bluuebunny/crossref_metadata_2025 huggingface dataset:
Deteksi Tingkat Kerentanan Keamanan Website dengan Metode Manual Pentest dan Tools Xspear
Authors: Jazuli Ahmad , Salamah Irma , Soim Sopian
Published: January 2025

Currently, the internet has evolved into a source of information across various fields and demographics, making it easily accessible to many people. SQL injection and XSS payloads are among the most common types. The objective of this research is to detect the level of vulnerability of security gaps found and provide recommendations to the host for mitigating those risks. This research is qualitative in nature, focused on detecting the security gap levels on the Hotel Embryo website. The study uses vulnerability evaluation and penetration testing methods, with a manual penetration testing approach targeting specific URLs and vulnerability scanning using the Xspear tool. The research stages begin with gathering information from relevant sources through case studies and literature reviews of scientific articles, software and tools installation, followed by the core phase, which involves exploitation through pentest techniques and documenting the analysis results of the vulnerabilities found. The research subject is the Hotel Embryo website, and the research object is the security vulnerabilities detected on the website. Our findings identified a parameter in the room menu of the Hotel Embryo website, where 10 vulnerabilities with a HIGH status were discovered, posing significant risks, particularly to important data such as administrative information, personal data, institutional details, and more, which could be hacked and misused by cyber attackers.
Pengembangan Sistem Monitoring Kinerja FWG untuk Optimalisasi Produksi Air Tawar di Atas Kapal
Authors: Kurniawan Edi , Sonhaji Sonhaji , Ar-Ridho Bayu Rahmiyarto
Published: January 2025

Fresh water is a basic need for ship crews to support smooth operations. An auxiliary aircraft that can produce fresh water on board is required to reduce operational costs, namely the Fresh Water Generator (FWG). This research aims to develop an FWG performance monitoring system to optimize freshwater production. The research model used is a prototype with design, modeling, and prototype formation stages. The system uses an Arduino Mega 2560 microcontroller to process data from temperature, pressure, and TDS sensors, which are then sent via the LoRa transmitter and received by the LoRa receiver. The data is processed by the ESP 32 microcontroller and displayed on the LCD. In real-time, it monitors critical parameters such as heater temperature, filter quality, and freshwater quality, enabling rapid problem detection and timely corrective action. The findings show that the FWG performance monitoring tool can optimize freshwater production; based on the test results, it can operate stably at a pressure of 0.44 bar and a maximum temperature of 84°C and can work reliably under extreme conditions, making the FWG more efficient in producing freshwater.
Media Pembelajaran Android Network Integrated pada Mata Pelajaran Informatika berbasis Mobile
Authors: Lestari Isnania , Permana Ryan
Published: January 2025

The integration between the world of education and technology today has created various types of innovations in learning. Android learning media integrated with the internet network is one example of the type of media that can be produced from innovation in learning. The purpose of this study is to produce android-based learning media integrated with the internet network. The type of research used in this development is Research and Development (R&D) with the ADDIE model which has five stages, namely Analysis, Design, Development, Implementation and Evaluation. The subjects in this study were divided into two, namely the development subjects consisting of 2 media validators and 2 material validators. Furthermore, the product trial subjects were 35 students of class VIII MTS Al-Mujtahid. The data collection technique used was a questionnaire. The data analysis used was quantitative descriptive analysis. The results of the material expert test obtained a score of 81.75%, including the very feasible category. The results of the media expert test were 82.8%, including the very feasible category. The response given by students after using this media was 84%, which means that the students' response was very good. This proves that the learning media developed has provided good results because it has fulfilled the aspects needed to produce good learning media.
Optimalisasi Aplikasi Financial Tracker berbasis Mobile dengan Penerapan Design Pattern MVVM untuk Mengelola Keuangan
Authors: Jaelani Muhammad Naufal Hady Anshari , Asriningtias Yuli
Published: January 2025

The use of an appropriate design pattern is crucial in application development to maintain code consistency and simplify task division. This research aims to optimize the development of a mobile-based financial tracker application by implementing the Model-View-ViewModel (MVVM) design pattern. MVVM was chosen because it separates business logic (Model), the interface (View), and presentation logic (ViewModel), making the code more structured, easier to test, and more maintainable. This study falls under the Research and Development (R&D) category, employing the waterfall model through the stages of analysis, design, implementation, testing, and maintenance. Data were collected through literature review and observation, and analyzed to evaluate the effectiveness of MVVM implementation. Our findings show that the mobile-based financial tracker application developed with MVVM design pattern successfully aids in financial management. Application testing results indicated significant performance improvements, with CPU efficiency at 74.8% on the RenderThread and 27.8% on the MainThread. This study contributes by demonstrating how MVVM improves responsiveness, simplifies real-time data synchronization, and enhances application flexibility and efficiency. These findings fill the gap in previous studies that have underexplored the technical aspects of financial application architecture.
Perbandingan Cosine Similarity dan Mean Squared Difference dalam Rekomendasi Buku Fiksi berbasis Item
Authors: Rosydah Lucyta Qutsyaning , Widiyaningtyas Triyanna
Published: January 2025

The need for recommendations is increasingly crucial in the digital era, especially with the abundance of fiction book data from e-book platforms and digital libraries. This study aims to evaluate the effectiveness of item-based collaborative filtering using cosine similarity and Mean Squared Difference (MSD) metrics for book recommendations. The knowledge discovery in databases method was applied, encompassing data selection, pre-processing, transformation, data mining, and evaluation. The dataset includes 100,000 user ratings obtained from Kaggle's "Book Recommendation Dataset." Our findings show that the Mean Absolute Error for MSD is 0.152307, slightly better than cosine similarity at 0.152406. The Root Mean Squared Error for MSD is lower at 0.185551, compared to cosine similarity's 0.185636. However, Cosine Similarity is more efficient in processing time, with 0.50 seconds compared to 0.59 seconds for MSD. Understanding these metrics is crucial, as they reveal differences in accuracy and efficiency in book recommendation. The results indicate that MSD performs better in the accuracy of fiction book recommendations compared to cosine similarity, making it more suitable for applications prioritizing recommendation precision, while Cosine is more efficient for large data processing.
Implementasi BERT dan Cosine Similarity untuk Rekomendasi Dosen Pembimbing berdasarkan Judul Tugas Akhir
Authors: Sabilillah Ferris Tita , Winarno Sri , Abiyyi Ryandhika Bintang
Published: January 2025

Challenges in completing final projects, which often contribute to delays in student graduation, are frequently due to a mismatch between students' research topics and the expertise of their supervisors. Therefore, a method is needed to address this misalignment in the final project process. This study aims to implement a Bidirectional Encoder Representations from Transformers (BERT) model and cosine similarity to recommend supervisors based on students' final project titles. The research dataset includes 3,723 research titles collected through web scraping from Google Scholar and ResearchGate, representing the expertise of 63 lecturers in the Informatics Engineering Program at Universitas Dian Nuswantoro. Data processing includes preprocessing to generate embedding vectors from lecturers' research titles, which are then compared with students' final project titles. Our findings indicate that the developed recommendation model achieves an accuracy of 90% in identifying relevant supervisors based on topic alignment between students' final project titles and lecturers' areas of expertise, as reflected in their publications. This result can make a significant contribution to supporting students in completing their final projects more efficiently and improving the quality of academic supervision by facilitating more appropriate supervisor selection.
Analisis Metode Collaborative Filtering menggunakan KNN dan SVD++ untuk Rekomendasi Produk E-commerce Tokopedia
Authors: Hazizah Chalista Yulia , Widiyaningtyas Triyanna
Published: January 2025

The rapid development of internet technology has driven increased adoption of e-commerce, yet companies face challenges in enhancing users' shopping experiences. To assist users in finding products that match their preferences, relevant recommendation analysis is crucial. This research compares the effectiveness of K-Nearest Neighbors (KNN) and Singular Value Decomposition Plus Plus (SVD++) algorithms for e-commerce product recommendations using the Tokopedia Product Reviews dataset from Kaggle, which contains 40,893 reviews. The study includes data collection and preprocessing steps such as removing duplicates, replacing missing values with the average, and normalizing ratings. KNN and SVD++ are then applied to predict ratings using cosine similarity and factor matrices. Evaluation using Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) shows that SVD++ outperforms KNN, achieving a lower MAE of 0.161176 and RMSE of 0.185252, compared to KNN's MAE of 0.163964 and RMSE of 0.197045. This indicates that SVD++ is more effective in delivering accuracy and capturing data complexity. The findings highlight the potential to enhance recommendation effectiveness in e-commerce, improving user satisfaction by efficiently matching products to preferences.
Integrasi Kamus Multibahasa pada Feed Forward Neural Network dan IndoBERT dalam Pengembangan Chatbot Mobile
Authors: Pamungkas Arba Adhy , Alam Cecep Nurul , Atmadja Aldy Rialdy , Juliansyah Roby
Published: January 2025

The development of digital technology drives the need for efficient and responsive communication services that support multilingual. This study aims to develop a chatbot that facilitates communication and operational tasks for users of the DigiTeam application by integrating a multilingual dictionary into the Feed Forward Neural Network (FFNN) model and IndoBERT. The research method used is CRISP-DM, a systematic approach in data exploration, preparation, modeling, and implementation. The DigiTeam application was developed using the Agile methodology to gradually enhance the features and functionalities of the application. The dataset consists of 456 patterns and 106 tags containing common and operational work-related questions. This study utilizes a multilingual dictionary with 309 words to improve the chatbot's context understanding and response accuracy to user queries. The test results show that integrating the multilingual dictionary into the FFNN and IndoBERT models yields an accuracy of 95.45% with balanced precision and recall, demonstrating the chatbot's ability to understand and respond to multilingual queries in real-time, while also improving operational efficiency and information access in the workplace.
TaniSidemen: Aplikasi Pengadaan dan Penjualan Bibit biji Tanaman berbasis Mobile
Authors: Maulana Muhammad Hizbi , Asriningtias Yuli
Published: January 2025

Procuring and selling seeds is an important part of sustainable agriculture. To facilitate this process, mobile applications are a promising solution. This research aims to develop a mobile application specifically designed for the procurement and sale of plant seedlings. The method used for the development of this software is Software Development Life Cycle (SDLC) with waterfall approach. The planning stage is carried out for system planning, the analysis stage is carried out to analyze the running system and collect data by conducting observations and interviews, the design stage is carried out to design use case diagrams, activity diagrams and user interfaces, the implementation stage uses Kotlin when the implementation process and the testing stage uses black box testing. The results of black box testing are the main functionality of applications such as procurement and sales menus that work properly. The result of this research is an application called TaniSidemen, which is a mobile-based plant seed procurement and sales application. The TaniSidemen application facilitates the procurement and sale of plant seeds, increases time and cost efficiency, and supports the digitization of the agricultural sector for industrial sustainability.
Analisis Value Proposition dan Persepsi Pengguna Terhadap Sistem Informasi Laboratorium (LIS) di Rumah Sakit
Authors: Cahyati Ade Puput , Subhiyakto Egia Rosi
Published: January 2025

Patient data management information in the health sector is not only a technological consideration but also includes an evaluation to facilitate medical personnel to store patient data. Thus, the hospital, which is a forum for medical personnel, needs to consider the development of a new recording system. This study aims to analyze the value proportion and user perceptions of Laboratory Information System (LIS) for application development so that developers can offer features and designs that users need. Data collection techniques in this study used a questionnaire with a sample of 52 people. The data analysis technique used uses the UX Honeycomb method and the System Usability Scale to be able to analyze the LIS application. The results of this study indicate that the value proposition variable has a significant influence on the LIS application based on the UX Honeycomb indicator. The dominant indicators are useful and usable, while the indicators that need to be improved are findable and valuable. User perception has a significant influence on the LIS application; the average value of 85.14 means that it has a very usable influence and is easy to use. So that hospitals can switch to digital data and reduce physical documents.
Algoritma SARIMA sebagai Pendukung Strategi Peramalan HPS dalam Persaingan Tender di LPSE Indonesia
Authors: Fernando Daud , Syawanodya Indira , Muhammad Raditya
Published: January 2025

Tender in Indonesia's Electronic Procurement Service (LPSE) is the procurement of goods/services in the form of public facilities and managed by the provider with the lowest estimated price (HPS) value during the reverse auction process. The fluctuating value of HPS and the tight competition of competitors make winning for providers increasingly difficult and competitive. The purpose of this research is to create a forecasting model of the HPS value of tenders in LPSE Indonesia using the Seasonal Autoregressive Integrated Moving Average (SARIMA) algorithm. This type of research is experimental research to determine the order of the best SARIMA model. The research variables used are tender publication date and HPS value as much as 747,098 tender data from historical data from web scraping of the LPSE website with a withdrawal date range of January 7, 2013 to November 30, 2022. The data analysis technique uses data exploration analysis to determine the characteristics of the data distribution and then the implementation of the SARIMA forecasting algorithm. The results of this study show that the SARIMA((5,1,1),(4,1,1,7)) model is the optimal model with an evaluation value of mean absolute percentage error (MAPE) percentage error value of 33.56% which in relation to LPSE can provide a reasonable forecasting value. The results of forecasting for the next 30 days show that the distribution of HPS values is in the range of 680 million - 700 million rupiah in the period December 2022.
Machine Learning untuk Deteksi Stres Pelajar: Perceptron sebagai Model Klasifikasi Efektif untuk Intervensi Dini
Authors: Zahrah Febrina Nabila , Muljono Muljono
Published: January 2025

Stress is a serious challenge for students that can negatively impact physical health, mental well-being, and academic performance. However, accurate and effective stress detection approaches to support early intervention are still limited. This study aims to evaluate machine learning models for detecting student stress levels with optimal accuracy to facilitate early intervention. The research employs a quantitative approach using a dataset containing 1,100 student samples from Nepal, encompassing 20 stress-related features from psychological, social, academic, environmental, and physiological aspects. Data were collected via a self-report questionnaire, processed with StandardScaler scaling, and analyzed using 10-fold cross-validation. The models tested include Perceptron, Gradient Boosting Trees Classifier (GBTC), Naive Bayes (NB), Logistic Regression (LR), and AdaBoost. The results show that Perceptron performed the best with an accuracy of 97.27%, followed by NB (95.45%), GBTC (94.54%), LR (94.54%), and AdaBoost (93.63%). Perceptron, with its advantage in linearity and evaluation through 10-fold cross-validation, shows great potential as an effective classification model for student stress detection, which can accelerate early intervention and enhance student well-being and learning environments.
Sistem Cerdas Deteksi Status Gizi Anak melalui Eksplorasi Algoritma C.45 dan Forward Feature Selection
Authors: Arif Alfis , Gusmaliza Debi
Published: January 2025

The problem of high rates of child malnutrition remains in Pagar Alam City. The lack of understanding of nutritional interventions and the limited ability of Posyandu cadres to conduct accurate nutritional assessments are the main factors. This situation makes it difficult for the community to monitor the nutritional status of children and provide appropriate nutritional intake. This research aims to create an intelligent system for detecting children's nutritional status through the exploration of C.45 algorithm and Forward Feature Selection in Pagar Alam City. This system is designed to detect children's nutritional status and provide recommendations for appropriate nutritional intake based on detection results with variables of children's weight and height. The data used amounted to 7519 data obtained from the Pagar Alam City Health Office. The model we use to build this system is waterfall with stages of planning, analysis, design, development, testing and implementation. Then the method we apply to this system is CRISP-DM and the C.45 algorithm and Forward Feature Selection technique. Our results are in the form of an intelligent system for detecting children's nutritional status, with the results of system testing using test data and training data showing 100% accuracy. In addition, black box testing also proves that the system works well as expected.
Heritage and Language Values Hidden in Khmer Palm Leaf Manuscripts in An Giang Province, Vietnam
Authors: Nguyen Tran Cao , Van Sang Nguyen , The Dinh Dinh , Ho Thanh Nguyen
Published: January 2025

The manuscripts on Khmer palm leaves in An Giang province are a distinctive element of the cultural and linguistic heritage of the Khmer community in southern Vietnam. These manuscripts, made from processed palm leaves, serve as a repository of Buddhist scriptures, sacred texts, and traditional knowledge, reflecting the spiritual and cultural values of the Khmer people within the Theravada Buddhist tradition. This study examines the origins, the techniques of manuscript creation, and their cultural significance, highlighting their role in preserving the Khmer language and traditional teachings. The study also addresses the challenges posed by environmental degradation and the decline of traditional craftsmanship, which threaten the preservation of these manuscripts. The research employs methods such as ethnographic observation, document analysis, and interviews to clarify how data is collected and how this information will be used in the study. Along with providing criteria for selecting research subjects and locations, including pagodas in Tri Tôn and Tịnh Biên districts, the study is more systematic and verifiable, enhancing the scientific rigor and reliability of the results. The study proposes solutions such as raising community awareness, applying digital preservation methods, and encouraging community participation in preservation efforts. Through this, the research emphasizes the importance of Khmer palm leaf manuscripts as a cultural treasure and their relevance in preserving Khmer heritage and identity in the modern era.
Evaluation of Pesticide Effects on Honeybee Health and Colony Collapse: Findings from a Beekeeper Survey in the Beni Mellal-Khenifra Region, Morocco
Authors: Brhich Amina , Hachimi Tarik , Chatoui Hicham , Ait Sidi Brahim Malika , Hnini Rachid , Chatoui Redouane , Merzouki Hasna , Merzouki Mohamed
Published: January 2025

Since it first appeared in 2022, the phenomenon referred to as Colony Collapse Disorder (CCD) has affected several regions of Morocco to varying degrees. In order to assess the possible impact of pesticides on the appearance of this syndrome, we conducted a study aimed at evaluating the impact of pesticide use on the emergence of this syndrome through a year-long survey involving 160 beekeepers in the Beni Mellal–Khenifra Region (BKR) who also experienced an unprecedented desertion of hives during the same period. The majority of surveyed beekeepers practice mixed (45%) or migratory beekeeping (42%) and provide supplementary feeding (83.75%) to support their bees. Nearly 37.5% of the hives are located near crops treated with pesticides, exposing the bees to these chemicals. The results showed that the majority of beekeepers reported a cessation of queen laying (74.38%), high mortality rates among worker bees (81.25%), drones (65.63%), and queens (61.88%). Abnormal behaviors such as immobility with trembling (42.50%), reduced flights (47.50%), and disoriented navigation (28.75%) were also observed. Correlation analyses indicate that proximity to treated crops significantly increases the risk of queen laying cessation (Odds Ratio 6.0) and a reduction in waggle dances (Odds Ratio 2.41). Extended foraging flights show a borderline statistical significance (Odds Ratio 2.33), suggesting a disruption of natural food sources. These results highlight the potential impact of pesticides on colony health and bee behavior, pointing out the need to adapt beekeeping practices and implement protective measures against pesticides.
The impact of intent-based networking on network configuration management and security
Authors: Adeola Adewa  , Vincent Anyah  , Omoniyi David Olufemi  , Adedeji Ojo Oladejo  , Toluwanimi Olaifa
Published: January 2025

Intent-based networking (IBN) has emerged as a transformative paradigm in network management, revolutionizing how networks are configured, monitored, and secured. By leveraging artificial intelligence (AI) and machine learning (ML), IBN translates high-level business objectives into automated network configurations, ensuring that operational intents are consistently achieved. This paper explores the profound impact of IBN on network configuration management and security.
Firstly, we examine how IBN streamlines network configuration through automation, reducing manual intervention and mitigating configuration errors, which are among the leading causes of network outages. IBN’s ability to validate intents against real-time network states ensures that configurations align with business policies, enabling agile and reliable network operations.
Secondly, the role of IBN in enhancing network security is analyzed. By continuously monitoring network behavior against predefined intents, IBN systems can detect and respond to anomalies or potential threats in real time. This proactive approach minimizes the window of vulnerability and ensures compliance with security policies. Furthermore, the use of AI-driven insights facilitates predictive threat management and adaptive security measures.
Finally, we discuss the challenges and future prospects of adopting IBN, including the integration with legacy systems, the reliance on accurate intent definitions, and the need for robust AI models. The findings underscore that IBN not only simplifies network management but also fortifies network defenses, making it a cornerstone of modern, resilient network architectures.
The role of data analytics in enhancing ESG transparency in the corporate sector of Bangladesh
Authors: Ibrahim  , Nurul Huda Razib  , Imran Hossain Rasel
Published: January 2025

This study explores the role of data analytics in enhancing the transparency, accountability, and reliability of Environmental, Social, and Governance (ESG) reporting within the corporate sector. As global demand for more accurate and standardized ESG disclosures increases, organizations are turning to advanced data analytics tools, such as artificial intelligence (AI), machine learning, and blockchain, to improve the quality and verifiability of their ESG reports. This research employs a mixed-methods approach, combining a survey of corporate sustainability officers, in-depth interviews with industry experts, and case studies of companies utilizing data analytics in their ESG reporting. The findings reveal that while larger corporations have successfully integrated data analytics into their ESG practices, small and medium-sized enterprises (SMEs) face significant barriers, including resource constraints, data quality issues, and lack of standardized ESG metrics. The study also identifies the key benefits of data analytics, including improved transparency, better risk management, and enhanced regulatory compliance. Despite challenges, the adoption of data analytics in ESG reporting is shown to increase stakeholder trust and offer a competitive advantage. The study concludes with recommendations for companies to invest in data quality, build technical capacity, and leverage emerging technologies to meet growing regulatory requirements and improve their ESG performance.
Clinicopathological profile of renal cell carcinoma at the anatomical pathology laboratory, Saiful Anwar General Hospital from 2019 until 2023
Authors: Kenty Wantri Anita  , Ihda Dian Kusuma  , Rifka Ulfa Rosyida
Published: January 2025

Renal Cell Carcinoma (RCC) represents about 2% of all cancers worldwide, denotes cancer originated from renal epithelium and accounts for >90% of cancers in the kidney, and is more commonly seen in men than women. The histologic classification of RCC based on histologic subtypes is Clear Cell, Chromophobe, and Papillary. Since of RCC is different across regions and may change over time, global distribution patterns, risk factors need to be assessed to developing measures and prevention. The purpose of this study was to analyze RCC patients based on histopathological type, age, and gender. This study is a descriptive analytic study. The data was collected from RCC patients at the Anatomical Pathology Department of Dr. Saiful Anwar Hospital between 2019 and 2023, all of whom underwent histopathological examinations. A total of 77 RCC cases were identified, with an average age group of 51-60 old age group (4.28%) and a higher prevalence in men (52%). The most frequent histopathological type was Clear Cell Renal Cell Carcinoma (74%), followed by Papillary Renal Cell Carcinoma (15.6%) and Chromophobe Renal Cell Carcinoma (10.4%)
Effect of growth period on optical properties of CBD grown nano-scale ZnO thin films for application in CIGS solar cell
Authors: Rajni Seth  , Rubi
Published: January 2025

In the present study, ZnO thin films were deposited for different deposition time periods using chemical bath deposition technique on a seeded substrate at a selected pH value and concentration based on the earlier findings. In order to optimize the deposited thin film to be used as buffer layer in thin film CIGS solar cell, optical characterization was done by using UV/VIS spectro-photometry and various parameters like transmittance, reflectance, refractive index, absorption coefficients, dielectric constant, optical conductivity etc. were calculated. The highest transmittance of 92.9% was recorded for the sample with deposition time 1 hour, which further decreased to 90.8% for deposition time of 1.5 hour and then fell down to 87% for a growth period of 2 hours. A blue shift as compared to the bulk was observed in the band gaps of all the three samples. Absorbance, reflectance, absorption coefficients, refractive indices and optical conductivities were found to increase with deposition time. The study laid a foundation stone for understanding the use of as deposited ZnO nano-crystalline thin films in thin film CIGS solar cell by correlating the growth period at a optimized pH and concentration with its various optical parameters.
Predicting precision-based treatment plans using artificial intelligence and machine learning in complex medical scenarios
Authors: Temitope Oluwatosin Fatunmbi
Published: January 2025

The integration of artificial intelligence (AI) and machine learning (ML) in healthcare has emerged as a pivotal shift, facilitating the development of precision-based treatment plans that are tailored to the individual characteristics of patients, particularly those with chronic and multi-faceted health conditions. This paper explores the application of advanced AI and ML algorithms to predict and optimize treatment strategies by analyzing complex medical data and identifying patterns that would be challenging for traditional methods to discern. The paper begins by reviewing the fundamental principles and evolution of AI and ML techniques used in healthcare, focusing on their roles in predictive analytics and decision-making support systems.
This investigation also assesses the evolving landscape of AI and ML in healthcare by examining future directions and the potential for integration with other technologies, such as wearable health monitoring devices and telemedicine platforms. The potential to harness data from these additional sources is significant, offering a more comprehensive view of patient health and enabling more nuanced treatment planning. The implications of integrating AI and ML with electronic health records (EHRs) for real-time analysis and the enhancement of clinical decision support systems are discussed. Additionally, the prospective role of AI in predictive modeling for preventive care and its application to patient stratification for targeted interventions is considered, reinforcing the paradigm shift from reactive to proactive healthcare.
The findings presented in this paper highlight the transformative potential of AI and ML in precision medicine, where tailored treatment plans are no longer a theoretical aspiration but an emerging reality. The ability to integrate complex datasets, extract actionable insights, and predict treatment responses with high accuracy opens new frontiers in the management of chronic and complex conditions. However, realizing this potential requires a concerted effort to overcome technical, ethical, and logistical hurdles. This research emphasizes that, with appropriate safeguards and continued development, the adoption of AI and ML in medical practice can revolutionize the approach to patient care, leading to better outcomes and an optimized allocation of medical resources.
Implementation of content marketing strategies in micro and small enterprises in Makassar City - Indonesia
Authors: Muhammad Nurreski Muis  , Muhammad Rakib  , Muhammad Jamil
Published: January 2025

The implementation of the content marketing strategy at Business “Kopi 1000 Nurhidayah” in building customer engagement. This research used a qualitative method with data collection techniques through observation and the distribution of questionnaires to the followers of the SMEs Instagram account. The results of the study indicate that the implementation of the content marketing strategy through content idea development, copywriting, editing, and the use of relevant captions and hashtags successfully increased customer interaction on social media. The number of followers and sales increased significantly after the implementation of this strategy. The study concludes that content marketing is effective in increasing customer engagement and driving sales growth at Micro and Small Enterprises.
Potential for dental caries in asthma patients with inhaler therapy
Authors: Delfia Amanda Putri  , Andree Salim
Published: January 2025

Introduction: Asthma is a heterogeneous disease associated with airway hyperresponsiveness and airway inflammation. Some drug treatments in asthma sufferers have a stronger effect on oral health than the disease itself, including causing dental caries. Objective: To determine the potential for caries in asthmatic patients with inhaler therapy.

Methods: Systematic literature database search using PubMed and ScienceDirect databases. Literature data search used the following keywords: “Inhaled Therapy”, “Inhalation Therapy”, “Caries”, “Dental Caries”, “Asthma Medications”, “Asthma”, “Asthma Drug”, “Oral Health”, “Treatment of Asthma”. The search was conducted from March 2023 to April 2023 with the inclusion criteria being a clinical trial and a randomized controlled trial, using inhaler therapy as one of the interventions, a population of people with asthma who experienced dental caries, and published in English from 2013 to April 2023.

Results and Discussion: The initial search identified a total of 275 articles from 2013 to 2023 across the two databases. After manual review of titles and abstracts and appropriate articles for inclusion, 9 relevant articles were identified in the systematic review. From the literature study conducted, it was shown that the treatment of asthma with inhaler therapy showed the potential for caries to occur with the mechanism of decreasing salivary flow and decreasing the buffering ability of the oral cavity resulting in the proliferation of Streptococcus Mutans and Lactobacillus as aciduric bacteria which play a role in the demineralization of tooth enamel.

Conclusion: Prolonged use of inhalation therapy in asthmatic patients has the potential to cause caries. This condition is supported by the awareness of asthma patients about poor oral hygiene.
Head-to-head comparison of Rezum vs Urolift for patient with benign prostatic hyperplasia: A systematic review
Authors: Muhammad Alvin Ramadhan Usman  , Asyam Syafiq Hasbullah  , Ulinnuha Khirza Kafalah  , Raih Viguruh Hermarwan
Published: January 2025

Introduction: Minimally invasive surgical therapies (MISTs) have been developed to treat Benign Prostatic hyperplasia (BPH) while minimizing adverse surgical effect. Most recent developed MIST, Rezum and Urolift, showed effective efficacy in improving, but head-to-head comparison still lacking. This study aims to compare the efficacy and safety of Urolift and Rezum in managing BPH-related LUTS.

Methods:A systematic search was conducted in Cochrane, PubMed, EMBASE, SCOPUS and EBSCOhost, identifying observational studies comparing rezum and urolift in BPH patient. Data extraction included demographics, intervention protocols, follow-up duration, and outcomes International Prostate Symptom Score (IPSS) score, IPSS-QoL, sexual function, and reintervention rate. The quality of studies was assessed using the Newcastle-Ottawa Scale.

Results:Two cohort with a total of 101 patients with BPH were included. At 12 months, Rezum tends to be superior in improving symptoms severity, while at 2 months of follow-up, Urolift outperformed Rezum. Both intervention preserved patient’s sexual function and does not differ significantly. Reintervention rate significantly higher in Urolift compared to Rezum group.

Conclusion: Rezum offers a more effective alternative to Urolift for managing BPH in long term setting, with lower reintervention rate and preserved sexual function. In early setting, Urolift showed higher efficacy and rapid improvement compared to Rezum.
Influence of two drying methods (oven and solar dryer) in modeling the drying kinetics of Ricinus communis L. capsules
Authors: Reyes Herdenn GAMPOULA  , Roniche NGUIE  , Michel ELENGA  , Haïshat Lucadeïde MAHOUMI SOULEYMANE  , Sylvia Pétronille NTSOSSANI  , Dieuvey Johnmarline MATADIA DE MABIRI
Published: January 2025

Castor beans are herbaceous perennials found in tropical and subtropical climates. They are very cold-hardy and belong to the Euphorbiaceae family. The aim of this work was to study the drying kinetics of castor oil capsules and the variations in thermal quantities that can occur during drying. Two drying methods were used: conduction drying in an oven at temperatures ranging from 50 °C, 60 °C and 70 °C, and radiation drying in a boat-type direct solar dryer at an average temperature of 49 °C. The results showed that the mass loss of castor oil capsules varied as a function of time and applied temperature, and was faster in the oven at 60 °C and 70 °C than in the solar dryer at an average temperature of 49.2±0.03 °C. It was found that the higher the drying temperature, the shorter the drying time. Seven (7) models were used for modeling. Modeling data based on analysis of R2 ; χ2 and RMSE showed that the best models for oven-drying castor oil capsules were those of Midili et al., for drying temperatures of 50 °C and 70 °C, and the logarithmic model for drying at 60 °C. For sun-drying, the best model was that proposed by Henderson and Pabis, modified.
A cross-sectional comparative study to evaluate the efficacy and safety of levetiracetam with other antiepileptics among epileptic patients at a tertiary care teaching hospital
Authors: Anupama P S  , Christina Biju  , Hareesh M  , Lijo Joseph Thomas  , Chitra C Nair  , Beena P
Published: January 2025

Background: Epilepsy is a neurological disorder characterized by recurrent seizures, and about one-third of patients do not respond to a single antiepileptic drug (AED). Levetiracetam (LEV) is commonly used as a first-line treatment for partial seizures and in combination with other AEDs. This study aimed to determine which combination therapy with LEV is more effective and safer for treating focal epilepsy.

Method: The study analyzed 90 patients diagnosed with focal epilepsy, who were treated with LEV in combination with other AEDs. The efficacy was assessed by comparing the seizure count before and after combination therapy, and safety was evaluated based on adverse effects. Statistical analysis was performed using IBM SPSS 22.0.

Result: There were five groups in which levetiracetam was used in combination with other AED

Group A: Levetiracetam + Lacosamide
Group B: Levetiracetam + Clobazam
Group C: Levetiracetam + Oxcarbazepine
Group D: Levetiracetam + Sodium valproate
Group E: Levetiracetam + Phenytoin
Due to an insufficient sample size, only Group A (LEV-LCM) and Group B (LEV-CLB) were statistically analyzed. The t-values for these groups were 15.132 and 13.889, respectively, both statistically significant with a p-value <0.001.

Conclusion: The results from this study showed that the addition of a second AED significantly reduced the seizure count when compared with a single AED regimen. LEV-LCM & LEV-CLB combination were taken for the analysis of safety and efficacy. It was found that there was a significant difference in seizure count within the groups with a p value <0.001. Comparing the t test value, it was found that the addition of LCM to LEV produce a greater difference in seizure count. Only a few minor side effects were observed in both the groups
Women and Kula
Authors: Kuehling Susanne
Published: January 2025

This article argues that the hosting of kula partners is an important part of the exchange system that requires more attention. Women’s management of their households and resources, their training of children, and the internal networks that provide for a visiting kula partner are regarded as the benefits and key motivations (‘profit’) of kula. If the hospitality is underwhelming, a visitor will not continue the partnership and, because he will share his experiences back home, this will negatively affect the future kula affairs of that household. By isolating the movements of valuables from the deep experiences of visiting and hosting, the role of women in kula is typically misrepresented as marginal and of lower value. Kula, to me and to most islanders, is not about the fame of traders, but about the cooperation of families to ensure the services, hospitality, and generosity that are so special to the region.
Key words: Kula exchange, Melanesia, gender roles, women, hospitality, ethnography, power relations
ANALISIS SYSTEM KLASIFIKASI BARANG CEPAT HABIS MENGGUNAKAN METODE AHP PADA GUDANG BANK BSI LABUAN
Authors: Wardah Neli Nailul , Susanti Ervi Nurafliyan , Sugiarto Agung
Published: January 2025

Decision making to determine stock of goods in a banking industry warehouse must be precise and fast, as is the case at Bank BSI Labuan. Determination of stock of goods is carried out when classifying fast-running goods in the warehouse based on level of need, price, type of need, user and class with respective weights determined by the bank. The aim is to obtain fast and accurate information in making decisions regarding the classification of goods that run out quickly or goods that are urgently needed in the BSI Labuan bank warehouse in order to maintain the efficiency and effectiveness of work at an institution. This research will implement a system using the AHP (Analytical Hierarchy Process) method as a problem solving analysis method in creating a decision support system.
CALCULATION METHOD FOR SINGLE-SPAN FRAMES, CONSIDERING THE JOINT OPERATION OF THE COLUMNS AND THE SHAPE OF THEIR DEFORMATIONS
Authors: Yarovoj S.M. , Tytiuk A.O. , Tytiuk A.A. , Bogachenko S.V.
Published: January 2025

Problem statement. A specific characteristic of modern skeleton calculation is the fact that only one column in a frame can be loaded with the maximum probable load. If one of the columns (at which the crane trolley with the load is located) is under maximum longitudinal force and bending moment, the opposite column of the same cross-section is loaded with significantly less effort. In the transverse direction, two columns of a single-span shop are connected by a crossbar into a frame system and the columns are not free to move. The development of significant plastic deformations in one of the columns does not cause loss of stability of the column, as it works as part of the frame. The opposing column takes up the growing load. Consideration of the joint operation of the columns as part of the frame will allow a more rational design according to current standards. The shape of the deformation of the short-curved frame is stimulated by the loads acting, usually not coinciding with the first proper form laid down in the standards. The load-bearing capacity depends on the ratio of the loads stimulating the different eigenforms and is always higher than that of the first curvature. The larger the higher forms are, the lower the deformability and the higher the load-bearing capacity of the system, and this has been experimentally verified. An approximate method for calculating the stability of compression-bent columns of steel frames with crane loads has been developed, which takes into account the joint operation of unequally loaded columns in the frame and the form of deformation under the action of active forces. The calculated column lengths determined for frames with crane loads according to the proposed method are smaller than the calculated lengths determined according to the standard method by 8−20 %.
ORGANIZATION OF EDUCATIONAL AND HEALTH-IMPROVING SURROUNDINGS FOR CHILDREN 5−12 YEARS OLD ON THE BASE OF A TECHNICAL PROFILE HIGHER EDUCATION INSTITUTION
Authors: Solohubova S.V. , Shyyan V.M. , Shyyan O.V. , Marusych O.G. , Kaplenko D.D.
Published: January 2025

Problem statement. Since the beginning of 2020, almost all state educational institutions in the city of Dnipro work remotely, and clubs and sports sections do not work. Due to the constant threat of air strikes, the children of Dnipro hardly visit parks and sports grounds, and do not spend time outdoors. All this has a negative impact on their physical and psycho-emotional state. The purpose of the article: to investigate the organization’s peculiarities of educational and health-improving surroundings for children of 5−12 years old on the base of a technical profile higher education institution under martial law. The analysis of scientific publications confirmed the possibility of organizing educational and health-improving process on the base of a higher education institution during hostilities in the country, while complying with all safety requirements. Organization of the study: children of PSACEA employees and internally displaced persons aged 5−12, who who wished to attend the educational and health-improving courses (60 people), were divided into 3 age groups: 5−6 years (15 people), 7−9 years (20 people) and 10−12 years old (25 people). In each subgroup, educational and health-improving classes were held from 9:00 a.m. to 4:00 p.m. from Monday to Friday for 2 calendar months (June − July 2023) under the guidance of experienced teachers (recruited from the staff of scientific and pedagogical staff of PSACEA and volunteers), taking into account age characteristics of children and included: creative, linguistic, general educational, cognitive, musical, dance, psychological, communicative and sports components. Conclusions: 1. The most effective means of reducing stress and improving the psycho-emotional state in the war’s conditions, the age characteristics of children, the staff of scientific and pedagogical workers and the possibilities of the material and technical base of PSACEA were the basis of the development of the program for educational and health-improving activities for children aged 5−12 years. 2. According to the results of the student survey (conducted using the Microsoft Forms application at the end of the courses), the satisfaction of the respondents with the program of educational and health-improving classes and the quality of the educational process is ascertained. Children's willingness to continue classes in separate sections and groups is recorded 3. The conducted research confirmed the effectiveness of educational and health-improving classes organized on the basis of a technical profile higher education institution under martial law and aimed at improving the physical and psycho-emotional state of children aged 5−12, and also contributed to the creation of children's sections and circles on the basis of PSACEA, which continued their work after completing the courses, while complying with all safety requirements.