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International Journal of Multidisciplinary Sciences and Arts
Published by Information Technology and Science
ISSN : -     EISSN : 29621658     DOI : https://doi.org/10.47709
Core Subject : Economy, Science, Education,
Computer Science & IT Economics, Econometrics & Finance Languange, Linguistic, Communication & Media
International Journal of Multidisciplinary Sciences and Arts is an international, multidisciplinary, peer-reviewed and open-access journal that provides a platform to produce high-quality original research, Reviews, Letters, and case reports in natural, social, applied, formal sciences, arts, and all other related fields. Our aim is to ameliorate the speedy distribution of new research ideas and results and allow the researchers to create new knowledge, studies, and innovations that will aid as a reference tool for the future.
Arjuna Subject : Seni dan Humaniora - Seni dan Humaniora (Lain-Lain)
Articles 294 Documents
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AI in Healthcare: Revolutionizing Diagnosis and Therapy Shah Zeb; Nizamullah FNU; Nasrullah Abbasi; Muhammad Fahad
International Journal of Multidisciplinary Sciences and Arts Vol. 3 No. 3 (2024): International Journal of Multidisciplinary Sciences and Arts, Article July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v3i3.4546

Abstract

Artificial Intelligence (AI) is revolutionizing healthcare through its integration into various domains, significantly enhancing the efficiency, accuracy, and effectiveness of medical practices. This review explores the transformative impact of AI across multiple aspects of healthcare, including diagnostics, personalized treatment, drug discovery, surgery, and more. AI's capabilities in diagnostics and early detection are improving the precision and speed of disease identification, enabling earlier and more effective interventions. Personalized treatment approaches leverage AI to analyze patient data and tailor therapies to individual needs, optimizing outcomes and reducing adverse effects. AI-driven robotics in surgery offer enhanced precision, control, and minimally invasive options, leading to improved surgical outcomes and faster recovery times. Despite these advancements, the adoption of AI in healthcare presents challenges and ethical considerations, including data quality, algorithmic bias, patient privacy, and the responsible use of AI technologies. Addressing these issues is crucial for maintaining trust and ensuring equitable access to AI-powered healthcare solutions. AI's role in drug discovery and development is accelerating the creation of new therapies by optimizing predictive modeling, drug design, and clinical trials, thus reducing costs and speeding up the development process. Future trends and innovations in AI highlight ongoing advancements and the potential for further transformation in healthcare. These include advancements in natural language processing, AI-enhanced telemedicine, wearable health technologies, and ethical AI governance. As AI technology continues to evolve, its impact on healthcare will become increasingly significant, driving progress in patient care, operational efficiency, and medical research. Collaborative efforts among technologists, clinicians, researchers, and policymakers will be essential in harnessing AI's full potential while addressing the complexities and ethical challenges associated with its use. This review underscores the promise of AI to revolutionize healthcare and improve patient outcomes while emphasizing the need for responsible implementation and ongoing evaluation.
3D Printing Techniques: Transforming Manufacturing with Precision and Sustainability Shahrukh Khan Lodhi; Ahmad Yousaf Gill; Ibrar Hussain
International Journal of Multidisciplinary Sciences and Arts Vol. 3 No. 3 (2024): International Journal of Multidisciplinary Sciences and Arts, Article July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v3i3.4568

Abstract

Additive manufacturing, sometimes known as 3D printing, has advanced quickly and has the potential to revolutionize a number of industries. This analysis examines the noteworthy developments and upcoming trends in 3D printing, emphasizing the effects on accuracy, eco-friendliness, and industrial uses. The first section of the book explores how advances in materials have affected 3D printing, with a focus on the creation of thermoplastics, photopolymers, metal powders, ceramics, and bio-printable materials. These developments have increased 3D printing's potential and made it possible to produce components that are biocompatible, customizable, and high-performing. The topic of sustainability is then brought up, with particular emphasis on how 3D printing helps to cut down on energy and material waste. The key components of the technology's environmental benefits are its on-demand part production capability and its utilization of environmentally benign resources like recycled and biodegradable polymers. The essay also discusses the difficulties associated with material disposal and energy use in the perspective of sustainability. Examining industrial applications, the paper emphasizes how 3D printing is revolutionizing industries like consumer products, construction, healthcare, automotive, and aerospace. The technology's versatility and effect across multiple fields are demonstrated by highlighting its role in enabling rapid prototyping, customized production, and novel design solutions. The assessment highlights major developments in 3D printing for the future, such as advances in materials science, technological advancements, and integration with other cutting-edge fields like artificial intelligence, the Internet of things, and robotics. Highlighted are the possibilities for increased customization, on-demand production, and sustainability, demonstrating how these advancements will continue to influence the market? The assessment highlights the significant effects that 3D printing will have on manufacturing and design, emphasizing how technology may spur innovation, lessen its negative effects on the environment, and adapt to changing needs in a variety of industries. Technology will play an ever-more-important role in improving sustainability and revolutionizing sectors as it develops.
AI-Powered Innovations in Contemporary Manufacturing Procedures: An Extensive Analysis Lodhi, Shahrukh Khan; Gill, Ahmad Yousaf; Hussain, Ibrar
International Journal of Multidisciplinary Sciences and Arts Vol. 3 No. 4 (2024): International Journal of Multidisciplinary Sciences and Arts, Article October 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v3i4.4616

Abstract

The industrial sector is undergoing a transformation thanks to artificial intelligence (AI), which is bringing revolutionary changes to a number of areas like robots and automation, supply chain efficiency, predictive maintenance, and quality control and assurance. This thorough analysis investigates AI's significant influence on contemporary manufacturing procedures. Artificial Intelligence (AI) improves machine capabilities in robotics and automation, creating more intelligent and flexible systems. Robots can now complete complicated tasks with more flexibility and precision thanks to AI-driven developments, which boosts manufacturing efficiency and human-robot cooperation. Another crucial area where AI has a big impact is predictive maintenance. With the use of machine learning algorithms and real-time data analysis, artificial intelligence (AI) helps manufacturers anticipate equipment faults before they happen. By taking a proactive stance, unplanned downtime is decreased, resource usage is optimized, and machinery longevity is increased. AI has a significant positive impact on quality assurance and control because to cutting-edge technologies like data analytics and computer vision. Artificial intelligence (AI) solutions facilitate predictive quality management, improve fault identification, and offer real-time monitoring. Higher quality standards, less waste, and more customer happiness are the outcomes of this. Artificial Intelligence (AI) tackles issues related to supplier performance, accurate forecasting, and inventory management in supply chain optimization. Automation and analytics powered by AI simplify supply chain processes, increase transparency, and facilitate improved decision-making, which lowers costs and increases flexibility. All things considered, integrating AI into manufacturing processes offers a strategic advantage by promoting increased accuracy, flexibility, and efficiency. The continued developments in AI technology have the potential to significantly influence how manufacturing develops in the future by creating new avenues for creativity and excellence in the sector.
Using AI to Increase Heat Exchanger Efficiency: An Extensive Analysis of Innovations and Uses Lodhi, Shahrukh Khan; Hussain, Hafiz Khawar; Hussain, Ibrar
International Journal of Multidisciplinary Sciences and Arts Vol. 3 No. 4 (2024): International Journal of Multidisciplinary Sciences and Arts, Article October 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v3i4.4617

Abstract

Artificial intelligence (AI) has made significant strides toward cost reduction and performance optimization in heat exchanger technologies. Artificial intelligence (AI) methods in machine learning, deep learning, and expert systems provide significant advancements in diagnostics, performance optimization, and predictive maintenance. While deep learning is superior at recognizing intricate patterns, machine learning offers flexibility through data analysis. Expert systems use domain expertise to make decisions, although they might not be as flexible as data-driven methods. Hybrid approaches integrate these strategies to improve flexibility and performance. New developments include smart heat exchangers with IoT capabilities for real-time monitoring, compact designs for a variety of applications, and new materials and coatings that improve durability and efficiency. Reducing environmental effect is also reflected in sustainable solutions like waste heat recovery. Nevertheless, issues like computing costs, data quality, and interaction with current systems still need to be resolved. Optimized computational methodologies, modular integration, and sophisticated sensor technology are required to address these problems. AI has the power to completely transform heat exchanger technology by enhancing sustainability and efficiency. Future breakthroughs will be fueled by ongoing improvements in materials, designs, and AI approaches, offering more complex solutions to satisfy changing environmental and performance requirements.
A succinct synopsis of predictive analysis applications in the contemporary period Valli, Latha Narayanan
International Journal of Multidisciplinary Sciences and Arts Vol. 3 No. 4 (2024): International Journal of Multidisciplinary Sciences and Arts, Article October 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v3i4.4625

Abstract

A potent subset of data analytics called predictive analytics is revolutionizing a number of industries by using historical data, machine learning methods, and statistical algorithms to predict future events and guide strategic choices. The uses and advantages of predictive analytics in the fields of finance, healthcare, manufacturing, energy and utilities, retail, and marketing are highlighted in this thorough overview. Predictive models improve market risk management, fraud detection, and credit risk assessment in the financial sector, promoting stability and confidence. Applications in healthcare include operational efficiency, tailored treatment, and patient risk assessment, all of which improve patient outcomes. Supply chain risk management, quality assurance, and predictive maintenance all help manufacturers maximize efficiency and reduce downtime. Demand forecasting, asset performance management, and regulatory compliance all help the energy and utilities sector by guaranteeing dependable and effective service delivery. Predictive analytics helps retailers satisfy customer requests and keep a competitive edge by assisting with inventory management, customer satisfaction, and competitive analysis. Customer segmentation, personalized marketing, campaign optimization, sales forecasting, churn prediction, customer lifetime value prediction, market trend analysis, and sentiment analysis all greatly improve marketing techniques.
Artificial Intelligence in Healthcare: Revealing Novel Approaches to Cancer Treatment, Fraud Investigation, and Petroleum Industry Perspectives Fahad, Muhammad; Ibrar, Muhammad; Qayyum, Muhammad Umer; Husnain, Ali
International Journal of Multidisciplinary Sciences and Arts Vol. 3 No. 4 (2024): International Journal of Multidisciplinary Sciences and Arts, Article October 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v3i4.4637

Abstract

Artificial Intelligence (AI) is increasingly transforming healthcare by enhancing diagnostic accuracy, personalizing treatment, and improving operational efficiencies. This review explores AI's impact across several key areas: cancer medicine, fraud detection, and lessons from the petroleum industry. In cancer medicine, AI-driven advancements are leading to more accurate diagnostics, personalized treatment plans, and predictive models for patient outcomes. In fraud detection, AI techniques such as anomaly detection and natural language processing are effectively identifying and mitigating fraudulent activities, safeguarding financial and operational integrity. Insights from the petroleum industry reveal how AI applications, such as predictive maintenance and operational optimization, can be adapted to healthcare settings to enhance equipment reliability and resource management. Emerging trends include the integration of AI with genomics, telemedicine, and cross-disciplinary innovations, which promise further advancements in personalized care and operational efficiency. However, ethical considerations such as data privacy, bias, and transparency must be addressed to ensure responsible AI deployment. The review concludes by highlighting the need for continued innovation, collaboration, and patient-centric approaches to fully realize AI's potential in transforming healthcare and improving patient outcomes.
The Inhaling Danger: How Air Pollution Affects Asthma Patients – A Phenomenological Study Jan, Maryam; Ali, Asrar; Alam, Memoona; Shahid, Arooba; Gul, Nimra
International Journal of Multidisciplinary Sciences and Arts Vol. 4 No. 4 (2025): International Journal of Multidisciplinary Sciences and Arts, Article October 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v4i4.7033

Abstract

Background: Asthma is a chronic respiratory condition characterized by episodes of airway construction, inflammation and mucus production. It affects millions of people worldwide and is influenced by various environmental factors such as air pollution. Objective: The objective of the article is to determine how asthmatic student health is impacted by air pollution, how asthma affects students' daily tasks and the awareness among asthma students about the risks caused by air pollution. Method: The results presented were obtained through a qualitative phenomenological study. The study was conducted on university students who are asthma patients. The sample consisted of 30 students patients with asthma experiences. Result: The findings revealed that effects of air pollution is one of the leading cause of asthma; triggering asthma and other respiratory health conditions. Conclusion: People with asthma especially students and young patients, will be further exposed to the threat of air pollution, and suffer from more serious health consequences. There have to be detailed assessments connected to the main air pollutants particulate matter (PM) and their causal relationship with respiratory disease, more in each country.
Design and Implementation Results of an Integrated System for Converting Fruit Waste into Bio-Energy Briquettes: Focus on the Pyrolyzer, Disc Mill, Cylindrical Oven, and Hydraulic Press Machine Perdana, M. Alkadri; Custer, Johny; Nofiar.Am, Andri; Nasution, Lukman Hakim; Triyono, Wahyu; Rahayu, Siti
International Journal of Multidisciplinary Sciences and Arts Vol. 4 No. 4 (2025): International Journal of Multidisciplinary Sciences and Arts, Article October 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v4i4.7200

Abstract

Fruit waste poses significant environmental and socioeconomic challenges, particularly in agricultural countries such as Indonesia. This study presents the development of an integrated system to convert fruit biomass waste into bio-energy briquettes using a pyrolyzer, disc mill, cylindrical oven, and hydraulic press. Pyrolysis was conducted at 350–500°C under limited oxygen, producing solid carbon, bio-oil, and syngas. The carbonized material was then milled, sieved, dried, and compacted into high-density briquettes. Laboratory characterization using X-Ray Fluorescence (XRF), Field Emission Scanning Electron Microscopy with Energy Dispersive X-ray Spectroscopy (FESEM-EDS), and bomb calorimetry revealed a carbon content of approximately 82.5% and an average calorific value of 5,800 kcal/kg with a moisture content of 9.4%, indicating high energy potential and good mechanical stability. The system achieved a production capacity of 300–500 kg/day, making it suitable for small-scale, community-based renewable energy applications. The results confirm the technical feasibility and economic viability of the integrated system while supporting rural energy independence and local economic development. Future work should focus on system automation and exploring diverse biomass feedstocks for broader implementation.
Systematic Literature Review: World Oil Commodity Price Fluctuations Financial Accounting Perspective Septemberiyanti, Elita; Virliana Muliawan, Ryani; Agustria, Rahma; Ayu Ramadhani, Amanda; Henda Safitri, Rika; Wahyudi, Tertiarto; Samantha Hamzah, Ruth
International Journal of Multidisciplinary Sciences and Arts Vol. 4 No. 4 (2025): International Journal of Multidisciplinary Sciences and Arts, Article October 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v4i4.7181

Abstract

Global oil price volatility creates complex challenges for the transparency of financial reporting of national energy companies, especially PT Pertamina as a strategic state-owned enterprise that faces double accountability pressure to shareholders and the public. This study aims to analyze the influence of fluctuations in world oil commodity prices on the transparency of PT Pertamina's financial statements from a financial accounting perspective through a systematic literature review approach. The PRISMA 2020 method was applied to review 16 reputable journals for the 2020-2025 period selected from 309 initial articles through the Scopus, Web of Science, and Google Scholar databases. The results of the study revealed that oil price volatility had a significant impact on net profit fluctuations, the complexity of exchange rate differences, and the decline in financial health for the 2016-2020 period. PT Pertamina's transparency shows improvements through the implementation of ISO 37001 and GRI Standards 2021, but still faces the challenges of weak ethical principles, inconsistency of PSC regulations, and performance gaps with global competitors. The research recommends comprehensive governance reforms, business diversification, regulatory harmonization, and strengthening supervision to improve the credibility of financial reporting in the face of global market dynamics.
Diversity in the Workplace: A Systematic Literature Review of Global Research: English Venesia, Venesia; Ramadania, Ramadania
International Journal of Multidisciplinary Sciences and Arts Vol. 4 No. 4 (2025): International Journal of Multidisciplinary Sciences and Arts, Article October 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v4i4.7243

Abstract

Employee diversity has increasingly been recognized as a strategic factor influencing organizational innovation, performance, and sustainability across sectors and countries. However, previous studies reveal limited geographical coverage and a predominant focus on demographic dimensions. This study aims to systematically review the global literature on employee diversity and identify emerging thematic, methodological, and theoretical trends. This research employed a Systematic Literature Review (SLR) using the PRISMA approach to ensure a transparent and rigorous selection and analysis process. Data were collected from the Scopus database for the period 2020–2025, yielding 56 eligible peer-reviewed articles. The analysis examined research contexts, theoretical frameworks, methodologies, core variables, and empirical findings. The results indicate that employee diversity research is dominated by themes of diversity management, gender equity, inclusive leadership, and psychological safety. Intersectionality and Social Identity Theory are the most frequently applied frameworks, while quantitative methods, particularly Structural Equation Modeling, remain dominant. Notable gaps include underrepresentation of developing countries, insufficient integration of cross-cultural perspectives, and inconsistent measurement of psychosocial variables. This review concludes that managing diversity should be viewed as a strategic organizational resource rather than a moral obligation. The study proposes the Multidimensional Diversity Integration Framework (MDIF) to integrate social, psychological, and cultural dimensions into inclusive and sustainable human resource management practices.

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