bluuebunny/crossref_metadata_2025 huggingface dataset:
Streamlining the Recruitment Process: The Future of Automatic Job Application
Authors: Mulgund Saheel , Ahmed Quazi Uzair , Shaikh Mohamed Adil , Manna Surajit
Published: November 2024

The job application process, traditionally a time consuming and repetitive task, can be significantly streamlined through automation. This paper explores the feasibility and potential benefits of automating various stages of the job application process, including job searching, resume and cover letter generation, application form filling, and follow up communication. We delve into the technical aspects of automation, such as web scraping, natural language processing, and machine learning, and discuss their applications in the context of job search. Additionally, we examine the ethical implications of automated job applications, including potential biases and the impact on the human element of the recruitment process
Brain Cancer Detection Using Advanced Deep Learning Algorithm
Authors: P Maria Jesi
Published: November 2024

The disease needs to be treated cautiously because of the complexity of brain cancer. Since each patient’s brain tumor is unique in terms of dimension, shape, and localization, it is challenging to identify them in medical imaging. Magnetic Resonance Imaging (MRI) process is used to diagnose the brain tumor anatomy results in inaccurate detection of the tumor and it is very time consuming. Therefore, many classification techniques from Machine Learning (ML) and Deep Learning (DL) are utilized to rapidly recognize the tumor. This paper proposes segmenting and detecting the brain cancer using Deep Convolutional Neural Network (DCNN). An image is first pre processed using a median filter to minimize noise in the image. Global thresholding is a simple image segmentation technique that uses a single threshold value to separate an image into distinct regions. After that, the feature extraction method of Histogram of Oriented Gradients (HOG) is employed to detect brain tumors with higher accuracy and lower computational complexity than other methods. This performance measure is applicable to quantifying the performance of the segmented tumor region. Additionally, DCNN classification algorithm has achieved high performance and accuracy. For the purpose of identifying the performance of the model, this proposed project produced a confusion matrix. With a classification accuracy of 91.23% and a precision of 90.39%, the experiment’s results demonstrated that the method is more successful than the current methods.
(Classification of Blood Group) Classification of Diseases Based On Blood Test Using Machine Learning
Authors: S Sadhana , Uppar Radhika , Nilugal Pooja B , MV Sneha
Published: November 2024

This study focuses on the importance of blood analysis in diagnosing a variety of diseases, as it provides key parameters that signal specific blood disorders. Accurate disease prediction from blood data requires identifying distinct patterns linked to each one edition. Machine learning plays a critical role in building predictive models based on historical data, and the success of these models largely depend on the quality and reliability of the data used. This research introduces a new benchmark dataset comprising 668 records, meticulously gathered and verified by expert physicians from trusted sources. Several traditional machine learning algorithms were applied to this dataset, yielding promising predictive results.
Battery Management System in Microgrid using LabView
Authors: Y H Shreyanka , T R Sinchana , H M Vishwas , N Lavanya , K V Malini , K Ramya
Published: November 2024

Battery management systems (BMS) play a vital role in enhancing the efficiency and reliability of microgrids, especially with increasing reliance on renewable energy sources. This paper presents an innovative approach to battery management in microgrids using LabView software. The proposed system monitors, controls, and optimizes battery performances within a microgrid environment. Experimental results demonstrate Lab View’s capability in real time data acquisition, charge/discharge control, and fault detection. This approach offers an adaptable and cost effective solution for efficient microgrid operation and implementations can expand this model’s scalability and interoperability within larger energy networks.
Chronic Kidney Diseases Prediction Using K-Means Algorithm
Authors: G Chandana , J Haritha , J Janani , S Kalpana , DM Vijaya Lakshmi
Published: November 2024

This transformation allows the model to capture the relationships between different health indicators and their correlation with CKD risk. At the core of the predictive analysis lies a Random Forest Classifier, a powerful ensemble learning method known for its accuracy and robustness in classification tasks. The model is trained on a comprehensive dataset encompassing various health metrics associated with CKD. By analysing this data, the classifier predicts the likelihood of a user developing CKD based on their input, enabling early detection and timely intervention. In addition to predicting CKD risk, the application utilizes K means clustering to categorize users into distinct stages of CKD, based on their health data patterns. This clustering approach aids in providing a clearer understanding of an individual’s kidney health status, which is essential for appropriate treatment planning and management. Furthermore, to enhance user experience and support proactive healthcare decisions, the application employs the K Nearest Neighbors (KNN) algorithm to offer personalized recommendations for nearby hospitals. This web application is designed to predict chronic kidney disease (CKD) through an intuitive user interface that enables individuals to securely log in and input their health details. The application employs a robust data processing pipeline to ensure the reliability of the predictions. Initially, it utilizes interpolation techniques for data cleaning, addressing any missing values in the user input to enhance dataset integrity. This is crucial, as incomplete data can lead to inaccurate predictions and hinder effective analysis. To facilitate the handling of categorical variables, the application incorporates Label Encoder, which converts these categories into numerical values that machine learning algorithms can process effectively.
Brain Tumor Detection Using Image Processing
Authors: Princye P. Hosanna , Mehak Suzain
Published: November 2024

This proposed work presents an innovative artificial intelligence (AI) based algorithm for the accurate identification of brain tumors through medical imaging analysis. Brain tumors pose a significant health risk, and timely and precise diagnosis is crucial for effective treatment planning. Traditional diagnostic methods often require extensive manual analysis and are subject to human error. In this context, our proposed algorithm leverages the capabilities of deep learning and image processing to enhance the efficiency and accuracy of brain tumor identification. The algorithm utilizes a convolutional neural network (CNN) architecture trained on a diverse and extensive dataset of brain images, encompassing various tumor types, sizes, and locations. The CNN is designed to extract intricate features from medical imaging modalities such as magnetic resonance imaging (MRI) and computed tomography (CT) scans. Transfer learning techniques are employed to capitalize on pre trained models, allowing the algorithm to generalize effectively across different datasets and patient populations. To ensure clinical relevance and reliability, our algorithm incorporates a multi modal approach, combining information from various imaging sequences. The algorithm’s performance is validated through extensive experimentation on a large dataset of anonymized patient scans, demonstrating superior sensitivity and specificity compared to existing diagnostic methods. Furthermore, the algorithm’s interpretability is enhanced through the incorporation of attention mechanisms, providing insights into the regions influencing tumor identification. This proposed work contributes to the advancement of AI in healthcare by offering a robust and efficient solution for brain tumor identification. The proposed algorithm has the potential to significantly reduce the time required for diagnosis, enabling clinicians to make informed decisions promptly. As a result, patients can receive timely and tailored treatment plans, ultimately improving outcomes and prognosis for individuals affected by brain tumors. The performance of the algorithms are evaluated using MATLAB software.
Comparative Analysis of Two-Wheeler Engine Cylinder Fins for Enhanced Performance
Authors: V Pandiyarajan , Samad Abdul
Published: November 2024

The engine cylinder is a critical component in automobiles, subjected to high thermal stresses. Cylinder fins are designed to dissipate heat effectively, ensuring engine efficiency and preventing damage. This report analyzes the thermal properties of cylinder fins using ANSYS Workbench, focusing on varying fin geometry, material, and thickness. The aim is to enhance the heat dissipation rate by optimizing the fin design. Simulations reveal that modified fin designs improve heat transfer and reduce thermal stress, leading to better engine performance.
Machine Learning for Climate Data Analysis
Authors: V Bhagyalakshmi , P V Nandha Kumar , S Harinivas , M Hari Rudhran , S Harish Raj , S Prem Kumar
Published: November 2024

An urgent worldwide concern that calls for creative methods of research and solution is climate change. A useful tool for analyzing complicated climate data, machine learning (ML) offers insights into climate trends, enhanced predictions, and anomaly detection. This study examines many machine learning (ML) approaches, including supervised learning, unsupervised learning, and deep learning, in relation to climate data, outlining the main drawbacks, advantages, and potential ramifications. We hope to increase forecasting accuracy, detect extreme weather occurrences, and assist policymakers in developing climate mitigation policies by integrating machine learning (ML) into climate science.
A Mental Health Tracker
Authors: N Karnika , G Logesh , S Kiruthik Dhaya , K Mohana Priya , V A Poojashri , DM Vijayalakshmi
Published: November 2024

The project focuses on building a mental health tracker. You will try to get an idea of the mental state of your user (in the least intrusive ways), find out if they are suffering and then suggest measures they can take to get out of their present condition. A user answers some questions and based on the answers that they provide, you will suggest tasks to them and maintain a record of their mental state for displaying on a dashboard. Mental disorders are widespread in countries all over the world. Nevertheless, there is a global shortage in human resources delivering mental health services. Leaving people with mental disorders untreated may increase suicide attempts and mortality. To address this matter of limited resources, conversational agents have gained momentum in the last years. In this work, we introduce a mobile application with integrated Chabot that implements methods from cognitive behavior therapy (CBT) to support mentally ill people in regulating emotions and dealing with thoughts and feelings. Application asks the user on a daily basis on events that occurred and on emotions. It determines automatically the basic emotion of a user from the natural language input using natural language processing and a lexicon based approach. Depending on the emotion, an appropriate measurement such as activities or mindfulness exercises is suggested by application.
Studies on Chemical Properties of Carbon Dots Synthesized by Green Technique
Authors: C S Preethi , M Girish , D S Nandakumar , K Kanivalan
Published: November 2024

In this study, the carbon quantum dots (CQDs) are prepared by using 2 natural precursors namely Carica Papaya and Lemon by one step Micro wave assisted method. The sample emits green light due to its charming fluorescence property when it is kept under UV illuminator. The energy gap and the Refractive Index of the synthesized sample is obtained by UV Vis spectroscopy. The nature of the CQDs is confirmed by the X-RAY DIFFRACTION (XRD) Spectroscopy. The surface chemistry analysis is done by Raman and Fourier transform infrared spectroscopy (FT-IR).
Smart Lock for Parking Violation: Using loT
Authors: M Mala , Fazil Fatima , V Gamya Shree , R Yashwanth , BP Tejas
Published: November 2024

Parking violations in urban areas, particularly in densely populated and rapidly developing countries like India, exacerbate traffic congestion, obstruct emergency routes, and result in frequent vehicle seizures. Traditional towing methods frequently lack timely notification for vehicle owners, pose a risk of vehicle damage, and impose a time consuming database management burden on authorities. This paper introduces a Smart Lock system for Parking Violations, utilizing Internet of Things (IoT) technology to provide an efficient and responsive solution for managing illegal parking. The system employs IoT enabled smart locks that activate automatically when a vehicle is parked in a restricted area, temporarily immobilizing it and alerting the owner through a mobile app. The owner receives real time updates and instructions to address the violation, avoiding costly and potentially harmful towing actions. Through GPS based monitoring and integration with local traffic management databases, the smart lock system facilitates coordinated enforcement and optimizes the violation management process. Our implementation and analysis demonstrate the solution’s potential to reduce congestion, enhance enforcement efficiency, and improve urban mobility, all while providing a user friendly experience for vehicle owners.
Predictive Maintenance of Industrial equipment using Temporal Graph Neural Networks: A step towards Novelty
Authors: Ramya Velvizhi , N Navyashree , P Nandana
Published: November 2024

Predictive maintenance is important for improving industrial activities and achieving minimum downtime. The most common methods focuses on temporal features that are static and extracted from a set of sensors which may not account for the dynamic of time evolution in the degradation of the equipment .In this paper , we develop a Temporal Graph Neural Networks (TGNN) model to address the limitations. Since sensor data comprises of temporal data which can be structured as graph with time points as nodes and relationships between time points as edges, TGNN can learn advanced timing configurations to enhance accuracy of the model’s forecast. The method has been tested on dataset, which has a real industrial applications and conducted a comparison of its result with the traditional system. Our findings confirm that TGNN are effective than other baseline methods and thus, generalising the type of tasks for predictive maintenance.
Home Automation and Monitoring System using Internet of Things
Authors: P Narmatha , A Bhagyashree , N Chaya Devi , T S Aditya , S Giriraj , R Lakshmi Ganesh
Published: November 2024

The integration of Internet of Things (IoT) devices in smart homes has revolutionized the way we interact with our living spaces. In this paper, we present a comprehensive smart home innovation aimed at enhancing safety and comfort. Our system includes several IoT devices controlled through a mobile application for seamless user interaction. A mobile controlled LED bulb, integrated with the Blynk app, provides users with remote lighting control. Live data from an MQ 5 gas sensor is monitored through the mobile application, triggering the activation of a fan in case of gas leakage, ensuring safety within the home environment. An infrared (IR) sensor detects human presence, enabling an automatic pump system for convenient water usage. Additionally, another IR sensor is employed to detect human presence and illuminate mini lights for safer navigation, particularly on staircases. The system is built using Node MCU, providing a cost effective and efficient solution for smart home automation. Through the integration of these IoT devices, our smart home innovation aims to provide users with a safer, more comfortable, and energy efficient living environment. This paper presents the design, implementation, and performance evaluation of our smart home system, demonstrating its effectiveness in enhancing the quality of life for homeowners.
Proof of Stake Beyond Wealth: A Novel Blockchain Consensus Algorithm
Authors: C Vinola , M Naveen Rajan , M Guruprasath , V Mounasri
Published: November 2024

This research paper addresses the limitations of the Proof of Stake (PoS) consensus mechanism in blockchain technology. Consensus is the foundational element of blockchain, and two of the most widely discussed mechanisms are Proof of Work (PoW) and PoS. While PoS offers advantages over PoW, it also presents significant challenges, notably wealth concentration. This paper investigates these limitations in depth and proposes a novel framework aimed at mitigating these issues. By exploring the dynamics of stake distribution and validator incentives, this study seeks to enhance the security and fairness of PoS systems.
Pelatihan Penggunaan Aplikasi Mendeley Untuk Penulisan Skripsi Bagi Mahasiswa Semester Akhir Jurusan PTA Universitas Negeri Makassar
Authors: Samad PI. S. Samad , Wahrini Retyana , Mantasia Mantasia , Mustamin Mustamin , C. Arnanto Ganggang
Published: November 2024

Kemampuan mengelola referensi secara efektif merupakan salah satu aspek penting dalam penulisan skripsi mahasiswa. Namun, banyak mahasiswa masih menghadapi kendala dalam manajemen referensi, terutama dalam menyusun kutipan yang konsisten dan daftar pustaka yang sesuai format. Program pengabdian masyarakat ini bertujuan untuk memberikan pelatihan penggunaan aplikasi Mendeley bagi mahasiswa semester akhir Jurusan PTA Universitas Negeri Makassar guna membantu mereka mengelola referensi secara efisien. Metode pelatihan mencakup sosialisasi awal, pengenalan fitur dasar Mendeley, latihan praktis, serta pendampingan integrasi referensi ke dalam dokumen skripsi. Hasil dari pelatihan ini menunjukkan peningkatan signifikan dalam keterampilan mahasiswa dalam manajemen referensi, termasuk kemudahan dalam penyusunan daftar pustaka otomatis. Dampak positif dari program ini diharapkan dapat mendukung mahasiswa dalam menyusun skripsi dengan kualitas yang lebih baik dan mengurangi kesalahan kutipan. Rekomendasi untuk keberlanjutan program ini adalah penyelenggaraan pelatihan serupa secara berkala untuk meningkatkan keterampilan manajemen referensi mahasiswa.
KLASIFIKASI PENYAKIT ANEMIA BERBASIS CITRA PALPEBRAL KONJUNGTIVA DENGAN ALGORITMA TRANSFER LEARNING
Authors: Amalia Elva , Lamada Mustari , Baso Kaswar Andi , Darma Andayani Dyah
Published: November 2024

Anemia merupakan masalah kesehatan yang ditandai dengan kekurangan kadar hemoglobin. Kemungkinan terburuk dari penyakit anemia adalah kematian. Anemia sangat sering disepelekan masyarakat sehingga menjadi permasalahan dunia. Wanita lebih rentang mengalami penyakit anemia. Berdasarkan prevalensi Dinas Kesehatan Republik Indonesia, sebagaian besar wanita pada usia produktif dan wanita hamil mengalami anemia. Diagnosis anemia dapat dilakukan dengan mengambil sampel darah kemudian dilakukan uji laboratorium, atau sering disebut dengan pemeriksaan invasive. Seiring berjalannya waktu, berbagai metode non-invasive yang lebih praktis dikembangkan untuk mendeteksi penyakit anemia sebagai alternatif seperti pemeriksaan yang dilakukan dengan melihat tingkat kepucatan konjungtiva pada mata. Sehingga peneliti melakukan pengembangan dalam klasfikasi penyakit anemia secara non-invasive dengan menerapkan algoritma Transfer Learning AlexNet berbasis citra palpebral konjungtiva. Sebelum dataset palpebral konjungtiva melalui tahap training dilakukan augmentasi citra yang bertujuan untuk menghindari terjadinya overfitting atau underfitting akibat kekurangan data latih. Transfer learning yang digunakan yaitu model AlexNet yang diuji menggunakan hyperparameter batch size dan epoch berbeda. Model AlexNet menghasilkan performansi yang optimal yaitu akurasi 85% dengan waktu komputasi tahap training selama 16 menit 13 detik.
FACE RECOGNITION MENGGUNAKAN METODE HAAR CASCADE CLASSIFIER DAN LOCAL BINARY PATTERN HISTOGRAM
Authors: Mega Saraswati Nurul , Cipta Sigitta Hariyono Rito , Chandra David
Published: November 2024

Peningkatan ancaman keamanan data menjadi konsekuensi dari kemajuan teknologi yang terus berkembang, terutama dengan adanya teknologi yang memungkinkan akses ke data dari jarak jauh. Penting untuk selalu menjaga keamanan data dan mengambil langkah-langkah preventif untuk mencegah terjadinya pencurian data. Face Recognition (pengenalan wajah) merupakan salah satu dari beberapa teknologi biometrik yang dapat digunakan untuk sistem verifikasi identitas. Tujuan penelitian ini adalah untuk mengetahui akurasi dari penerapan metode Haar Cascade Classifier dan Local Binary Pattern Histogram untuk pengenalan wajah. Data yang digunakan berjumlah 5 kelas, dengan masing-masing kelas memiliki250 citra wajah. Total data yang digunakan berjumlah 1250 citra wajah, terdiri dari 1000 data latih (train) dan 250 data uji (test). Proses pengambilan gambar dilakukan secara otomatis, sistem secara otomatis mengambil 250 wajah per kelas. Tahapan selanjutnya adalah ekstraksi fitur dengan menggunakan metode Local Binary Patterns Histograms (LBPH). Selanjutnya sistem akan mengenali wajah yang dideteksi dengan yang ada di dataset. Penggunaan metode Haar Cascade Classifier dan Local Binary Pattern Histogram (LBPH) untuk mendeteksi wajah menggunakan 250 data uji (test) mendapatkan nilai akurasi sebesar 92%. Pengujian secara real time dilakukan sebanyak 75 kali dengan jarak 30 cm, 50 cm, dan 100 cm. Penggunaan metode Haar Cascade Classifier dan Local Binary Pattern Histogram (LBPH) untuk mendeteksi wajah secara real time mendapatkan akurasi sebesar 90%.
BLACKOUT MESIN MAN DAN KOMATSU AKIBAT KETIDAKSTABILAN FREKUENSI PADA SISTEM TENAGA LISTRIK KABUPATEN FAKFAK PT. PLN (Persero) ULP FAKFAK
Authors: Lembang Naomi
Published: November 2024

Pemadaman listrik secara total kamis 02 Januari 2022 pada sistem tenaga listrik Kabupaten Fakfak akibat trip-nya mesin MAN-04 dan mesin MAN-07 (PLN) dengan daya terpasang 528 kW, daya operasi 350 kW, dan akibat trip-nya mesin KOMATSU-09 dan mesin KOMATSU-12 (P3) mesin mempunyai daya terpasang 800 kW, daya operasi 450 kW pada PLTD Kebun Kapas, terjadi kelebihan beban (overload) pada mesin-mesin pembangkit yang masih beroperasi. Hal ini tidak efektif dan efisien daya yang dibangkitkan lebih kecil dari beban pada sistem mengakibatkan ketidakstabilan frekuensi mengalami penurunan frekuensi sehingga terjadilah blackout. Untuk meminimalisir blackout, perlu dilakukan pelepasan beban agar mesin pembangkit yang masih beroperasi tidak kelebihan beban (overload) dan frekuensi sistem tetap normal, untuk itu perlu dilakukan analisis pengolahan data skema pertahanan frekuensi pada PLTD Kebun Kapas serta pengukuran beban dan frekuensi pada salah satu mesin di PLTD Kebun Kapas. Penormalan Frekuensi dilakukan merujuk pada hasil simulasi pelepasan beban dilakukan untuk menjaga keseimbangan daya yang dibangkitkan dengan beban pada sistem. Berdasarkan hasil penelitian untuk mesin MAN mengembalikan frekuensi dari awal pelepasan beban 49,44 Hz ke frekuensi normal 50 Hz membutuhkan waktu 3,6 detik pada mesin MAN pada mesin KOMATSU untuk mengembalikan frekuensi dari 49,28 Hz ke frekuensi normal 50 Hz membutuhkan waktu 5,2 detik pada masing-masing mesin KOMATSU.
PENGEMBANGAN MEDIA TIMER PENCAMPURAN PAINTING PESAWAT BERBASIS MIKROKONTROLER PROMINI DI HANGGAR POLTEKBANG MAKASSAR
Authors: Nur Mulyadi , Louis Latif Hendri , Wahyudi Wahyudi
Published: November 2024

Penelitian ini bertujuan untuk menganalisis proses pelaksanaan pembelajaran aircraft maintenance procedure menggunakan timer sistem pencampuran cat pesawat berbasis mikrokontroler mega 2560 dimana sebuah perangkat yang digunakan dalam proses pencampuran cat untuk pesawat dan menghasilkan timer pencampuran painting pesawat berbasis mikrokontroler Promini yang valid, praktis, dan efektif. Metode penelitian ini menggunakan Riset and Development (R&D) dengan model 4D. Model 4D adalah sebuah pendekatan penelitian yang mengacu pada empat dimensi, yaitu Define (Mendefinisikan) dimana peneliti menganalisis kebutuhan pentingnya dilakukannya pengembangan, Design (Merancang) peneliti melakukan perancangan media beserta perangkat-perangkat yang berkaitan dengan media, Develop (Mengembangkan) peneliti memastikan produk yang dikembangkan layak untuk dipergunakan atau di uji cobakan di lapangan yang didasarkan oleh penilaian para ahli, dan Deploy (Menerapkan) peneliti mengimplementasikan produk yang telah dirancang dan telah layak ke taruna untuk dapat memperoleh data kepraktisan dan keefektifan penggunaan media. Hasil penelitian ini menunjukkan bahwa media yang dikembangkan pada aspek media dan materi berada pada kategori sangat valid untuk dipergunakan. Implementasi media trainer mendapat respon peserta didik yang berada pada kategori sangat praktis dalam penggunaanya dan hasil nilai tes taruna setelah implementasi mengalami peningkatan berada pada kategori tinggi. Kesimpulan data tersebut menyatakan bahwa media yang telah dikembangkan dinyatakan valid/layak untuk digunakan serta praktis dan efektif dalam penggunaanya.
PENGEMBANGAN ALAT PENANAM BENIH PADI BERBASIS MIKROKONTROLLER
Authors: Najamuddin Faisal , Wahrini Retyana
Published: November 2024

Penelitian ini didasari oleh keperluan mata kuliah Praktik mikrokontroler dalam melakukan praktikum, sehinggga perlunya dibuat media pembelajaran berupa prototype alat penanam benih padi berbasis mikrokontroler. Tujuan penelitian ini adalah (1) mengembangkan prototype alat penanam benih padi berbasis mikrokontroleer sebagai media pembelajaran, (2) mengetahui tingkat kelayakan dari prototype alat berbasis mikrokontroller dan (3) mengetahui respon pengguna terhadap prototype alat yang telah dibuat. Adapun model  pengembangan yang digunakan adalah model pengembangan ADDIE (Analyze, Design, Development, Implement, Evaluation). Kelayakan media pembelajaran pada penelitian ini menggunakan penngumpulan data instrumen penelitian yang diuji oleh ahli media, dan ahli materi. Kemudian dilakukan pengumpulan data pengguna atau responden menggunakan lembar angket. Penelitian ini menghasilkan produk berupa alat penanam benih padi berbasis mikrokontroler beserta modul praktikum dan buku panduan pada Program Studi Pendidikan Vokasional Mekatronika yang telah melakukan pengujian kelayakan oleh ahli media, ahli materi, dan respon pengguna yang dinyatakan secara keseluruhan dari penelitian ini sangat layak untuk digunakan.
PENGARUH MODEL PEMBELAJARAN INKUIRI TERHADAP AKTIVITAS BELAJAR SISWA SEKOLAH MENENGAH KEJURUAN
Authors: Zulfikar Yusuf Andi
Published: November 2024

Penelitian ini bertujuan untuk mengetahui pengaruh model pembelajaran inkuiri terhadap aktivitas belajar siswa SMK Negeri 5 Sidrap. Variabel dalam penelitian ini adalah: (1) Model pembelajaran inkuiri sebagai variabel bebas, dan (2) Aktivitas Belajar sebagai variabel terikat.. Teknik pengumpulan data dilakukan dengan observasi, kuesioner dan dokumentasi. Teknik analisis data dilakukan dengan menggunakan analisis deskriptif, uji instrumen, dan uji hipotesis. Berdasarkan hasil analisis data yang dilakukan, maka diperoleh hasil analisis deskriptif model pembelajaran inkuiri dengan persentase rata-rata sebesar 88,07%, dan hasil analisis deskriptif aktivitas belajar dengan persentase rata-rata sebesar 86,52%. Di hasilkan model persamaan regresi linear sederhana Y = 23,860 + 0,611X, hal ini berarti bahwa jika variabel model pembelajaran inkuiri nilainya nol, maka variabel aktivitas belajar sebesar 23,860. Berdasarkan hasil perhitungan analisis korelasi pearson product moment, maka diperoleh korelasi antara model pembelajaran inkuiri dan aktivitas belajar dengan koefisien r yaitu 0,702 yang memiliki tingkat korelasi kuat. Adapun hasil analisis koefisien determinasi (R2) sebesar 0,493 atau 49,3%. Hal ini berarti Model pembelajaran inkuiri memiliki kontribusi kepada aktivitas belajar sebesar 49,3 persen sedangkan 50,7% dipengaruhi oleh faktor lain. Hasil uji t diperoleh nilai signifikan 0,000 lebih kecil dari 5 persen (0,000 < 0,05) yang berarti bahwa terdapat pengaruh yang signifikan antara model pembelajaran inkuiri terhadap aktivitas belajar, dengan demikian hipotesis diterima.
ANALISIS POTENSI PEMBANGKITAN LISTRIK TENAGA MIKROHIDRO PADA BENDUNGAN LALENRI`E KECAMATAN LAPPARIAJA KABUPATEN BONE
Authors: Yantahin Muliaty , Arham Arham
Published: November 2024

Penelitian ini bertujuan untuk; 1) mengetahui hasil kajian potensi pembangunan PLTMH di bendungan Lalenri`e Kecamatan Lappariaja Kabupaten Bone. 2) mengetahui seberapa besar potensi daya yang dapat dibangkitkan dari PLTMH bendungan Lalenri`e. 3) mengetahui seberapa luas jangkauan distribusi layanan kelistrikan dari PLTMH bendungan Lalenrie. Teknik pengumpulan data yang diterapkan yaitu observasi lapangan, wawancara pihak terkait dan dokumentasi. Teknik analisis data yang digunakan adalah analisis statistik deskriptif dan analisis menggunakan software hydropower casimir berdasarkan pada data dinas terkait, badan pusat statistik dan pengelola bendungan. Hasil penelitian ini adalah; 1) debit air per tahun yakni Q2020 = 6,455 m3/s, Q2021 = 6,948 m3/s, Q2022 = 7,211 m3/s. 2) potensi daya listrik yang dapat dihasilkan oleh PLTMH bendungan Lalenri`e adalah P2020 = 106,1 kW, P2021 = 114,1 kW, P2022 = 118,5 kW. Potensi luas jangkauan distribusi layanan listrik dari PLTMH bendungan Lalenri`e adalah 50-100 konsumen.
استخدام المرأة اليمنية لمواقع التواصل الاجتماعي وعلاقته باحتياجاتها المجتمعية
Authors: الأغبري سامية عبد المجيد محمد
Published: November 2024

هدف البحث إلى التعرف على كيفية استخدام المرأة اليمنية (عينة البحث) لمواقع التواصل الاجتماعي وعلاقته بتلبية احتياجها المجتمعية. ووظف نظرية الاستخدامات والاشباعات، واعتمد على منهج المسح الإعلامي، حيث طبق استبيان على عينة عمدية من النساء اليمنيات اللواتي يستخدمن مواقع التواصل الاجتماعي من 18 سنة وما فوق، وبلغ حجم العينة (717) مفردة. وتوصل البحث للعديد من النتائج أهمها: ارتفاع معدل استخدام المبحوثات لمواقع التواصل الاجتماعي، واحتل الواتساب المرتبة الأولى من حيث الاستخدام، تلاه الفيسبوك واليوتيوب. احتلت الدوافع الطقوسية مثل التواصل مع الاهل والأصدقاء، وشغل أوقات الفراغ المراتب الأولى، بينما احتلت الدوافع النفعية مثل تعلم مهارات جديدة في مراتب تالية فيما جاء البحث عن فرص عمل والترويج للسلع والخدمات في مراتب متأخرة. وتركز اهتمام النساء على الموضوعات الاجتماعية الصحية والفنية مع نشاطات المتابعة والتعليق وتعلم المهرات فيما كانت صناعة المحتوى مثل انشاء مجموعة أو قنوات بنسبة أقل.
اكدت النتائج أن مواقع التواصل الاجتماعية ساهمت إلى حد كبير في تلبية معظم الاحتياجات المجتمعية للمرأة اليمنية كتعلم مهارات جديدة، وتطوير قدراتها العلمية والعملية في مجال التخصص، ومتابعة الاحداث المحلية والعالمية، والتحرر من القيود الاجتماعية والثقافية المعيقة لها.. الخ.
وأثبتت النتائج وجود علاقة ارتباطية دالة احصائياً بين معدل استخدام المبحوثات لمواقع التواصل الاجتماعي وتلبيتها لاحتياجاتهن المجتمعية لدرجة كبيرة.
The Challenges of Nuance
Authors: Leutheusser-Schnarrenberger Sabine , Risini Isabella , Tuchtfeld Erik
Published: November 2024

Five Questions to Sabine Leutheusser-Schnarrenberger
KONSEP KEHIDUPAN DUNIA AKHIRAT DAN IMPLIKASINYA TERHADAP PENDIDIKAN ISLAM
Authors: Suhendri  , Suhartini Andewi
Published: November 2024

Differences in views regarding the concepts of “dunia” and akhirat” are due to differences in the epistemological basis used by the Western view and the Islamic view. This research aims to explain Islamic views on the concept of “dunia” and akhirat”, explain the consequences of faith in the last day, explain the concept of balance in world life and the afterlife, and explain the implications for Islamic education. The method used in this research is library research, namely exploring the opinions of Muslim commentators or scholars regarding the concepts of “dunia” and akhirat” which they interpret from the main sources, namely the Qur'an and al-Hadith. The results of the research state that Islam views “dunia” and akhirat” as having to be lived in balance. Life on earth is a field leading to the afterlife. This has implications for the concept of balance in the world and the afterlife, physical and spiritual, individual and society. It also has implications for the Islamic education system which combines and integrates general knowledge and religious knowledge that appears in various educational institutions. Conclusion; Islam's universal view of all aspects of life creates balance. The implications of the concept of balance in the afterlife in educational studies can be seen when Islamic education is present in providing challenges and answers to change as well as responses to development that suit the needs of the people.
A Study on the Policies and Practices of Digital International Education Cooperation between Higher Education Institutions in Yunnan and South and Southeast Asian Countries
Authors: Luo Fang
Published: November 2024

本研究集中探讨了云南地区高等院校与南亚及东南亚国家在数字国际教育合作方面的政策框架、实施路径以及所遭遇的挑战。在全球数字化转型的趋势下，数字教育已经成为推动教育国际化进程的关键力量。特别是在“一带一路”倡议不断深化的背景下，云南凭借其独有的地理和政策优势，逐渐凸显出其在促进区域教育合作中的核心作用。然而，研究揭示，虽然云南的高等教育机构在远程教育和在线课程领域已经取得了一定的进展，但仍然面临着政策协调、基础设施建设、文化适应性以及师资培训等多方面的重大挑战。有鉴于此，本研究通过对现有合作模式的深入分析，提出了一系列针对性的策略，包括加强跨国政策的整合、提高教育资源共享的效率、改善技术基础设施等，以期推动云南高等院校与南亚东南亚国家在数字教育领域的进一步合作。
Szabályozási korszellem a Big Tech korában
Authors: Beyer Fülöp , Ződi Zsolt
Published: November 2024

A kapitalizmus digitális átalakulásának figyelemre méltó szereplői a tömeges közvetítést végző, más néven platformvállalkozások. E gazdasági szereplők hatalma közkedvelt téma, a jog fogalomkörében leginkább a versenyjog és a piacszabályozás tekintetében releváns. A klasszikus aggály, hogy a platformok hálózatosan működő, de a hálózatos iparágaknak meg nem feleltethető gazdasági aktivitását a versenyjog képtelen kezelni, már jó pár éve része a szakmai köztudatnak. E szakmai köztudat a versenyjog területén vizsgálatra érdemes, hiszen a platformok szabályozása körében kialakult vita nemcsak a jó szabályozásról szól, de a versenyjog belső igazolóelveit és történetiségét is érinti. E vitát a Regulatory Mind episztemológiai-analitikai módszertanával járjuk körül, és kísérletet teszünk a szabályozási korszellem összefoglalására.
L’identification des profils créatifs sur les communautés virtuelles purement sociales : clef de succès de l’innovation utilisateur
Authors: ABBES Intissar , HALLEM Yousra , HIKKEROVA Lubica
Published: November 2024

This research examines purely social virtual communities and their creative members, particularly Lead-users (Lu) and Opinion Leaders (Lo), seen respectively as innovators and disseminators of innovation. The study aims to identify the characteristics of creative profiles within these communities to better leverage them in user innovation. Two studies were conducted on three consumer communities: a quantitative study using self-assessment (225 participants) and a qualitative study through netnography. The results confirm the scarcity of Lead‑users and show that their profile is closely linked to that of Opinion Leaders. These findings provide theoretical and managerial perspectives for leveraging these profiles in the innovation process.
Innovative financing channels: International evidence from initial coin offering and project start-up success factors
Authors: FTITI Zied , HAMZA Taher , ZOUHOUR Mnif , LOUHICHI Waël
Published: November 2024

This study investigates Initial Coin Offerings (ICOs) as an innovative financing channel, focusing on the factors influencing their success and the project start-up post-ICO. Using a hand-collected dataset of 410 ICOs from the 2016–2018 period, we analyze ICOs as a mechanism that enables startups to raise significant capital. We categorize the success factors into voluntary disclosure quality, team characteristics, deal characteristics, and country of issuance or geographic location. We also examine security and payment tokens to explore their differing impacts on ICO outcomes. Our study contributes to the extant literature by offering a comprehensive view of the factors that drive ICO success and those that explain post-ICO performance. Our study provides critical insights for investors, regulators, and entrepreneurs.
Modern Türk Şiirinde Kudüs’ün Ele Alınmasında Miraç’ın ve Peygamber Kıssalarının Yeri
Authors: Ünlü Kocakoç Betül
Published: November 2024

Kudüs; Yahudilik, Hıristiyanlık ve İslamiyet olmak üzere üç semavi dinde de oldukça önemli kutsal bir beldedir. Hz. Mâsâ, Hz. Zekeriyyâ, Hz. Ya‘kūb, Hz. Yûsuf, Hz. İsmâil ve Hz. Îsâ’nın acıları Peygamberler yurdu olan bu şehirde gizlidir. Hz. Süleyman, Hz. Dâvud, Hz. İbrâhim de bu mübarek şehrin sınırları içinde bulunmuştur.
Tarihî, coğrafi ve dinî açıdan önemi sebebiyle Kudüs, farklı dönemlerde farklı millet ve medeniyete mensup kişi ve devletler tarafından yönetilmiştir. Müslümanlar için Kudüs’ün önemli olmasının asıl sebebi ise Hz. Muhammed’in miraç mucizesinin burada gerçekleşmesi ve Mescid-i Aksâ’nın Müslümanların ilk kıblesi olmasıdır.
Klasik Türk Şiiri döneminde İslam medeniyetiyle yönetilen, özgür ve güvenli bir belde olan Kudüs; hacnâmelerde, fetihnâmelerde, seyahatnâmelerde ve miraçnâmelerde faziletleri ve kutsiyeti dolayısıyla anlatılır. Cumhuriyet Dönemi Türk Edebiyatı ve sonrasındaysa Kudüs, işgal altındadır. Cumhuriyet Dönemi Türk Edebiyatı yazar ve şairleri iç sorunlara yöneldikleri için bakış açılarını Orta Doğu ve Kudüs’e yöneltememişlerdir. Kudüs’ü Modern Türk şiirine taşıyan ilk isim Sezai Karakoç olmuştur. Nuri Pakdil, Cahit Zarifoğlu, Akif İnan gibi şairler Karakoç’u takip etmiştir.
Cumhuriyet Dönemi şair topluluklarından bazıları, Orta Doğu’ya yönelseler de Orta Doğu’yu İslamî bir hassasiyetle sahiplenmedikleri ve dert edinmedikleri için bu bölgenin şiiri onların dizelerinde yüksek sesli olmamıştır. Zamanla sayıları çoğalan edebiyat dergileri çevresinde toplanan Modern Türk şairleri, İsrail’in Kudüs üzerindeki zulmünü eleştiren, Kudüs’e sahip çıkan şiirler yazmışlardır. Modern şiir, özünde bireysel duygu ve imgelere yöneliyor olsa da ortak meselelerde şairler farklı imgeler kullanmakla birlikte şiirlerinde benzer tema ve anlatılara yer vermişlerdir. Kudüs, şairlerin ortak derdi olmuş ve Kudüs denilince akla gelen belli başlı konu, kişi ve olaylar şiirlerinde yer almıştır. Peygamber kıssaları ve miraç mucizesi de bu ortak anlatı ve temalar arasındadır.
7 Ekim 2023’ten bu yana İsrail’in Gazze’de gerçekleştirdiği soykırım dolayısıyla şairler Gazze’deki soykırımı yer yer şiddetle eleştiren şiirler kaleme almışlardır. Bu şiirlerin bazılarında Kudüs ve Gazze birlikte anılmış, miraç mucizesi ve Kudüs’le bağı olan peygamberler Gazze şiirlerinde de konu olarak işlenmiştir. Bu makalede çeşitli edebiyat dergileri ve şiir kitapları taranarak Modern Türk şairleri tarafından yazılan Kudüs ve Gazze temalı şiirler tespit edilmeye çalışılmış, şiirlerin miraç mucizesi ve peygamber kıssalarıyla ilgisinin ortaya konması hedeflenmiştir.
Hiba Ebu Nada: Bir Edebiyatçının Ölümü Karşılayışı
Authors: Bulut Uslu Nurefşan , Gidiş Pınar Ayşe
Published: November 2024

Hiba Ebu Nada, 1991 doğumlu Filistinli bir şair ve edebiyat ödüllü başarılı bir yazardır. 7 Ekim 2023 tarihinden sonra İsrail’in Filistin’de tekrar ağır bir şekilde başlattığı soykırım bombardımanı sonucunda küçük oğlu ile birlikte şehit edilmiştir. Hiba Ebu Nada’nın şiirlerinde, yaşadığı vahşet ortamı ve ölüme karşı sergilediği yaşama motivasyonunu yansıtışı, onun ölüm kavramına bakış açısını anlayabilmemize olanak tanır. Ebu Nada için ölüm, bir son değil aksine bir başlangıçtır. Bu anlayış onun eserlerinde derin bir inanç olarak tezahür eder. Günümüz insanı için bu inancı kavramak zor olsa da, bu çaba, modern edebiyatın, içinde bulunduğu insan hakları ihlalleri ve soykırımın ortasında, derin inancıyla direniş gösteren bir şairin dünyasını anlamaya yönelik önemli bir adım olacaktır. Bu çalışma, çağdaş bir edebiyatçının karşılaştığı zulüm ve adaletsizlik karşısında, şiirinde nasıl bir direnç ve inanç sergilediğini ortaya koymayı amaçlamaktadır. Bu makale, Hiba Ebu Nada’nın şiirlerini analiz ederek onun eserlerinde inanç ve direnişin temsiline odaklanmaktadır. Nitel bir yaklaşım benimsenmiş ve yazarın eserleri felsefi bağlam içerisinde incelenmiştir. Çalışmanın sınırlılığı, Hiba Ebu Nada’nın son anlarında sesini sosyal medya aracılığıyla duyurabilmesi, ölüme dair görüşlerini bu şekilde ifade edebilmesi ile ilgilidir. Bununla birlikte çalışma, modern edebiyat ve insan hakları ihlalleri bağlamında bir edebiyatçının yazılarında direniş kavramının nasıl tezahür ettiğine dair güncel bir perspektif sunmayı hedeflemektedir. Ulaşabilinen bilgiler, edebiyatın, savaş ve zulüm ortamında insanın yaşama bakış açsısına dair önemli bir ifade alanı sunduğunu göstermeyi amaçlamaktadır.
الجهود الحديثية في غزة
Authors: Alhila Nour
Published: November 2024

يُعدُّ علم الحديث من أقوى العلوم الشرعية في الساحة الأكاديمية في غزة من حيث المفردات والدراسات العلمية والكوادر، إلا أنه لم يتوقف عند الساحة الأكاديمية؛ بل تجاوز إلى حلقات الحديث الخارجية والدروس والدورات. وقد وقفت على جودة الدراسات الحديثية من خلال البحوث التي نشرها أساتذة وطلاب الحديث في غزة، ووقفت على ذلك من خلال المساقات التي تُدرس في المراحل التعليمية المختلفة في الجامعات هناك، ومن خلال المجالس الحديثية التي عُقدت وشارك فيها العديد من الشخصيات الأكاديمية والقيادية والمجتمعية. كما ظهر الاهتمام بإقراء صحيح البخاري في هذه المجالس، ثم وقفت على الدورات الحديثية المختلفة بما فيها تعليم السنة النبوية وتطبيقها. وتوصل البحث إلى وجود حركة علمية نشطة في مجال الحديث الشريف، والعناية بهذا العلم من خلال جوانبه المختلفة، وعدم الاقتصار على الناحية النظرية؛ بل الاهتمام بالجانب العلمي للسنة والجانب التطبيقي في الدراسات، وبروز دور الجامعة الإسلامية بغزة في ذلك.
Indirect Infringement of Intellectual Property in International Documents
Authors: Najafi Hamed
Published: November 2024

It is obvious that mere relying on the domestic laws in intellectual property rights studies and neglecting to pay attention to international documents, is not acceptable, because ultimately, it is international documents that determine and explain the rights and obligations of governments in the international arena. Therefore, it seems necessary to study and review these documents and determine their position regarding the indirect infringement of intellectual property rights and the responsibility arising from it. Several international documents regarding the protection of intellectual property rights have been approved by international assemblies. The Paris Convention for the Protection of Industrial Property Rights, the Berne Convention for the Protection of Literary and Artistic Works (Copyrights), WIPO Internet Treaties and the Agreement on Trade-Related Aspects of Intellectual Property Rights (TRIPS), are among the most important documents in this field. This article is dedicated to examine the position of the indirect infringement of intellectual rights in these documents.
The Use of The Lingodeer Application in Enhancing Students’ Vocabulary Mastery
Authors: Hasanah Nur , Ulfa Siti Maria
Published: November 2024

This research aims to reveal the implementation and responses of students using the Lingodeer application as a medium used by students to find students' vocabulary gains after they use the Lingodeer application in class 7B of SMPN 01 Konang trough a qualitative research. The Lingodeer applicationwas chosen because it provides a variety of interactive and engaging language learning features, which can be accessed by students anytime and anywhere. The research method used is a case study with data collection trough field note observation, interview, and documentation.The result showed that students who used the Lingodeer Application in enhance students’ vocabulary. Observation during teaching and learning activities showed that students were more enthusiastic and active in the learning process. interview with students revealed that they felt more motivated and interested in learning English using the Lingodeer application because of the interactive and fun learning  medium. Documentation also supports this finding, showing an enhance in the number of vocabulary words that students mastered after using this application. This research concludes that Lingodeer application is effective in enhancing students’ vocabulary and can be a useful tool for teachers in teaching English. It is recommended that teachers consider using learning applications like Lingodeer to create a more dynamic and effective learning experiencenext research could explore the use of this application in other language skills as well as its long-term effects on students’ language proficiency
KEPEMIMPINAN DAN KOMUNIKASI DAKWAH NABI SULAIMAN A.S DALAM PERSPEKTIF DAKWAH DIGITAL
Authors: Moh Syahri Sauma
Published: November 2024

This paper explores the leadership and communication strategies employed by Prophet Sulaiman in the context of da'wah (Islamic propagation) and how they can be interpreted and applied within the framework of digital da'wah. Drawing from Islamic literature and contemporary understandings of digital communication, the study investigates the multifaceted approaches of Prophet Sulaiman in leading and communicating the message of Islam, examining their relevance and implications for digital da'wah in the modern age.
Firstly, the paper delves into the leadership qualities demonstrated by Prophet Sulaiman, emphasizing his wisdom, justice, and strategic decision-making abilities. It highlights how these attributes enabled him to effectively govern and lead his people, establishing a just and prosperous society conducive to the propagation of Islamic teachings.
Secondly, the communication strategies employed by Prophet Sulaiman are analyzed, focusing on his skillful utilization of language, diplomacy, and persuasion to convey the message of Islam to diverse audiences. His interactions with various stakeholders, including fellow monarchs, subjects, and supernatural beings, exemplify effective communication methods adaptable to the digital realm.
Furthermore, the paper examines the relevance of Prophet Sulaiman's leadership and communication approaches in the context of digital da'wah. It explores how contemporary digital platforms such as social media, websites, and multimedia content can be leveraged to emulate Prophet Sulaiman's strategies, reaching a global audience and fostering engagement with Islamic teachings.
The study underscores the importance of integrating principles of wisdom, justice, creativity, and humility into digital da'wah efforts, drawing inspiration from Prophet Sulaiman's exemplary leadership and communication style. By applying these principles in the digital sphere, contemporary da'wah practitioners can enhance their effectiveness in conveying the message of Islam, promoting understanding, and fostering positive engagement with diverse audiences worldwide.
POLA KOMUNIKASI ORGANISASI PERHIMPUNAN ORGANISASI PASIEN (POP) TB INDONESIA
Authors: Rudi Trianto
Published: November 2024

Komunikasi organisasi memegang peran penting dalam kelancaran operasional dan pencapaian tujuan sebuah organiasi. Pola komunikasi organisasi yang baik dapat meningkatkan koordinasi, meminimalkan kesalahpahaman, dan menciptakan lingkungan kerja yang produktif serta harmonis. Penelitian ini bertujuan mendiskripsikan pola komunikasi organisasi dan hambatan komunikasi di Perhimpunan Organisasi Pasien (POP) Tuberkulosis (TB) Indonesia. Landasan filosofis penelitian ini adalah paradigma Interpretif. Pendekatan penelitian menggunakan metode kualitatif deskriptif. Penelitian ini menggunakan teori Pola Komunikasi Joseph A. Devito dan Samuel P. Robbin yakni pola Pola Lingkaran, Pola Roda, Pola Y, Pola Rantai, dan Pola Bintang atau Semua Saluran. Subyek penelitian dalam penelitian ini adalah Ketua, Sekretaris, dan 3 koordinator Wilayah POP TB Indonesia. Informan ditentukan dengan metode Purposive Sampling. Teknik pengumpulan data menggunakan dokumentasi, observasi, dan wawancara. Teknik analisis data menggunakan model Miles, Huberman, dan Sadana dengan tahapan pengumpulan data, kondensasi data, display data, dan penarikan kesimpulan. Hasil penelitian menunjukkan bahwa pola komunikasi orgnisasi di POP TB Indonesia menggunakan pola Bintang atau Semua Saluran (All-Channel) dan pola Rantai. Hambatan komunikasi organisasi yang terjadi adalah hambatan kerangka berfikir dan budaya