bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessing Financial Distress Drivers: Financial Metrics and Corporate Practices in Indonesian Manufacturing Companies
Authors: Fazila Paula
Published: December 2024

Understanding the factors that contribute to financial distress is crucial for assessing the financial health of companies. This research examines, validates, and analyses the influence of leverage, liquidity, profitability, sales growth, good corporate governance (GCG), and corporate social responsibility (CSR) on financial distress. The study utilizes secondary data derived from financial statements. The sample consists of 310 financial reports from manufacturing companies listed on the Indonesia Stock Exchange (IDX) over five years (2015-2019), selected through purposive sampling. Logistic regression analysis was applied in this study. The findings indicate that leverage, liquidity, profitability, and CSR significantly impact financial distress. In contrast, sales growth and GCG do not substantially affect financial distress.  These results suggest that companies should focus on managing leverage and liquidity while enhancing profitability and CSR practices to mitigate financial distress risks. On the other hand, policymakers need to establish regulations and incentives that encourage responsible financial management and social responsibility initiatives. It is important to prevent financial distress and provide a direction for companies and policymakers to enhance financial stability and sustainability.
De ce dedicăm acest număr educației culturale?
Authors: Croitoru Carmen
Published: December 2024

The present issue tackles the notion of museums as dynamic educational institutions. It is therefore of utmost importance to discuss the multifaceted concept of cultural education and how it can be implemented in public cultural institutions, especially in museums, while also preserving the essential mission of museums in society.
Shades of Darkness: Politics, Objects, and Displays in Sighet’s Dark Heritage Sites
Authors: Lazar Teodora
Published: December 2024

This article explores the interpretation and communication of dark heritage in Sighetu Marmației, focusing on three sites: the Memorial of the Victims of Communism and Anti-Communist Resistance, Pauper’s Cemetery, and the Elie Wiesel Memorial House. We argue that these sites convey Romania’s dark heritage by being associated with events and histories of troubled pasts, namely the Communist oppression and the Holocaust. The analysis addresses how and to what extent objects, politics, and spatiality contribute to the making of a sense of darkness identified in these sites. The article argues that the darkness of these sites is shaped not only by their histories, but also by the narratives constructed around them through the museum exhibits and curation. The study reveals that while these sites aim to educate and memorialise, they also navigate complex political and social dynamics, influencing how their dark heritage is presented and perceived.
Hubungan Dukungan Sosial Dengan Post Traumatic Syndrome Disorder (PTSD) Pada Korban Bencana Tanah Longsor di Desa Sirnaresmi Kecamatan Cisolok Kabupaten Sukabumi
Authors: Rahmanishati Woro , Dewi Rosliana , Indriani Kusumah Rani
Published: December 2024

Negara Indonesia rawan bencana yang menyebabkan rasa trauma atau post traumatic stress disorder (PTSD). Diperlukan berbagai upaya untuk mengurangi PTSD salah satunya ialah dukungan sosial. Individu yang mendapat dukungan sosial bisa mengurangi trauma. Tujuan penelitian ini untuk mengetahui hubungan dukungan sosial dengan post traumatic syndrome disorder (PTSD) pada korban bencana tanah longsor di Desa Sirnaresmi Kecamatan Cisolok Kabupaten Sukabumi. Dukungan sosial adalah keadaan bermanfaat dari orang lain yang menimbulkan efek perilaku bagi penerima. Post Traumatic Stress Disorder (PTSD) adalah kecemasan patologis setelah mengalami/menyaksikan trauma berat. Bencana adalah peristiwa mengancam dan mengganggu kehidupan masyarakat mengakibatkan kerugian dan kehilangan. Jenis penelitian korelasional dengan pendekatan cross sectional. Populasi  dan sampel sebanyak 38 orang. Pengambilan sampel menggunakan total sampling. Pengambilan data menggunakan kuesioner dan analisis statistik menggunakan uji fisher’s exact test. Hasil penelitian menunjukkan terdapat hubungan dukungan sosial dengan post traumatic syndrome disorder (PTSD) (p-value 0,008). Kesimpulan, terdapat hubungan dukungan sosial dengan post traumatic syndrome disorder (PTSD) pada korban bencana tanah longsor di Desa Sirnaresmi Kecamatan Cisolok Kabupaten Sukabumi. Diharapkan penelitian ini menjadi masukan untuk mencegah PTSD dengan melakukan tindakan psikoterapi.
Faktor-Faktor Yang Berhubungan Dengan Kepatuhan Masyarakat Dalam Protokol Kesehatan di Era Adaptasi Kebiasaan Baru di Desa Cijagamulya Kecamatan Ciawigebang Kabupaten Kuningan Tahun 2020
Authors: Rimandasari Ikmah , Heriana Cecep , Kurnia Rahim Fitri
Published: December 2024

Latar Belakang: Desa Cijagamulya merupakan salah satu desa di Kecamatan Ciawigebang, Desa Cijagamulya berdekatan dengan desa yang terdapat salah satu warganya yang menjadi suspect Covid-19. Dari studi pendahuluan yang dilakukan di Desa Cijagamulya dari 10 responden hanya 6 reponden yang menerapkan protokol kesehatan dan 4 responden tidak menerapkan protokol kesehatan. Tujuan penelitian untuk mengetahui faktor-faktor yang berhubungan seperti pendidikan, pekerjaan, pengetahuan dan sikap dengan kepatuhan masyarakat dalam protokol kesehatan di era adaptasi kebiaan baru di Desa Cijagamulya Kecamatan Ciawigebang Kabupaten Kuningan Tahun 2020. 
Metode: Jenis penelitian observasional analitik dengan desain cross sectional. Populasi penelitian sebanyak 1.051 orang. Sampel penelitian menggunkan metode proportionate stratified random sampling sebanyak 110 responden. Penelitian ini dilaksanakan tanggal 03-13 Agustus 2020 di Desa Cijagamulya. Instrument yang digunakan dalam penelitian ini yaitu lembar kuesioner dengan wawancara secara langsung. Analisis data yang digunakan yaitu uji chi square.  Hasil: Hasil penelitian menunjukan bahwa dari 110 responden yang patuh terhadap protokol kesehatan sebanyak 41 responden (37,3%). Hasil uji statistik menunjukan bahwa ada hubungan antara pendidikan dengan p value 0,000, Pekerjaan dengan p value 0,000 dan 95%CI =3,400 (2,517- 4,592), Pengetahuan dengan p value 0,000, Sikap dengan p value 0,000 dan 95%CI =281,667 (54,159-1464,887).
Simpulan: Ada hubungan antara pendidikan, pekerjaan, pengetahuan dan sikap dengan kepatuhan masyarakat dalam protokol kesehatan di era adaptasi kebiasaan baru di Desa Cijagamulya Kecamatan Ciawigebang Kabupaten Kuningan Tahun 2020.
Pengaruh Kredensial Terhadap Kinerja Perawat di RSUD R Syamsudin, SH Kota Sukabumi
Authors: . Ida , Setiawan Asep , Dewi Rahmayanti Siti , Suryati Yayat , . Murtiningsih
Published: December 2024

Berdasarkan PMK No.40 tahun 2017 bahwa rumah sakit yang bertugas melakukan proses kredensial keperawatan wajib melakukan assessment kompetensi sesuai dengan kewenangan klinis keperawatan. Proses pelaksanaan kredensial dalam upaya peningkatan kinerja perawat di RSUD R Syamsudin, SH Kota Sukabumi perlu dilakukan kajian mendalam. Tujuan penelitian untuk mengetahui pengaruh kredensial terhadap kinerja perawat klinis level 1. Penelitian ini merupakan penelitian deskriptif komparatif diperoleh dari data sekunder yaitu data yang diambil tidak dari sumber langsung akan tetapi dari dokumen data kinerja perawat yang ada di komite keperawatan. Sampel dalam penelitian ini perawat klinis level PK I dengan jumlah 170 perawat. Instrumen penelitian yang digunakan kuesioner yang berlaku di RSUD R Syamsudin, SH Kota Sukabumi. Analisis data menggunakan Bivariat dengan Uji Paired Sampel T-Test dan Analisis of Varianve (Anova). Hasil penelitian terdapat pengaruh kredensial terhadap kinerja perawat perspektitif Growth, perspektif Customer focus, perspektif Business Process, persepektif Learning and Growth, perspektif kegiatan tambahan, Terdapat pengaruh kredensial terhadap kinerja perawat. Berdasarkan hasil penelitian direkomendasikan untuk melakukan penelitian dengan pengembangan Instrumen Kredensial dan Kinerja yang baku.
Implementasi Program Sekolah Siaga Bencana di Sekolah Dasar Desa Sinaresmi Kecamatan Cisolok Kabupaten Sukabumi
Authors: Novianti Utami Rima
Published: December 2024

Desa Sinaresmi pada tahun 2018 mengalami bencana longsor yang dapat menimbulkan banyak korban dan melumpuhkan beberapa bangunan salah satunya adalah bangunan sekolah, untuk itu perlu dikaji mengenai implementasi program sekolah siaga bencana. Tujuan penelitian ini, untuk mengetahui implementasi program sekolah siaga bencana di Sekolah Dasar Desa Sinaresmi Kecamatan Cisolok Kabupaten Sukabumi. Penelitian ini menggunakan pendekatan deskriptif analitik. Teknik penentuan informan yang digunakan dalam penelitian ini menggunakan purposive sampling yakni sebanyak 5 informan selaku kepala sekolah, guru dan murid. Analisis implementasi program sekolah siaga bencana dilakukan dengan deskriptif kualitatif yang mengintegrasikan keempat aspek diantaranya adalah parameter sikap dan tindakan, parameter kebijakan, parameter rencana tanggap darurat, dan parameter mobilisasi sumberdaya.  Hasil penelitian menunjukkan pada parameter sikap dan tindakan, sekolah-sekolah di Desa Sirnaresmi sudah diberikan pengetahuan bencana, namun dilakukan hanya sekali; berdasarkan parameter kebijakan belum terlaksana sepenuhnya; pada parameter rencana tanggap darurat belum maksimal, dibuktikan dengan adanya dua indikator belum terpenuhi mengenai penilaian kerentanan gedung/bangunan sekolah dan rencana aksi sekolah; pada parameter mobilisasi sumberdaya masih belum maksimal mulai dari segi bangunan, perlengkapan penunjang penanggulangan bencana, gugus siaga bencana, kerjasama, pemantauan dan evaluasi. Kesimpulan, implementasi sekolah program sekolah siaga bencana di Sekolah Dasar Desa Sinaresmi Kecamatan Cisolok Kabupaten Sukabumi belum diterapkan secara optimal.
Hubungan Persepsi Kepala Keluarga Tentang Covid-19 Dengan Tindakan Pencegahan Penularan Covid-19 di Kelurahan Sindangpalay Wilayah Kerja Puskesmas Limusnunggal Kota Sukabumi
Authors: Tresnawan Teten , Lidiyawati Herlina
Published: December 2024

Penelitian ini dilatar belakangi masih terjadinya penambahan kasus Covid-19 juga menyebabkan kematian khususnya di Kelurahan Sindang Palay Kota Sukabumi. Data Puskesmas Limus Nunggal sampai dengan bulan Maret 2021  menyatakan bahwa ada 1 orang meninggal dari total 80 pasen yang terkonfirmasi di Kelurahan Sindang Palay. Tujuan penelitian ini untuk mengetahui Hubungan Persepsi Kepala Keluarga tentang Covid-19 dengan Tindakan Pencegahan Penularan Covid-19. Jenis penelitian ini menggunakan studi korelasional dengan pendekatan cross sectional. Populasi dalam penelitian ini 1681 dengan sampel berjumlah 322 kepala keluarga. Cara pengambilan sampel menggunakan teknik Cluster Random Sampling. Analisis hipotesis menggunakan analisis Chi Square. Hasil penelitian menunjukan sebagian besar persepsi kepala keluarga dengan kategori baik, dan sebagian besar kepala keluarga melakukan tindakan pencegahan penularan Covid-19. Hasil uji Chi Square didapatkan P-Value 0,000 sehingga dapat disimpulkan terdapat hubungan antara persepsi kepala keluarga dengan tindakan pencegahan penularan Covid-19 dengan nilai P-Value < 0,05, maka Ho ditolak. Penelitian ini dapat disimpulkan bahwa terdapat hubungan antara persepsi kepala keluarga dengan tindakan pencegahan penularan Covid-19 sehingga hasil penelitian ini dapat dijadikan dasar dalam upaya peningkatan program kesehatan masyarakat melalui promosi kesehatan tentang pencegahan Covid-19.
Hubungan Dukungan Teman Sebaya Dengan Harga Diri Pada Remaja di SMPN 1 Jampangkulon Kabupaten Sukabumi
Authors: Indriani Kusumah Rani , Rahma Yanti Siti
Published: December 2024

Usia remaja merupakan usia dengan banyaknya kenakalan dan konformitas yang salah satunya disebabkan oleh teman sebaya. Tujuan penelitian ini adalah untuk menganalisis hubungan antara dukungan teman sebaya dengan harga diri pada remaja di SMPN 1 Jampangkulon Kabupaten Sukabumi.Remaja merupakan masa perkembangan yang memiliki perubahan dalam berbagai aspek dalam kehidupannya. Dukungan teman sebaya adalah dukungan yang berasal dari kelompok yang memiliki usia, hobi atau kebiasaan yang sama. Harga diri adalah hasil evaluasi seseorang mengenai dirinya sendiri, atau sikap seseorang mengenai dirinya yang berada dalam dimensi positif-negatif. Jenis penelitian ini menggunakan metode korelasional dengan pendekatan cross sectional. Populasinya adalah siswa/i kelas VII dan VIII SMPN 1 Jampangkulon Kabupaten Sukabumi, dengan sampel 187 responden menggunakan teknik simple random sampling. Analisa data menggunakan Koreksi Yates. Hasil penelitian didapatkan responden memiliki dukungan teman sebaya baik sebanyak 96,3%, dan responden yang memiliki harga diri postif sebanyak 96,3%. Hasil penelitian uji statistik menunjukan nilai P-value 0,000 yang berarti H0 ditolak, sehingga terdapat hubungan dukungan teman sebaya dengan harga diri pada remaja.Penelitian ini disimpulkan bahwa terdapat hubungan antara dukungan teman sebaya dengan harga diri di SMPN 1 Jampangkulon Kabupaten Sukabumi. Diharapkan instansi pendidikan dapat memasukan topik mengenai dukungan sosial teman sebaya maupun tentang harga diri di program konseling sekolah.
Hubungan Perubahan Fungsi Seksualitas Dengan Frekuensi Hubungan Seksual Pada Lansia Wanita Usia 45-59 Tahun di Kelurahan Tipar Wilayah Kerja Puskesmas Tipar Kota Sukabumi
Authors: Octascriptiriani Nuur , Putri Kusuma
Published: December 2024

Masalah kesehatan pada lansia wanita mengenai kesehatan reproduksi salah satunya penurunan fungsi organ reproduksi. Tujuan penelitian untuk mengetahui hubungan perubuhan fungsi seksualitas dengan frekunsi hubungan seksual pada lansia Wanita usia 45-59 tahun di kelurahan tipar wilayah kerja puskesmas tipar kota sukabumi. Desain penelitian korelasional dengan pendekatan cross sectional. Populasi adalah lansia wanita usia 45-59 tahun dengan jumlah sampel 285 lansia wanita dengan cluster random sampling. Uji hipotesis menggunakan chi-square. Hasil penelitian, sebagian besar mengalami disfungsi seksual sebanyak 188 orang (72,3%) dan tidak aktif melakukan hubungan seksual sebanyak 137 orang (52,7%). Terdapat hubungan antara perubahan fungsi seksualitas dengan frekuensi hubungan seksual pada lansia wanita usia 45-59 tahun dengan Chi Square P value  =0,000. Simpulan terdapat hubungan antara fungsi seksualitas dengan frekuensi hubungan seksual pada lansia wanita usia 45-59 tahun di Kelurahan Tipar Wilayah Kerja Puskesmas Tipar Kota Sukabumi. Disarankan kepada puskesmas Tipar untuk melakukan konseling mengenai sistem reproduksi serta konseling mengenai aktivitas seksual pada lansia, karena aktivitas seksual pada lansia merupakan kebutuhan dasar yang bertujuan untuk menjaga keharmonisan keluarga.
Pengaruh Dukungan Suami, Motivasi Dan Self Eficacy Terhadap Kepatuhan Dalam Pemeriksaan AnC (Antenatal Care) di Kelurahan Nangeleng Wilayah Kerja Puskesmas Nangeleng
Authors: Fauzia Laila Eka
Published: December 2024

Kepatuhan ibu dalam kunjungan antenatal care (ANC) merupakan ketaatan dalam melakukan kunjungan kepelayanan kesehatan oleh ibu hamil sesuai dengan saran dari petugas kesehatan dengan standar yang sudah di tetapkan yaitu minimal 4 kali dalam masa kehamilan dapat dipengaruhi oleh dukungan suami, motivasi serta self efficacy. Tujuan penelitian untuk mengetahui pengaruh dukungan suami, motivasi, dan self efficacy terhadap kepatuhan dalam pemeriksaan antenatal care (ANC) pada Ibu Hamil. Antenatal Care adalah pengawasan kehamilan untuk mengetahui kesehatan umum ibu, menegakkan secara dini penyakit penyerta, komplikasi, dan menetapkan resiko kehamilan (resiko tinggi, resiko meragukan dan resiko rendah). Desain penelitian adalah korelasional dengan pendekatan cross sectional. Populasi penelitian adalah ibu hamil dengan sampel 30 orang ibu hamil dengan Total Sampling. Hasil penelitian, analisis koefisien regresi linier berganda terdapat pengaruh yang signifikan  ketiga variabel dukungan suami, motivasi dan self efficacy terhadap kepatuhan dalam pemeriksaan ANC (Antenatal Care). Hal ini ditunjukkan dengan nilai p-value (sig.) pada uji koefisien regresi bernilai 0,000 nilai ini kurang 0.05 Terdapat pengaruh dukungan suami, motivasi, dan self efficacy terhadap kepatuhan dalam pemeriksaan antenatal care (ANC) pada Ibu Hamil. Simpulan terdapat pengaruh secara simultas pengaruh dukungan suami, motivasi dan self efficacy terhadap kepatuhan dalam pemeriksaan ANC (Antenatal Care). Diharapkan untuk meningkatkan pendidikan kesehatan dan promosi kesehatan terkait kepada ibu hamil, suami dan keluarga betapa pentingnya pemeriksaan kehamilan atau ANC (Antenatal Care) yang di dukung oleh dukungan suami, motivasi dan self efficay yang baik, agar ibu sehat serta bayi selamat untuk menurunkan resiko masalah pada kehamilan ibu.
Hubungan Pola Asuh Gizi Balita Dengan Status Gizi Anak Balita di Kelurahan Cipanengah Wilayah Kerja Puskesmas Cikundul Kota Sukabumi
Authors: Utami Shinta , Wahyuni Septica Qorry
Published: December 2024

Masa balita adalah masa pertumbuhan sehingga memerlukan gizi yang baik. Salah satu faktor yang mempengaruhi status gizi balita adalah pola asuh gizi balita. Tujuan penelitian adalah mengetahui hubungan pola asuh gizi balita dengan status gizi balita di Kelurahan Cipanengah Wilayah Kerja Puskesmas Cikundul Kota Sukabumi. Desain penelitian yang digunakan adalah korelasional dengan pendekatan cross sectional. Populasi penelitian adalah ibu balita dengan jumlah sampel 215 responden menggunakan cluster random sampling. Analisis hipotesis menggunakan chi square p-value=0,000. Hasil penelitian menunjukkan bahwa sebagian besar menerapkan pola asuh demokratis sebanyak 147 orang dan status gizi balita normal sebanyak 185 balita. Terdapat hubungan antara pola asuh gizi balita dengan status gizi balita. Simpulan terdapat hubungan antara pola asuh gizi balita dengan status gizi balita. Saran bagi pihak puskesmas yaitu untuk mempertahankan status gizi yang baik untuk balita dengan lebih operasional dalam menjalankan promotif dan preventif seperti diadakannya lomba balita sehat, jadi ketika diadakan lomba oleh petugas kesehatan ibu bisa diarahkan mengenai perilaku dalam pemberian gizi khususnya kepada balita.
Comparison of Anterior Chamber Depth before and after Cataract Surgery by Phacoemulsification with IOL Implantation
Authors: Ayoub Nimra , Nadeem Aleena , Najam Muhammad Hamza , Zulfiqar Nabila , Iqbal Sara
Published: December 2024

Objective: The purpose of this study was to compare the changes in anterior chamber depth before and after cataract surgery by phacoemulsification with posterior chamber intraocular lens implantation.
Methodology: This was comparative pre and post-operative observational study in which 75 patients included who underwent for cataract surgery via phacoemulsification with posterior chamber IOL implantation. ACD is measured on A-scan before surgery and after surgery at 1 week and 1 month.
Results: Out of 75 patients who participated in this study, there were 31 (41.3%) males and 44 (58.7%) females. The mean anterior chamber depth increased from 2.9548 ± 0.41785 mm to 3.1928 ± 0.31698 mm with a mean increase of -0.23800 ± 0.44520 mm. There was statistically significant difference in the mean change anterior chamber depth.
Conclusion: The anterior chamber was deepened by phacoemulsification and IOL implantation.
Key words: Cataract, Anterior chamber depth, Phacoemulsification
PEMBERDAYAAN KADER DALAM UPAYA PENCEGAHAN MALARIA PADA IBU HAMIL DI PUSKESMAS ARSO KOTA KABUPATEN KEEROM
Authors: Muji Lestari  , Sri Wahyuni  , Eka Setyaning Suci
Published: December 2024

The incidence of malaria in pregnant women in Keerom Regency in 2020 was 75 people, in 2021 it was 48 people and in 2022 it rose again to 77 people. Arso Kota Community Health Center is a community health center where the incidence of malaria in first-time pregnant women has been quite high in the last three years, namely 12 people in 2020, then decreased to 10 people in 2021 and increased again in 2022 to 21 people.   The aim of this community service activity is to assist the Community Health Center in reducing malaria rates in pregnant women by empowering cadres.
The method used is to empower malaria cadres by providing education about malaria prevention, malaria diagnosis and malaria management using a pocket book. Cadres are also trained to carry out RDT checks.  The results showed that knowledge about malaria among the cadres who were trained increased on average, where the average pre-test score was 70 and the average post-test score was 90. The level of skill in carrying out RDT examinations for cadres increased, where the pre-test skill score was 60 and the post test skills score was 95. Conclusion This activity was successful in increasing the knowledge and skills of malaria cadres in preventing malaria in pregnant women at the Arso City Community Health Center. Continuation of this program is highly recommended to maintain the results achieved.
Peran Pancasila dalam Pembentukan Undang-Undang Anti- Terorisme di Indonesia
Authors: Ashfiya Nur Atqiya  , Ahmad Muhamad Mustain Nasoha  , Cintya Bella Marathusholia  , Zahra Riyani Aulia  , Melia Agustina Ramadhani
Published: December 2024

This research discusses how Indonesia can integrate Pancasila values in anti-terrorism policies, amidst international pressure which often leads to harsher approaches based on the standards of Western countries. An approach that prioritizes security can conflict with Pancasila principles, such as respect for human rights and social justice. Pancasila as the basic ideology of the state emphasizes the importance of balance between individual rights and the interests of society. In facing the threat of terrorism, Indonesia needs to adopt policies that not only strictly enforce the law, but also prioritize prevention through education, community empowerment and strengthening human values. This research aims to analyze how Pancasila values are implemented in Indonesia's anti-terrorism policy and the challenges that arise in harmonization with international norms. Globalization and technological developments pose new challenges in the spread of radical ideology, so policies are needed that are responsive but still based on Pancasila. Indonesia's anti- terrorism legal policy must be able to balance tough law enforcement with a humanist and dialogical approach, in line with the spirit of Pancasila which upholds just and civilized humanity. It is hoped that this research can contribute to more humane and effective policies.
Enhancing Immutable IoT Data Collection through Distributed Reinforcement Learning Framework
Authors: M. Shakila  , A. Rama  , Anitha Govindaram  , A. Jegatheesan  , Karpagam V  , S. Christy
Published: December 2024

The Intelligent Mobile Data Collection (IMDC) framework is presented in this study for use in IoT-based sensor networks. Clusters of nearby Internet of Things (IoT) devices and sensors are organised using this approach. A gateway node acts as the coordinator of each cluster and is responsible for gathering information from its members, processing it, and then sending it on to the main data collector (MDC). In order to examine trends in data creation, the framework uses a labelling method called FRL (Very Rare Labels). Time intervals, packet numbers, and types are some of the parameters that can be used to classify clusters using these labels. Local models that take into account states, actions, and rewards are developed by individual Internet of Things (IoT) sensors or devices within the FRL framework using reinforcement learning (RL) approaches. After collecting data from various regional models, the gateway compiles it into a global model and returns it to the IoT-Internet of Things sensors. In addition, the framework uses cluster categories to find the MDC's sleep length, visitation time, and Time Division Multiple Access (TDMA) slots, among other factors. This framework's efficacy in lowering latency and energy usage during data collecting and enhancing accuracy is demonstrated by its implementation using NS2.
CrTDL: An Advanced Deep Learning Framework for Intrusion Detection in Wireless Sensor Networks
Authors: K. Nitya  , S. Venkatesan  , B. Nancharaiah
Published: December 2024

The Wireless Sensor Network stands out as a highly practical framework for a diverse array of social network interactions. In communication within the WSN network, data transmission distances play a crucial role in facilitating information exchange among network nodes. However, the open and mobile nature of the WSN environment introduces security concerns and energy usage restrictions. Consequently, an effective security system becomes imperative for the WSN network to guarantee secure data transmission between nodes. In a WSN setting, this article suggested -attack security prevention. Three phases are included in the proposed Cryptographic Transductive Deep Learning (CrTDL) scheme. For data encryption and decryption, attributes-based homomorphic cryptography is initially used. Second, the network employs the deep learning approach. Finally, the WSN network uses the Markov process is applied in a transductive deep model to avoid and categorise attacks. A concealed Markov model was employed to assess the produced data in order to detect attacks. The reinforcement learning model is used to compute and process the detected attack. The suggested CrTDL is subjected to simulation analysis using traditional ANN, CNN, and RNN models.
The Role of E-CRM Systems in Strengthening Bank-Customer Relationships: Evidence from Visakhapatnam Banks
Authors: Suchitra M S  , Dr. Pratima Merugu
Published: December 2024

This study report delves into the impact of E-CRM systems on improving bank-customer interactions, specifically examining a few banks in Visakhapatnam. The purpose of this research is to find out how electronic customer relationship management (E-CRM) systems affect customer happiness and loyalty and how they help banks build deeper ties with their customers. Bank clients were surveyed and bank personnel were interviewed as part of a mixed-methods approach to data collection. Personalised communication, customer assistance, and data management were some of the E-CRM characteristics that were evaluated in the study. Banks in Visakhapatnam shared their implementation plans and the difficulties they encountered in interviews. By providing individualised services, improving communication, and elevating the customer experience as a whole, E-CRM systems considerably boost consumer engagement, according to the findings. In addition, the research pinpoints the role of technological infrastructure, employee training, and customer feedback mechanisms as critical determinants of E-CRM system efficacy. Based on these results, it seems that good E-CRM practices are essential for banks to create and maintain strong connections with their customers, which in turn increases customer loyalty and retention. At the conclusion of the study, the authors provide some suggestions on how banks may improve their E-CRM strategies to stand out in a crowded banking market, while also strengthening connections with their clients.
Revolutionizing Interaction: Python-Driven Speech Assistant Powered by Long Short-Term Memory (LSTM)
Authors: Mithun B.Patil  , Vipul V.Bag  , Santosh D Jadhav  , Namrata S. Jadhav  , Shraddha L. Kolhapure  , Vidya S. Ingaleshwar
Published: December 2024

This research is the dispensation of a choice-based voice-driven system built around Python which embraces machine learning algorithms in improving user experience. Don’t forget that Python is a language that is very rich in libraries and open-source resources. Voice assistant goes to the point by bringing speech recognition, natural language processing (NLP), and algorithms working based on machine learning allowing us users to give voice commands and get help from them. This implementation includes many functions, take the example of opening web browsers, playing music, checking weather forecasts, and answering normal questions to mention just a few, all by voice without any physical effort at all. User’s voice assistant offers a lot of configuration flexibility very specifically tuned to users’ preferences and requirements. Additionally, the same assistant tackles accommodation issues by being an invaluable and vital tool for individuals with disabilities who aim to visit the digital realms. Therefore, it allows people with disabilities to participate in the virtual environment alongside everyone else. Although the adoption of complex auditory recognition and NLP applications involves certain challenges including the consumption of more computing resources and concerns related to voice data storing and processing, they bring unique opportunities. Nevertheless, our project reminds the strengths of Python as a development platform by analyzing the capabilities of such systems to be built on Python which in turn reinforces its leadership pectiniform what we have analyzed, our research builds on the growing trend of voice-first systems, offering users a much greater level of satisfaction and inclusion in the digital world. Through human-centric design thought principles and ethics considerations, we see a prospect in which voice assistants become more fulfilling devices that will cause comfortable and natural man-machine communication and make the users more delighted in any domain it is used.
Revolutionizing Emotion-Driven Sentiment Analysis using Federated Learning on Edge Devices for Superior Privacy and Performance
Authors: Manisha S. Otari  , Deepika Patil  , Mithun B. Patil
Published: December 2024

People constantly connect, generating vast unstructured data that edge devices can process. Emotion recognition and sentiment analysis are becoming more popular because of the need to study this data to understand how people act. Traditional machine learning algorithms need to centralize data to train models, making it harder to comply with GDPR and build user trust.
 Federated Learning (FedL), is a decentralized method that improves data protection and privacy while following GDPR rules.  A real Federated learning framework is designed and developed to demonstrate the concept of on-device emotion prediction instead of a simulated framework.
This study utilizes the extensive GoEmotions dataset, comprising 58,000 hand-labeled English Reddit comments across 27 distinct emotion categories, including "neutral." A FedL-based projected attention neural network model is proposed. This model combines trainable projections with attention and convolutions in a federated setting. The proposed model is tested on several users' social interaction comments to uncover the true feelings and emotions underlying them. The test results demonstrate that the design and development of the FL framework is successful and our model performs very near to standard models. The proposed model acquires 12% better precision with an accuracy similar to the non-FedL PRADO model. The main challenge of time required for model training per epoch in a federated learning environment is near the non-FedL PRADO. Our method performed almost as well as the best methods on long texts. These findings show that the suggested FedL-based projected attention neural network can pick up on subtle mood differences while still protecting data privacy and security.
Empowering Health Prognosis: Quine Mccluskey Binary Classifier Algorithm for Predicting Heart Disease
Authors: Shanthi Makka  , S. Bharath Reddy  , Preeti Jaidka  , R. Raja Kumar  , Asma Begum
Published: December 2024

Numerous researchers employed the Quine McCluskey Binary Classifier (QMBC) for rapid identification of cardiac patients. These integrated models, including decision trees, random forests, K-nearest neighbors, naive Bayes, support vector machines, and multilayer perceptron’s, demonstrate effective performance on binary classification datasets. Use chi-square, analysis of variance, and principal component analysis to find and select features for predictive modeling. The ensemble model uses the Minimum Boolean expression from the seven models, works better than the best methods that are currently available. The collection includes examples from Cleveland HD, HD Comprehensive, and CVD. Its main goal is to improve accuracy by using advanced ensemble methods. In addition, a more in-depth study looks into how to combine Voting Classifier and Stacking Classifier, with the goal of reaching 100% accuracy. This paper adds to the field by introducing a strong method called QMBC and showing how strategic ensemble methods can be used to improve performance even more.
Optimization of the Agroindustrial Process through Image Segmentation Techniques for the Detection of Affected Leaves
Authors: Joan P. Cobeña Cevallos  , María Verónica González Cabrera  , Luis Stalin López Telenchana  , Julie Andrea Gil Gómez
Published: December 2024

This study investigates the implementation of advanced image processing techniques, specifically color-based segmentation using K-Mean Clustering, to optimize agroindustrial processes by enhancing the detection of foliar diseases in crops. The research demonstrates a significant improvement in the precision of disease detection, achieving a 92% accuracy rate compared to traditional visual inspection methods, which showed only 75% accuracy. Additionally, the use of these techniques reduced detection time by 75%, allowing for faster and more effective interventions. The economic analysis revealed a 20% reduction in operational costs and a 12% increase in net profitability, highlighting the financial viability of adopting these technologies. The study also addresses the challenges associated with implementation, such as environmental variability and the need for adequate infrastructure. It concludes that while these technologies offer substantial benefits in terms of operational efficiency and sustainability, their successful adoption depends on overcoming these challenges and providing adequate support to farmers.
Motivation of Teachers Teaching English in Public and Private Schools
Authors: Isabel Bejarano Restrepo
Published: December 2024

This bibliometric review analyzes the scientific production related to the variables of school education, teachers, and motivation, as registered in the Scopus database during the period 2018-2023 by Latin American institutions. The primary objective of the study was to identify and characterize the volume of publications, resulting in a total of 169 documents. The information collected was organized using graphs, categorizing it by year of publication, country of origin, area of knowledge, and type of publication. The results indicate that Brazil is the Latin American country with the highest number of publications, with a total of 53 scientific papers. The Social Sciences area demonstrated the greatest productivity in terms of bibliographic contribution, with 110 documents. Journal articles accounted for 75% of the total publications. This analysis also includes a qualitative study on the positions of various authors in relation to the topics addressed, providing a comprehensive view of the current state of research in this field. Among the principal findings is the conclusion that a motivated teacher will be of fundamental importance in the student's learning process. This is because the teacher becomes a role model, which stimulates and facilitates active participation in the classroom.
Energy Efficient Virtual MIMO Communication Designed for Cluster Based on Cooperative WSN using OLEACH Protocol
Authors: Shitiz Upreti
Published: December 2024

To monitor physical conditions, wireless sensor networks (WSNs) employ a large number of sensor nodes. These nodes have limited energy resources that is major issue in wireless communication systems. Virtual MIMO (vMIMO) is a technology that can enhance energy efficiency in WSNs by transmitting or receiving data from numerous nodes, enhancing signal quality, and lowering power. This research offers Energy-Efficient Virtual MIMO Communication (EE-VMC), a novel solution to addressing the energy efficiency dilemma in Wireless Sensor Networks (WSNs). EE-VMC presents a viable option for long-term deployments in cluster-based cooperative WSNs by exploiting virtual Multiple-Input Multiple-Output (MIMO) communication. The suggested method employs an optimized LEACH (OLEACH) protocol to promote energy efficiency by promoting effective communication while minimizing energy consumption. The simulation findings show that the OLEACH algorithm performs well in wireless sensor networks. At an SNR of -10dB, OLEACH has the highest Packet Delivery Ratio (PDR), showing improved performance in low signal-to-noise ratio conditions. Increasing the number of antennas also improves OLEACH's data delivery performance. When compared to state-of-the-art protocols (LEACH, HEED, BRICH, and B-LEACH), OLEACH regularly beats them in terms of PDR, SNR values, and data transfer rounds. Furthermore, OLEACH has greater remaining energy levels, indicating better energy management and increased network lifespan. The results back up the conclusion that OLEACH is a promising algorithm for optimizing energy consumption, improving packet delivery, and improving overall network performance in wireless sensor networks.
Digital Marketing Strategies In The Age Of Social Media: A Comparative Study Of Global Brands
Authors: Nargis Parveen  , Rima Osama Mohammad Othman  , Dima Mahmoud Aref Abbadi  , Esraa M. Al-Lobani  , Hina Skhawat  , Muhammad Skhawat Ali  , Khaled Mejdi
Published: December 2024

This paper discusses the way in which global brands adopt social media to execute digital marketing activities keeping culture subtleties, and market-specific interest intact. The research investigates various strategies of the firms from a broad spectrum, exploring how social media is overhauling traditional marketing in to less-expensive, more sophisticated and interactive ways their brands interface with consumers. The results also show the importance to customize content and strategies based on local consumer behaviour as well as maximize engagement or visibility through built in platform features. What is more, the research highlights how essential data analytics has become in enhancing marketing strategies so that brands reach their audience with even better intent-driven campaigns. The document investigates the world landscape of social media marketing and offers information on what works in various places, finding out how to combine cultural adaptability with strategic use from online tools to expand brand awareness & connect along with consumers.
Remote Patient Health Monitoring Using Iot And Artificial Intelligence
Authors: Tumrugoti Satish Kumar  , Dr. G Anil Kumar  , Dr. Amjan Shaik
Published: December 2024

There is a chance for extremely intelligent and clever IoT-based use cases in the modern period thanks to developments in ICTs like Cyber-Physical Systems (CPS), 5G cellular technology, and the Internet of Things (IoT). As IoT enables Ambient Assisted Living (AAL), Mobile Health (mHealth), and Electronic Health (eHealth), one such use case with a significant social impact is healthcare. People devote a large portion of their income to their health. In addition to resulting in patient deaths, traditional healthcare services are prone to delays, waste of time, and financial loss. When used in conjunction with the IoT's intelligence and prediction capabilities, regular Remote Patient Monitoring (RPM) at home, work, or at a hospital can help individuals who specifically require it overcome obstacles presented by traditional healthcare facilities. Wearable technology, sensor networks, and other digital infrastructure are used in IoT-based RPM can serve as a precursory warning system for approaching situations that, if ignored or care is postponed, could result in serious health problems or even patient death. Doctors can receive real-time patient vital signs through wearable devices (biosensors) with IoT integration. That way, medical professionals can start treating patients right away. The term "RPM" refers to this occurrence, which has the potential to reduce wait times, save healthcare expenses, and enhance patient comfort and service quality. In order to implement a Remote Patient Monitoring System (RPMS) with data analytics capabilities, this paper aims to develop an Internet of Things (IoT) and Artificial Intelligence (AI) enabled framework. We implemented RPM for data collection and proposed an algorithm for disease diagnosis. Our experimental results revealed that our method outperforms existing methods.
Exploring Investment And Economic Growth In Global Prospective: A Technology Based Development Model
Authors: Manoj Kumar Mishra  , Ravi Kanth Makarla  , Salim Ahmed Alshehri  , Nimmagadda Lakshmi Gayathri  , Binita Kumari
Published: December 2024

This paper studies an upgraded neo-classical model and board information examination from 1995 to 2020 in the context of physical and human capital investment based on panel data. The outcomes affirm that both physical, and human capital are significant for development as is anticipated under neo-traditional hypothesis but investment in human capital is more important for economic growth. In truth, financial opportunity drives development by empowering interest in human resources. Financial opportunity increments human resources venture, which is a critical driver of development. Our outcomes feature the significance of institutional quality in deciding monetary results, and an expected pathway by which worked on financial institutionality — reasonable supported by better political establishments, for example, more prominent opportunity or contestability empowers human resources improvement which prompts higher development rates. Policy makers are urged to explore policies and strategies on enhancing institutional frameworks in creating the enabling environment for investment inflow as well as achieving sustainable economic development.
Machine Learning In Bioinformatics: Disease Prediction Models
Authors: Dr. T. Ravi  , Amar Pal Yadav  , Dr. Syed Salim  , K.Sony  , Dr S. Asif Alisha  , Dr. Khalid Nazim Abdul Sattar
Published: December 2024

This paper discuss machine learning applied in bioinformatics, particularly focusing on models to predict the occurrence of diseases using disease diagnosis with improved accuracy and with the possibility of biomarkers for heart disease, Alzheimer's, and cancer among others. Utilizing deep neural networks, hypergraph learning, and transformer-based methods, models are assessed against datasets developed from genetic sequences and medical records. Among the most important findings is a 15% improvement in predictive accuracy for the prediction of miRNA-disease association and 12% reduction in false positives using a transformer-based model, particularly to detect heart disease, while selecting genes by feature screening in Alzheimer studies showed specificity at 91%, thus providing a means of accurately identifying genetic markers. In summary, this works of research exemplify the effectiveness of hybrid techniques that combine the power of digital twins and ensemble learning for dependable data and potentially large-scale generalizability across models. In the future, optimization towards real time applications and wider use cases in precision medicine are envisioned. The contributions of the study affirm the vital role machine learning plays in predictive bioinformatics - a pathway to further accurate diagnostics and personalized treatment plans.
Evaluating The Impact Of EGR On Butanol-Diesel Blends In A CRDI Engine: Performance And Emission Analysis
Authors: Ganesh Vantepaka  , Boda Hadya
Published: December 2024

The study evaluates the performance and emission characteristics of a single-cylinder CRDI research engine using Pure Diesel (PD) and butanol-diesel blends (B10, B20, and B30) under varying Exhaust Gas Recirculation (EGR) rates (0%, 10%, 20%, and 30%). Among the tested fuels, B20 exhibits the most balanced performance, achieving a favorable Brake Thermal Efficiency (BTE) while maintaining manageable emission levels. Although BTE generally decreases with higher butanol content due to its lower calorific value, B20 shows a moderate increase in Brake Specific Fuel Consumption (BSFC) compared to pure diesel, with less of a trade-off in efficiency than B30. Emission results indicate that HC and CO emissions increase with rising EGR rates and higher butanol percentages, but B20 maintains lower emissions compared to B30 across all EGR levels. Additionally, B20 effectively reduces NOx emissions due to the cooling effect of butanol and controlled combustion temperatures, particularly at higher EGR rates. Overall, B20 strikes an optimal balance between performance and emissions, demonstrating its potential as a viable alternative fuel blend for enhancing engine efficiency while minimizing environmental impact.
Market Efficiency on Trial- A Semi-Strong Form Analysis of BSE
Authors: R Madhusudhanan , Dr. D. Senthilkumar
Published: December 2024

This study examines the reaction of stock market returns in relation to dividend announcements, using BSE SENSEX company’s information. Samples from BSE SENSEX selected 30 companies have been selected for research. The Market Model using Average Abnormal Return (AAR) and Cumulative Average Abnormal Return (CAAR) are tested for the period of from 1ST APRIL 2013 TO 31ST MARCH 2023. Event window of 31 days, 15 days before and 15 days after the announcement is used. Event day is represented by 0. Estimation window is used 120 days before the event window. Findings indicate that AAR shows BSE Sensex index that have been declined. The study concluded that BSE Sensex coefficients are negative and cannot fully reflect the changes on the stock price. Therefore, the BSE SENSEX is not in Semi Strong form efficiency. Finally, BSE SENSEX companies react inefficiently in releasing of information of dividends announcements.
Audio Transmission Through Li-Fi Using Nodemcu
Authors: Sampoornam K P  , Kalaivani R  , Vaishnavi V  , Sobika S K  , Vinothini R
Published: December 2024

In today's interconnected world, the proliferation of wireless devices accessing the internet continues to surge, leading to escalating network complexity and a strain on available wireless radio bandwidth. This surge also raises concerns about the potential for interference in radio frequencies, which can compromise the reliability and security of data transmission. However, Li-Fi technology offers a promising solution by using light-emitting diodes for data transmission. Li-Fi operates by using LEDs as transmitters and photodiodes as receivers, utilizing light waves to carry data instead of traditional radio frequencies. The use of light for data transmission not only enhances security but also mitigates concerns about radio frequency interference. Moreover, the rapid advancements in LED manufacturing have led to the development of highly efficient, durable, and long-lasting LEDs, making them suitable for both private lighting and data transmission purposes. The effectiveness of Li-Fi is further underscored by its ability to achieve data transmission rates of several gigabits per second (GBPS), surpassing many existing wireless technologies. Consequently, the implementation of Li-Fi technology holds immense potential for revolutionizing communication systems, particularly in environments where security, speed, and reliability are paramount. The design and implementation of Li-Fi audio transmission systems exemplify the innovative applications of this cutting-edge technology, offering a glimpse into the future of wireless communication. As research and development in Li-Fi continues to progress, the possibilities for its integration into various industries and everyday applications are limitless, paving the way for a more efficient and interconnected world.