bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of Targeting Accuracy of Sembako Programme in Rangkasbitung Sub-district through Logical Framework Approach (LFA)
Authors: Maulana Asep , - Harianto , - Sumardjo 
Published: December 2024

Abstract. Sembako programme is a government programme in reducing poverty, in practice the sembako programme often faces problems, one of which is target accuracy. The inaccuracy of targeting in the sembakoprogramme often results in food assistance that is not appropriate and does not touch the people who really need it, thus hampering the success of the programme. Therefore, this study analysed the Sembako program in Rangkasbitung Sub-district with a focus on the accuracy of targeting using the Logical Framework Approach (LFA). The main objectives of this study were to find the problems of targeting for the Sembako program and to make an improvement plan to improve the accuracy of the targeting of the Sembako program. The results showed that targeting accuracy in the kecamatan was affected by low data quality and weak verification. To ensure that the targeting accuracy is met, this study suggests creating clearer poverty indicators and training human resources. There is also a need for updated and connected data. The results of this study are expected to have an impact on the improvement of the Sembako programme so that it can target the people who really need it. Keywords: Sembako Program, Targeting Accuracy, Logical Framework Approach (LFA), Data Quality, Verification, Human Resources (HR). Abstrak. Program sembako merupakan program pemerintah dalam mengurangi kemiskinan pada praktiknya program sembako sering menghadapi masalah salah satunya adalah ketepatan sasaran. Ketidaktepatan sasaran dalam program sembako sering kali mengakibatkan bantuan sembako tidak tepat guna dan tidak menyentuh masyarakat yang benar-benar membutuhkan sehingga menghambat keberhasilan program. Oleh karena itu Penelitian ini menganalisis program Sembako di Kecamatan Rangkasbitung dengan fokus pada ketepatan sasaran menggunakan pendekatan Logical Framework Approach (LFA). tujuan utama penelitian ini adalah untuk menemukan masalah tepat sasaran untuk program Sembako dan untuk membuat rencana perbaikan untuk meningkatkan ketepatan sasaran program Sembako. Hasil penelitian menunjukkan bahwa ketepatan sasaran di kecamatan dipengaruhi oleh kualitas data yang rendah dan verifikasi yang lemah. Untuk memastikan tepat sasaran terpenuhi, penelitian ini menyarankan pembuatan indikator kemiskinan yang lebih jelas serta pelatihan sumber daya manusia. Selain itu diperlukan juga penyempurnaan data yang diperbarui dan terkoneksi. Hasil penelitian ini diharapkan dapat berdampak pada perbaikan program Sembako yang tepat sasaran sehingga sembako dapat menyasar masyarakat yang benar-benar membutuhkan. Kata Kunci: Program Sembako, Ketepatan Sasaran, Logical Framework Approach (LFA), Kualitas Data, Verifikasi, Sumber Daya Manusia (SDM).
K-Drama Excessive Watching Behavior and Loneliness of Parasocial Interaction in College Students
Authors: Saptari Saptari , Suhesty Aulia , Rasyid Miranti , Handayani Nanik 
Published: December 2024

Abstract. The emergence of the Korean Wave, encompassing K-dramas and K-pop, has garnered significant interest, particularly among college students. This research investigates how excessive viewing and feelings of loneliness impact social interactions. Utilizing a quantitative research design, the study involved 83 students from the Faculty of Social and Political Sciences at X University, selected through probability sampling methods. Data collection methods included scales measuring parasocial interactions, excessive viewing habits, and loneliness levels. The analysis employed multiple linear regression techniques. Key findings indicate that: (1) excessive viewing and loneliness significantly affect parasocial interactions, with an F-value of 3.992 exceeding the F-table value of 3.18 and a p-value of 0.001, contributing an influence of 42.1% (R²); (2) excessive viewing positively correlates with parasocial interactions, shown by a beta coefficient (β) of 0.377, a t-value of 2.071 surpassing the t-table value of 2.008, and a p-value of 0.044 (p < 0.05); (3) however, loneliness does not significantly impact parasocial interactions, evidenced by a beta coefficient (β) of 0.156, a count of 0.156.859 falling below the t-table value of 2.008, and a p-value of 0.395 (p < 0.05). Keywords: Social interaction, excessive watching, loneliness. Abstrak. Perkembangan fenomena Korean Wave, yang mencakup K-Drama dan musik K-Pop, telah menarik perhatian yang luas, khususnya di kalangan mahasiswa. Penelitian ini bertujuan untuk mengeksplorasi dampak dari menonton secara berlebihan dan perasaan kesepian terhadap interaksi parasosial. Metode yang digunakan dalam penelitian ini adalah pendekatan kuantitatif. Subjek penelitian terdiri dari 83 mahasiswa Fakultas Ilmu Sosial dan Ilmu Politik Universitas X yang dipilih melalui teknik probability sampling. Pengumpulan data dilakukan dengan menggunakan skala untuk mengukur interaksi parasosial, tingkat menonton berlebihan, dan kesepian. Analisis data dilakukan menggunakan regresi linier berganda. Hasil penelitian menunjukkan bahwa: (1) terdapat pengaruh signifikan antara menonton berlebihan dan kesepian terhadap interaksi parasosial, dengan nilai F hitung sebesar 3.992 yang lebih besar dari F tabel 3.18 dan nilai p sebesar 0.001, serta kontribusi pengaruh (R²) mencapai 42.1%; (2) terdapat pengaruh positif yang signifikan dari menonton berlebihan terhadap interaksi parasosial dengan nilai koefisien beta (β) sebesar 0.377, t hitung 2.071 lebih besar dari t tabel 2.008, dan nilai p sebesar 0.044 (p < 0.05); (3) tidak ditemukan pengaruh signifikan dari kesepian terhadap interaksi parasosial dengan nilai koefisien beta (β) sebesar 0.156, t hitung 0.859 lebih kecil dari t tabel 2.008, dan nilai p sebesar 0.395 (p < 0.05).Kata Kunci: Interaksi parasosial, menonton berlebihan, kesepian.
The Policy Formation Process of Inclusivity PEKKA Foundation with Australian DFAT
Authors: Jihan Nur , Yudono Raden Maisa 
Published: December 2024

Abstract. This research discusses the inclusion policy formulation process conducted by Pemberdayaan Perempuan Kepala Keluarga (PEKKA) Foundation and the Australian Department of Foreign Affairs and Trade (DFAT). This research background is the social and economic vulnerability experienced by female-headed households in Indonesia. This research examines multi-stakeholder collaboration and the process of formulating inclusive policies in Indonesia. The research method is descriptive qualitative, with interview techniques and non-participant observation. The results show that policy-making involves five stages: agenda setting, policy formulation, policy adoption, policy implementation, and policy evaluation. At each stage, both PEKKA and DFAT play their respective roles through collaboration using the multi-stakeholder partnership (MSP) approach, resulting in empowerment programs such as the Klinik Layanan Informasi dan Konsultasi (KLIK PEKKA) and the Paradigta Academy, which have increased access to basic services and political participation of the female-headed family. Keywords: Policy; female- headed family; PEKKA; DFAT; MSP Abstrak. Penelitian ini membahas proses perumusan mengenai kebijakan inklusivitas yang dilakukan oleh Yayasan Pemberdayaan Perempuan Kepala Keluarga (PEKKA) bersama dengan Australian Department of Foreign Affairs and Trade (DFAT). Latar belakang penelitian ini adalah isu kerentanan sosial dan ekonomi yang dialami oleh perempuan kepala keluarga di Indonesia. Penelitian ini bertujuan untuk mengkaji kolaborasi multi-stakeholder serta proses perumusan kebijakan inklusivitas di Indonesia. Metode penelitian yang digunakan adalah kualitatif deskriptif, dengan teknik wawancara dan observasi non-partisipan. Hasil penelitian menunjukkan bahwa proses pengambilan kebijakan melibatkan lima tahap, yaitu agenda setting, formulasi kebijakan, adopsi kebijakan, implementasi kebijakan, dan evaluasi kebijakan. Dalam setiap tahap, baik PEKKA maupun DFAT memainkan perannya masing-masing melalui kolaborasi menggunakan pendekatan multi-stakeholder partnership (MSP) yang menghasilkan program-program pemberdayaan seperti Klinik Layanan Informasi dan Konsultasi (KLIK) PEKKA dan Akademi Paradigta yang berhasil meningkatkan akses layanan dasar dan partisipasi politik perempuan kepala keluarga. Kata Kunci: Kebijakan; perempuan kepala keluarga; PEKKA; DFAT; MSP
Developing an early detection model for skin diseases using a hybrid deep neural network to enhance health independence in coastal communities
Authors: Harumy Tengku Henny Febriana , Br Ginting Dewi Sartika , Manik Fuzy Yustika , Alkhowarizmi Alkhowarizmi 
Published: December 2024

The object of study is a solution for early skin disease diagnosis by integrating hybrid deep neural networks – EfficientNetB7 for Classification and YOLOv8 for detection. The system is designed to classify five skin conditions: Melanoma, Basal Cell Carcinoma (BCC), melanoma is a type of skin cancer that originates from melanocytes, the cells that produce skin pigment, Melanocytic Nevi (NV) Melanocytic nevus is a mole or dark spot on the skin formed due to the accumulation of melanocytes, Benign Keratosis-like Lesions (BKL) is a term for a group of skin changes that resemble keratosis but are non-cancerous, and Seborrheic Keratoses and other benign tumors to enhance the health diagnostics. The problem to be solved in this study revolves around improving early and accurate skin disease diagnosis, particularly in resource-limited or underserved areas and the lack of Accessible Diagnostic Tools and Low Efficiency of Current Diagnostic Methods. The study highlights EfficientNetB7's classification accuracy at 94 % and YOLOv8's means average precision (mAP) of 0.812 for detection. This hybrid system processes skin images efficiently, providing classification and detection outcomes with consistent performance in multiple tests. The results demonstrate that the EfficientNetB7 model achieved an accuracy of 94 % on test data, while YOLOv8 delivered a detection performance with a mean average precision (mAP) of 0.812. The web-based system efficiently processed skin images and provided classification and detection outcomes.
Furthermore, integrating EfficientNetB7 and YOLOv8 allowed the skin disease detection system to classify five different diseases and assess malignancy risk. The systems are portable and can be used with minimal setup, making them practical for real-world diagnostic use. The Scope and Practical applications are designed for accessibility in resource-limited settings. The website-based skin disease detection tool provides a user-friendly platform accessible to the public and healthcare providers, especially in underserved areas. Each application's high accuracy and ease of use make them viable aids in early diagnosis, potentially improving healthcare access
Rationale for choosing the airfoil of a UAV wing using a dynamic ground effect principle
Authors: Dreus Andrii , Kravets Olena 
Published: December 2024

Vehicles that use the principle of dynamic ground effect principle are innovative vehicles that have prospects for use as high-speed unmanned vehicles. It is known that when an aircraft moves near the ground, the phenomenon of increasing lift occurs, which allows for contactless movement at high speeds. However, the effectiveness of this ground effect depends on the airfoil shape. The object of this study is the aerodynamic processes that occur during the movement of an unmanned aerial vehicle near the ground. The influence of the effect of approaching the ground on the aerodynamic characteristics of four airfoil of different shapes has been considered: Clark YH-12, NACA-M6, USA-35B, TsAGI-721, which are used in subsonic high-speed aircraft, including unmanned aerial vehicles. The aim of the work is to evaluate the performance of these aerodynamic airfoils in near-surface operation and to determine the most promising shape for use in small unmanned WIGs. CFD modeling methods were used as a research tool. The pressure and velocity fields around the wing airfoils were determined and the influence of the distance to the ground and the angle of attack on the aerodynamic characteristics was established. It was found that the best aerodynamic quality for all airfoils is achieved at angles of attack of 4–6°. It is not recommended to use airfoils with angles of attack close to 0° as the ground may have a negative effect on lift. The USA-35B airfoil demonstrated the greatest increase in aerodynamic quality when approaching the surface, with a maximum increase of 67 %. This makes it possible to recommend USA-35B as small unmanned aerial vehicles with a dynamic ground effect principle
Advancing real-time echocardiographic diagnosis with a hybrid deep learning model
Authors: Bolshibayeva Aigerim , Rakhmetulayeva Sabina , Ukibassov Baubek , Zhanabekov Zhandos 
Published: December 2024

This research focuses on developing a novel hybrid deep learning architecture designed for real-time analysis of ultrasound heart images. The object of the study is the diagnostic accuracy and efficiency in detecting heart pathologies such as atrial septal defect (ASD) and aortic stenosis (AS) from ultrasound data.
The problem is the insufficient accuracy and generalizability of existing models in real-time cardiac image analysis, which limits their practical clinical application. To solve this, the convolutional neural networks (CNNs), combining local feature extraction was integrated with global contextual understanding of cardiac structures. Additionally, a YOLOv7 for precise segmentation and detection was utilized.
The results demonstrate that the hybrid model achieves an overall diagnostic accuracy of 92 % for ASD detection and 90 % for AS detection, representing a 7 % improvement over the standard YOLOv7 model. These improvements are attributed to the hybrid architecture's ability to simultaneously capture fine-grained anatomical details and broader structural relationships, enhancing the detection of subtle cardiac anomalies.
The findings suggest that combination of CNNs enhances pattern recognition and contextual analysis, leading to better detection of cardiac anomalies. The key features contributing to solving the problem include the hybrid architecture's ability to capture detailed local features and broader structural context simultaneously.
In practical terms, the model can be applied in clinical settings that require real-time cardiac assessment using standard medical imaging equipment. Its computational efficiency and high accuracy make it suitable even in resource-constrained environments, reducing analysis time for clinicians, supporting personalized treatment plans, and potentially improving patient outcomes in cardiology
Development of a magnetic activator to protect an electric water heater against scale formation
Authors: Mekhtiyev Ali , Sarsikeyev Yermek , Gerassimenko Tanya , Alkina Aliya , Mekhtiyev Ruslan , Neshina Yelena , Kirichenko Lalita 
Published: December 2024

The paper is dedicated to the research and development of a magnetic activator for the prevention of scale formation in electric water heaters, which is a pressing problem in regions with hard water, typical for Сentral Kazakhstan. During the operation of water heaters, salt deposits on heating elements lead to increased energy consumption and reduced efficiency. The developed activator uses powerful neodymium magnets that change the structure of the hardness salts in the water, preventing their deposition in the form of scale. Research has shown that the use of a magnetic activator can reduce water hardness by 15–20 %, resulting in a significant reduction in scale formation. In particular, under normal operating conditions, the thickness of the scale layer can reach 2–4 mm, but with the use of the magnetic activator this indicator is reduced to less than 1 mm. Descaling the heating elements not only extends the life of the water heater, but also reduces energy costs. Energy consumption is reduced by 10–15 %, as water heaters with less scale work more efficiently without requiring additional energy for heating. The paper also discusses the design features of the magnetic activator, the principles of its operation and the results of laboratory and field tests. Economic analysis has shown that the installation of the magnetic activator pays for itself within 1–2 years due to the reduction in limescale and energy costs. This makes it an attractive solution for private households as well as for industrial companies that use water heaters in their production process, as the proposed magnetic activator is an effective solution for protecting water heaters from the negative effects of hard water
Big data analytics for seasonal crop patterns: integrating machine learning techniques
Authors: Yunis Roni , Halim Arwin , Pardosi Irpan Adiputra 
Published: December 2024

This study addresses the challenge of predicting rice growing season lengths, crucial for agricultural planning in tropical regions. Climate variability and season timing create uncertainties in decision-making, and while machine learning is widely used in agriculture, a gap persists in integrating spatial-temporal data for accurate season length prediction and region-specific pattern analysis influenced by rainfall. Using a combination of Random Forest algorithms with hyperparameter optimization (grid search), and clustering techniques such as PCA, K-Means, and Hierarchical Clustering, this study analyzes key features such as the start of the season (SOS), end of the season (EOS), and their significance indicators (sig_sos and sig_eos). The findings reveal a strong correlation (0.98) between SOS and EOS, with an optimal growing season ranging from day 93 to day 207 (113.82 days). The Random Forest model, optimized with Grid Search, achieved a MSE of 28.9474 and an R2 of 0.8636, showing an outstanding predictive result. SHAP and LIME analyses identified sos and eos as the most influential predictors, while cluster analysis highlighted three distinct growing season groups characterized by variations in rainfall and seasonal stability. These results underscore the importance of understanding localized agricultural conditions and provide actionable insights for optimizing planting schedules, resource allocation, and climate adaptation strategies. By integrating advanced machine learning techniques with spatial-temporal data, this study establishes a foundation for improving agricultural resilience and sustainability in the face of climate variability
Devising investment strategies as a source of financial support to the development of territorial communities in the era of digitalization
Authors: Radynskyy Serghiy , Ratynskiy Vadym , Lobodina Zoryana , Shpylyk Svitlana , Pohrishchuk Halyna , Dobizha Nataliia , Bei Snizhana , Diachenko Nataliia , Diachenko Valentyn , Piniak Iryna 
Published: December 2024

The object of this study is the process of financial support to the development of territorial communities under the conditions of digitalization. The task addressed was insufficient financial support to territorial communities, which, in turn, limits their development under the conditions of digitalization. The need to devise and implement an investment strategy as a basis of financial support to the development of territorial communities has been identified. The interpretation of the research results demonstrates the significant impact of digitalization on the directions and technologies of the investment strategy of territorial communities. This makes it possible to choose the most popular sources of funding for investment strategies of territorial communities under conditions of digitization. An example of sources of funding for the strategic goals of the digital development of the urban territorial community was given, among which the local budget funds and grant funds prevail. The results prove that the successful development of territorial communities in the era of digitalization depends on their ability to determine target orientations and diversify their funding sources. A distinctive feature of the research results is the construction of a model for the development of territorial communities under conditions of digitalization based on an investment strategy. In order to increase the effectiveness of the process of development and implementation of the investment strategy of territorial communities, the implementation of two-level filtering has been envisaged – according to goals and financial resources. The use of the proposed model would create prerequisites for the further development of territorial communities under the conditions of digitalization. The domain of practical use of the results extends to the management of regional investment development, which involves increasing the size of financial investments and improving the well-being of residents of territorial communities
Estimating the influence of the rigidity of support assemblies on the resonance phenomena and the vibration state of a hydraulic unit
Authors: Tretiak Oleksii , Kovryga Anton , Kravchenko Stanislav , Shpitalnyi Denys , Zhukov Anton , Serhiienko Serhii , Arefieva Mariia , Penkovska Nataliia , Madonych Andrii 
Published: December 2024

Many factors affect the vibration of the hydraulic unit, including the natural oscillation frequencies of the structural elements, which in some cases may contribute to an increase in vibration because of the occurrence of resonance phenomena.
In this work, the case of design optimization of the support assemblies of the shaft pipeline of the hydrogenerator-motor was considered, installed at HSPP during its reconstruction in order to improve vibration parameters. The effect of increasing the stiffness of the upper crosspiece and reducing the weight of the rotating parts on the value of the first and second critical rotation frequencies was analyzed. Based on the results of computations, operability of the proposed new reinforced structure of the upper crosspiece of the hydrogenerator-motor with increased rigidity was confirmed. Using this design could increase the first critical rotation frequency from 9 Hz (540 rpm) to 17.6 Hz (1056 rpm). This would lead to the avoidance of resonance phenomena caused by the proximity of the first critical rotation frequency of the rotor to the rated rotation frequency (600 rpm).
The computations were performed in a three-dimensional setting in two stages for each of the considered design cases. At the first stage, the supporting elements rigidity of the shaft line of the hydrogenerator-motor were studied by determining the structural element elastic deformations when it was loaded by a transverse force. At the second stage, these determined stiffnesses of the support elements were used as input data for calculating the critical rotation frequencies of the hydraulic unit rotor