bluuebunny/crossref_metadata_2025 huggingface dataset:
FRANZ LISZT MEPHISTO WALTZ NO. 1: PROGRAMMATIC EXPRESSION AND THE DYNAMICS OF PERFORMANCE
Authors: Yahşi Fahrettin Eren
Published: February 2025

ABSTRACT
The 19th century marked the emergence of storytelling through music, later known as “programmatic music.” This style of narrative expression invites performers to engage their imagination to bring the music to life. For the performer, the interpretation of a piece is shaped by imaginative insight, which then guides its execution. Simultaneously, programmatic music provides listeners with a framework for forming expectations about the performance. In this context, it becomes crucial for the performer to decipher the composer’s intended narrative through musical elements and notational cues. This imaginative approach to interpretation serves as a foundation for contemporary performance practices.
Franz Liszt’s Mephisto Waltz No. 1, a quintessential example of 19th-century programmatic music, holds a prominent place in piano literature. Its narrative, outlined by the composer in accompanying program notes, offers valuable interpretive guidance to performers.
This study explores Mephisto Waltz No. 1 as a work that conveys a specific narrative through music, examining its impact on performance interpretation and the interplay between the written score and its realization in performance.
IT Philosophy: Philosophical Paradigms in Information Technology Research
Authors: Swaleh Mohammed , Wabwoba Frankline
Published: February 2025

This study examines three major philosophical perspectives in information technology (IT) research: Positivism, Interpretivism, and Pragmatism. It investigates their various points of view, strengths, shortcomings, and most appropriate study methodologies. In addition, the report digs further into three more philosophical frameworks in IT research: postmodernism, Critical Realism, and postpositivism. Understanding these diverse philosophical foundations enables researchers to make informed decisions regarding research design and execution while navigating the rapidly evolving IT landscape.

The paper emphasizes the importance of considering the broader social, cultural, and ethical implications of IT systems and their applications. By adopting a more inclusive, responsive, and responsible approach to IT research, this work aims to contribute to the development of technologies that genuinely benefit and empower users, organizations, and societies. The diversity of philosophical paradigms underscores the complexity and richness of the IT research landscape, offering different lenses to examine the multifaceted nature of technology and its societal implications.

At the end of the study, researchers are encouraged to be aware of the philosophical underpinnings of their chosen paradigms and remain open to exploring alternative perspectives. This openness and reflexivity can enhance the quality, rigor, and relevance of IT research, fostering innovation, collaboration, and progress within the field.

By using the information in this article, researchers may be able to make better decisions about their research design and carry out their studies, which will improve IT research and its use in a wide range of settings.
THE EFFECT OF ANIMATED VIDEO MEDIA ON PREVENTION OF DENGUE HEMORRHAGIC FEVER (DHF) ON STUDENTS' KNOWLEDGE AND ATTITUDES AT SDN 002 SUNGAI PINANG
Authors: Alphard Zada Alyfa , Chifdillah Nino Adib , Bernadetha Bernadetha
Published: February 2025

In elementary school children, the selection of unqualified snacks is a problem that is a major concern in society. The animated video is made with a fun, simple storyline so that it can attract children's attention and the message conveyed can be maximized. Video animation is expected to change the mindset of children in preventing dengue hemorrhagic fever. This study aims to analyze the effect of animated video media on the prevention of dengue hemorrhagic fever on increasing knowledge, and attitudes of students of SDN 002 Sungai Pinang. This study used the Quasy experimental design research method with Time Series design. The population in the study was 5th grade students with amount of 45 people and used total sampling technique in sampling. There was an increase in the average knowledge score from 57.85 to 94.59. The average attitude score also increased from 60.52 to 93.11. Likewise with the average score of behavior, which increased from 62.22 to 94.17. Statistically, the results of the Wilcoxon test on the knowledge variable was ρ=0.000 < α 0.05 , and attitude ρ =0.000 < α 0.05. There is an influence of animated video media on increasing knowledge, and attitude in students of SDN 002 Sungai Pinang.
The Relationship Between Breast Care and Breast Milk Production in Postpartum Mothers at PMB Khoiruzan Talang Padang Tanggamus in 2022
Authors: Diantina Hera , Simanjuntak Farida M , Anggraini Ani , Marbun Vermona , Silitonga Riris Octryna
Published: February 2025

Background: The low rate of exclusive breastfeeding will impact the quality and survival of future generations. Globally, in 2019, 144 million children under five were estimated to experience stunting. Breast care is the practice of taking care of the breasts to ensure smooth breastfeeding and to prevent common issues that arise during nursing. Research Objective: To determine the relationship between breast care and breast milk production in postpartum mothers at PMB Khoiruzan Talang Padang Tanggamus in 2022. Research Method: This study used a quantitative research design. The population in this study consisted of 30 postpartum and breastfeeding mothers at PMB Khoiruzan Talang Padang Tanggamus in 2022. The sampling technique used was total sampling, so the total number of samples in this study was 30 respondents. Statistical testing used the chi-square test. Research Results: Univariate analysis showed that 26 respondents (86.7%) practiced breast care, and 21 respondents (70.0%) had adequate breast milk production. Bivariate analysis revealed a relationship between breast care and milk production, with a p-value of 0.005. Conclusion: There is a relationship between breast care and breast milk production.
The Impact of Sea Erosion on The Development of The Coastal Real Estate Market in The South Baltic Zone – Simulation of Changes
Authors: KLOSKOWSKI Dariusz , Kosek Weronika
Published: February 2025

The article presents the contemporary problem of the coastal real estate market related to the influence of wind and waves on the shape of the coast from the geodetic side. The problem indicated is not new on a global scale, because the effects of climate warming are known, including the rise in sea levels. However, the influence of sea erosion on investments, including the development of the coastal market in the Polish South Baltic zone, is one of the few examples that can be seen in the literature. This topic became the inspiration for conducting research and analyses in the context of the influence of erosion on coastal areas, which are a pole of economic growth. The article, based on the collected archival data of the Maritime Institute in Gdańsk, presents a simulation of erosion-accumulation changes in geodetic selected locations of the Polish South Baltic coast. The presented erosion simulation is a prognostic element, presented in prediction cycles until 2110. The simulation of erosion changes was based on a cartographic database with a generated digital terrain model. Spatial interpolation tools were used to determine changes over time.
BUKU CERITA BERGAMBAR BERBASIS KEARIFAN LOKAL KALIMANTAN BARAT SEBAGAI MEDIA PENDIDIKAN KARAKTER SISWA SEKOLAH DASAR
Authors: FATMAWATI RISDIANA ANDIKA , AFRYANINGSIH YUNIKA
Published: February 2025

Individual character will develop well, if it gets the right reinforcement, namely in the form of education. As many as 60% of schools in implementing the Character Education Program (PPK) seem to “just have time and remember” and are not conceptualized. So that character education, which should be fully implemented and have an impact on the development of student character, cannot be fully felt. Therefore, researchers tried to develop picture storybooks with a local wisdom approach to West Kalimantan as a feasible character education media. This study used a modified research development design from the ADDIE development model. The ADDIE development model consists of 5 stages, namely analysis, design, development, implementation, and evaluation. The results of this picture storybook development research have been declared worthy of contributing to the development of character education learning media for elementary school students. The feasibility of West Kalimantan local wisdom-based picture storybooks resulting from the validation test resulted in an average score of 3.4 with details of the media feasibility score of 3.1, material feasibility of 3.65 and language feasibility of 3.5.
ABSTRAKKarakter individu akan berkembang dengan baik, apabila memperoleh penguatan yang tepat, yaitu berupa pendidikan. Sebanyak 60% sekolah dalam pengimplementasian Program Pendidikan Karakter (PPK) terkesan “asal sempat dan ingat” dan tidak terkonsep. Sehingga Pendidikan karakter yang seharusnya bisa terlaksana secara utuh dan berdampak pada perkembangan karakter siswa, menjadi tidak bisa dirasakan sepenuhnya. Oleh sebab itu peneliti mencoba untuk mengembangkan buku cerita bergambar dengan pendekatan kearifan lokal Kalimantan Barat sebagai media pendidikan karakter yang layak. Penelitian ini menggunakan modifikasi desain pengembangan penelitian dari model pengembangan ADDIE. Model pengembangan ADDIE terdiri dari 5 tahapan, yaitu analisis (Analysis), desain (Design), pengembangan (Development), penerapan (Implementation), dan evaluasi (Evaluation). Hasil penelitian pengembangan buku cerita bergambar ini  telah dinyatakan layak memberikan kontribusi terhadap pengembangan media pembelajaran pendidikan karakter bagi siswa sekolah dasar. Kelayakan buku cerita bergambar berbasis kearifan lokal Kalimantan Barat yang dihasilkan dari uji validasi menghasilkan skor rata-rata 3,4 dengan rincian skor kelayakan media 3,1, kelayakan materi 3,65 dan kelayakan bahasa 3,5.
FEATURES OF REFLECTING THE QUALITY OF LIFE IN SOME CIS COUNTRIES IN DIGITAL FORMAT
Authors: Tilep B. , Simtikov Z. , Sadyrova A.
Published: February 2025

The article presents the evolution of the concept of quality of life. The author’s definition of this category is given. The transition to the concept of digital quality of life is justified. The emergence of a new human social quality, which is called Homo informaticus by the authors, is justified. It is postulated that this quality, provided it is properly developed, provides a person in a modern digital society with a decent quality of life and allows them to achieve a decent standard of living. A comparative analysis of the digital quality of life in the countries of the Commonwealth of Independent States on the main key parameters is carried out on the statistical material of the Interstate Statistical Committee of the CIS. Conclusion dwells upon the fact that there is a digital inequality, which is a new type of social inequality generated by the digital society. Such inequality is intertwined with traditional types of social inequality, primarily income inequality, but is not completely reduced to the existence of poverty. It is postulated that the key cause of digital inequality is digital illiteracy, which puts people in a marginal position with regard to access to the benefits of human civilization in modern society.
Drought and Salinity Intrusion in the Lower Chao Phraya River: Variability Analysis and Modeling Mitigation Approaches
Authors: Tomkratoke Saifhon , Kongkulsiri Siriwat , Narenpitak Pornampai , Sirisup Sirod
Published: February 2025

Abstract. Saltwater intrusion in the Lower Chao Phraya River (LCPYR) is a significant national concern for Thailand, requiring a thorough understanding and a development of effective prediction systems for current and future management. This study investigates the key drivers influencing saltwater intrusion in the LCPYR. Cross-wavelet analysis was applied to examine the interactions between tidal forces, drought conditions represented by the standardized discharge index (SDI) and standardized precipitation index (SPI), and salinity levels. Numerical simulations are used to explore the covariation among these drivers further. The results show that hydrological drought, particularly indicated by the SDI, plays a major role in driving the sub-annual to annual variability of saltwater intrusion, while extreme events are largely governed by sea-level oscillations, underscoring the importance of non-tidal sea levels. Local precipitation, as reflected by the SPI, strongly influences salinity levels, at times weakening the usual correlation between salinity and hydrological drought. The numerical model demonstrates high accuracy in simulating both hydrodynamic and salinity behaviors, validating the cross-wavelet analysis and offering a reliable approach for modeling salinity in this complex estuarine system. These findings offer essential insights to guide management strategies and the development of prediction tools for the LCPYR and surrounding regions.
Comprehensive Non-targeted Molecular Characterization of Organic Aerosols in the Amazon Rainforest
Authors: Leppla Denis , Hildmann Stefanie , Zannoni Nora , Kremper Leslie , Hollanda Bruna , Williams Jonathan , Pöhlker Christopher , Wolff Stefan , Sà Marta , Solci Maria Cristina , Pöschl Ulrich , Hoffmann Thorsten
Published: February 2025

Abstract. The Amazon rainforest plays a crucial role in the global climate system, hydrological cycle, and earth's energy balance. As one of the planet's least industrialized regions, it allows investigation of organic aerosol formation and constituents under almost pristine conditions. Nevertheless, human activities are known to affect this ecosystem – especially during the dry season. In this study, ambient aerosol samples collected at the Amazon Tall Tower Observatory (ATTO) during two dry and two wet seasons were characterized by high-resolution mass spectrometry (HR-MS). Comprehensive non-targeted data evaluation was applied to identify thousands of molecular formulae. Most were found to be associated with oxidation products of isoprene and monoterpenes, highlighting the predominance of biogenic secondary organic aerosols (SOA) at ATTO. The chemical composition exhibited distinct seasonal patterns with more processed organic compounds during the dry season, which can be explained by an increase of later-generation oxidation products due to reduced wet deposition and enhanced long-range transport. Mono- and polycyclic heteroaromatic components from biomass burning (BB) sources were enhanced during the dry seasons and the second wet season. The wet season was generally characterized by less oxidized compounds, associated with freshly formed SOA particles. Height-resolved measurements showed the forest canopy to be the main source for biogenic emissions with higher concentrations of early terpene oxidation products lower down. Overall, our results provide new insights into the molecular characteristics and seasonality of organic particulate matter at ATTO, helping to constrain the sources and interactions of aerosols, clouds, and precipitation in the Amazon rainforest.
Observational-based quantification of physical processes that impact the evolution of global mean sea level
Authors: Groeskamp Sjoerd
Published: February 2025

Abstract. The global mean sea level (GMSL) rise budget can be closed by integrating over global density distribution to account for ocean expansion, combined with satellite altimetry and ice sheet mass balances obtained from satellites and models. Such methods are of great importance, but the disadvantage is that they gloss over the individual fundamental physical processes that impact the evolution of GMSL. Such process are for example (but not limited to) the impact of ocean mixing and stirring, neutral physics, shortwave radiation and boundary heat and freshwater fluxes. It is valuable to quantify these processes as it provides understanding in the fundamental processes behind the observed GMSL rise and how these processes may change and in a transient ocean and climate. This study estimates the contribution of individual physical processes contributing to GMSL rise, using observational based products. It is not the intention and neither possible at this stage, to close the GMSL budget by means of this approach. Instead the results allow us to gain insights in the magnitude and uncertainty of processes and their relative importance in shaping GMSL rise, and allows for a comparison of the impact on GMSL by single processes or parameterizations. Results indicate the great uncertainty related to boundary heat, mass and freshwater fluxes, and the importance of ocean mixing for GMSL rise. Unexpected results are the significant impact of shortwave radiation depth penetration parameterizations and the way by which neutral physics is implemented. Many of the results are of importance for observational-based calculations as well as for modelers that have specific choices to make about which method and parameterizations they choose. These choices significantly impact the accuracy of predicted future sea level rise upon which policy will be based.
The Effect of Leadership on Employee Performance Through Work Motivation as a Mediating Variable in Employee PT Conisla Karya Indonesia
Authors: Putri Diana Suryami , Fatimah Nuzulul , Putra Riyan Sisiawan , Anshori Mohamad Yusak
Published: February 2025

This study aims to examine the effect of leadership on employee performance through work motivation as a mediating variable. This study uses quantitative methods with primary data obtained from the distribution of questionnaires to 89 employees of PT Conisla Karya Indonesia, with sampling techniques using purposive sampling determined by researchers with consideration of certain characteristics or characteristics based on employee status and division of each employee. Where the results of the questionnaire obtained are processed using Structural Equation Modeling (SEM) PLS 3.0 analysis through outer model analysis, inner model, and hypothesis testing. The results of this study indicate that there is a significant effect of leadership on employee performance, leadership has a significant effect on work motivation, work motivation has a significant effect on employee performance, and work motivation variables can significantly mediate the effect of leadership on performance employees.
Towards “Glass Bead Games 2.0”: Nurturing Global Cultural Memories by Means of New Forms of Art and Knowledge Interaction in the Age of AI
Authors: Bartosch David
Published: February 2025

The advent of AI calls for an existential self-redefinition of humanity. It necessitates the establishment of a pluralistic global humanist culture that enables us to coexist in the new world of active media and autopoietic technology. In this paper, related philosophical questions give rise to the proposal of a novel metaculture that elevates human heritages and cultural memories to the plane of a digital AI-based infrastructure. I argue for a balanced and holistic approach to human-to-human and human–AI interactions and metaculture that can be developed in the form of combinatorial “metagames” that reflect the potential of human consciousness, transcend the boundaries between technology, human embodiment and biology, the arts, sciences and humanities, and philosophy, and, finally, include the element of meaningful coincidence and spontaneity “in the second potency.” Hermann Hesse’s final novel, The Glass Bead Game, offers a key to understanding this basic idea. His vision is extremely relevant today. Based on this, the concept of cultivating global cultural memories through innovative aesthetic-epistemic “Glass Bead Games 2.0” is discussed further from a systematic angle. To complement this, reference is also made to Hesse’s own source of inspiration: Novalis’s “encyclopedist” approach interlinks aesthetic and epistemic productivity in a way that could become a major starting point to create a new holistic metaculture in the Age of AI.
Use of Big Data, Artificial Intelligence and Other Emerging Technologies in Public Health Communication Campaigns: A Systematic Review
Authors: Mireia Faus  , Francisco Alonso  , Cesáreo Fernández  , Cristina Esteban
Published: February 2025

Introduction: Public health campaigns have begun to employ various emerging technologies such as artificial intelligence (AI) and Big Data for their design, implementation, and evaluation. These technologies offer new opportunities to enhance the effectiveness of health communication strategies by enabling more precise audience segmentation, personalized messaging, and real-time impact assessment. However, despite their potential, their application in public health campaigns remains a relatively new field of study. This systematic review aims to identify and analyze the scientific literature that examines the role of these tools in optimizing communication strategies aimed at promoting healthy behaviors and attitudes among the population. Methods: Following the PRISMA methodology, 129 potentially relevant articles were initially identified from the search in the WOS, Scopus and PubMed databases. However, only 18 met the established inclusion criteria. Results: We identified a scarcity of scientific articles focused on presenting findings on the application of emerging technologies in public health campaigns. Most of the research focused on the use of these tools for audience segmentation and impact assessment, while their use in campaign design was a minority. Conclusions: This study supports the usefulness of the application of these technologies at any stage of the campaign implementation process, and presents some limitations that can help optimize this approach and improve the reach and effectiveness of public health communication strategies.
Coral Reef Coverage in the 17 Islands Marine Natural Tourism Park, Riung District, Ngada Regency, East Nusa Tenggara Province
Authors: Tony Frans , Bijaksana Untung , Fitriliyani Indira , Mahmud Arief , Widiyanto Daniwari , Hutomo Mulyo , Iskandar Rina
Published: February 2025

The 17 Islands Marine Nature Tourism Park (TWAL), located administratively in Riung District, Ngada Regency, East Nusa Tenggara Province, has limited information regarding the diversity of its marine biota. Therefore, further research on its underwater potential, particularly coral reefs, is essential. This research is expected to provide a deeper understanding of the richness of the marine ecosystem in the 17 Islands Marine Nature Tourism Park. The purpose of this study was to identify the types of coral reefs and assess the condition of coral cover in the 17 Islands Marine Nature Tourism Park (TWAL), Riung District, Ngada Regency, East Nusa Tenggara Province.This study employed data collection methods including observation and interviews with the local community and government. Coral reef data were collected using the Line Intercept Transect (LIT) method. The identification results show the presence of: (1) Four Acropora coral lifeforms, namely: Acropora Digitate Coral (ACD), Acropora Branching Coral (ACB), Acropora Tabulate Coral (ACT), and Acropora Encrusting Coral (ACE); (2) Six Non-Acropora coral lifeforms, including Branching Coral (CB), Massive Coral (CM), Encrusting Coral (CE), Foliose Coral (CF), Mushroom Coral (CMR), and Heliopora Coral (CHL); (3) One form of Dead Scleractinia, identified as Dead Coral with Algae (DCA); (4) Three types of Algae, consisting of Macro Algae (MA), Coralline Algae (CA), and Halimeda Algae (HA); (5) Four other faunal lifeforms: Soft Coral (SC), Sponges (SP), Zoanthids (ZO), and Others (OT). Additionally, two abiotic forms were identified: Sand (S) and Rubble (R). The condition of coral reef cover in the 17 Islands Marine Nature Tourism Park (TWAL), Riung District, Ngada Regency, East Nusa Tenggara Province, ranges from moderate to good.

Keywords: Coral, Tourism Park, 17 Islands Riung, Ngada Regency, East Nusa Tenggara
Kontestasi Pemaknaan Kepemimpinan Publik di PILGUB DKI: Perspektif Relasi Kuasa
Authors: Zauhair Al Fawwaz Fajriz , Musthafa Adib Khairil
Published: February 2025

This article explains about the hegemony of MUI related to the blasphemy case in the 2017 DKI Pilgub which is based on surah al-Maidah verse 51, there are various opinions that give birth to community polarization. Therefore, this article will answer the question of how the relevant meaning today of the word "Auliya" in surah al-Maidah verse 51. This article uses Michel Foucault's theory of power relations related to the knowledge produced by MUI. The result of this discussion is that there are opinions of interpreters who do not allow non-Muslim leaders as Muslim leaders, such as Ibn Kathir and Sayyid Qutb. Some others allow it, such as Ibn Taymiyah, Muhammad Abduh and Ashgar Ali Engineer and Sahiron Syamsuddin. The MUI's "Religious Opinion and Position" states that Basuki Tjahaya Purnama has blasphemed and cannot lead the Muslim community. Meanwhile, there is a counter from Kiai Muda Ansor Youth Movement and Sahiron Samsuddin's interpretation with ma'na cum maghzanya approach that views the interpretation of the word "Áuliya" verse 51 surah Al-Maidah from the side of the agreement that has been agreed upon then broken by one of them and is far different from MUI's "Opinion and Religious Attitude" especially that the interpretation of this verse is not about leadership, but the breaking of promises.
Subject Index 2024
Authors: Editorial Article
Published: February 2025

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SEGMENTASI YOUTUBE TRENDING MENGGUNAKAN ALGORITMA FUZZY C-MEANS BERDASARKAN VIEWERS
Authors: Ubaidillah Agdi Anas , Chisnanto Yulison Herry , Abdillah Gunawan Abdillah
Published: February 2025

Youtube merupakan platform video paling populer di dunia saat ini. Banyak video viral di Youtube dari Indonesia. Tapi, membuat video viral di Youtube adalah tantangan yang berat, baik untuk berpengalaman YouTuber dan khususnya untuk youtuber baru. Penelitian ini akan berfokus pada menemukan sifat video viral dengan mengelompokkannya ke dalam kelompok yang berbeda. Algoritma Fuzzy C-Maeans digunakan untuk proses clustering. Tujuan dari proses clustering ini adalah untuk mencari pola dalam data yang sebelumnya tidak terlihat. Hasil menunjukkan bahwa video dibagi menjadi tiga kelompok yang dibangun dari 3 variabel; view_count, likes, comment_count. Pola dan wawasan yang ditemukan dalam penelitian ini dapat berguna bagi calon pembuat video yang ingin meraih kesuksesan sebagai Youtuber. Hasil analisis cluster yang dilakukan memiliki 3 cluster dengan 10184 video berada di cluster 1 dengan indikasi tidak trending, 551 video berada di cluster 2 dengan indikasi sangat trending dan 35 video berada di cluster 3 dengan indikasi trending. Adapun pengujian dan evaluasi kualitas cluster yang terdapat pada sistem menggunakan silhouette dengan hasil mencapai 0.8778072603970618 mendekati angka 1.
Perlindungan Privasi Data Lokasi pada Location Based Services menggunakan Advanced Encryption Standard dan Secure Hash Algorithm-3
Authors: Nurrokhimah Siti , Hadiana Asep Id , Kasyidi Fatan
Published: February 2025

Dalam era transformasi digital, Layanan Berbasis Lokasi (LBS) kini menjadi krusial dalam berbagai platform digital, termasuk website pengiriman untuk pelacakan lokasi paket secara real-time. Namun, penggunaan LBS membawa risiko keamanan data lokasi. Dalam penggunaannya, website ini mengirimkan data ke server dalam bentuk teks biasa, yang menimbulkan kelemahan dalam keamanan data privasi pengguna. Padahal, kerahasiaan data pribadi termasuk data lokasi diatur dalam Pasal 26 UU ITE Revisi 2016 yang mengatur tentang privasi data pengguna. Berdasar hal tersebut, pada penelitian ini diterapkan algoritma AES dan SHA-3 untuk mengenkripsi dan hashing data lokasi pengguna sebelum dikirimkan ke server. Penelitian ini menunjukkan bahwa proses enkripsi dan hashing data lokasi dengan menggunakan kombinasi dua algoritma dapat diterapkan pada database sistem LBS. Pengujian dilakukan dengan melihat waktu tempuh pengiriman data pada seluruh sistem sebanyak 10 kali dengan variasi jumlah input data berbeda, yang menunjukkan adanya peningkatan waktu proses setelah implementasi Algoritma AES dan SHA-3. Selanjutnya, dari hasil pengujian avalanche effect menunjukkan hasil yang kurang baik sehingga tidak memberikan tingkat keamanan yang maksimal. Pengujian integritas juga dilakukan, dengan memeriksa hasil hashing data menggunakan SHA-3. Dari hasil pengujian tersebut, menunjukkan bahawa aspek integritas data lokasi pengguna terpenuhi sesuai dengan hasil pengujian integritas yang dilakukan.
Evaluation of Quality of Service on Megavision Internet Services Provider in Jelekong Village Using Speedtest by Ookla
Authors: Rusdan Muchamad
Published: February 2025

This research aims to test the Quality of Service (QoS) on the internet service provider Megavision in Jelekong Village, Baleendah District, Bandung Regency using Speedtest by Ookla Mobile. Measurement methods include download speed, upload speed, throughput, latency (ping), jitter, and packet loss. The research results show that the Megavision Provider can provide relatively good quality internet services, with an average download speed of 19.10 Mbps, an average upload speed of 19.78 Mbps, average throughput of 38.886 kbps in the "Good" category, average latency of 52.78 ms in the "Very Good" category, average jitter of 17.33 ms in the "Good" category, and average packet loss of 1.25% in the "Very Good" category based on the TIPHON standard. Although performance variations occur, especially during peak hours during the day, the test results generally show the stability and reliability of Provider Megavision's internet service. The results of this research can be used as a basis for carrying out continuous monitoring and improving infrastructure and service quality to provide a more satisfying user experience in Jelekong Village
Value Chain Mapping Based on Deep Learning in Cyber Security for Sustainability Development Smart Bandung City
Authors: Wijaya Rahmadi , Rosmiati Mia , Hidayati Hetti
Published: February 2025

Smart City is a lifestyle of people who use computers or electronic media to make their information needs easier. Through digitalization, everyone can get a more efficient, controllable, economical, productive, integrated, and sustainable life. However, to get this progress, a model for developing smart city initiatives is needed and becomes a chain so that it can continue to be developed in the context of a smart city. Therefore, to develop global smart city technologies, a smart city must create a Value Chain Mapping (VCM).  This paper aims to map the layers program with the currently running value chain mapping for smart city sustainable development. For this purpose, this research focused on the use of value chain mapping based on security services on smart city components: the environment and lifestyle, mobility, and health. Furthermore, deep learning methods as well as technology correlation in a smart city are explained. Mapping an environmental program layer using Deep Learning in Cyber Security services could prevent vulnerabilities that occur when implementing information technology
CHALLENGES WITH MSME BANK FINANCING IN UTTARAKHAND WITH SPECIAL REFERENCE TO DEHRADUN, INDIA: AN ANALYSIS
Authors: Brajesh Kumar Choubey, Luxmi Devi
Published: February 2025

The current research focused on understanding the challenges in bank financing for MSMEs in Uttarakhand with special reference to Dehradun. For conducting the research adopts both qualitative and quantitative approach, Random Sampling Technique for MSME respondents. The researcher approached Three hundred and seventy-five people gave their consent to take part in the survey, so total sample size is 375 out of 500 entrepreneurs of MSME in which 50 bank officials are selected for MSME financing in Dehradun. It was concluded, MSMEs are not aware of many sources of finance that are available to them. Due to lack of awareness, the lack of finance prohibits business growth, limiting the reach of refined-talent to a particular region. Hence, the null hypothesis was rejected and the alternative hypothesis (H10, H20, H30, H40, H50) was approved due to their p-values being below 0.05 with respect of research objective for MSME financing in Dehradun, Uttarakhand. The suggestion was also made in this respect to create good link between entrepreneurs and government information to start venture in proper ways to reduce risk and offer convenience to the customer.
Problems on using Mobile Payments Applications
Authors: Deepa Paul
Published: February 2025

Mobile payment applications have transformed financial transactions. They are convenient and efficient but face several challenges that impact the user experience and adoption. Some of the common problems include device incompatibility, limited support for certain currencies, and technical difficulties resulting from poor internet connectivity. Privacy and data security issues, such as fraud risks and data breaches, also discourage trust among users. In addition, accessibility barriers, ranging from geographical restrictions to high transaction costs and usability issues for lesser tech-savvy folks, add to the woes of adoption. Ensuring widespread acceptance and satisfaction through addressing these issues with proper security protocols, improving infrastructures, and focusing more on user-centric design innovation is important.
Analysing the Impact of Machine Learning on Textile Quality Enhancement and Defect Detection
Authors: A.Raghuvardhan Babu
Published: February 2025

One of the mainstays of global manufacturing is the textile sector, where quality control is essential to guaranteeing both customer happiness and product dependability. Conventional techniques for identifying flaws in fabric textures and improving quality frequently depend on manual examination, which is laborious, arbitrary, and prone to mistakes. This study examines the revolutionary effects of machine learning (ML) in improving textile quality and identifying flaws. Machine learning (ML) provides accurate, automated, and scalable methods for detecting anomalies in fabric textures and enhancing manufacturing efficiency by utilizing sophisticated algorithms, such as supervised learning, unsupervised learning, and deep learning approaches. This paper highlights the effective use of ML models in the textile industry by reviewing current practices and investigating ML applications in pattern recognition, anomaly detection, and predictive maintenance. There is also discussion of difficulties including integration into conventional procedures, computing complexity, and data restrictions. The results highlight how machine learning (ML) has the potential to transform the textile industry by lowering faults, streamlining procedures, and spurring innovation in quality control systems. This study ends with suggestions for future developments, such as new technologies and cooperative strategies to strengthen machine learning's position in the textile sector.
The Impact of Digital Marketing and Information Technology Capabilities on the Marketing Performance of SMEs in Türkiye
Authors: Aziz Öztürk
Published: February 2025

Purpose: Digital marketing competence is the capacity of a business to organise, carry out, and oversee digital marketing in order to boost its perceived competitiveness by customers. Small and medium-sized businesses' (SMEs') performance may be significantly improved by digitalisation. The majority of researchers tackled the issue from several angles by looking at how company performance is affected by technological skills, digital skills, information systems capabilities, adoption of information and communication technologies (ICT), and digital transformation. In addition to examining the effects of technological orientation, relationships with customers, and digital marketing on SMEs' business performance in emerging markets (EMs), this study attempts to provide a comprehensive conceptualisation of how digital marketing and its adoption boost the productivity of SMEs.
Method: Convenience sampling was used to gather data from SMEs in Türkiye’s Konya Region in order to evaluate the suggested model. Using the framework of structural equation modelling with partial least- squares estimation (PLS-SEM) method, 119 responses from SMEs that were gathered via online and in-person surveys were examined. 82% of those surveyed said they were partnerships or entrepreneurs. Eight respondents are white-collar workers, 13 are high-ranking managers, 14 are mid-level managers, and two said they have various roles.
Findings: The findings demonstrate the beneficial effects of organisational agility and digital maturation on corporate achievement. However, it is shown that organisational agility, when considered as a moderator, lessens the impact of digital maturation on firm performance.
Conclusion: While there are many advantages to digitalisation for businesses, it is still debatable whether it has a direct impact on performance results. The results of earlier research evaluating the effect of digital maturity on company performance were not entirely consistent. Therefore, several studies recommended investigating potential intervening factors. Thus, the impact of organisational agility and digital maturity on business performance is investigated in this research. Additionally, the moderating function of organisational agility in the relationship between business performance and digital maturity is also examined.
Use of AIML Powered Algorithm to Detect Illicit Activity Inside the Bitcoin Organisation
Authors: Jaykrishna Joshi,
Published: February 2025

When the technology behind Bitcoin was first revealed in the form of a white paper in 2009 and the corresponding reference implementation was released subsequently. Bitcoin has been accused by critics for pro- viding and shielding a sanctuary to criminal operations. A wide range of illegal means are used by people taking cover behind the sweeping of namelessness (anonymity). Revealing these substances is most crucial point for legal examinations. State-of-the-art techniques use Artificial Intelligence for comparing and identifying these actors but concentrate on a limited number of illegal trades. The ongoing research embarks to resolve the issue by executing a machine-learning enabled auto- mated rule based classification for various types of illegal activities, viz., ponzi schemes, blackmailers, frauds, scams, extortionists, spam- mers, gambling websites, darknet markets, terrorists and sextortionists.
Controlling, Analyzing, and Augmenting the Efficiency of IoT Enabled Devices using Juxtaposed Symmetric Block Cipher Algorithms
Authors: Savima K
Published: February 2025

Internet of Things (IOT) is becoming ubiquitous day by day and most of the gadgets used at home, office, hospitals, manufacturing plants etc try to employ this technology where ever possible. Devices that employ IOT technology range from smallest device that tracks the temperature etc, through RFID devices, house hold gadgets like televisions, and ovens and to large manufacturing machining. Such devices link and communicate with the cloud server to provide data for analysis. This results in possibilities of malware attacks at various levels that may challenge privacy and security. This research paper aims at building a modified version of the Present Block Cypher algorithm that will be embedded as part of the IOT device itself. The proposed algorithm has used 256 keys for encrypting the data and it creates a 64-bit key. Block cipher - a type of symmetric cipher, perform continuous mapping which processes information blocks in the size of 64 or 128 bits.
Secure Data Sharing in Machine Learning: Exploring K-Anonymization and Differential Privacy
Authors: Malath Sabri Kareem
Published: February 2025

The problem of data privacy has now become one of the most pressing ones, particularly with the growth of the number of people who use their identity data to sign up for various services. This work examines the combined application of k-anonymity and differential privacy approaches to achieve privacy preservation on health related information while maintaining its usefulness for analysis. The concept of K-anonymity tries to ensure that nobody can be uniquely identified from his records by making each record indistinguishable from at least k-1 other records; differential privacy also offers a measure to unable a person’s contribution to the overall data measurement outcome. These techniques are used in this study to health-related datasets, and assess the performance of a combined approach to achieving privacy and data utility. A significant piece of empirical research is provided to show that a combination of k-anonymity and differential privacy is not only realistic in a practical application but also provides optimum privacy protection while inflicting minimum loss in data quality. The reduction in reidentification risk is by a whopping 80% when data is processed through the combined method, but the utility of the data gathered only equals 85% the extent of the original data gathered from raw contextual information. Doing so proves the applicability of these privacy-preserving methods for the protection of health data represented by the results given in the paper.
Data Stream Learning Evaluation: Experimenting with Prequential Approach Over Real Data Streams
Authors: Shailaja B. Jadhav
Published: February 2025

Current IoT and sensor device-led computing systems are giving rise to enormous streaming data . This ever-growing streaming data necessitates data analytics to do ; on-the-fly decision making thus giving rise to stream learning enabled decisions. These new demands of data stream learning algorithms require evolving algorithms , evaluation methods and dynamic learning capabilities from the machine learning systems. Thus, changing data distribution over stream learning environments is  very less suitable to do with the existent and static environments of data analytics. This article addresses the prequential learning evaluation in data stream learning environment over real data streams like covertypeand airline with scikit multiflow stream learning APIs . The major objective of the paper is to analyse the better alternative to traditional hold-out evaluation . The classifier machine learning algorithms like  tree based adaptive classifiers and some ensemble-based alternatives are empirically evaluated over both hold-out and prequential methods. The results of the experimental evaluation suggest that prequential evaluation is able to achieve improvements  in accuracy. Further this article has evaluated time complexity which again suggests that GPU and similar computing environments if utilized , prequential evaluation may be the optimal solution for dynamic stream learning environments.
An Adaptive Bacterial Foraging Algorithm Based Faster Region–CNN for Classifying Personality Traits
Authors: Amit Garg
Published: February 2025

Mechanized personality discovery from image features has arisen and acquired a lot of consideration in the branch of knowledge of full of feeling registering and opinion examination. This work presents a deep learning model that can measure personality characteristics on five classes which is Conscientiousness (CON), Openness to experience (OPN), Extraversion (EXT),  Neuroticism (NEU) and Agreeableness (AGR) from a picture. This work proposes a model utilizing Convolutional Neural Networks to naturally extract highlights from a representation that are marks of personality qualities. To improve the detection level of personality Traits, Faster Region Convolutional Neural Network (F-CNN) model with Adaptive Bacterial Foraging Optimization (ABFO) is presented. The proposed model exhibits the effectiveness of the acquainted technique with a promising personality forecast model and can group the client's personality qualities when contrasted with the best-in-class procedures. While assessing the proposed technique, results show a ruthless and critical exactness improvement in contrast with the latest outcomes for the Personality dataset for personality recognition. Moreover, present the usually utilized datasets and call attention to a portion of the difficulties of personality-mindful proposal frameworks.
Context-Aware Transformer Models for Ambiguous Word Classification in Code-Mixed Sentiment Analysis
Authors: Shruti Mathur
Published: February 2025

Introduction: In text-based sentiment analysis, an ambiguous word that has more than one meaning can result in ambiguity, which creates challenging issues in analysing the sentiment. The Deep Learning models have achieved effective classification of ambiguous words. The traditional models acquirecertain limitations in accuracy and efficiency due to the ignorance of context features and parallelization.
Objectives: To classify ambiguous words in code-mixed sentiment analysis using context-aware transformer models, improving accuracy, efficiency, and adaptability while addressing limitations in traditional methods.
Methods: This study employs transformer-based models (DistilBERT, IndicBERT, XLM-RoBERTa, TinyBERT) to classify ambiguous words in code-mixed text. Data preprocessing techniques, including stopword removal, stemming, and lemmatization, prepare inputs for training. Each model's performance is evaluated using metrics like accuracy, precision, recall, and F1-score. DistilBERT's superior efficiency is compared against others to identify the best-suited approach for ambiguous word classification.
Results: The study demonstrates the effectiveness of transformer models for context-aware ambiguous word classification in code-mixed sentiment analysis. DistilBERT outperforms others with an accuracy of 88.75%, precision of 92.87%, recall of 88.75%, and F1-score of 90.39%. Its lightweight architecture ensures faster inference and reduced memory usage compared to IndicBERT, TinyBERT, and XLM-RoBERTa.
Conclusions: The findings confirm DistilBERT's robustness and reliability for code-mixed language tasks, offering significant advancements over conventional methods by achieving superior accuracy and efficiency in sentiment analysis. Context-aware transformer models are uniquely optimized for ambiguous word classification in code-mixed sentiment analysis, ensuring high precision, efficiency, and applicability to multilingual challenges.
A Novel Framework for Protein Sequence Classification using LSTM and CNN
Authors: Prativesh Pawar
Published: February 2025

Protein sequence classification has retained its status as one of the biggest challenges in the pharmaceutical industry due to the involved complexities of the subject matter. Technological developments have justified that there needs to be (some) knowledge of identifying and classifying the protein families. On the other hand, and rather cursorily, current methodologies consider a meagre set of protein sequence descriptors. The authors set forth here the amalgamation of BLSTM and BTCN wherein the deeper features within the protein sequence shall be explored. The thesis seeks to divide protein sequences by the sliding duration of the sliding window applied. Local dependencies within these segments may be explored with the proposed convolutional network, capturing interactions between global residues involving BLSTM network. Hence, a BLSTM has been taken as needed in the whole creation, because there is a dependency between amino acid classification and past and future secondary features, and method is that it achieves bidirectional properties avoiding any knowledge of the past and future information for gaining a necessary amount of additional insight. The proposed ensemble model has been concluded as more suitable for protein structure prediction research