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Air Quality Prediction Using RNN and LSTM
No full textEstimates of discuss quality that are rectify are basic to natural administration and open wellbeing.
The perplexing transient relationships in discuss quality estimations have demonstrated
troublesome for conventional approaches to get it. This paper evaluates the discuss quality
expectation execution of repetitive neural systems (RNNs), in specific long short-term memory
(LSTM) systems. Taking into account factors like contaminants and climate designs, LSTM
models look at authentic information on discuss contamination. Since these models are able to
capture long-term conditions and oversee non-linear associations, they outflank customary
strategies in recognizing designs and connections between factors. Our discoveries appear that
LSTMs have a extraordinary bargain of potential for discuss contamination expectation
The Impact of Social Media Influencers Towards Consumers’ Attitude
No full textThe rapid evolution of marketing trends is closely tied to the increasing use of social media, driven
by advancements in technology and the preferences of the younger generation. Brands are
increasingly leveraging the influence of social media personalities as endorsers, making social
media influencer marketing one of the most prevalent and effective strategies for promoting
products and services. Compared to traditional marketing methods, influencer marketing has
demonstrated greater effectiveness in shaping consumer attitudes and behaviors. This study
examines the impact of social media influencers on consumers’ attitudes, focusing on the
Malaysian context. Data were collected through an online survey to explore how influencer
marketing influences purchasing decisions. The findings reveal that consumers are more inclined
to trust and purchase products endorsed by influencers than those promoted through official
advertising. By analyzing the role of influencers in shaping consumer attitudes, this research
underscores the importance of promoting responsible consumption patterns, aligning with
Sustainable Development Goal 12 (SDG 12). The study advocates for brands and influencers to
encourage ethical consumption and sustainable practices, ensuring that marketing efforts
contribute to the broader goal of achieving sustainable production and responsible consumer
behavior
Facial Recognition Using Convolutional Neural Network Using Real-Time Data
No full textRecent years have seen the rise of facial recognition as a significant technological
advancement, with several applications in the fields including security, surveillance,
authentication systems, and Human-Computer Interface. Numerous sectors have undergone
radical change as a result of their ability to automatically identify and validate people based on
their facial traits, opening new doors for innovation. The main objective of facial recognition
is to create automated systems that can correctly identify and validate people from pictures or
videos. The limitations of traditional methods in capturing complex and discriminative facial
patterns included the reliance on handmade features and shallow learning techniques. However,
facial recognition has made great progress since the introduction of deep learning, more notably
Convolutional Neural Networks (CNNs). CNNs are the perfect tool for capturing fine facial
characteristics because they have demonstrated an amazing capacity for hierarchical
representations that can be directly learned from unprocessed image data. In this paper, the
authors focus on facial recognition using a CNN model, intending to improve the accuracy and
resilience of this crucial technology. The authors have applied a well-built CNN model to
address the challenges of facial recognition. We utilize deep learning to automatically identify
and extract high-level features from facial images, enabling more accurate and reliable
identification. The CNN model's architecture was thoughtfully created to utilize the underlying
spatial links and regional patterns visible in facial data. By utilizing a large number of
convolutional and pooling layers, the model can successfully capture both low-level qualities
like edges and textures and high-level facial traits like facial landmarks and expressions
SOS Smart Reminder and Emergency Detection Device Using ESP8266 and MPU6050
No full textResearch indicates that approximately 85% of deaths are caused by heart attacks, strokes, shortness of breath, and other medical conditions could be prevented through timely treatment. Hence, immediate access to an easily reachable SOS button plays a vital role in providing prompt assistance. Vehicle accidents result in a significant number of fatalities. Delays in reaching the hospital contribute to about 76% of deaths in each vehicle category. An urgent solution is needed: a gadget or technology capable of detecting collisions and promptly alerting their local guardians. This would enable immediate medical assistance, potentially saving lives and reducing the fatality rate associated with such accidents. The current work is driven by three key factors: the necessity for a dedicated device to remind patients with chronic illnesses to take their medications at the prescribed times, the absence of a convenient SOS button readily accessible during emergencies, and the delay in communication between accidents and contacting guardians. The authors in this study emphasizes the importance of timely medical care and interventions which significantly decrease mortality rates associated with these conditions. Not adhering to medication schedules and taking incorrect medicines at inappropriate times can have serious consequences. A specialized reminder device that prompts individuals with medication names at specific times is necessary to ensure proper administration and improve health outcomes
Researching Factors that Affect the Shopping Decisions of Shopping in Tiktok
No full textIn recent years, Tiktok Shop, a social networking platform that was born, has been changing the landscape of the e-commerce market. The way of shopping through short videos is a new method of shopping and the key to the success of TikTok. When customers watch short videos, TikTok will build on consumer habits and journeys to better meet user needs. The article analyzed the influence of 9 factors on the purchase intention of users based on the combination of the Theory of Reasoned Action (TRA) and the Technology Acceptance Model (TAM). The result shows that there are 4 factors that directly and positively affect shopping behavior: "Opinion of the reference group", "My own beliefs", "Videomaker", and "Perceived value". Thus, the article proposes appropriate and practical solutions to help sellers better understand customer psychology and have strategies to keep the consumers and increase sales efficiency
Comparison Analysis of Unit Prices for Reinforced Concrete Column Work using the 2022 Indonesian National Standard (Sni) Method and Field Data (An Empirical Study On the Construction Project of the National Land Agency Building in Banjarbaru)
No full textIn construction management, there are various stages of problems in terms of managing the project budget, so it is necessary to have a design or estimation of the project budget by analyzing construction costs. Currently, service providers tend not to fully calculate unit price analysis based on SNI analysis but rather on their own analysis or previous experience in completing construction work. Based on this, it is necessary to compare unit price analysis between the SNI method and field data. This study aims to determine the unit prices in the field and compare the price differences between the SNI 2022 method and field data in the National Land Agency Building Construction Project in Banjarbaru. The results of this analysis show that the price based on SNI 2022 analysis is Rp368,900,072.55, while the price based on field observations is IDR 269,231,757.50. Based on the analysis results of both methods, the cost difference between the SNI 2022 analysis and the actual field conditions for the National Land Agency Building Construction Project in Banjarbaru is IDR 99,668,315.02
Data-Driven Web-Based Service Travel Resume Information System
No full textThe Energy and Mineral Resources Department (ESDM) of South Sumatra Province has significantly enhanced its operational efficiency by implementinga Web-Based Official Travel Resume Information System. This system was developed to address the inefficiencies and risks associated with the previous manual method of managing official travel data. The new system leverages PHP, MySQL, Javascript, JQuery, and Bootstrap to provide a robust, secure, and user-friendly platform for handling travel reports, assignment orders, and official travel documentation. The digital transformation has streamlined data entry, improved data integrity, and facilitated real-time information access,enabling better decision-making and strategic planning. A System Usability Scale (SUS) test was conducted with 120 participants to evaluate the system's usability. The results showed a mean SUS score of 78.5, indicating good usability, with a standard deviation of 8.3. High scores were recorded for the system's ease of use, integration of functions, and user confidence, while lower scores highlighted initial complexity and a need for additional user training. The successful implementation and positive usability results underscore the system's effectiveness in enhancing the ESDM Department's operational capabilities. Recommendations for further improvements include enhancing mobile accessibility, providing ongoing user training, integrating advanced reporting features, and refining the user interface to ensure continued user satisfaction and system efficiency
Enhancing STEM Interest through Robotics Education in a Malaysian Primary School
No full textThis study investigates the impact of robotics education on enhancing STEM interest among students in a Malaysian primary school. As Malaysia aims to become a technological innovation hub, fostering STEM interest in youth is crucial. Traditional education methods focusing on rote memorization contribute to a significant gap in practical STEM skills, especially in robotics. This study addresses these challenges through a mixed-methods approach, conducting a "Robotic Day" workshop at SJK(C) Pei Chih for 30 Standard 5 students. Pre- and post-workshop surveys and in-depth interviews assessed changes in students' STEM knowledge, attitudes, and interests. Results showed a significant increase in students' understanding and enthusiasm for STEM, with the proportion of participants demonstrating good and very good levels of knowledge rising from 10.3% to 69.2%. Additionally, the percentage of students with low interest in STEM dropped from 44.8% to 7.6% post-workshop. These findings underscore the effectiveness of hands-on robotics education in bridging educational gaps, fostering critical thinking, and nurturing future STEM professionals. This study supports Sustainable Development Goal 4, promoting inclusive and equitable quality education
Implications of Therapeutic Communication for Avoiding Lawsuits in Health Services
No full textHealth services in Indonesia have a very important role in improving the welfare of the Republic
of Indonesia. To prevent misunderstandings between patients and paramedics in health services,
good communication is needed. Communication in health services can be called therapeutic
communication. Previous research mostly only highlights the importance of using informed
consent as valid proof of a therapeutic agreement, therefore in this research the important point is
that in implementing informed consent, adequate, detailed, and easy to understand information
must be given to the patient, this can be done by providing information using therapeutic
communication. This article uses a literature study of legal research methods with a normative
approach and a conceptual approach. Sources of research material used in this literature review
include journal articles, legal regulations, and books. Therapeutic communication should be
carried out in the entire series of patient care, especially in conveying informed consent, where the
patient must receive a detailed explanation regarding the diagnosis, therapy plan, risks if treatment
is carried out or not carried out, and the treatment prognosis, so that the patient can determine
properly what treatment is needed. will be chosen consciously. When the treatment carried out is
determined by the patient and carried out based on mutual agreement, this will reduce the
possibility of disputes between the doctor and the patient. Therapeutic communication cannot
completely prevent lawsuits and medical disputes, but by carrying out effective therapeutic
communication, patients and paramedics can have equal views regarding the patient's condition,
treatment plans, and the risks that may occur if medical action is or is not carried out
Reactive Power Compensation for Standalone Hybrid Power System Using Facts Devices
No full textReactive power compensation is essential in hybrid grid-connected systems because power
electronic inverters utilized for supplying DC energy into the grid causes a reduction in the
overall power factor of the power systems. Due to the ability to provide a reliable and efficient
power supply to remote and off-grid areas, hybrid power systems are growing in popularity.
It can provide greater opportunities for operational growth by combining economic and
technology advancement. To meet the demand for electrical energy in both regular and critical
situations, operators must be in charge of the power systems reliable and secure operation. The
primary objective of the work is to control the reactive power flow in a grid-connected hybrid
renewable energy system (PV-wind-battery). The power quality problems that these systems
frequently experience include voltage sags, harmonics, and flicker. A FACTS device Unified
Power Quality controller (UPQC) with a Genetic Algorithm based PI controller is suggested
to handle these power quality issues. In order to improve the performance of the power system,
the proposed optimization approaches are used to tune the UPQC in a multiline transmission
system. The model was developed with the help of the MATLAB/Simulink work framework