Abstract:Psychological measurement tools are fundamental in sports psychology for assessing mental toughness, performance anxiety, motivation, and resilience in athletes. Despite increasing research in this field, a comprehensive…
bibliometric analysis of global trends, collaboration networks, and thematic developments remains limited. This study conducts a bibliometric analysis of 489 Scopus-indexed articles published between 1977 and 2025 to examine publication trends, key contributors, and thematic structures. Results indicate that the United States (32.5%), United Kingdom (15.8%), Germany (9.6%), and Canada (7.3%) are the leading contributors, with emerging research from Slovenia (2.1%) and Uruguay (1.7%). Institutional collaborations highlight strong interdisciplinary ties, particularly between the Center for Addictive Disorders and the Faculty of Medicine and Health. Co-authorship analysis identifies Nikos Ntoumanis (98 publications) and Jennifer Cumming (76 publications) as pivotal researchers, while citation network analysis highlights influential clusters led by Joan L. Duda (4,532 citations) and Andreas Ivarsson (3,215 citations). Bradford’s Law identifies Psychology of Sport and Exercise and Journal of Applied Sport Psychology as core journals. Thematic mapping reveals that mental toughness (18.4%) and resilience (14.7%) are dominant topics, while psychometrics (6.3%) and competitive anxiety (5.1%) remain underexplored. These findings provide strategic insights for enhancing global research collaboration, bridging psychological theory and practice, and guiding future research directions in sports psychology.
Abstract:The Malacca Strait is a vital maritime route that faces significant challenges from high traffic volumes and increasingly frequent extreme weather scenarios. These conditions pose serious risks to navigational safety, environmental…
vironmental integrity, and maritime operational security. This study aims to analyse the needs and components of a robust maritime surveillance architecture in the Malacca Strait, particularly in dealing with the impacts of extreme weather and climate change. Additionally, this research will explore the role of geospatial maritime intelligence in enhancing situational awareness and response to maritime incidents. The study findings indicate that a resilient surveillance architecture in the Malacca Strait requires the integration of advanced sensor systems (including multi-spectral radar and meteorological/oceanographic sensors), redundant communication networks, and AI/ML-based intelligent data processing. The adaptive capabilities of the system, including the use of UAVs and USVs, are critical to maintaining operational effectiveness in adverse weather conditions. Additionally, international cooperation and a robust policy framework, encompassing climate change adaptation and ethical considerations, are fundamental to the successful implementation and sustainability of surveillance systems. The Malacca Strait case study highlights specific vulnerabilities and proposes concrete solutions, illustrating a shift from a reactive to a proactive paradigm in maritime security. Building a resilient surveillance architecture in the Malacca Strait is a strategic imperative to safeguard global trade, regional stability, and environmental sustainability amid increasing climate uncertainty. Integrating cutting-edge technology with robust policies and international collaboration will ensure the safety and security of this vital waterway, making it a model for resilient maritime governance globally. A new aspect emphasised is the importance of adapting to climate change and the role of AI in predictive decision-making. This article presents a comprehensive and integrated approach to building a resilient maritime surveillance architecture, with a particular focus on the challenges of extreme weather in the Malacca Strait. Its originality lies in its emphasis on multi-sensor data fusion, the role of artificial intelligence in predictive analytics, and the integration of climate change adaptation into surveillance system design. Additionally, the article underscores the importance of a robust policy framework and international cooperation as the cornerstones of maritime surveillance resilience, offering a blueprint applicable to other critical maritime routes worldwide
Abstract:This study evaluates the effectiveness of the East Java Province DPMPTSP marketing communication strategy in investment promotion in 2023, focusing on the marketing mix elements: product, price, place, and promotion. Through…
ough a qualitative approach, this study analyzes promotional activities that include the development of promotional materials, expansion of international networks, and strengthening of regional branding. The results of the study indicate that innovative efforts in developing promotional materials using the latest technology and interactive approaches have been carried out. However, an in-depth evaluation is needed to ensure the effectiveness of promotional materials in meeting investor needs. Price transparency, although not explicitly focused on, is important for investment decisions. This study recommends improving information related to investment costs and incentives.
International cooperation, such as with the State of Neuvo Leon-Mexico, shows efforts to expand investment networks and global market visibility, with an evaluation of the benefits and costs required. Promotional activities such as seminars on investment strategies focus on strengthening regional branding and effective promotional techniques. The novelty of this study lies in the comprehensive analysis of marketing mix elements in the context of investment promotion as well as recommendations for continuous adaptation according to market changes. These findings provide new insights for the development of more effective investment marketing communication strategies in the future.
Abstract:Gangguan tidur seperti insomnia dan sleep apnea merupakan masalah kesehatan global yang dapat menurunkan kualitas hidup. Deteksi dini terhadap gangguan ini penting dilakukan, khususnya dengan bantuan teknologi seperti algoritma…
goritma data mining untuk meningkatkan ketepatan diagnosis. Data mining adalah bagian esensial dari analitik data dalam disiplin ilmu data science, yang memberikan berbagai manfaat luas dan aplikasi yang relevan. Penelitian ini menggunakan dataset Sleep Health and Lifestyle dari Kaggle untuk mengevaluasi kinerja tiga algoritma data mining, yaitu Naïve Bayes, Support Vector Machine (SVM), dan Neural Network, dalam mengklasifikasi gangguan tidur. Proses pengembangan model mengikuti tahapan CRISP-DM dengan pengujian akurasi menggunakan Cross Validation dan evaluasi menggunakan Confusion Matrix dan kurva ROC. Berdasarkan hasil pengujian, algoritma Neural Network menunjukkan kinerja terbaik dengan akurasi 93,08% dan nilai AUC yang termasuk dalam klasifikasi "Excellent." Temuan ini menunjukkan bahwa Neural Network efektif dalam mengklasifikasi gangguan tidur, sehingga dapat mendukung proses diagnosa dan penanganan gangguan tidur secara lebih akurat.
Abstract:Stunting pada balita merupakan permasalahan kesehatan masyarakat yang serius dan memerlukan penanganan segera melalui deteksi dini yang akurat. CNN (Convolutional Neural Network) merupakan metode yang akurat, efektif dan…
tepat sasaran dalam memberikan hasil yang akurat dan presisi. Implementasi metode CNN dapat mengklasifikasikan status stunting pada balita berdasarkan parameter antropometri dan karakteristik kesehatan. Dataset yang digunakan terdiri dari 6.500 sampel data balita dengan 8 variabel meliputi jenis kelamin, usia, berat lahir, panjang lahir, berat badan, panjang badan, riwayat ASI eksklusif, dan status stunting. Metodologi yang digunakan melibatkan serangkaian tahapan preprocessing data termasuk standardisasi fitur menggunakan StandardScaler, pemisahan data training (80%) dan testing (20%), serta penggunaan arsitektur CNN yang terdiri dari layer konvolusi 1D dengan 32 filter, max pooling, dan dense layer. Model dilatih menggunakan optimizer Adam dengan fungsi loss categorical crossentropy selama 10 epoch dan batch size 32. Evaluasi performa model dilakukan menggunakan berbagai metrik termasuk accuracy, precision, recall, dan F1-score.
Hasil penelitian menunjukkan bahwa model CNN yang dikembangkan mencapai performa yang sangat baik dengan akurasi 90%, precision 89%, recall 92%, dan F1-score 91%. Analisis confusion matrix mengkonfirmasi kemampuan model dalam mengklasifikasikan kedua kelas yaitu pada stunting dan non-stunting secara seimbang. Temuan ini mengindikasikan bahwa implementasi CNN efektif dalam mengidentifikasi status stunting pada balita dan berpotensi menjadi alat bantu yang berharga dalam screening stunting di fasilitas kesehatan.
Abstract:Perkembangan teknologi yang pesat mendorong masyarakat untuk beradaptasi dalam aktivitas sehari-hari dengan cara yang lebih mudah, cepat, dan efektif. Salah satu inovasi di bidang administrasi adalah Sistem Informasi Administrasi…
inistrasi Kependudukan (SIAK), yang memungkinkan pembuatan data kependudukan secara cepat dan akurat di seluruh wilayah Indonesia. Pemerintah pusat, melalui Dukcapil Kementerian Dalam Negeri, meluncurkan identitas kependudukan digital sebagai bentuk digitalisasi dokumen kependudukan yang dapat diakses melalui aplikasi di ponsel. Meskipun aplikasi ini memudahkan masyarakat, beberapa pengguna masih menghadapi kendala, terutama terkait keamanan data. Sebagai solusi keamanan, teknologi pengenalan wajah berbasis machine learning menjadi opsi potensial dalam memastikan identitas digital yang lebih aman. Teknik seperti Convolutional Neural Networks (CNN) terbukti efektif dalam mengenali fitur wajah, memungkinkan sistem untuk mengidentifikasi individu dengan akurasi tinggi, terutama dalam konteks keamanan. Namun teknologi ini menghadapi tantangan, seperti variasi pose, pencahayaan, dan ekspresi wajah, yang mempengaruhi kinerja sistem pengenalan wajah. Studi ini mengkaji pentingnya evaluasi model pembelajaran mesin, seperti akurasi dan recall, untuk memastikan efektivitas sistem dalam mendeteksi dan mencegah akses yang tidak sah. Dalam masyarakat, pemerintah memiliki tanggung jawab memberikan layanan optimal sebagaimana diatur dalam Undang-Undang Nomor 25 Tahun 2009 tentang Pelayanan Publik. Optimalisasi informasi teknologi diharapkan memberikan manfaat luas bagi masyarakat, memperkuat peran aparat
Abstract:The purpose of this study is to determine the management of employee work stress in improving the performance of public service UPT Pelayanan Pajak Daerah Tanjungpinang. This study used qualitative research methods. The…
design of this study uses a descriptive design. The data collection method used is a field study which includes open observation, unstructured interviews, documentation studies, and triangulation. The results of this study indicate that the factors that cause work stress on service employees at UPT PPD Tanjungpinang include: 1) network problems; 2) different characteristics of Taxpayers; 3) personal problems of employees; and 4) pressure from agencies. The management of work stress carried out by service employees is by refreshing, or leaving the room for a moment, chatting with colleagues, and others. Management of work stress carried out by agencies through three categories, namely, organizational communication, employee performance appraisal, and employee welfare.
Abstract:The spread of Islam on Sumatra Island originated in coastal regions before expanding into the hinterlands. Utilizing a historical approach, this study reveals that maritime trade routes served as the gateway for traders…
and missionaries from Arabia, Persia, and Gujarat to engage in commerce and dawah across Sumatra. Islam initially flourished in Barus, Samudera Pasai, and Aceh before eventually expanding into the interior through river networks, intermarriage, and the political influence of the sultanates. The findings of this study indicate that the process of Islamization in Sumatra was not uniform; in coastal areas, Islam tended to be more Cosmopolitan, whereas in the interior, cultural acculturation with local traditions occurred. The success of this expansion marked the starting point of a religious transformation across the Indonesian archipelago
Abstract:Ikan hiu adalah kelompok hewan yang menarik dan menakutkan di dunia laut. Mereka termasuk dalam kelas Chondrichthyes bersama dengan pari dan hiu bersirip. Mereka dapat ditemukan di berbagai perairan dan memiliki peran penting…
nting sebagai indikator kesehatan ekosistem laut. Namun, populasi ikan hiu terancam karena penangkapan ikan ilegal dan kurangnya konservasi. Dalam proses mengidentifikasi dan mengklasifikasikan spesies hiu, peneliti membuat program dengan menggunakan teknik pengenalan visi komputer, seperti Convolutional Neural Network (CNN), dapat sangat membantu. Salah satu arsitektur CNN yang efektif adalah ResNet50, yang terbukti berhasil dalam klasifikasi gambar. Dengan menggunakan 4720 data citra ikan hiu dari 14 kelas model ResNet50 berhasil mencapai akurasi 86% dalam klasifikasi spesies ikan hiu. Model ini dapat digunakan untuk mengidentifikasi spesies hiu dengan baik, kecuali pada beberapa kelas tertentu yang perlu diperbaiki.