attacks and server failures through a Byzantine fault tolerance protocol, a data encoding and decoding mechanism using the Dusky architecture to improve reliability and confidentiality; and Shamir's secret sharing scheme to guarantee data trustworthiness and privacy during storage at the cost of a minor performance implication. They compared the security and privacy of their hybrid approach with well-known protocols such as SAML with proxy encryption and Kerberos, showing the benefits in terms of memory footprint, encryption/decryption time and totaltimetoauthenticate. The experimental results show that our hybrid scheme provides considerable improvements with regard to encryption\\/decryption time, memory consumption and average precision.

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