Multidisciplinary Journal of Akseprin Indonesia
The Multidisciplinary Journal of Akseprin Indonesia (MJAI) is a scientific journal dedicated to publishing research results, case studies, work reports and literature reviews that are interdisciplinary and multidisciplinary in nature from various major disciplines. The journal aims to bridge the gap between sciences, promote collaboration, and present comprehensive solutions to complex challenges. The scope of MJAI includes studies from the main groups of sciences which, including: Engineering ,Physical and Chemical Science : Engineering and Technology, Material Science, Statistics, Chemical Engineering, Chemistry, Computer Science, Information Technology, Earth and Planetary Science, Energy, Mathematics, Physics and Astronomy, Mathematics Life Sciences : Agricultural, Biological Sciences, Biotechnology, Arachnology, Biodiversity and Conservation, Entomology, Limnology, Ichthyology, Malacology, Immunology and Microbiology, Neuroscience, Biochemistry, Genetics, Molecular Biology, Environmental Science, Ecology, Marine Biology. Health & Medical Science : Medicine and Dentistry, Nursing, Health Professions, Pharmacology, Toxicology, Pharmaceutical Science, Veterinary Science, Veterinary Medicine, Health Care, Medical Education. Social Science and Humanities: Arts and Humanities, Business Management, Hotel Management, Management, Economics, Law, Finance, Psychology, Political Science Tourism, Accounting, Decision Science, Education, , Physical Education, English Literature, Social Work and History., Sociology, Corporate Governance.
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<![CDATA[The Potential of Rivers as Renewable Energy Power Plants ]]>
<![CDATA[Michael Okon Bassey]]>;
<![CDATA[Aniekan Essienubong]]>
<![CDATA[ Multidisciplinary Journal of Akseprin Indonesia Vol. 2 No. 2 (2024): May-August ]]>
Publisher : <![CDATA[AKADEMI SERTIFIKASI PROFESI INTERNASIONAL ]]>
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<![CDATA[Globally, the demand for cheap energy source has risen as a result of population growth, urbanization, and industrialization. While the electricity consumption in emerging nations like Nigeria is rising, the supply, which is often derived from fossil fuels is diminishing, leading to an energy crisis and pollution. Thus, in order to cover both the present and future energy needs, it is necessary to investigate alternate or renewable energy sources. This study seeks to offer a broad overview of the economic design consideration, practical implementation parameters, and interconnections of the key components of small hydropower plants for River Nnwankwo, in Ikot Ekpene local government area of Akwa Ibom State, Nigeria. The focus is to offer a foundational understanding of micro-hydro systems, planning, the advantages and limitations of micro-hydro energy estimation, which is a function of head and flow rate. If this exploitable source of energy could be harnessed using environmentally friendly technology, the entire energy situation in Ikot Ekpene sub urban which has a thriving population would be improved.]]>
<![CDATA[Artificial Intelligence (AI) is being Swiftly Integrated into Various Application Domains ]]>
<![CDATA[Ihor Hunko]]>
<![CDATA[ Multidisciplinary Journal of Akseprin Indonesia Vol. 2 No. 2 (2024): May-August ]]>
Publisher : <![CDATA[AKADEMI SERTIFIKASI PROFESI INTERNASIONAL ]]>
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<![CDATA[Artificial intelligence (AI) is quickly being used in areas like self-driving cars, healthcare, and cybersecurity, so there is a growing need for dependable and strong AI systems in these changing environments where conditions can be unpredictable. Traditional software testing methods that depend on set test cases and fixed situations often fail Traditional software testing methods that use fixed test cases and scenarios often fail to effectively handle the complexities of modern AI systems, which can result in hidden problems and security risks. This study will evaluate adaptive testing methodologies employing reinforcement learning (RL), fuzz testing, and other hybrid techniques for their application in software reliability assurance across various environments, including stable, low-resource, high-load, and adversarial contexts. The study is based on a series of experiments involving conversational chatbots, fraud detection systems, and autonomous navigation modules, illustrating that RL-adaptive testing methods enhance defect detection by 35-47% in dynamic environments relative to static testing methods and attain 40-50% increased stability under stress (pertaining to the system itself). Reinforcement learning (RL)-based approaches reduced failure rates by 75% compared to traditional testing methods. Fuzz testing was useful for finding edge cases, but it was less stable in adversarial situations when the same edge cases were used again. Moreover, the article delineates significant issues in AI Software Testing, such as environmental drifts and non-deterministic outputs, which are perceived to be more effectively addressed by reinforcement learning-based methodologies. Even though there is a balance between how easy it is to understand and the complexity of computing, the evidence shows that adaptive testing can greatly improve safety-critical systems and highlights the benefits of combining reinforcement learning's ability to optimize dynamically with fuzz testing's ability to find unusual problems. This document delineates application areas, providing explicit advice for developers and engineers to enhance the safety and reliability of AI in practical systems.]]>
<![CDATA[The Anterior Cruciate Ligament (ACL) Is Extensively Studied Due to Its Anatomical Position and Its Role In Preventing Anterior Tibial Translation and Rotational Stresses At The Knee Joint ]]>
<![CDATA[Lakshmipriya Jeyanthi]]>
<![CDATA[ Multidisciplinary Journal of Akseprin Indonesia Vol. 2 No. 2 (2024): May-August ]]>
Publisher : <![CDATA[AKADEMI SERTIFIKASI PROFESI INTERNASIONAL ]]>
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<![CDATA[ACL injuries predominantly arise in sports, typically resulting from twisting or pivoting actions. Reduced range of motion, along with diminished muscle strength and functional capacity, is more prevalent in persons who have undergone ACL reconstruction. Russian current is an innovative modality in musculoskeletal physiotherapy. Objective: To evaluate the impact of Russian current combined with structured exercise on enhancing knee function post-ACL surgery. Methodology: This study had 44 patients who underwent ACL reconstructions. They were randomly assigned to Group A (n=22), which received organized exercise alone, and Group B (n=22), which received Russian current in conjunction with structured exercise over a duration of 6 weeks. The knee's range of motion, isometric muscular strength, and function were evaluated using a universal goniometer, a handheld dynamometer, and Lysholm knee scores, respectively. The evaluation was conducted six weeks post-treatment. The intergroup comparison was conducted using an unpaired t-test, revealing statistically significant improvements (p<0.00) in knee flexion (t=29.41), extension range (t=2.08), isometric quadriceps strength (t=10.04), hamstring muscle strength (t=17.81), and functional status (t=13.74) in the group that received Russian current in conjunction with structured exercises, as opposed to those who received structured exercises alone. Conclusion: The findings indicate that Russian current, in conjunction with structured exercise, significantly enhanced knee range of motion, muscle strength, and functional status in individuals with ACL repair compared to structured exercise alone]]>
<![CDATA[The influence of using Stripe, Firebase, and OpenAI in sophisticated API solutions ]]>
<![CDATA[Shalom Izakr Drofa]]>
<![CDATA[ Multidisciplinary Journal of Akseprin Indonesia Vol. 2 No. 2 (2024): May-August ]]>
Publisher : <![CDATA[AKADEMI SERTIFIKASI PROFESI INTERNASIONAL ]]>
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<![CDATA[This research examines the effect of incorporating Stripe, Firebase, and OpenAI into advanced API solutions to enhance user experience (UX) in web and mobile applications. This study employs a case study examination of existing apps utilizing these APIs, incorporating empirical data collection, performance metrics evaluation, and user feedback assessment to determine the effectiveness of the APIs. Experiments are conducted to evaluate API integration, comparing the application's performance before and after the integration. Key performance indicators, including transaction success rate, data synchronization velocity, and AI-driven engagement metrics, were employed to assess the influence on user experience. Data was collected from application logs, user interaction reports, and developer insights to finalize the evaluation. The report characterizes UX optimization as encompassing loading speed, navigational ease, transaction velocity, real-time response, and engagement metrics. Our findings indicate that Stripe decreases the checkout abandonment rate by 40% and enhances the transaction success rate by 30%, consequently augmenting user trust in transactions and improving financial transaction efficiency. This reduces data synchronization latency by around 70%, resulting in a more seamless application experience and improved retention rates. The AI models from OpenAI increase session durations by 25-40% and promote engagement through improved user interaction via a more tailored experience. Scientific evidence substantiates the specific benefits of API integration, such as decreased latency, enhanced interactivity, and accelerated application processes. The research identifies them as integration problems and outlines effective practices for future API implementations. This study effectively proposes methods for enhancing user experience through the implementation of APIs]]>
<![CDATA[Optimization of Lead Time in Jewellery Manufacturing: Differentiation in Design and Model ]]>
<![CDATA[Stephen Welldhies]]>
<![CDATA[ Multidisciplinary Journal of Akseprin Indonesia Vol. 2 No. 2 (2024): May-August ]]>
Publisher : <![CDATA[AKADEMI SERTIFIKASI PROFESI INTERNASIONAL ]]>
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<![CDATA[One of the qualities that a firm must possess is the capability to launch new models more rapidly than its competitors. It will provide the organization with the potential to seize market share. However, the corporation must rapidly initiate mass production of the new models following the prototype's market introduction. Gradual mass production will provide competitors the opportunity to replicate the prototype, enabling them to seize market share if they can achieve faster production rates. This issue occurs in jewelry companies in Indonesia, namely at XYZ Company. Prototype models from XYZ Company are extensively replicated by competitors with expedited manufacturing timelines. To address this issue, the organization must analyze the fundamental reason for the sluggish mass production process. This analysis enables the formulation of recommendations for the company to enhance the production process, hence preventing market loss. A root cause analysis was performed utilizing a fishbone diagram in a case study at XYZ firm. The analysis reveals that the primary cause of the prolonged manufacturing time is the insufficient human resources engaged in the production process. In light of this conclusion, initiatives such as recruiting extra personnel and instituting overtime for employees may be implemented to expedite production time and enhance capacity.]]>
