bluuebunny/crossref_metadata_2025 huggingface dataset:
KNOWLEDGE, ATTITUDE, AND PRACTICE OF MOTHERS ON ACUTE RESPIRATORY INFECTION IN CHILDREN UNDER FIVE YEARS
Authors: Yolanda Ignatia Thassya , Septiandani Lydia Putri , Sirait Maria Nespita , Siregar Deborah
Published: December 2024

Background: Acute Respiratory Infection (ARI) significantly affects the respiratory tract, contributing to high mortality rates and a decline in quality of life for children under five, with an incidence of 3-5 episodes per child annually. In Indonesia, ARI remains prevalent, with cases increasing in 2015 (63.45%) and reaching 48.56% in Tangerang Regency by 2017. Knowledge Gap: Despite these figures, there is limited research on maternal knowledge, attitudes, and practices concerning ARI prevention. Aims: This study aims to analyze maternal knowledge, attitudes, and actions in Binong Village regarding ARI prevention among toddlers. Methods: A cross-sectional quantitative design was employed, with 50 mothers of toddlers completing a Google Forms questionnaire. Accidental sampling was used, and univariate analysis was applied to assess frequency and percentage distributions of the variables. Results: The findings revealed that 74% of mothers exhibited poor knowledge, while 100% had positive attitudes and 84% engaged in good practices toward ARI prevention. Novelty: This study highlights the discrepancy between maternal knowledge and attitudes/practices, showing that even with poor understanding, mothers maintain positive attitudes and preventive actions. Implications: The results underscore the need for improved educational interventions targeting maternal knowledge on ARI, as current positive attitudes and practices could be enhanced with better information. Future research should explore factors influencing ARI incidence in infants to develop more comprehensive prevention strategies. Ethical approval for the study was granted (085 / KEP-FON / III-2020).acute respiratory infection,
Genetic Variability of Monkeypox Virus and Its Implications for Human Disease
Authors: AL-Azzawi Mustafa Kareem , Khlaif Salam Mohammed , Zubaidi Nabaa Abbas
Published: December 2024

The genomic sequencing of Monkeypox virus (MPXV) isolates has offered crucial insights into the virus's genetic variability and population biology. This review provides a concise summary of the current state of MPXV genetics and phylogenetics, with a particular emphasis on the potential of a broader dataset to improve molecular diagnostic methods and inform the development of antiviral medicines and diagnostic tests. The virus's evolutionary biology, particularly its interactions with natural reservoir hosts, can be better understood through the investigation of genetic data, precise outbreak identification, and improved surveillance. The genetic diversity among genotypes of monkeypox, a rare zoonotic infection with clinical manifestations similar to smallpox, significantly influences the severity of the disease and its transmission. The objective of this investigation is to enhance the genetic information on MPXV, evaluate the correlation between genotypic variations and disease outcomes, and investigate the manner in which these distinctions influence the pathogenesis of monkeypox. It is emphasized in the research that a multidisciplinary approach is crucial for the advancement of vaccine development, drug discovery, and the comprehension of virus-host interactions. The results underscore the necessity of ongoing genetic and serological surveillance to mitigate the obstacles presented by monkeypox and enhance public health responses.
THE IMMUNOLOGICAL ROLE OF ANTI-H. PYLORI ANTIBODIES LEVEL, INF-Γ, AND TNF-Α IN A NUMBER OF PATIENTS WITH A TUMOR IN THE DIGESTIVE SYSTEM IN BABYLON GOVERNORATE
Authors: Jaafar Salim Shamkhi , Jabber Ehab Y. , Alwish Amer Abdul Husain , Al- Mammori Raheem Tuama Obayes , Shareef Hasanain Khaleel
Published: December 2024

General Background: Helicobacter pylori is a well-known bacterium responsible for chronic infections, significantly contributing to gastric and mucosa-associated lymphoid tissue cancers, as well as peptic ulcer disease.  Specific Background: The link between H. pylori infection and gastrointestinal (GIT) tumors remains under-explored, particularly concerning immunological parameters.  Knowledge Gap: The role of immune markers, such as anti-H. pylori IgG antibodies, TNF-α, and IFN-γ, in distinguishing between malignant and benign GIT tumors is unclear.  Aims: This study aimed to assess the relationship between H. pylori infection and immunological factors in patients with malignant and benign GIT tumors, as well as controls, using serum levels of Anti-H. pylori IgG, TNF-α, and IFN-γ.  Results: The study included 100 serum samples from patients with malignant (n=40) and benign (n=35) GIT tumors, irritable bowel disease (IBD) controls (n=15), and healthy controls (n=10). The results revealed significantly elevated levels of anti-H. pylori IgG in patients with malignant tumors compared to those with benign tumors, IBD controls, and healthy controls. Male patients had higher anti-H. pylori IgG levels than females. Elevated levels of TNF-α and IFN-γ were also observed in patients with malignant tumors, correlating with higher anti-H. pylori IgG levels.  Novelty: This study highlights the association between elevated H. pylori IgG antibodies and increased TNF-α and IFN-γ levels in malignant GIT tumors, particularly in males, suggesting H. pylori's role in cancer progression.  Implications: The findings suggest that early detection of elevated anti-H. pylori IgG and inflammatory cytokines could improve the diagnosis and management of GIT malignancies, especially in male populations. Further research on a larger cohort is recommended to explore the mechanisms driving this relationship.
ANALYSIS OF THE CONTENT MARKETING, INFLUENCER MARKETING, BRAND IMAGE AND PRICE PERCEPTION ON PURCHASE DECISIONS FOR WARDAH SKINCARE PRODUCT ON THE TIKTOK
Authors: Maretha Sindy Diva , Yani Muhammad , Nugroho Tofan Tri
Published: December 2024

General Background: Effective digital marketing strategies are crucial for influencing consumer purchasing decisions in the skincare industry. Specific Background: Despite the rise of TikTok as a marketing platform, understanding the relative impact of content marketing, influencer marketing, brand image, and price perception on purchasing decisions remains underexplored. Knowledge Gap: Previous studies have not sufficiently addressed the specific role of these factors within the context of TikTok for skincare products. Aims: This research aims to evaluate the influence of content marketing, influencer marketing, brand image, and price perception on the purchasing decisions of Wardah skincare products on TikTok. Results: Utilizing a quantitative approach with a sample of 100 Wardah skincare buyers and/or TikTok followers, the study reveals that content marketing and influencer marketing do not significantly impact purchasing decisions. In contrast, brand image and price perception have a significant positive effect. Novelty: The study introduces new insights into the effectiveness of TikTok marketing strategies specifically for skincare products and highlights the dominant role of brand image and price perception over content and influencer marketing. Implications: To enhance marketing efficacy, Wardah should focus on optimizing brand image, improving content marketing quality, selecting credible influencers, and employing strategic pricing. This integrated approach will help Wardah strengthen its market position and achieve better consumer engagement in the competitive skincare industry.
APPLICATION OF LEADERSHIP AND ENTREPRENEURSHIP AND THEIR INFLUENCE IN THE HOSPITAL ENVIRONMENT
Authors: Juliana Dewi Sri , Ratnawati Yeni , Widjaja Yani Restiani , Purwadhi
Published: December 2024

Abstract— Health care operates within a complex and dynamic environment, particularly in the context of hospital care in Indonesia. General Background: The effectiveness of an organization in this sector is influenced by various factors, necessitating continuous improvement in innovation to foster growth and adaptability. Specific Background: Leadership plays a crucial role in guiding organizations toward achieving their vision and mission, especially in a landscape marked by financial constraints, resource shortages, and heightened competition. Knowledge Gap: Despite the recognized importance of entrepreneurial principles in enhancing innovative work behavior, there is limited empirical research focusing on their application within Indonesian hospitals. Aims: This study aims to investigate the impact of entrepreneurial leadership on fostering innovation in hospital settings, with a specific focus on its effects on organizational performance and adaptability. Results: Preliminary findings suggest that integrating entrepreneurial practices not only enhances innovative behaviors among healthcare professionals but also improves overall organizational effectiveness. Novelty: This research contributes to the existing literature by demonstrating how entrepreneurial leadership can serve as a catalyst for innovation in a challenging health care environment. Implications: The results underline the necessity for hospital leaders to embrace entrepreneurial approaches to navigate the complexities of the health care sector, thereby ensuring the delivery of high-quality services and maintaining competitive advantage.
CLASSIFICATION OF PRODUCT PREDICATES BASED ON SALES RATE USING THE C4.5 DECISION TREE ALGORITHM IN RETAIL COMPANIES
Authors: Haafizh Salman , Merdekawati Agustiena , Yuliani Yuri
Published: December 2024

General Background: Retail companies serve as crucial intermediaries between producers and end consumers, providing a wide range of products to meet daily needs. Specific Background: However, many retail companies encounter challenges in inventory management and stock provision, often stemming from insufficient analysis of sales and inventory data. Knowledge Gap: Existing research on inventory management in retail lacks a focus on predictive analytics techniques that leverage sales data to optimize ordering strategies. Aims: This study aims to identify sales patterns using the Decision Tree C4.5 algorithm, with the goal of predicting sales for various products to enhance ordering strategies. Results: Employing primary data collected via the company’s API and direct interviews with Order Management staff and the regional director of Jabodetabek, sales data spanning six months (November 2023 to April 2024) was analyzed using data mining techniques on the RapidMiner platform. The findings reveal that the Decision Tree algorithm effectively identifies product sales predicates, achieving a model accuracy of 96.20%. Novelty: This research introduces a data-driven approach to inventory management in retail, utilizing advanced decision tree algorithms for enhanced sales prediction. Implications: The implementation of the proposed model is expected to significantly improve the efficiency and effectiveness of the company’s ordering processes, ultimately leading to better inventory control and customer satisfaction.
SELECTION OF ROUND EGGPLANT BASED ON COLOR AND SIZE BASED ON ARDUINO
Authors: Rahady Redwin Arie , Ayuni Shazana Dhiya
Published: December 2024

Eating vegetables is important for both humans and farmers who process them to meet consumer needs. Round eggplant is a popular vegetable because it maintains its high nutritional value even with minimal cooking, leading to increased demand. A system for sorting eggplants based on color and size using Arduino Mega is needed. The research method used is research and development to test sensor accuracy and tool reliability in accordance with the research objectives. The tool uses Arduino Mega as a microcontroller, TCS3200 sensor for eggplant color detection, and HC-SR04 sensor for object detection. During the separation process, the eggplant rounds will be moved by a conveyor using a DC motor. In the last step, the tool will direct the round eggplant into the container based on its color and size using a servo motor
PRODUCT QUALITY ANALYSIS USING SIX SIGMA METHOD AND FAILURE MODE AND EFFECT ANALYSIS (FMEA) IN FURNITURE PRODUCTS
Authors: Arifianto Muhammad Adi , Sulistiyowati Wiwik
Published: December 2024

PT KKA is an export-oriented rattan furniture industry. In production, product defects often occur due to many factors that have not found a solution to fix them. Based on the results of observations in May, there were 487 units produced with 63 units or 13% returned, June 513 units produced with 57 units or 11% returned, and in July 445 units with 72 units returned. or 16%. This means that for 3 months the value of the reject percentage has increased by 3%. The application of the Six Sigma method is expected to identify and minimize the root causes of defects. FMEA is used to identify potential failures and the effects of failure on a process. The results of the Six Sigma test obtained a DMPO value of 27,590.8. The biggest percentage of defects are loose defects of 39%, and 22% color defects. The results of the FMEA analysis for loose defects have the highest RPN value of 294, this is due to the use of nail guns that are not appropriate and the checking method is only visual, suggestions for improvement are given, namely providing supervision and improving technical checking by moving one by one the joints and selecting materials which exists.
QUALITY IMPROVEMENT USING LEAN SIX SIGMA AND FAILURE MODES AND EFFECT ANALYSIS AT PT. CIPTA WARNA PELANGI
Authors: Putra Zam Zam Permana , Sulistiyowati Wiwik
Published: December 2024

PT. Cipta Warna Pelangi is a service company engaged in printing, which serves the needs and desires of customers related to printing. Products produced by the company include packing, cigarettes, label brochure books, invitations, food boxes, paper bags, letterheads, envelopes, calendars and so on, but still found some products that have defects. In the first three months of the year 2023, namely January, February, and March, a total of 321,175 pieces defects occurred. Then, in the following three months, the defects escalated further to a total of 499,005 pieces. This situation has become a significant concern as the total defects each month continue to increase. As a result, it is necessary to implement corrective measures in order to minimize the defects present at PT. Cipta Warna Pelangi. It is noted that there were 109,650 pieces defects in April 2023, 163,880 pieces defects in May 2023, and 225,475 pieces defects in June 2023. The products that experienced the highest number of defects are offset, spot UV, and die cut. This study aims to help companies determine the value of reject and waste rates using the lean six sigma method; find out the highest RPN value using the Failure Mode and Effect Analysis (FMEA) method. This research uses lean six sigma method to overcome these problems, Lean Six Sigma is a quality control method that is a combination of Lean and Six Sigma. Lean is an approach that is constantly taken with the aim of eliminating waste and increasing the value of the product provided to consumers. Six Sigma is a method used in the manufacturing industry to improve product quality by identifying and minimizing factors or root causes of product defects. FMEA is used to evaluate and analyze the hazard level of any type of failure that may occur in the production process or in the products used by consumers. The results of this research indicate that the waste defect has obtained the first rank among the other seven types of waste, meaning that waste defect is the top priority for improvement. From the FMEA results, varnish damage obtained the highest RPN value of 252, which is caused by inconsistent quality of the UV liquid brand. Therefore, it is recommended to switch to a different brand of UV liquid
IMPLEMENTATION OF SIX SIGMA AND KAIZEN TO IMPROVE THE QUALITY OF HEALTH PLASTER PRODUCTS IN THE COATING PROCESS
Authors: Janah Ragillia Fitri Nur , Wahyuni Hana Catur
Published: December 2024

General Background: Product quality control is essential to ensure consistent quality from the beginning to the end of the production process. Specific Background: PT. FGH faces significant quality challenges, specifically during the health plaster coating stage, which has resulted in numerous product defects. Knowledge Gap: Although previous research has applied Six Sigma for quality improvement, detailed studies on health plaster manufacturing using combined Six Sigma and 5S Kaizen methodologies remain limited. Aims: This study aims to assess the product defect rate at PT. FGH using the Six Sigma methodology, measure defect levels via the sigma level through Defect Per Million Opportunities (DPMO) conversion, and propose improvement strategies through 5S Kaizen. Results: Findings reveal a DPMO of 7,039.4959, with a sigma level of 3.96, indicating that while the process capability values for Cp and Cpk are 1.00, suggesting production aligns with specification limits, tighter monitoring is required. Notably, product defects are predominantly folding, perforated edges, and asymmetry, comprising 80% of defects and leading to financial losses of IDR 340,524,744 over a one-year period. Novelty: This study uniquely combines Six Sigma and 5S Kaizen in addressing specific defect types and sources, including mechanical and human factors, within the health plaster industry. Implications: By implementing targeted process improvements, this research contributes a practical framework for defect reduction and cost mitigation in production, supporting broader quality control efforts in similar manufacturing sectors.
RISK ANALYSIS IN SANDWICH PANEL PRODUCTION WITH THE INTEGRATION OF FMEA AND FTA METHODS
Authors: Qur'ani Nur Azmil , Wahyuni Hana Catur
Published: December 2024

General Background: Ensuring consistent product quality is crucial for maintaining competitive advantage, especially in manufacturing. PT. Starr Panel Industry, a company in the refrigeration sector, focuses on high-quality sandwich panels but experiences frequent defects in its production processes. Specific Background: Despite prioritizing premium raw materials, the company faces recurring product failures, particularly in the finishing phase, which affect production flow and on-time delivery. Knowledge Gap: Current quality assurance measures at PT. Starr Panel Industry lack a systematic approach to identifying and prioritizing the root causes of defects, hindering the development of targeted improvement strategies. Aims: This study aims to identify, analyze, and address potential failure modes and their root causes within the production processes, employing Failure Modes and Effects Analysis (FMEA) and Fault Tree Analysis (FTA). Results: The findings reveal that the finishing process has the highest Risk Priority Number (RPN) of 112, primarily due to insufficient adherence to standard operating procedures (SOPs) by the workforce. Novelty: The integration of FMEA and FTA provides a comprehensive failure analysis model, with FMEA ranking failure risks and FTA tracing them to foundational causes, offering a new dual-method approach to improve operational standards effectively. Implications: Implementing the proposed FMEA-FTA framework can significantly reduce product defects, improve quality consistency, and minimize delivery disruptions, especially in the critical finishing stage. Emphasizing SOP compliance across divisions, particularly in finishing, can lead to sustained quality improvements and enhanced operational efficiency in sandwich panel production.
ANALYSIS OF THE EFFECT OF BX 92, BX ULTIMAXX FUEL AND THEIR MIXTURES ON THE PERFORMANCE OF THE R15 MOTORCYCLE
Authors: Afif Muhammad Syauqi , Firdaus Rachmat
Published: December 2024

General Background: With the rapid advancement of automotive technology, especially motorbikes, fuel performance has become increasingly crucial in optimizing vehicle efficiency and meeting the demands of rising motorbike usage. Specific Background: Among commonly used fuels like BX 92 and BX Ultimaxx, the performance of different fuel types and combinations on power, torque, and specific fuel consumption (SFC) remains underexplored. Knowledge Gap: While various fuels are utilized, a detailed comparative analysis of motorbike performance using different fuels and blends, including ethanol mixes, is limited, particularly in the context of octane levels and engine power. Aims: This study aims to analyze motorbike performance differences when using BX 92, BX Ultimaxx, a 50:50 blend of BX 92 and BX Ultimaxx, and an 85:15 blend of BX 92 and ethanol, assessing power, torque, and SFC on an R15 motorbike using dynotest equipment. Results: The study found that higher octane levels yield improved power and torque, with BX Ultimaxx performing best in terms of power but consuming more fuel. BX 92 proved most efficient in fuel consumption but ranked lower in performance compared to BX Ultimaxx. The BX 92-BX Ultimaxx blend showed moderate improvements in power over BX 92 alone, while the BX 92-ethanol blend exhibited the lowest performance of all fuels tested. Novelty: This study provides a novel comparative framework for evaluating mixed fuel impacts on motorbike performance, particularly in utilizing ethanol as an alternative fuel component. Implications: These findings suggest that while higher-octane fuels enhance performance, fuel blending strategies could be optimized for specific outcomes, balancing efficiency with performance, thereby contributing to more sustainable fuel use in the automotive industry.
COMPARISON OF THE EFFECT OF SUXXX, V-POXXX FUEL AND THEIR MIXTURES ON R15 MOTORCYCLE ENGINE PERFORMENCE
Authors: Wahid M. Luqman , Firdaus Rachmat
Published: December 2024

General Background: With the increase in motorcycle usage worldwide, optimizing engine performance through fuel selection has become a focus, as fuel type significantly impacts torque, power, and specific fuel consumption. Specific Background: Public motorcycle transportation options include various fuel types, such as suxxx and v-poxxx, as well as blends with ethanol, which are commonly used for enhanced engine efficiency. Knowledge Gap: There is limited research directly comparing the performance impacts of suxxx, v-poxxx, and their mixtures, especially with ethanol, on motorcycles over a range of RPMs. Aims: This study aims to evaluate the differences in motorbike performance using pure suxxx, v-poxxx, a 50-50 blend of suxxx and v-poxxx, and an 85-15 blend of suxxx and ethanol by examining torque, power, and specific fuel consumption (SFC) on an R15 motorbike through dynotest trials. Results: Findings indicate that v-poxxx, with its higher octane level, provides superior torque, power, and SFC compared to suxxx and mixed fuels, especially at low and high RPMs. Meanwhile, the 85% suxxx and 15% ethanol blend achieves the best SFC but has slightly lower torque and power at specific RPMs compared to v-poxxx. Novelty: This study provides comparative insights into the effectiveness of mixed ethanol fuels in motorcycles, identifying performance variances across a range of RPMs, which is less explored in the context of motorcycle engines. Implications: The results suggest that high-octane fuels enhance engine performance, while ethanol mixtures could serve as efficient alternatives for fuel savings. These insights are valuable for consumers and manufacturers aiming to optimize fuel usage for different riding conditions.
DESIGN OF A LIGHTNING STRIKE COUNTER TOOL IN THE MOJOSARI ULP DISTRIBUTION NETWORK BASED ON IOT
Authors: Maulana Mochamad Rizal , Ahfas Akhmad
Published: December 2024

General Background: Electrical distribution systems frequently face disruptions, particularly in tropical climates like Indonesia, where lightning strikes are prevalent due to high humidity. Specific Background: These disruptions necessitate effective monitoring tools to manage lightning impacts on power distribution networks. Knowledge Gap: Despite existing solutions, there is a lack of real-time monitoring systems tailored for the specific conditions of Indonesian distribution networks. Aims: This study aims to develop an Internet of Things (IoT) based lightning monitoring device that leverages ACS712, DHT11, and LDR sensors, facilitating real-time data acquisition and notifications. Results: The system achieved sensor accuracies of 95.2% for the ACS712, 98.5% for the DHT11, and a satisfactory performance from the LDR sensor. The processed data is displayed on a 16x2 LCD and sent as notifications via Telegram. The device also includes a buzzer for immediate alerts during lightning strikes and features buttons for data logging and resets. Novelty: The research presents a novel application of IoT technology to create a user-friendly monitoring solution for lightning strikes, specifically designed for the 20KV distribution networks in the ULP Mojosari work area. Implications: By enabling timely notifications and efficient localization of lightning-related disruptions, this tool significantly enhances the operational response of field officers, improving the resilience of power distribution systems during adverse weather conditions. However, it is essential to note that the device requires an internet connection for Telegram notifications, and the ACS712 sensor has a maximum current reading limit of 30 amperes.
STUDY OF PROPERTIES CDS NANOCRYSTALLINE THIN FILM AS A PHOTODETECTOR
Authors: Abdulelah Haider , Shabeeb Ghufran Mohammad
Published: December 2024

It has been discussing the use of cadmium sulfide (CdS) as a material for photodetectors. CdS is a direct bandgap II-VI semiconductor with desirable properties for photodetectors, including high sensitivity, fast response time, and wide spectral range from ultraviolet to near-infrared. X-ray diffraction analysis confirmed the cubic crystal structure of the porous CdS thin film. Scanning electron microscopy revealed a porous morphology with macropores ranging from 200-300 nm in size. The performance of the porous CdS photodetector was evaluated. Under visible light illumination, the device generated a photocurrent of 16 nA, with response times of around 5 seconds for both the rising and falling edges of the light-induced current
SPLIT DUCT AC LEAKAGE MONITORING SYSTEM VIA GOOGLE SHEETS
Authors: Cahyo Chandra Darmawan Dwi , Jamaaluddin Jamaaluddin
Published: December 2024

General Background: Split duct air conditioners are prone to leaks, often resulting from corrosion in water catchment systems, which can lead to significant operational hazards such as electrical fires. Specific Background: Given the prevalence of these issues, there is an urgent need for effective monitoring solutions to maintain optimal air conditioner performance and prevent leaks. Knowledge Gap: Current monitoring systems lack integration with real-time data reporting mechanisms that can alert users promptly to potential issues. Aims: This research aims to develop a monitoring device utilizing NodeMCU ESP8266, water level sensors, and Google Sheets to enable real-time monitoring and management of water levels in split duct air conditioners. Results: The device successfully operates by turning on the fan when water levels are below 2 cm and activating the pump when levels exceed this threshold. The data is continuously sent to Google Sheets, allowing for easy monitoring and management. Novelty: This study presents a novel approach to air conditioner leak monitoring by integrating IoT technology, offering an efficient and user-friendly solution for residents. Implications: The developed monitoring tool significantly enhances the ability to detect and manage potential leaks in real time, thereby improving safety and operational efficiency. Future research should focus on enhancing sensor accuracy through specialized equipment and exploring alternative IoT platforms for improved data visualization, thereby providing users with an even more effective monitoring experience.
AUTOMATIC COOKER HOOD MONITORING SYSTEM BASED ON INTERNET OF THINGS
Authors: Raharjo Annas Wismo , Ayuni Shazana Dhiya
Published: December 2024

Acute Respiratory Tract Infection (ARI) poses a significant health risk, particularly for housewives frequently exposed to kitchen smoke, which contains harmful pollutants like carbon monoxide, potentially leading to serious conditions such as cancer and pneumonia. To address this issue, the development of an effective smoke removal system is crucial. This research employs a Research and Development methodology to design and test an automatic cooker hood that utilizes the MQ-7 sensor for smoke detection, controlling a 12V DC fan through a relay to operate at three adjustable speeds: low, medium, and high, based on real-time smoke intensity. The Aims of this study are to create a monitoring tool that efficiently removes kitchen smoke and provides immediate feedback on air quality. Results indicate that the system functions optimally, with the fan speed successfully adjusting according to detected smoke levels and displaying data on a 16x2 I2C LCD as well as through the Blynk application, offering clear visualization of air quality metrics. This research introduces a Novelty in integrating IoT technology for real-time air quality monitoring in kitchens, enhancing user awareness and intervention capabilities. However, fluctuations in smoke readings from the MQ-7 sensor present a Knowledge Gap, highlighting inconsistencies that affect PPM accuracy. The Implications of this study suggest the potential for improved health outcomes through better indoor air quality management, while future research should explore sensor accuracy enhancements and optimal placement strategies to ensure more reliable measurements, thereby further advancing the effectiveness of the automatic cooker hood system.
IMPLEMENTATION OF THE FUZZY TSUKAMOTO METHOD TO EARLY DETECTION TYPES OF GASTRIC DISEASES
Authors: Kholifah Rizka Nur , Azizah Nuril Lutvi
Published: December 2024

Abstract: The stomach is a critical organ within the human digestive system, and gastric diseases represent significant health concerns often underestimated by the public. Factors such as poor dietary habits, stress, and bacterial infections contribute to these ailments, whose initial symptoms can easily be misinterpreted due to their similarity with other gastrointestinal disorders. The knowledge gap exists in the diagnostic challenges faced by both patients and healthcare professionals, necessitating the development of improved diagnostic tools. This study aims to enhance the diagnostic process for gastric diseases through the implementation of an expert system utilizing the Fuzzy Tsukamoto method. By employing questionnaires and expert interviews to gather data on symptoms, we develop a comprehensive fuzzy inference system. Results indicate that the system accurately classifies stomach ailments based on user-reported symptoms, facilitating early diagnosis and treatment. The novelty of this research lies in the application of the Fuzzy Tsukamoto method, which allows for nuanced symptom analysis and inference, providing a more accessible means for the general public to identify potential gastric diseases. Furthermore, the system design includes flowcharts, data flow diagrams, and entity relationship diagrams to ensure a user-friendly interface. The implications of this study are significant, as it offers a robust tool for early detection of gastric diseases, thereby potentially improving patient outcomes and reducing healthcare costs associated with late-stage interventions. This expert system not only assists in diagnosing gastric conditions but also serves as a valuable resource for enhancing the understanding of symptomology in gastroenterology.
MAINTENANCE PRIORITIZATION FOR AN INDUCTION FURNACE WITH ANALYTICAL HIERARCHY PROCESS IN PT. LINGGA SAKTI INDONESIA
Authors: Putra Alvian Aries , Wulandari Indah Apriliana Sari
Published: December 2024

Abstract: The effective operation of induction furnaces in steel casting is crucial for maximizing production efficiency, yet equipment breakdowns remain a significant concern for manufacturers like PT. Lingga Sakti Indonesia. Despite existing maintenance strategies, there is a need for a more systematic approach to enhance Overall Equipment Effectiveness (OEE). This study addresses the knowledge gap in maintenance system optimization by employing the Analytical Hierarchy Process (AHP) to prioritize predictive maintenance tasks. The aim of this research is to assess the current OEE, calculated at 73.26%, and propose an updated maintenance framework based on the AHP findings, which involved input from four respondents across six criteria and nine alternatives. The results indicate that electrical monitoring emerged as the highest-ranked maintenance task, suggesting its implementation as a critical strategy for improving equipment reliability. The novelty of this approach lies in integrating AHP for maintenance decision-making, offering a quantifiable method for prioritizing tasks based on expert criteria. The implications of this study are significant, as the recommended maintenance system could enhance OEE and operational efficiency, ultimately leading to reduced downtime and improved productivity. Future research should focus on the practical implementation of these proposals and their impact on long-term maintenance effectiveness within the steel casting sector.
ANALYSIS OF SPARE PART INVENTORY CONTROL USING ECONOMIC ORDER QUANTITY (EOQ) AND CONTINUOUS REVIEW METHODS
Authors: Damayanti Maharani Lutfiah , Sukmono Tedjo
Published: December 2024

General Background: In the concrete manufacturing industry, the reliance on machines for production activities necessitates a robust spare parts inventory management system to ensure operational continuity. Specific Background: However, fluctuating demand for spare parts often leads to overstock or stockout situations, significantly impacting inventory costs and cash flow. Knowledge Gap: Existing studies primarily focus on static inventory management approaches, neglecting the dynamic nature of spare parts demand in manufacturing environments. Aims: This research aims to optimize total inventory costs while determining efficient order and reorder point quantities by integrating the Economic Order Quantity (EOQ) method with continuous review techniques. Results: The findings reveal an optimal order quantity of 131 units and a reorder point of 18 units, resulting in a total inventory cost of IDR 2,414,609,989—an efficiency improvement of IDR 293,152,400, equivalent to an 11% cost saving compared to previous inventory management practices. Novelty: This study innovatively employs a probabilistic approach to account for demand variability, enhancing the accuracy of inventory control measures. Implications: The outcomes suggest that implementing the proposed inventory management strategy can mitigate the risks of overstocking and stockouts, ultimately fostering improved financial performance in the company. Furthermore, the research highlights the necessity for regular inventory reviews and suggests future studies to develop more dynamic inventory control models that incorporate price fluctuations for spare parts, thereby addressing potential risks associated with cost variability.
IMPLEMENTATION OF FUZZY INVENTORY METHOD AND ARTIFICIAL NEURAL NETWORK IN DETERMINING SAFETY INVENTORY OF BAG PRODUCTS
Authors: Rahmansyah Muhammad Miftah Arzaq , Sukmono Tedjo
Published: December 2024

General Background: Effective inventory management is crucial for small and medium enterprises (SMEs) to address fluctuating demand and avoid shortages, especially in sectors like handcrafted products. Specific Background: In the context of PTK MSMEs (Karangtanjung Bag Craftsmen) in Sidoarjo Regency, bag product sales often vary monthly, necessitating accurate demand forecasting and optimal inventory levels. Knowledge Gap: While previous studies have explored demand prediction and inventory management, few have integrated advanced methodologies like Artificial Neural Networks (ANN) and Fuzzy Inventory approaches to cater specifically to SMEs in the handicraft sector. Aims: This research aims to predict the sales demand for bag products and establish safety inventory levels using ANN and Fuzzy Inventory methods, ultimately to control demand and reduce inventory costs. Results: The study yielded a Root Mean Square Error (RMSE) of 45.031 from the ANN analysis, indicating a good forecasting performance, while the Fuzzy Inventory method calculated a safety stock of 43,647 pieces for 2023. Novelty: The integration of ANN for demand forecasting and Fuzzy Inventory for safety stock determination offers a novel approach for SMEs, enabling them to respond proactively to market fluctuations. Implications: The findings provide a framework for MSMEs to enhance their inventory management practices, thus improving operational efficiency and reducing holding costs, which can significantly impact their sustainability and competitiveness in the market.
COMPARING OF ARTIFICIAL NEURAL NETWORK AND MULTIPLICATIVE HOLT WINTERS EXPONENTIAL SMOOTHING METHODS IN FORECASTING DEMAND
Authors: Safitri Salsa Zulfa , Sukmono Tedjo
Published: December 2024

General Background: Fluctuations in raw material orders pose significant challenges for business operators, especially during peak seasons like holidays and the new year, often resulting in shortages or excess inventory. Specific Background: This study focuses on forecasting demand for wallet products from UMKM Pengerajin Dompet Khas Tanggulangin (PDKT) by comparing two forecasting methods: Artificial Neural Networks (ANN) and the Multiplicative Holt-Winters method, which is tailored for seasonal data. Knowledge Gap: While existing literature recognizes the effectiveness of various forecasting techniques, there is limited comparative analysis of ANN and Holt-Winters specifically in the context of UMKM wallet production, highlighting the need for empirical validation. Aims: This research aims to identify the most accurate forecasting method to optimize raw material usage and production planning. Results: The findings indicate that the ANN method yields a superior Root Mean Square Error (RMSE) of 14.249, compared to 93.436 for the Holt-Winters method, establishing its higher predictive accuracy. Novelty: The study contributes to the field by providing a comparative analysis of forecasting methods tailored to the specific context of UMKM, demonstrating the efficacy of ANN over traditional methods. Implications: These results suggest that adopting ANN for demand forecasting can significantly enhance inventory management and production efficiency for PDKT MSMEs, ultimately leading to better resource allocation and reduced operational costs.
EFFECT OF SALINITY CONCENTRATION AND WATER TEMPERATURE ON THE RAYLEIGH WING ACCORDING TO FOUR-PHOTON POLARIZED SPECTROSCOPY DATA
Authors: Khakberdi Jumanov , Mukhammadzoir Khadjaev , Abdulla Ergashev
Published: December 2024

Objective: The purpose of this study is to examine how the temperature of the water and the concentration of NaCl affect the Rayleigh wing line, with an emphasis on how supersonic lattice modulation contributes to the narrowing of the Rayleigh wing and the creation of maxima. Method: To examine the nonlinear optical characteristics of water and aqueous solutions, the study uses four-photon polarization spectroscopy under pre-threshold Brillouin scattering circumstances. The modification of nonlinear cubic susceptibility and its effect on anisotropic scattering were investigated under controlled experimental settings, such as varied salt concentrations and laser beam intensities. Result: The results show that higher water temperatures and NaCl concentrations improve adiabatic compressibility, which in turn raises the Brillouin scattering threshold and decreases the degree of nonlinear cubic susceptibility modulation. Novelty: This study provides new insights into the interplay between the anisotropy of Brillouin scattering, hypersound lattice modulation, and the structural changes in water induced by NaCl concentration and temperature variations, offering a deeper understanding of the microscopic mechanisms influencing water's scattering properties.
INNOVATIVE BANKING SERVICES IN WORLD COUNTRIES ACCORDING TO INCOME
Authors: Kizi Makhmudova Mukhlisa Kodirjon
Published: December 2024

Objective: This study analyzes the development trends of innovative banking services, with a focus on the implementation of digital banking across countries categorized by income level. The research aims to examine the disparity in digital banking service advancements between high-income, upper-middle-income, and lower-middle-income countries, identifying underlying causes and opportunities for improvement. Methods: The study employs methods such as induction, deduction, and synthesis, supported by official statistical data from the World Bank and International Monetary Fund. The analysis covers the period from 2014 to 2021, focusing on specific years within this timeframe, and evaluates the global economy, high-income countries (HIC), upper-middle-income countries (UMC), and lower-middle-income countries (LMC). Results: The findings indicate that high-income countries have made substantial progress in digital banking, with nations such as Sweden, Norway, and the Netherlands nearing a cashless economy. Upper-middle-income countries show significant improvement in recent years, while lower-middle-income countries face challenges due to a strong informal economy, limited scientific development, and high corruption levels. Novelty: This study highlights the correlation between economic classification and digital banking adoption. It emphasizes the untapped potential in middle-income countries, suggesting opportunities for expanding digital banking services despite structural challenges, thus providing actionable insights for stakeholders in digital banking innovation.
CORPORATE REPUTATION AND THE PATH FROM CSR TO PROFIT IN CHINA'S FOOD COMPANIES
Authors: Ali Azlan , Jiaqi Xu
Published: December 2024

The financial success of a business is closely tied to its ability to meet its social responsibilities towards its stakeholders, who contribute valuable resources to the business. Corporate Social Responsibility (CSR) is the embodiment of corporate social behaviour, which has an impact on both a company's reputation and its performance. The study seeks to examine the influence of fulfilling corporate social responsibility (CSR) on financial success, with a focus on the mediating effect of company reputation. In order to accomplish this objective, this study focuses on examining publicly traded companies in China's food market. By utilizing both domestic and foreign theoretical study findings and practical exploration experiences on corporate social responsibility (CSR), business reputation, and financial performance. This study employs the literature review method to elucidate the theoretical foundation that supports the research and uncover the mechanism by which corporate performance is enhanced by the fulfilment of social responsibility by listed businesses in the food industry in China. And find the intermediary role of corporate reputation and investigates the mechanisms and pathways through which social responsibility and corporate reputation influence corporate performance. The findings will help to enhance the current understanding of the relationship between corporate social responsibility (CSR) and financial success. Additionally, it will offer valuable insights for future research and practical applications in this field..
THE EFFECT OF TAX INCENTIVES ON INCREASING THE TAX BASE
Authors: Kiyosov Sherzod Uralovich
Published: December 2024

the article describes the essence of tax benefits, the organization of tax services in providing them, the priority areas of tax services. Proposals and recommendations for improvement in the direction of modernization of production of tax benefits, technical renewal and diversification, wide introduction of innovative technologies have been developed.
WAYS TO IMPROVE OPEN MARKET POLICY BASED ON FOREIGN EXPERIENCE
Authors: Qizi Murodova Mohigul Chori
Published: December 2024

In the article, the current problems related to the introduction of the foreign experience of the open market lever in the monetary policy of the Republic of Uzbekistan are identified and scientific proposals aimed at solving them are developed
MONETARY CREDIT POLICY OF THE CENTRAL BANK AND ITS MACROECONOMIC SIGNIFICANCE
Authors: Choriyevna Murodova Dilnoza
Published: December 2024

The article includes the purpose, tasks, strategy and tactics of regulating the activities of commercial banks through the monetary and credit policy instruments carried out by the Central Bank of the Republic of Uzbekistan. It describes the nature of commercial banks, threats affecting their economic security, methods of protection against them, criteria for assessing the economic security of commercial banks
A NEURAL NETWORK MODEL FOR AUTOMATED LOGISTICS PROVIDER SELECTION
Authors: Maratovna Mirzanova Nozima
Published: December 2024

In the article, using artificial intelligence technologies in the digital economy, the problems of organization of logistics flows were identified and scientific proposals aimed at solving them were developed
THE EFFECT OF TAXATION ON THE ACTIVITY OF ENTERPRISES
Authors: Ramatullayevich Kudiyarov Kishibay
Published: December 2024

This research examines the impact of taxation on the activities of enterprises. Theoretical and empirical approaches have been studied regarding the impact of taxation on the activities of enterprises. The issues of regulating the ratio of debt and private capital of enterprises by means of taxes are analyzed. As a result of the analysis, relevant conclusions were formed.
APPLICATION OF VAT TO FINANCIAL SERVICES
Authors: Bisenbaev Sharyar Kuanishbaevich
Published: December 2024

This study examines the application of VAT to the financial sectors and the implications of exempting financial services from VAT. An analysis of VAT collection from financial services and the consequences of VAT exemption from theoretical and practical points of view was conducted. The application of VAT to financial institutions is a very complex issue in the area of public finance. For various technical and practical reasons, financial services are generally exempt from VAT in most countries. The banking sector provides credit services and paid services to consumers. VAT exemption for financial services creates some distortions for banks and the real economy. Based on the results of the study, a conclusion was made on the application of VAT to financial services
THE INFLUENCE OF TIKTOK CONTENT ON DIGITAL MARKETING OF ELECTRONIC PRODUCTS ON E-COMMERCE: A SYSTEMATIC LITERATURE REVIEW
Authors: Yulianto Mochamad Rizal , Mubarok Akhmad Nur , Suyogo Muhammad , Pebrianggara Alshaf , Almanfaluti Istian Kriya
Published: December 2024

This study aims to analyze the influence of TikTok content on digital marketing of electronic products in e-commerce through a systematic literature review. TikTok, as an increasingly popular social media platform, offers various engaging content features for users. This study examines how elements of content on TikTok, such as creative short videos, viral challenges, and influencer collaborations, can affect digital marketing strategies and sales performance of electronic products on e-commerce platforms. The methodology used is systematic literature review (SLR) by gathering and analyzing various relevant previous studies on the topic. The findings of this review indicate that TikTok content has a significant impact on brand awareness, consumer engagement, and sales conversion. Effective marketing strategies implemented on TikTok can increase product exposure, attract consumer attention, and drive purchasing decisions. These findings provide valuable insights for digital marketing practitioners in leveraging social media platforms to enhance the marketing performance of electronic products in e-commerce.