bluuebunny/crossref_metadata_2025 huggingface dataset:
A Health Status Monitoring and Water Intake Tracking System based on Smart Cup using Artificial Intelligence and Internet of Things
Authors: Hsu Chloe , Sahagun Jonathan
Published: November 2024

Dehydration is a common and serious condition that affects millions of people globally, despite increasing access to clean drinking water. Staying hydrated is one of the most important habits for maintaining overall health and energy levels but sadly, due to higher levels of business among people. It is often overlooked. This causes health issues like fatigueness, headaces and etc [1].Dehydration is linked to various health issues, including heat-related illnesses, kidney diseases, and even death. Studies show that 75% of Americans are chronically dehydrated, with elderly populations being at higher risk. Addressing this, our project proposes a solution to ensure optimal hydration: a smart water bottle, Smartflask, integrated with sensors and an application to monitor and encourage regular water consumption. The Smartflask app allows users to set daily hydration goals, and through its combination of a distance sensor placed at the bottle’s cap and real-time notifications, it tracks the user’s water intake and sends reminders when needed. This smart system ensures that users meet their hydration targets consistently. Several challenges were addressed during the development, including selecting a suitable microcontroller (Particle Boron), ensuring sensor accuracy, and designing a user-friendly interface. The results of our experiments show that the ToF distance sensor is accurate in measuring water levels and that the smart water bottle's performance can be enhanced by optimizing power consumption and sensor integration. This project showcases the potential of smart technology to significantly improve hydration habits and overall health.
A Personalized Mental Health Support System using AI-Driven Facial Expression Classification and Real-Time Image Generation
Authors: Zhang Zeyu , Sun Yu
Published: November 2024

This research paper presents the development and evaluation of a personalized mental health support application that leverages AI-driven features for real-time user interaction [1]. The application includes components for facial expression classification and real-time image generation, both of which were subjected to rigorous testing through targeted experiments [2]. The first experiment evaluated the accuracy of the emotion recognition system, revealing strong performance with distinct emotions but highlighting challenges with subtle expressions. The second experiment tested the responsiveness of the image generation component, showing effective performance with simple inputs but identifying delays with more complex tasks. While the application demonstrates significant potential, especially in its ability to provide tailored emotional feedback and support, further refinement is needed to enhance accuracy, performance, and data security. The findings suggest that with continued development, this application could become a valuable tool in the field of mental health and emotional well-being.
An Intelligent Mobile Application for Career Development and Skill Enhancement using AI Technology
Authors: Liu Yelena , Cao Yu
Published: November 2024

This research paper presents an intelligent mobile application designed to assist job seekers with career development using AI technology [7]. In today’s competitive job market, finding employment can be challenging and stressful, leading to demotivation. Our app aims to address these challenges by offering real-time career guidance, skill assessments, and personalized recommendations through an AI-powered chat system [8]. The app integrates key technologies such as ChatGPT and Firebase to provide tailored support for users. Experiments conducted showed a significant improvement in users' confidence and skill levels, confirming the app's effectiveness in providing career guidance. Despite some limitations, such as the need for more accurate AI responses and expanded datasets, the app demonstrates substantial potential in assisting job seekers with their career paths. The results highlight the app's ability to offer a comprehensive, user-friendly solution to job search and career development.
An Immersive Disease Treatment and Cognitive Recovery System for Alzheimer's Patients using Artificial Intelligence and Virtual Reality
Authors: Zhong Xilei , Silverberg Samuel
Published: November 2024

The problem I’m trying to solve is the trouble with Alzheimer’s patients in recalling memories. This program will be used as a memory aid to help users with remembering past events through past memory image display. The key technologies I used are Unity, ChatGPT, and DALLE. The application is shown in Unity in Virtual Reality, it sends the memory prompts the user typed in Unity to ChatGPT, then DALLE will generate a memory image that is then displayed in Unity [1]. The three important systems are the ChatGPT prompt, the DALLE generator, and the Unity client. The ChatGPT prompt uses prompt engineering concepts to generate a visual description of what to make, which is then fed into DALLE, which attempts to create an artistic interpretation of the user’s memory [2]. This is in turn fed back to the Unity client on the VR headset for display in an art gallery. Several design considerations and challenges were encountered and resolved along the way. The principal challenge was considerations for user experience. In the end we found that since this is a service used by caretakers and patients alike it was essential to make the program as simple to use as possible, which required some simplification of the UI and strengthening of the backend systems [3]. The experiment results indicate that this design decision was positive.
A Content-Based Automatic Filter Recommendationsystem for Photography and Image Editing using Artificial Intelligence
Authors: Luo Yifan , Sun Yu
Published: November 2024

This paper presents the development and evaluation of PhotoGleam, a mobile application designed to enhance image quality through AI-generated filters.The app addresses the common issue of aesthetically unappealing colors in mobile phone photography by leveraging advanced AI models to create custom filters tailored to each image. The paper details the implementation of the AI-driven image processing engine, the backend Flask server, and the Flutter frontend user interface. Through two key experiments, the effectiveness of AI-generated filters was assessed in terms of both image quality and user engagement. Results showed that users consistently preferred AI-generated filters over standard ones, and the introduction of these filters led to increased time spent on the app and more images edited. While there are areas for improvement, such as server scalability and AI model reliance, PhotoGleam demonstrates significant potential as a valuable tool for enhancing mobile photography.
Sentiment Classification of Tweets using Machine Learning and NLP Techniques
Authors: Vladić Ervin , Mehanović Benjamin , Novalić Mirza , Kečo Dino , Mehanović Dželila
Published: November 2024

In the last ten years, social networks have appeared as main opinion-sharing and discussionenabling resources. At the same time, the development of machine learning (ML) and natural language processing (NLP) technologies has allowed for new approaches to analyzing the huge quantities of data created by users. This research uses data loading, class imbalance handling, text preprocessing and tokenization, sentiment analysis, and model assessment techniques to analyze the sentiment of the tweets. Using metrics like accuracy, precision, recall, and F1 score the study reveals that SVM and Logistic Regression are the most suitable machine-learning models for this purpose. SVM attained an accuracy of 90% for training and 77% for testing while Logistic Regression showed 83% for training and 78% for testing.
Model based Testing Approach for Tourism Applications : Use Case Scenarios for Booking Accommodations
Authors: Giritli Efe Batur , Can Yekta Said , Sen Alper , Alagöz Fatih
Published: November 2024

In the rapidly evolving landscape of the global tourism industry, efficient and reliable online accommodation booking systems are paramount. The primary objective of this paper is to explore the application of Model-Based Testing (MBT) in enhancing the efficiency and reliability of online accommodation booking systems within the global tourism industry. Our research developed and implemented a model-based testing framework that utilizes the GraphWalker tool to create detailed behavior models of tourism applications, specifically focusing on the booking accommodation process. Through the integration of GraphWalker with Selenium WebDriver, we successfully automated the testing process, ensuring comprehensive coverage of user scenarios from login to payment completion. Our results demonstrate the effectiveness of the MBT approach in identifying system vulnerabilities, improving test coverage, and providing a seamless testing experience, thereby contributing to the development of robust and user-friendly online booking platforms.
Leveraging Security Observability to Strengthen Security of Digital Ecosystem Architecture
Authors: Ramachandran Renjith
Published: November 2024

In the current fast-paced digital environment, enterprises are striving to offer a seamless and integrated customer experience across multiple touchpoints. This improved experience often leads to higher conversion rates and increased customer loyalty. To deliver such an experience, enterprises must think beyond the traditional boundaries of their architecture. The architecture of the digital ecosystem is expanding and becoming more complex, achieved either by developing advanced features in-house or by integrating with third-party solutions, thus extending the boundaries of the enterprise architecture. This complexity poses significant challenges for both observability and security in a digital ecosystem, both of which are essential for maintaining robust and resilient systems. Observability entails monitoring and understanding the internal state of a system through logging, tracing, and metrics collection, allowing organizations to diagnose performance issues and detect anomalies in real time. Meanwhile, security is focused on protecting sensitive data and ensuring service integrity by defending against threats and vulnerabilities. The data collected through these observability practices can be analyzed to identify patterns and detect potential security threats or data leaks. This paper examines the interconnections between observability and security within digital ecosystem architectures, emphasizing how improved observability can strengthen security measures. It discusses the additional data that observability practices can capture across different application layers and how this data can be leveraged to enhance overall system security. The paper also discusses studies conducted in the AI/ML field aimed at enhancing security through the use of observability. These studies explore how advanced machine learning techniques can be applied to observability data to improve security measures and detect anomalies more effectively.
A Smart Teenager Stress Analysis and Mental Health Monitor System based on Positive Psychology using Artificial Intelligence and Natural Language Processing
Authors: Tao Lishuo , Silverberg Samuel
Published: November 2024

This paper explores the development and evaluation of a mental health tracking app designed to monitor mood patterns and provide personalized support [1]. The app integrates AI technology to offer real-time guidance and recommendations based on user inputs, while a calendar feature visualizes mood trends over time [2]. We conducted two experiments to assess the accuracy of the AI responses and the effectiveness of the calendar in capturing mood patterns, finding both to be effective, although improvements in empathy and user engagement are needed. By comparing our approach with other mental health apps, we demonstrate the app's unique strengths in offering a tailored, interactive experience. Limitations such as reliance on user participation and AI empathy were identified, but proposed enhancements suggest potential for improved functionality. Our app presents a promising tool for mental health management, blending technology and selfreflection to foster better emotional well-being [3].
A Data-Driven Business Decision Making Education and Growth Simulation Platform using Artificial Intelligence and 3D Modeling
Authors: Gu Jiadong , Andaya Moddwyn
Published: November 2024

My research focuses on a gamified approach to teaching financial education, targeting students aged 10-18 [1]. I outline a method involving a simulated retail environment where players manage a retail store, enabling them to understand economic concepts through interactive gameplay. In my method analysis, I discuss three key algorithms: ordering items, tracking sales, and evaluating business performance. Each algorithm incorporates realtime data and complex calculations to simulate realistic retail operations, such as inventory management and sales probabilities based on customer foot traffic, location premium, and time of day. I aim to assess student preferences for this gamified learning model compared to traditional platforms like textbooks or Khan Academy, using a system of surveys to gather demographic information and feedback that provided excellent and satisfactory results [2]. The issue of financial literacy is urgent, highlighting statistics that reveal a significant knowledge gap in our youth.
Developing an Inclusive Tennis Simulation Game: Enhancing Physical Engagement and Social Skills for Children with Autism through Adaptive AI and Realistic Gameplay Experiences
Authors: Liu Juran , Andaya Moddwyn
Published: November 2024

During the long-term process of doing this tennis project, I had created and added many different features into the game, including different types of game modes, competitive tournament map, and music and sounds. One of the most significant features is the AI opponent with three different levels of difficulties for all the three game modes [1]. I designed these three game modes because of the challenges that I faced when I was trying to teach and communicate with children with autism, and that I think it might be a good idea for them to enjoy and relax themselves [2]. My idea of this project appeared in my mind after I was done with my volunteering event, I really wanted to help them out because of the situations that they are having in their lives. From the experiment that I did, I did find some inaccuracy of the swings in the game because sometimes when I swing my arm in front of the camera, the pose estimation didn’t really capture it. However, the data that I collected in this experiment tells me that I just need a little improvement on the calculations of the motion capturing system. People should start to try playing my game, especially the kids with autism, because the game could be played through a projector which allows the kids to experience the realism of the game of tennis and it builds up important social skills for them and provides a bunch of benefits to their lives [3]. This project is a game that could slowly help them to build up a better understanding for them about the game of tennis, which could bring benefits to their physical health while having fun playing the tennis mini games.
Detecting Kidney Stones Using Urine Test Analysis: A Machine Learning Perspective
Authors: Osei Isaac , Baafi-Adomako Acheampong , Opoku Boadu Dennis
Published: November 2024

Kidney stones, a prevalent urological condition, can cause severe discomfort and serious health complications if untreated. Traditional diagnostic methods, such as CT scans and ultrasounds, while effective, are often costly, expose patients to radiation, and may not be accessible in low-resource settings. This study explores a machine learning-based alternative that uses urine test data for kidney stone detection, aiming to provide a non-invasive, cost-effective, and accessible diagnostic tool. The study evaluates various machine learning models, including Random Forest (RF), Support Vector Machine (SVM), Logistic Regression, Decision Trees, and Gradient Boosting, to predict kidney stones using urine analysis data. Key urine parameters analyzed include specific gravity, pH, osmolality, conductivity, urea, and calcium concentrations. With a dataset of 79 samples, each labeled for kidney stone presence, preprocessing steps ensured data quality through normalization and exploratory analysis. Models were trained on 80% of the data and tested on the remaining 20%, with performance measured through accuracy, precision, recall, F1 score, and AUC-ROC metrics. The Random Forest model achieved the highest performance, with an accuracy of 94%, precision of 0.95, recall of 0.94, F1 score of 0.94, and AUC-ROC of 0.94, while Gradient Boosting achieved a slightly higher AUC-ROC at 0.96. Feature analysis identified osmolality and urea as the most significant predictors, followed by specific gravity and calcium concentration. These findings align with clinical knowledge on kidney stone formation. The high accuracy and reliability of the Random Forest model underscore its potential as a diagnostic tool for kidney stones. However, limitations include the need for larger datasets to improve generalizability and model transparency for clinical trust. Addressing these factors and facilitating integration into clinical workflows could enhance early detection, improve patient outcomes, and offer a promising alternative to traditional methods.
Perspectiva histórica y actual de la justicia indígena del pueblo Palta
Authors: Jimbo-Saez Isabel de Fátima , Maldonado-Ruiz Luis Mauricio
Published: November 2024

Este estudio de revisión bibliográfica tiene como objetivo realizar el análisis histórico de la aplicación de la justicia indígena del pueblo Palta. Con este propósito, se establece un breve análisis sobre la autodeterminación, el derecho indígena, la jurisdicción y cómo las comunas han desarrollado sus derechos basándose en sus costumbres y tradiciones. El estudio se sustenta en el método hermenéutico y en la técnica de análisis documental. Entre los principales hallazgos se identifican las funciones jurisdiccionales de las autoridades Palta, en base del derecho consuetudinario y derechos colectivos; en este sentido, se abordan el reconocimiento a los pueblos y nacionalidades indígenas en Ecuador, con respecto al derecho de la creación de organizaciones indígenas.
Enseñar matemáticas a estudiantes de segundo año de Educación General Básica con discapacidad intelectual moderada
Authors: Cobeña-Zambrano Maritza Rosaflor , Mayorga-Arreaga Brilleth María , Naranjo-Vaca Gregory Edison
Published: November 2024

La investigación se desarrolló en la Unidad Educativa Fiscal Especializada María Manuela Dominga de Espejo y Aldaz del Cantón Samborondón con niños de segundo año de EGB, con el objetivo de elaborar un sistema de recursos didácticos para el aprendizaje de la numeración por estudiantes con discapacidad intelectual moderada, a partir de la constatación en la práctica pedagógica de los autores, de insuficiencias en el aprendizaje de la numeración por estos estudiantes. En su desarrollo se utilizaron métodos teóricos (análisis y síntesis, inducción-deducción, modelación y enfoque de sistema), empíricos (observación, entrevista y prueba pedagógica) y matemáticos (estadística descriptiva), como resultado se elaboró un sistema de recursos didácticos. La valoración de la factibilidad y eficacia del sistema de recursos didácticos se realizó a través del taller con especialistas y el estudio de caso. Los resultados obtenidos corroboraron la eficacia del sistema de recursos didácticos elaborados para el aprendizaje de la numeración de niños con discapacidad intelectual. Por su parte los docentes participantes en el taller de socialización consideraron que el sistema de recursos didácticos es factible de aplicar, se corresponde con los propósitos del currículo y responde a las necesidades de aprendizaje de los niños con discapacidad intelectual
Eutanasia y buen vivir: un enfoque desde la filosofía del derecho y la bioética
Authors: Mejillones-Rodríguez César Antonio , Banda-Corrales Jhon Paúl , Morales-Castro Samuel
Published: November 2024

Este artículo lleva a cabo un análisis conceptual de la eutanasia en el marco del concepto de "buen vivir", con un elemento importante que ayuda a respetar la dignidad humana, colocándose de esta manera en la defensa de la plenitud de la vida. Se considera la eutanasia una proyección del derecho a la dignidad, permitiendo la propia autonomía sobre su cuerpo y la decisión de la terminación de la vida. Es compatible con el concepto de "buen vivir" contribuyendo en el mantenimiento de la dignidad humana y la justicia social. La constitución de la República del Ecuador de 2008 consagra el concepto de "buen vivir" como herramienta para la construcción política y un basamento ideológico que configura el carácter social del estado ecuatoriano. Así, esta investigación pretende mostrar la necesidad de una base en la que efectivamente pueda sustentarse el derecho a la "muerte digna", siendo dicha base la que debiera poder operar bajo las ideas de la dignidad humana fundamento del "buen vivir". Las alusiones a las consideraciones éticas y sociales de las desigualdades internacionales, o la muy urgente necesidad de crear una norma que respete y garantice la dignidad humana al enfrentarse al sufrimiento en el final de la vida, son las miradas de este artículo.
Digitalizované slamníky a generační citlivost
Authors: Faja Filip , Hanáčková Andrea
Published: November 2024

Responsive technology and digital learning influence how Generation Alpha (born after 2010) communicates and interacts with media (parfitt 2019, joones 2018, li 2021). This study analyses Czech radio plays for children and adolescents, focusing on narrative strategies and motifs. Using the theory of fictional worlds (doležel 2003) and the audionarratology (mildorf 2016, huwiler 2014), the authors examine thirteen radio titles from 2020 to 2022. They explore how current technologies and implicit communication models are reflected in categories such as narrator, spacetime, and narrative techniques in contemporary audio production.
Visual Aesthetics Semiotics Roland Barthes Photography Journalistic Works Phenomenal World
Authors: Prasetyo Martinus Eko , Imamul Masyhudi
Published: November 2024

Documentary photography as a medium of conveying information and documentation can document reality and tell important stories with integrity and honesty. Where journalistic photography will continue to be a powerful tool in reporting the truth and influencing social change, giving us a window into a wider and more diverse world. This research visually analyzes the phenomenal works of world photography from the aesthetic side with Roland Barthes' semiotic approach. It tells that aesthetically the photograph is an embodiment of visual beauty immortalized by the photographer not only by chance in capturing a moment that once existed. This research is conducted qualitatively descriptively according to Bogdan and Guba and proves that the science of photography does not only rely on luck but needs to understand how to photograph, the concept of visual framing in one frame that can be accepted by the general public as a conveyance of messages, information, and impressions from a photograph itself based on photographic theories.
EFEKTIFITAS KOMPLEKSITAS LOGO TERHADAP KESUKSESSAN BRAND AWARENESS PERUSAHAAN
Authors: Kurniadi Terry , Harnoko Irwan
Published: November 2024

Dalam landscape retail yang sangat kompetitif,
membangun identitas brand yang khas merupakan salah
satu hal yang sangat penting untuk pertumbuhan dan
kesuksesan sebuah brand. Salah satu elemen penting dari identitas mereka adalah brand logo, berfungsi sebagai representasi visual dari brand tersebut. Studi ini mempertanyakan: Apakah desain logo benar benar membuat pengaruh signifikan terhadap awareness sebuah brand?
Melalui pemeriksaan terhadap literatur yang ada, teori psikologi konsumen, artikel jurnal ini menyelidiki hubungan antara desain logo dan populeritas sebuah perusahaan. Dengan memfocuskan pandangan antara branding visual dan media following, penelitian ini bertujuan untuk memberikan wawasan berharga bagi pemasar, desainer, dan pemilik toko yang ingin memanfaatkan desain logo sebagai alat strategis untuk mendorong pertumbuhan dalam lingkungan retail yang dinamis saat ini.
ANALISIS KONTEN INSTAGRAM @FYI.KOREA SEBAGAI SUMBER INFORMASI INDUSTRI HIBURAN KOREA SELATAN
Authors: Kusariani Adinda Saraswati  , Hutasuhut Arif Maulana , Irwansyah
Published: November 2024

Budaya populer Korea yang biasanya disebut dengan Korean Pop atau KPOP telah menjadi industri yang berkembang sangat pesat. Oleh karena itu berbagai jenis media dan portal berita seputar KPOP juga sangat diminati masyarakat saat ini. Akun Instagram @Fyi.Korea merupakan salah satu portal berita KPOP dengan jumlah pengikut paling besar di Indonesia. Penelitian ini bertujuan untuk mencari tahu motif pengikut akun media sosial Instagram @Fyi.Korea sebagai sumber informasi hiburan Korea Selatan. Metode yang digunakan dalam penelitian ini adalah pendekatan kualitatif deskriptif. Peneliti menggunakan kajian literatur serta analisis isi untuk mendapatkan data yang diperlukan. Hasil penelitian ini menemukan bahwa akun Fyi.Korea mengunggah sebanyak 182 unggahan selama bulan April 2024 dan berita yang paling banyak dibaca dan paling interaktif adalah seputar kegiatan para idol, comeback lagu atau album terbaru dari girl group atau boygroup, gosip artis atau aktor yang sedang aktif bermain drama, hingga rekomendasi drama dan film Korea Selatan yang baru rilis.
OPTIMASI RANDOM FOREST DENGAN TEKNIK PRUNING UNTUK PREDIKSI DATA NASABAH BMT AL-HIKMAH PERMATA
Authors: Faturrahman Kharis , Sucipto Adi , Sarwido Sarwido
Published: November 2024

Perkembangan teknologi informasi dan kecerdasan buatan telah membawa perubahan signifikan dalam industri mikro keuangan syariah. Baitul Maal wat Tamwil (BMT) menghadapi tantangan dalam mengelola dan menganalisis data nasabah yang semakin kompleks. Penelitian ini bertujuan untuk mengoptimalkan prediksi data nasabah di BMT Al-Hikmah Permata menggunakan algoritma Random Forest dengan teknik pemangkasan. Metode yang digunakan meliputi pengumpulan data nasabah dari tahun 2021 hingga 2024, pra-pemrosesan data, pemodelan menggunakan Random Forest dengan dan tanpa pemangkasan, serta evaluasi model. Hasil penelitian menunjukkan bahwa penerapan teknik pemangkasan meningkatkan kinerja model secara signifikan, dengan peningkatan akurasi sebesar 3,9%, presisi 5%, recall 3,9%, dan F1-score 4,5%. Kompleksitas model juga mengalami penurunan dengan penurunan jumlah node sebesar 81% dan kedalaman pohon 59%. Kesimpulannya, teknik pemangkasan terbukti efektif dalam meningkatkan akurasi prediksi dan efisiensi model Random Forest untuk menganalisis data nasabah BMT, yang dapat mendukung pengambilan keputusan yang lebih baik dalam layanan keuangan mikro syariah.
OPTIMISASI PARAMETER SUPPORT VECTOR MACHINE DENGAN PARTICLE SWARM OPTIMIZATION UNTUK PENINGKATAN KLASIFIKASI DIABETES
Authors: Maulana Muhammad Reza , Sucipto Adi , Mulyo Harminto Mulyo
Published: November 2024

Penelitian ini mengeksplorasi efektivitas penggunaan Particle Swarm Optimization (PSO) untuk mengoptimalkan parameter Support Vector Machine (SVM) dalam diagnosis diabetes. Menggunakan dataset "Data Penyakit Diabetes" dari Kaggle, studi ini membandingkan kinerja SVM dengan parameter default dan SVM yang dioptimasi PSO. Hasil menunjukkan peningkatan kecil namun konsisten dalam akurasi, presisi, recall, dan F1-score untuk model yang dioptimasi PSO. Analisis feature importance mengidentifikasi glucose dan BMI sebagai prediktor utama diabetes. Kurva pembelajaran menunjukkan kedua model mampu mengurangi overfitting seiring bertambahnya data pelatihan. Meskipun peningkatan kinerja relatif kecil, penelitian ini menggambarkan potensi teknik optimasi dalam meningkatkan model pembelajaran mesin untuk aplikasi medis.
SISTEM INFORMASI GEOGRAFIS PEMETAAN FASILITAS KESEHATAN BPJS DI KABUPATEN JEPARA DENGAN ALGORITMA DIJKSTRA BERBASIS WEB
Authors: Musyarraf Fajrul Fahry , Sarwido Sarwido , Kusumodestoni R. Hadapiningradja
Published: November 2024

Pemetaan fasilitas kesehatan BPJS di Kabupaten Jepara merupakan langkah penting untuk meningkatkan aksesibilitas kesehatan. Untuk mendukung upaya ini, dikembangkan sistem informasi geografis berbasis web yang dirancang untuk memetakan fasilitas kesehatan BPJS dan menentukan rute terpendek menggunakan algoritma Dijkstra. Aplikasi ini dibangun dengan framework PHP Laravel 9 dan memanfaatkan Leaflet untuk tampilan peta interaktif. Hasil penelitian menunjukkan bahwa sistem ini efektif dalam menyajikan informasi lengkap tentang fasilitas kesehatan BPJS yang ada di Kabupaten Jepara. Fitur utama dari aplikasi ini adalah kemampuannya dalam menghitung dan menampilkan rute terpendek dari lokasi pengguna ke fasilitas kesehatan yang dipilih dengan menggunakan algoritma Dijkstra. Dengan fitur ini, pengguna dapat dengan mudah menemukan jalur tercepat menuju fasilitas kesehatan, sehingga meningkatkan efisiensi dan aksesibilitas perawatan kesehatan di wilayah tersebut
PERBANDINGAN METODE OPTIMASI PENENTUAN SENTROID AWAL PADA ALGORITMA K-MEANS MENGGUNAKAN ELBOW PSO DAN SSE
Authors: Muhamad Rodi  , Hendrik  , Amir Bagja  , M Nurul Wathani  , Zaenul Amri
Published: November 2024

Peningkatan heterogenitas dan kompleksitas data yang terus bertambah besarnya menyulitkan pengolahan data besar secara manual. Dalam bidang data mining, algoritma K-Means sering digunakan untuk mengelompokkan data berdasarkan kedekatan atau kemiripan. Tetapi, algoritma K-Means menghadapi beberapa tantangan, terutama dalam menentukan jumlah cluster dan pemilihan sentroid awal yang dapat memengaruhi hasil pengelompokkan. Artikel ini membahas persoalan tersebut dan menyajikan tiga metode optimasi berupa Elbow, Particle Swarm Optimization (PSO), dan sum square of error (SSE) untuk meningkatkan hasil evaluasi algoritma K-Means. Berdasarkan evaluasi, kesimpulannya adalah bahwa metode elbow lebih cepat dalam iterasi waktu dibandingkan dengan metode PSO, walaupun keduanya menghasilkan nilai DBI yang sama. Waktu iterasi metode elbow hanya 0.0002 detik, SSE hanya 1.8401 detik, sementara metode PSO memerlukan waktu iterasi selama 771.2143 detik. Dengan demikian, metode elbow lebih efisien dalam hal waktu iterasi karena menggunakan SSE. Rekomendasi untuk penelitian berikutnya adalah menggunakan kumpulan data yang berbeda dan mempertimbangkan metode optimasi lainnya untuk melakukan perbandingan evaluasi secara lebih komprehensif.
IMPLEMENTASI UML PADA PERANCANGAN SISTEM INFORMASI PELATIHAN KERJA DI BALAI LATIHAN KERJA KOTA MOJOKERTO
Authors: Susanto Dimas Dwi
Published: November 2024

Studi ini meneliti bagaimana menggunakan Unified Modeling Language (UML) untuk membuat sistem informasi pelatihan kerja di Balai Latihan Kerja Kota Mojokerto. Sistem ini akan menggantikan proses manajemen pelatihan dan pendaftaran yang masih dilakukan secara manual. Diagram seperti use case, kelas, urutan, dan aktivitas digunakan dalam UML untuk memodelkan struktur dan alur sistem dalam perancangan. Model waterfall juga digunakan dalam pengembangan perangkat lunak dan mencakup langkah-langkah perencanaan, analisis kebutuhan, desain, implementasi, pengujian, dan pemeliharaan. Implementasi sistem menghasilkan aplikasi berbasis web yang memudahkan proses pendaftaran peser. Selain itu, diagram UML telah ditunjukkan sebagai alat yang berguna untuk memodelkan sistem yang terstruktur dan mudah dipahami oleh pengguna. Lebih dari 85% peserta yang diuji merasa terbantu dengan visualisasi diagram UML. Sistem informasi ini memudahkan pengelolaan data pelatihan dan membuat proses pelatihan lebih mudah bagi peserta dan pengelola. Untuk meningkatkan pengalaman pengguna, studi lebih mendalam tentang antarmuka pengguna (UI) dan penggunaan teknik pengembangan sistem selain waterfall adalah saran untuk penelitian selanjutnya.
PENGUKURAN TINGKAT KEMATANGAN IMPLEMENTASI SCRUM DALAM PENGEMBANGAN PERANGKAT LUNAK MENGGUNAKAN SCRUM MATURITY MODEL
Authors: Putri Larasati  , Gandhi Arfive , Selviandro Nungki
Published: November 2024

Dalam beberapa tahun terakhir, Scrum semakin populer dan kini menjadi salah satu pendekatan pengembangan proyek yang banyak digunakan oleh organisasi di seluruh dunia. Startup XYZ telah menerapkan Scrum dalam pengembangan proyeknya sejak tahun 2021. Namun, hingga saat ini, proses implementasi Scrum tersebut masih mengalami banyak kendala. Berdasarkan identifikasi melalui diagram tulang ikan, permasalahan tersebut berasal dari penerapan Scrum yang belum maksimal dalam pengembangan perangkat lunak di Startup XYZ. Tujuan penelitian ini adalah mengukur tingkat kematangan implementasi Scrum dalam pengembangan perangkat lunak di Startup XYZ menggunakan Scrum Maturity Model (SMM). SMM berfokus pada evaluasi dan memberikan arahan untuk pengembangan perangkat lunak yang menerapkan Scrum. Kemudian digunakan Key Process Area (KPA) Rating untuk mendefinisikan pencapaian di setiap area proses, yang diadaptasi dari Agile Maturity Model (AMM). Hasil pengukuran menunjukkan bahwa tingkat kematangan Scrum di Startup XYZ masih berada pada level 1 (Initial). Berdasarkan hasil pengukuran tersebut, diberikan rekomendasi perbaikan yang disusun berdasarkan jawaban kuesioner SMM dan mengacu pada Scrum Guide 2020, SBOK Guide v3, dan Essential Scrum, dengan fokus pada peningkatan level 2 dan level 3 sesuai ekspektasi dari pihak Startup XYZ.
OPTIMALISASI PENCARIAN APOTEK TERDEKAT DENGAN METODE LOCATION BASED SERVICE PADA APLIKASI PERANGKAT BERGERAK
Authors: Hanggraini Dea Astuti  , Zaky Umar
Published: November 2024

Dengan adanya perkembangan teknologi informasi pada masa sekarang merupakan suatu faktor yang penting untuk kemajuan jaman. Perkembangan teknologi dimasa sekarang meliputi dari banyak bidang khususnya di bidang farmasi. Dari bidang farmasi ini sendiri memiliki banyak dampak positif yang ditimbulkan dari kemajuan teknologi. Apotek merupakan salah satu bidang farmasi yang sangat dekat dengan masyarakat. Namun dengan banyaknya apotek di wilayah akan menimbulkan kebingunan untuk masyarakat dalam menentukan apotek mana yang terdekat dan yang menyediakan kebutuhan secara lengkap. Tujuan dari penelitian yang dilakukan yaitu memudahkan Masyarakat dalam pencarian apotek dan mempersingkat waktu pengguna. Aplikasi yang akan dibangun memanfaatkan location based service (LBS) untuk menentukan lokasi apotek  terdekat. Proses pengembangan yang digunakan oleh peneliti yaitu metode SDLC (System Development Life Cycle), yang mencakup analisis, desain, implementasi, pengujian, dan perbaikan. Fitur utama dari aplikasi ini yaitu pendaftaran, pencarian apotek, dan pemindaian resep. Hasil pengujian dengan metode blackbox dari aplikasi yang telah dibangun menunjukan bahwa aplikasi berjalan sesuai dengan yang diharapkan
PENGUJIAN DETEKSI OBJEK MANUSIA MENGGUNAKAN JETSON NANO DENGAN MODEL SSD MOBILENETV2
Authors: Aziz Muhammad Abdul , Rachman A Sjamsjiar , Suksmadana I Made Budi
Published: November 2024

Teknologi kecerdasan buatan berkembang pesat, salah satunya melalui platform NVIDIA Jetson Nano yang mampu mendeteksi objek menggunakan model SSD MobileNetV2. Namun, penggunaan platform ini masih jarang dan referensi terkait performanya dalam berbagai kondisi pencahayaan dan keramaian objek masih terbatas. Penelitian ini bertujuan untuk mengevaluasi performa Jetson Nano dalam mendeteksi objek, mengukur frame rate, serta menganalisis akurasi SSD MobileNetV2 pada kondisi terang, remang-remang, objek ramai, dan tidak ramai. Pengujian frame rate dilakukan secara real-time selama 15 detik, sedangkan akurasi diuji menggunakan confusion matrix dari 20 frame video. Hasil menunjukkan peningkatan performa Jetson Nano dengan peningkatan frame rate, terutama pada mode daya 10W dibandingkan 5W. Pengujian akurasi juga memberikan data presisi, recall, dan F1-Score pada berbagai kondisi, baik pada kondisi terang, remang remang, objek ramai dan objek tidak ramai.sehingga memberikan wawasan mengenai faktor-faktor yang memengaruhi performa Jetson Nano dan SSD MobileNetV2.
PERBANDINGAN EFEKTIVITAS PENGENDALIAN ROBOT DENGAN PENGGUNAAN PID DAN TANPA PID PADA APLIKASI JARAK TERTENTU
Authors: Habibi Aazamzain , Suksmadana I Made Budi , Darmawan Budi
Published: November 2024

Mobile robot adalah jenis robot yang menggunakan sistem penggerak berupa roda atau kaki untuk bergerak secara efisien. Robot ini sangat bermanfaat di berbagai industri, terutama dalam meningkatkan efisiensi operasional melalui pergerakan otonom. Tugas akhir ini bertujuan untuk mengkaji kinerja kontrol PID pada robot ber-encoder dan efektivitasnya dibandingkan dengan sistem tanpa PID. Dalam penelitian ini, dilakukan pengujian kinerja robot pada berbagai jarak, baik dengan maupun tanpa kontrol PID. Hasil pengujian menunjukkan bahwa tanpa PID, robot mengalami penyimpangan yang lebih besar dari target, terutama pada jarak yang lebih jauh, seperti 220 cm. Sebaliknya, dengan kontrol PID, robot mampu mencapai target dengan akurasi yang lebih tinggi dan penyimpangan yang lebih terkontrol. Penggunaan PID juga mengurangi variasi dalam waktu dan jarak tempuh, serta meningkatkan stabilitas sistem. Penelitian ini menunjukkan bahwa kontrol PID memainkan peran penting dalam meningkatkan kinerja dan presisi gerakan robot encoder.
The influence of nitrogen nutrition on the yield and accumulation of nitrates by domestic and foreign varieties of table beets in the conditions of the Leningrad region
Authors:   Agrophysical Research Institute, Volkova Elena ,   St. Petersburg State University of Industrial Technologies and Design, Higher School of Technology and Energy
Published: November 2024

The selection of varieties and the level of nitrogen nutrition are important technological elements that determine the yield and quality of table beets when grown on sod-podzolic soil. The article discusses the varietal response of table beet varieties to an increased level of nitrogen nutrition N180 and deficient N0. The varieties that accumulate the maximum and minimum amount of nitrates in different phases of growth and development, more effectively using soil nitrogen compounds or nitrogen fertilizers are identified. The varieties Golden Beet (9.12 kg/m2), Kholodostoykaya 12 (8.94 kg/m2) turned out to be more responsive than others to the application of an increased dose of nitrogen fertilizers, and the greatest increase in the yield of root crops to the background N0 was obtained in the varieties Kholodostoykaya 19, Tsilindra, Egyptian flat and PabloF1. Keywords: TABLE BEET, NITROGEN NUTRITION, VARIETIES, NITRATES, YIELD
Expo2020 Dubai and Tourism Marketing: An Online User-Generated Content Analysis
Authors: Baquero Asier
Published: November 2024

Dubai is currently one of the world’s leading cities in the tourism field. Expo2020 has placed it in a remarkable position in sustainable tourism development amongst other tourist destinations. Information communication technologies (ICTs) have become essential for connecting tourism destinations with their visitors and other market partners. X (Twitter) facilitates online communication; embracing it have proved to be critical for boosting the brand image and reputation of tourism spots and augmenting their competitive advantage in the market. User-generated content (UGC) and electronic word of mouth (eWOM) have become important key players in this field. The purpose of this research was to deepen the study of the Expo2020 event in relation to tourism within the framework of ICTs. To do so, 3811 tweets posted from April 2021 to March 2022 using the hashtags #expo2020 and #visitdubai were analyzed. Users generated more than 10 tweets daily on this topic. Dubai’s institutional accounts were highly involved in creating content, leading personal accounts to follow the eWOM and UGC. Destination marketing organization (DMO) related to the Indian segment account stood out as one of the main players in the analyzed sample.
Improving Performance in Physical Education Through Students’ Enrichment Activity Training (SEAT)
Authors: Buenaventura, Chris John.  , Sanson Jr, Antonio T.  , Garciano, Verlyn P.
Published: November 2024

This study aimed to determine the Physical Activity and Students Performance of grade 11 students in Physical Education Class of Baliwasan Senior High School during the school year 2022-2023. The study employed quasi-experimental research design using pre-test and post-test in physical education during the second semester period. The participants of this study were 50 Grade 11 students of GAS A and 50 GAS B students under the GAS strand. A purposive sampling technique was utilized in determining the sample of the study. The findings revealed that the performance of grade 11 students was satisfactory. The pretest for both the control and experimental group was poor. The posttest results of the control and experimental group were satisfactory. The mean gain score of the control and experimental group increased significantly. There was a significant difference in the mean gain score of the control and experimental group. There was a significant difference between the pretest and posttest results in physical education of the control and experimental group. It is highly recommended that the senior high school teachers may use the FITT intervention program and the application of CSPAP strategy approach in teaching physical education. They may also integrate the SEAT in physical education class where the students’ performance was unified in their performance task and the teacher recorded their response and outcome through rubrics.
Harnessing Machine Learning for Adaptive Signature-Based Network Intrusion Detection: A Simulation-Driven Approach
Authors: Peter Paul Issah  , Ransford Ganyo
Published: November 2024

Network security is essential for data sharing on the internet. Traditional methods such as firewalls cannot detect fragmented packets and are often outmaneuvered by increasingly sophisticated attackers, resulting in productivity losses, financial damage, and reputational harm. This study investigates the use of machine learning (ML) models in developing effective intrusion detection systems (IDS) using signature-based methods. The research leverages the UNSW-NB15 dataset and compares four ML algorithms: K-Nearest Neighbor (KNN), Random Forest (RF), Bayesian Network (Bayes Net), and Decision Tree (J48), with feature reduction applied using Principal Component Analysis (PCA) to improve efficiency. The models were built and evaluated using the WEKA platform, with 10-fold cross-validation applied to assess accuracy, precision, recall, and F-measure. Results show that J48 significantly outperforms the other algorithms in terms of overall accuracy, while Bayes Net produces the least accurate results. These findings underscore the efficacy of J48 and Random Forest in signature-based IDS for network security.
Preparation of Acid – Base Indicator Papers Using Calyces of Habiscuss Sabdariffa (Zobo)
Authors: Musa Dallatu E. , Atumeyi Anthony U. , Onugwu Ernest O. , Cecilia E Yusufu
Published: November 2024

This research focuses on developing and assessing the performance of greenish-blue and pink paper indicators made from Hibiscus sabdariffa (zobo) calyces. The calyces were collected, processed, and ground into powder, which was then used to produce anthocyanin-based extracts. These extracts were treated with acidic and alkaline solutions to create pink and greenish-blue indicators, respectively. Paper strips were immersed in these solutions to produce the colour-changing indicators. The effectiveness of the prepared indicators was tested against standard litmus papers (SLP) in both acidic and basic environments. The pink Hibiscus sabdariffa indicator demonstrated 98.24% efficiency compared to red SLP, while the greenish-blue indicator showed 97.36% efficiency compared to blue SLP. Statistical analysis revealed that the pink indicator did not significantly differ from red SLP at the 95% confidence level but showed agreement at higher confidence levels. The greenish-blue indicator was consistent with blue SLP across all levels of confidence. In conclusion, the study suggests that Hibiscus sabdariffa indicators provide high performance and could be a cost-effective alternative to imported litmus papers. With large-scale production, these indicators could reduce import dependency and even be exported, contributing to foreign exchange earnings.
Maximizing hydrogen production through photovoltaic generator by using improved incremental conductance algorithm with proportional integral PI controller
Authors: Abssane Sara , Abdelkader Outzourhit , Amatoul Fatima-Zahra
Published: November 2024

Effectively storing energy for prolonged periods poses a primary challenge for renewable and innovative energy sources. This research focuses on two key objectives: first, converting photovoltaic (PV) voltage to the necessary level for electrolysis through a buck  converter, and second, utilizing a maximum power point tracking (MPPT) method to optimize the solar generator's efficiency. The simulation of the solar-driven buck converter for the electrolysis load was carried out using MATLAB/Simulink, integrating an Incremental Conductance (INC) MPPT algorithm with a PI controller for system optimization. The simulation results reveal the stabilization of both the generated power from the PV system and the load voltage. Significantly, the proposed system achieves an efficiency surpassing 90% under high irradiance levels.
Assessing the combined effect of metacognitive skills and scientific attitudes as catalysts for gender-specific academic achievement in science
Authors: Yuorsuu Stephen Naagmine Manmah
Published: November 2024

The synergistic effects of metacognitive skills and scientific attitudes on academic achievement have not been fully established by the dozens of studies that span through the margins of archives on these variables. This warranted an investigation to understand the combined role of these variables on gender-specific academic achievement. Employing a survey design, the researcher gathered data from 344 participants through the utilization of the simple random sampling technique. This was accomplished using three distinct instruments: the Metacognitive Awareness Inventory (MAI), the Scientific Attitude Assessment (SAA), and the Science Achievement Test (SAT). The obtained data underwent careful analysis employing correlation, independent samples t-test, and linear regression techniques. The findings unveiled parity in academic performance between male and female students, indicating an equal display of intellectual prowess in science among both genders. This suggests the implementation of pedagogical approaches that are both gender-sensitive and gender-neutral in our classrooms. Such approaches aim to ensure that educational practices cater to the needs and strengths of all genders equally, fostering an environment where both male and female students can reap the benefits of education without discrimination.Top of Form Moreover, the analysis underscored that both metacognitive skills and scientific attitudes significantly predict academic performance in science. Additionally, a robust association was observed between the combined influence of metacognitive skills and scientific attitudes, and academic achievement in science. This underscores the necessity of presenting both variables as a cohesive unit to students to enhance their academic success.