bluuebunny/crossref_metadata_2025 huggingface dataset:
Pediatric Spontaneous Intracranial Hemorrhage (SICH) with unknown etiology in rural area
Authors: Meilia Wulandari  , Whenny Aphrilia Pramusinta
Published: December 2023

Background: Spontaneous intracranial haemorrhage (SICH) on paediatrics is a rare condition which usually doesn’t present specific sign and symptoms. Therefore, quick diagnosis followed by appropriate initial treatment is necessary to reduce morbidity and mortality rate. Case Presentation: An 11-year-old boy was admitted to the ER (emergency room) with sudden altered mental status 2 hours prior to admission. According to his parents, he complains headache after playing with friends previously. No history of trauma was found. Non contras CT scan shows intracerebral haemorrhage in the left and right lateral periventricular of the posterior horn (Vol 0.77 cc) and intraventricular haemorrhage in all the ventricles. EVD (External Ventricular Drain) placement surgery was performed. After two weeks of hospitalization, he was allowed to go home without any neurological deficits, and continued follow up in outpatient unit. Summary: Spontaneous intracranial bleeding in children have high mortality and morbidity rates, but children do not always have specific signs and symptoms. Therefore, a quick diagnosis accompanied by appropriate initial treatment is very necessary to reduce morbidity and mortality rate, such as those to reduce intracranial pressure.
Recent development in fluid-flow problems: A brief review
Authors: Sasi Bhusan Padhi  , Tejaswini Pradhan
Published: December 2023

This particular article is a collection of some recent research articles on fluid flow problems. The present article summarizes the recent research developments regarding the experimental and theoretical examination about thermal conductivity of different nanofluids. The current investigate analyzes several factors those strongly affecting thermal conductivity of nanofluids include temperature, solid volume fraction, particle type, particle size, particle shape, magnetic field, different base fluids, pH, ultrasonic time and surfactant. Other than, different justifiably attractive models contributing enlargement of thermal conductivity of nanofluids are invoked. Lastly, major heat transfer mechanisms namely Brownian motion, thermophoresis, nanoclustering, interfacial nano-layer and osmophoresis responsible for remarkable role in upgrade the thermal conductivity. Hence the heat transfer characteristics of nanofluids are considered.
Personal Branding Beauty Vlogger (Studi Deskriptif pada Channel Youtube Tasya Farasya)
Authors: Amier Helmawati , Sopacua Yustina , Alfredo Ronald
Published: December 2023

The purpose of this study is to describe how personal branding was built by Tasya Farasya though video on her Youtube channel. This research is a qualitative descriptive study that aims to describe how the personal branding of a beauty vlogger Tasya Farasya through her youtube channel. And to find out what are the indicators needed to build personal branding based on what was stated by Peter Montaya. Primary data is done through video objects on Tasya Farasya’s youtube channel, which sees the number of viewers(viewers), likes (likes), and comments (comments) on several predetermined videos, while seconday data retrieval is done through several sources. Taken from online media related to Tasya Farasya’s youtube beauty vlogger channel.

The results of this study found that the personal branding that was formed by Tasya Farasya through the content on her Youtube video channel was judged to be in accordance with eight predetermind indicators, namely specialization, personality, perseverance, good name, leadership, appearance, unity, and difference. It can be concluded that Tasya Farasya displays all the indicators of the formation of personal branding in the video content on her youtube channel so that she can maintain the personal branding she has created.
Strategi Promosi Wisata Bukit Indah Desa Bombay Kecamatan Kei Besar, Kabupaten Maluku Tenggara
Authors: Heatubun Dewi , Rumra Fatmawati
Published: December 2023

Penelitian ini merupakan penelitian deskriptif kualitatif yang bertujuan untuk mengetahui strategi promosi wisata bukit indah. Penelitian ini dilaksanakan di Desa Bombay kecamatan kei besar kabupaten Maluku tenggara. Bukit Indah  sendiri terletak di Kabupaten Maluku Tenggara “Desa Bombay, Kec. Kei Besar. Bukit ini mempunyai potensi alam yang indah dan sayangnya belum banyak yang mengetahui keindahan Bukit Indah tersebut. Keindahan Bukit Indah terletak di bagian wisata alamnya yang sangat lokal dan wisata bukit indah  ini sendiri terdapat di daerah pegunungan, wisata bukit indah juga tak kala menarik seperti wisata pengunungan di kota ambon. Pengambilan data primer dilakukan melalui wawancara terhadap sejumlah informan yang terlibat dalam strategi promosi wisata bukit indah. Adapun informannya yaitu pengelola wisata bukit indah, kepala bidang pemasaran dinas pariwisata dan pengunjung.

Strategi promosi yang digunakan oleh pengelola wisata bukit indah untuk mempromosikan wisata bukit indah yaitu dengan menngunakan strategi periklanan, penjualan personal, promosi penjualan, hubungan masyarakat, pemasaran langsung.Pengembangan kawasan wisata merupakan salah satu strategi yang dilakukan oleh pemerintah untuk meningkatkan pendapatan daerah. Strategi ini umumnya diterapkan oleh daerah-daerah yang memiliki sumber daya alam yang dapat menjadi daya tarik wisata. Hasil penelitian menunjukan bahwa kerja sama antara pengelola wisata bukit indah dengan dinas pariwisata kabupaten Maluku tenggara sangat baik, sehingga starategi promosi yang dilakukan melalui akun-akun media sosial milik pengelola maupun dinas pariwisata berjalan dengan sukses dan menarik banyak pengunjung yang berkunjung ke wisata bukit indah. Jenis media sosial yang digukanan pengelola wisata adalah facebook, instagram, youtube dan google.
Analisis Komunikasi Dalam Penyebaran Informasi Covid-19 Di Kota Ambon
Authors: Tanamal Gladys Joy , Telussa Sandra , Lestaluhu Said
Published: December 2023

Penelitian ini merupakan penelitian kualitatif yang bertujuan untuk mengetahui bagaimana proses komunikasi dalam penyebaran  informasi Covid-19 di kota Ambon, dan untuk menganalisis sistem komunikasi yang digunakan dalam penyebaran informasi Covid-19 di kota Ambon dikarenakan adanya ketidakpercayaan masyarakat terhadap informasi yang disampaikan oleh pemerintah terkait dengan kasus covid-19 di Kota Ambon. Pengumpulan data primer dilakukan  dengan  teknik  wawancara  mendalam  terhadap  beberapa  informan yang dianggap terlibat dalam penelitian ini. Sedangkan pengumpulan data sekunder diperoleh dari dokumen, artikel, dan buku yang mendukung. Hasil penelitian menunjukkan bahwa pemerintah Kota Ambon menyampaikan informasi dengan memperhatikan stakeholder, yakni Pemerintah, Satgas Covid-19, Diskominfo, Kemenkes, dan tokoh-tokoh masyarakat sebagai sumber informasi.   Pesan yang disampaikan meliputi segala informasi yang berkaitan dengan perkembangan Covid-19 dan cara penanganannya. Informasi yang ada dikemas sebaik mungkin dan diedarkan melalui media-media komunikasi terpercaya, baik itu media online, media elektronik, maupun media massa. Kemudian muncul berbagai persepsi dari masyarakat sebagai bentuk respon mereka terhadap informasi yang ada, baik itu respon positif dan juga negatif.
ERKEN ÇOCUKLUK DÖNEMİ DEĞERLER EĞİTİMİ VEREN KURUMLARDA AİLE KATILIMININ İNCELENMESİ
Authors: YILDIRIM İsmet Ayşegül , KELEŞ Oğuz
Published: December 2023

Bu çalışmanın amacı erken çocukluk dönemi değerler eğitimi veren kurumlarda aile katılımının incelenmesidir. Durum çalışması deseninde yürütülen araştırmada, İstanbul ili Ümraniye ilçesinde 2021-2022 eğitim-öğretim yılında farklı iki 4-6 yaş grubu Kur’an kurslarında görev yapan 5 öğretici ve 5 veli ile yüz yüze görüşme yapılmış; Türkiye’nin çeşitli illerindeki 4-6 yaş grubu Kur’an kurslarında görev yapan 205 öğreticiye de “Okul Öncesi Öğretmenlerinin Uyguladıkları Aile Katılım Stratejilerini Belirleme Ölçeği (AKSBÖ)” uygulanmıştır. Veri analizinde nitel veriler üzerinde içerik analizi yapılmış; nicel veriler bilgisayar ortamında değerlendirilerek betimsel istatistiklere yer verilmiştir. Ölçek sonucuna göre öğreticilerin en çok tercih ettikleri aile katılımı stratejilerinin öğretmen-aile iletişim temelli stratejiler ve ev temelli stratejiler olduğu belirlenmiştir. Ayrıca öğreticilerin öğretmen temelli stratejilere nadiren, okul-aile temelli stratejilere ara sıra yer verdikleri belirlenmiştir. Benzer şekilde öğreticilerle ve velilerle yapılan görüşmeler sonucunda öğreticilerin ve velilerin aile katılımı ile ilgili yeterli bilgiye sahip olmadıkları, 4-6 yaş grubu Kur’an kurslarında aile katılımının yeterli düzeyde olmadığı sonucuna ulaşılmıştır.
MEDENİ HUKUKTAKİ BOŞANMA NAFAKASININ İSLAM HUKUKU AÇISINDAN DEĞERLENDİRİLMESİ
Authors: ALKIŞ Alpaslan , YILMAZ Gülnihal
Published: December 2023

Hayatın devamını sağlayan ve evlilik, hısımlık, mülkiyet gibi çeşitleri bulunan nafaka, günümüzde daha çok boşanma konusunda gündem oluşturmaktadır. Tartışmalara konu olan evlilik nafakası İslam hukukunda sahih nikahla birlikte evlilik süresince erkeğe yüklenen bir sorumluluk olup iddet ile sona erdiği kabul edilmekle birlikte boşanma sonrası içinde nafaka yükümlülüğünün olabilirliği konusunda görüşler bulunmaktadır. Türk Medeni Kanunu’nun nafaka hakkını süresiz olarak düzenlemesi son dönemlerde çokça tartışılmakta ve birçok hukukçu tarafından da adil ve hakkaniyetli bulunmayarak eleştirilmektedir. İslam hukukunda boşanan bireyler arasında nafaka hakkından bahsedilmemekle birlikte erkeğin kadına ödeme yükümlülüğü altında bulunduğu bazı mali sorumluluklarının olduğu kabul edilmektedir. Dinen yasaklanmayan hususlarda sosyal adaletin sağlanabilmesi için kamu otoritesinin toplum yararı gereği yeni hükümler koyma yetkisi bulunmaktadır. Bu nedenle devlet, nafaka hakkının hükümsüz sayılmasını gerektirecek bir sebep bulunmayan boşanmalarda, boşanan kadına "boşanma nafakası" adı altında nafaka ödenmesine karar verebilir.
الظواهر الصوتية في لهجات البدو والحضر، مقارنة بين اللهجات العربية القديمة واللهجات السورية الحديثة
Authors: ABAZOĞLU Muhammet
Published: December 2023

يُنظَرُ إلى اللهجات العربية المعاصرة على أنها امتدادٌ للّهجات العربية القديمة التي تحتوي الكثير من الخصائص اللهجية المشتركة. هذه الخصائص تُعتَبر مقياساً للفصاحة بالنسبة لعلماء اللغة. لذلك قسموا بين لغة أهل الحاضرة وبين لغة أهل البادية، واعتبروا لغةَ سكانِ الحضرِ من القبائلِ الحجازيةِ اللغةَ الأدبيةَ والنموذجيةَ، ولغةَ سكان البادية من القبائل التميمية اللغةَ التي تحتوي على صفاتٍ لهجيةٍ مختلفةٍ. فكانت اللهجات العربية تنقسم جغرافياً إلى قسمين؛ لهجاتُ غربي الجزيرة العربية ولهجاتُ وسطها وشرقيها. وهذا التقسيمُ مشابهٌ للبيئات اللهجية المعاصرة التي تمتاز عن بعضها بسبب التباعد الجغرافي. فالعامل الجغرافي يشكل نقطة التقاء بين اللهجات القديمة والحديثة من حيث البداوة والحضارة. وهذا التباين يشابه اللهجات السورية المعاصرة التي تنقسم إلى قسمين، يُعرفان بـلهجتي "الريف" و"المدينة". وهذا البحث يحاولُ الكشفَ عن بعض الظواهر الصوتية اعتماداً على المنهج الوصفي المقارن، لعرض نقاط التشابه والاختلاف بين اللهجات العربية القديمة واللهجات السورية المعاصرة، من خلال تناول الظواهر الصوتية المختلفة كالفتح أو الإمالة، والهمز أو تخفيفه، والإبدال.
Secure Information Flow for IoT Applications
Authors: Ngo Tri Minh , Duy Nguyen Nhat Vien
Published: December 2023

This paper discusses how to ensure security, i.e., confidentiality and integrity properties, for data in IoT applications. While confidentiality could be assessed via information flow analysis, integrity is ensured by error-correcting codes. In addition to errors, many communication channels also cause erasures, i.e., the demodulator cannot decide which symbol the received waveform represents. The paper proposes a method that might correct both errors and erasures together. Our method is efficient in reducing memory storage as well as decoding complexity.
Breed Lineage Prediction of Small Ruminants Using Deep Learning
Authors: Kamil Mohammad Farizshah Ismail , Akmal Jamaludin Nor Azliana , Mohd Isa Mohd Rizal
Published: December 2023

Sheep are a significant food source for humans, besides cattle and poultry. Despite its significance to Malaysian Muslims, who make up approximately 60% of the local population, the sheep supply is limited by the high mortality rate caused by fatal diseases such as foot and mouth disease (FMD) and tetanus. Infected sheep can spread food-borne bacteria, such as Escherichia coli, at various preparation phases, contaminating the meat. The objectives of this study are to identify internal and external factors that influence sheep breed lineage continuity, investigate current practices for collecting and managing data knowledge on sheep breed and hereditary diseases, and propose a sheep breed and disease data knowledge model based on the feedforward artificial neural network (FANN) deep learning method. This study utilized qualitative and quantitative data to obtain in-depth answers to the research questions, which involves collecting all the information required for the system development using the FANN deep learning method. This study found that breeding is the leading data group for tracking each sheep's ADG and BCS. Feed type, sanitization, and medication influence sheep’s daily increase and health. Collaboration, worker knowledge, and climate are recognized as external factors that potentially influence sheep's daily increase. The interview analysis also suggested attributes that could contribute to detecting breed lineage, including breed, category, ADG, and BCS. Therefore, it is recommended that future research adopt this method for other farmed animals.
Curriculum Management Systems for Blended Learning Support
Authors: Asrini Hari Windu , Wicaksono Galih Wasis , Budiono Budiono
Published: December 2023

The ongoing COVID-19 has left some serious impacts on education, bringing academic activities to a halt, and restrictions have been in place to hamper the proliferation of the virus. The utilization of technology these days plays a vital role in assisting students in attending education online or blended learning and keeping academic activities running. However, limited learning management systems present a new problem in online learning, especially in higher education. Thus, a new information system is required to resolve this issue. This study aims to develop the Bauran information system to assist lecturers in higher education with curriculum design and semester lesson plans and to evaluate the effectiveness of Bauran's implementation using the ISO 25010 model. The material used during the research process included the Bauran application, Guidelines for Developing Higher Education Curriculum, and some data from relevant users to test the application. Meanwhile, during the development stage of the research, the prototype method was used to adjust the development to the feedback given by stakeholders. This application received positive feedback from relevant users regarding the curriculum development flow in line with the Guidelines of Curriculum Drafting for Higher Education. Using the ISO 25010 model during the testing process, the results of user evaluations demonstrated its effectiveness with an average score of 4.84 out of 5. Future research is expected to evaluate the long-term effectiveness of Bauran using a larger sample size and a different software evaluation model
Improvement of Starling Image Classification with Gabor and Wavelet Based on Artificial Neural Network
Authors: Rahman Aviv Yuniar , Istiadi Istiadi , Hananto April Lia , Fauzi Ahmad
Published: December 2023

Indonesia is a country that has a diversity of animal species with the top 10 predicate in the world. The population of animal species, including starlings, is very widely known in the country. Starlings currently in Indonesia are diverse, ranging from standard to rare in Indonesia. This starling has its characteristics based on the type, color, sound, etc. In the first problem, the first accuracy performance when using the GLCM texture feature with Artificial Neural Network is 68%. Furthermore, the second problem is the accuracy performance of typing using the GLCM texture feature with a Decision Tree of 50%. This research aims to improve the starling classification system accuracy using Gabor and Wavelet texture features with artificial Neural Networks. Based on testing in the classification of starlings using the GLCM, Gabor, and Wavelet features, the highest degree of precision can, therefore, be concluded to be at the GLCM and Wavelet feature levels. The GLCM and Wavelet level accuracy results reached 83% at a rate of learning 0.9. In the experiments that have been done, the GLCM and Wavelet levels can increase accuracy using Artificial Neural Networks. In the classification process, the type of starlings also shows that the computational time in testing is much faster in producing accuracy values. In addition, the accurate accuracy while testing the starling category also increases.
Wi-Fi Fingerprint for Indoor Keyless Entry Systems with Ensemble Learning Regression-Classification Model
Authors: Putrada Aji Gautama , Alamsyah Nur , Fauzan Mohamad Nurkamal
Published: December 2023

Keyless entry systems have made human life more comfortable because the possibility of someone leaving a key is non-existent. However, there is a research opportunity to use Wi-Fi fingerprint localization in an indoor keyless entry system. The use of Wi-Fi as a solution is low cost because of the already hdeployed Wi-Fi access points (AP) around buildings. This study uses ensemble learning to utilize Wi-Fi fingerprints for keyless entry systems in indoor environments. The first step of this research is to obtain the UJIIndoorLoc Data Set, an open-source Wi-Fi fingerprint dataset. The next step is to design and implement a keyless entry system based on Wi-Fi Fingerprint. We compared four ensemble learning methods: Random Forest, AdaBoost, gradient boosting, and XGBoost. We use several metrics to compare the four methods, namely r2, the area under the receiver operating curve (AUROC), and the equal error rate (EER). The test results show that for localization based on ensemble regression, XGBoost has the best performance compared to the other three ensemble methods for both longitude and latitude predictions. The r2values are 0.94 and 0.98, respectively. For authentication based on ensemble classification, the gradient-boosting model performance increases as the number of weak learners increases. The optimum number of weak learners is 60. With AUROC = 0.99, gradient boosting outperforms random forest, AdaBoost, and XGBoost on authentication. Finally, our authentication method has EER = 0.01, which outperforms other state-of-the-art keyless entry systems. This research focuses on local building map datasets for future work.
Automated Staging of Diabetic Retinopathy Using Convolutional Support Vector Machine (CSVM) Based on Fundus Image Data
Authors: Novitasari Dian C Rini , Fatmawati Fatmawati , Hendradi Rimuljo , Nariswari Rinda , Saputra Rizal Amegia
Published: December 2023

Diabetic Retinopathy (DR) is a complication of diabetes mellitus, which attacks the eyes and often leads to blindness. The number of DR patients is significantly increasing because some people with diabetes are not aware that they have been affected by complications due to chronic diabetes. Some patients complain that the diagnostic process takes a long time and is expensive. So, it is necessary to do early detection automatically using Computer-Aided Diagnosis (CAD). The DR classification process based on these several classes has several steps: preprocessing and classification. Preprocessing consists of resizing and augmenting data, while in the classification process, CSVM method is used. The CSVM method is a combination of CNN and SVM methods so that the feature extraction and classification processes become a single unit. In the CSVM process, the first stage is extracting convolutional features using the existing architecture on CNN. CSVM could overcome the shortcomings of CNN in terms of training time. CSVM succeeded in accelerating the learning process and did not reduce the accuracy of CNN's results in 2 class, 3 class, and 5 class experiments. The best result achieved was at 2 class classification using CSVM with data augmentation which had an accuracy of 98.76% with a time of 8 seconds. On the contrary, CNN with data augmentation only obtained an accuracy of 86.15% with a time of 810 minutes 14 seconds. It can be concluded that CSVM was faster than CNN, and the accuracy obtained was also better to classify DR.
Convolutional Neural Network Model for Sex Determination Using Femur Bones
Authors: Nasien Dewi , Adiya M. Hasmil , Afrianty Iis , Farkhan Mochammad , Butar-Butar Rio Juan Hendri
Published: December 2023

Forensic anthropology is the critical discipline that applies physical anthropology in forensic education. One valuable application is the identification of the biological profile. However, in the aftermath of significant disasters, the identification of human skeletons becomes challenging due to their incompleteness and difficulty determining sex. Researchers have explored alternative indicators to address this issue, including using the femur bone as a reliable sex identifier. The development of artificial intelligence has created a new field called deep learning that has excelled in various applications, including sex determination using the femur bone. In this study, we employ the Convolutional Neural Network (CNN) method to identify the sex of human skeleton shards. A CNN model was trained on 91 CT-scan results of femur bones collected from Universiti Teknologi Malaysia, comprising 50 female and 41 male patients. The data pre-processing involves cropping, and the dataset is divided into training and validation subsets with varying percentages (60:4, 70:30, and 80:20). The constructed CNN architecture exhibits exceptional accuracy, achieving 100% accuracy in both training and validation data. Moreover, the precision, recall, and F1 score attained a perfect score of 1, validating the model's precise predictions. The results of this research demonstrate excellent accuracy, confirming the reliability of the developed model for sex determination. These findings demonstrate that using deep learning for sex determination is a novel and promising approach. The high accuracy of the CNN model provides a valuable tool for sex determination in challenging scenarios. This could have important implications for forensic investigations and help identify victims of disasters and other crimes.
A Review of Neural Network Approach on Engineering Drawing Recognition and Future Directions
Authors: Mohd Yazed Muhammad Syukri , Ahmad Shaubari Ezak Fadzrin , Yap Moi Hoon
Published: December 2023

Engineering Drawing (ED) digitization is a crucial aspect of modern industrial processes, enabling efficient data management and facilitating automation. However, the accurate detection and recognition of ED elements pose significant challenges. This paper presents a comprehensive review of existing research on ED element detection and recognition, focusing on the role of neural networks in improving the analysis process. The study evaluates the performance of the YOLOv7 model in detecting ED elements through rigorous experimentation. The results indicate promising precision and recall rates of up to 87.6% and 74.4%, respectively, with a mean average precision (mAP) of 61.1% at IoU threshold 0.5. Despite these advancements, achieving 100% accuracy remains elusive due to factors such as symbol and text overlapping, limited dataset sizes, and variations in ED formats. Overcoming these challenges is vital to ensuring the reliability and practical applicability of ED digitization solutions. By comparing the YOLOv7 results with previous research, the study underscores the efficacy of neural network-based approaches in handling ED element detection tasks. However, further investigation is necessary to address the challenges above effectively. Future research directions include exploring ensemble methods to improve detection accuracy, fine-tuning model parameters to enhance performance, and incorporating domain adaptation techniques to adapt models to specific ED formats and domains. To enhance the real-world viability of ED digitization solutions, this work highlights the importance of conducting testing on diverse datasets representing different industries and applications. Additionally, fostering collaborations between academia and industry will enable the development of tailored solutions that meet specific industrial needs. Overall, this research contributes to understanding the challenges in ED digitization and paves the way for future advancements in this critical field.
The Evaluation of Entropy-based Algorithm towards the Production of Closed-Loop Edge
Authors: Crysdian Cahyo
Published: December 2023

This research concerns the common problem of edge detection that produces a disjointed and incomplete edge, leading to the misdetection of visual objects. The entropy-based algorithm can potentially solve this problem by classifying the pixel belonging to which objects in an image. Hence, the paper aims to evaluate the performance of entropy-based algorithm to produce the closed-loop edge representing the formation of object boundary. The research utilizes the concept of Entropy to sense the uncertainty of pixel membership to the existing objects to classify pixels as the edge or object. Six entropy-based algorithms are evaluated, i.e., the optimum Entropy based on Shannon formula, the optimum of relative-entropy based on Kullback-Leibler divergence, the maximum of optimum entropy neighbor, the minimum of optimum relative-entropy neighbor, the thinning of optimum entropy neighbor, and the thinning of optimum relative-entropy neighbor. The experiment is held to compare the developed algorithms against Canny as a benchmark by employing five performance parameters, i.e., the average number of detected objects, the average number of detected edge pixels, the average size of detected objects, the ratio of the number of edge pixel per object, and the average of ten biggest sizes. The experiment shows that the entropy-based algorithms significantly improve the production of closed-loop edges, and the optimum of relative-entropy neighbor based on Kullback-Leibler divergence becomes the most desired approach among others due to the production of more considerable closed-loop edge in the average. This finding suggests that the entropy-based algorithm is the best choice for edge-based segmentation. The effectiveness of Entropy in the segmentation task is addressed for further research.
Comparison of the Packet Wavelet Transform Method for Medical Image Compression
Authors: Atmaja I Made Ari Dwi Suta , Triadi Wilfridus Bambang , Astawa I Nyoman Gede Arya , Radhitya Made Leo
Published: December 2023

Medical images are often used for educational, analytical, and medical diagnostic purposes. Medical image data requires large amounts of storage on computers. Three types of codecs, namely Haar, Daubechies, and Biorthogonal, were used in this study. This study aims to find the best wavelet method of the three tested wavelet methods (Haar, Daubechies, and Biorthogonal). This study uses medical images representing USG and CT-scan images as testing data. The first test is carried out by comparing the threshold ratio. Three threshold values are used, namely 30, 40, and 50. The second test looks for PSNR values with different thresholds. The third test looks for a comparison of the rate (image size) to the PSSR value. The final test is to find each medical image's compression and decompression times. The first compression ratio test results on both medical images showed that CT scan images on Haar and Biorthogonal wavelets were the best, with an average compression ratio of 40.76% and a PSNR of 33.77. The PSNR obtained is also getting more significant for testing with a larger image size. The average compression time is 0.52 seconds, and the decompression time is 2.27 seconds. Based on the test results, this study recommends that the Daubechies wavelet method is very good for compression, which is 0.51 seconds, and the Biorthogonal wavelet method is very good for medical image decompression, which is 1.69 seconds.
Node.js Performance Benchmarking and Analysis at Virtualbox, Docker, and Podman Environment Using Node-Bench Method
Authors: Pratama I Putu Agus Eka , Raharja I Made Sunia
Published: December 2023

As an asynchronous runtime environment (interpreter) for the development of scalable JavaScript-based network applications, it is necessary to know the performance of the web framework on Node.js in a virtualization-oriented development environment and a container-oriented development environment. This research aims to compare the performance of Node.js in several frameworks in VirtualBox, Docker, and Podman environments. The testing was carried out using some materials like a bench utility at Node Package Manager (NPM) involving the Adonis, Connect, Express, Fastify, Foxify, Hapi, Koa, Molecular, Plumier, Restify, and Sails frameworks, using Object Relational Mapping (ORM) and Raw Query Bookshelf, Knex, MySQL, MySQL2, and Sequelize at Ubuntu Linux operating system. The method research used in this research is the Node-Bench method with requests, latency, and throughput parameters. The testing results show that the best performance score is the Fastify framework with the Sequelize library (ORM) in a container-oriented development environment (Docker and Podman), and the worst performance score is the Express framework with the Mysql2 library (Raw Query) in a virtualization-oriented development environment (VirtualBox). Based on the testing results, developers who use Node.js are more advised to use the Fastify framework with the Sequelize library (ORM) in a container-oriented development environment (Docker or Podman) to obtain better performance. For further research, the implementation and testing at container-oriented development can use cloud-based service (IaaS cloud or PaaS Cloud) for the read-only immutable environment, scalability, and security reasons.Keywordsâ€” Docker, Node-Bench method, Node.js, Podman, VirtualBox.
The Extension of the UTAUT2 Model: A Case Study of Indonesian SMEs Acceptance of Social Commerce
Authors: Arista Artika , Tjahjanto Tjahjanto , Ernawati Iin , Purabaya Rudhy Ho , Abdullah Engku Fadzli Hasan Syed
Published: December 2023

An entirely updated e-commerce platform referred to as Social Commerce was developed in response to the rise in social media use. Social commerce integrates interactions between buyers and sellers made possible by social media platforms and Web 2.0 technology. It is frequently seen as a subfield of e-commerce. Social commerce has been successfully introduced in developing countries. Many businesses around the world are small and medium enterprises (SMEs). For instance, SMEs in Indonesia can contribute up to 60.34% of the country's GDP and have a substantial labor pool. Using social commerce as an e-commerce platform can significantly improve the operational efficiency of small and medium-sized enterprises (SMEs). However, little empirical research has specifically examined how SMEs embrace social commerce. Given the high level of concern, further research is required. Therefore, the current study experimentally examined how local SMEs in rural Indonesia introduced social commerce. The study was modeled using the Unified Theory of Technology Acceptance and Use (UTAUT) 2 model and several previous studies. SmartPLS 4 software was used to model and evaluate data using partial least squares structural equation modeling (PLS-SEM). The findings of the 114 samples showed that relative advantage, social support, facilitation conditions, and the government's support of social commerce influenced behavioral intention to use social commerce. Behavioral intention to use social commerce influences the actual use of social commerce. The findings of this study can help local governments and policymakers develop social trade promotion regulations to help potential SMEs and entrepreneurs gain long-term business support.
Literature Reviews of RBV and KBV Theories Reimagined - A Technological Approach Using Text Analysis and Power BI Visualization
Authors: Arief Ikhwan , Hasan Alizar , Putri Nilda Tri , Rahman Hafiz
Published: December 2023

Over the years, the Resource-Based View (RBV) and Knowledge-Based View (KBV) have solidified their roles as pivotal paradigms in strategic management literature. With an emphasis on Small and Medium Enterprises (SMEs), this study uses text analysis and Microsoft Power BI to explore these concepts innovatively. The study implements a systematic literature review, extracting data from Scopus, Web of Science, and DOAJ databases to assemble a comprehensive literature corpus. The methodology incorporates text analysis to draw out key themes, relationships, and trends, and these are subsequently visualized using Power BI to create an engaging, interactive representation of data. Components like word clouds, co-occurrence networks, and trend lines are generated, while Power BI's dynamic filtering and drill-down functionalities facilitate thorough data investigation. The results display significant overlap between RBV and KBV, denoting possible integration junctures for these theories within the domain of strategic management. Additionally, the study underscores the relevance of these insights for SMEs, emphasizing the part played by unique resources, encompassing knowledge assets, in catalyzing innovation and fostering a competitive edge. The study concludes by recognizing the significant theoretical and practical implications of integrating text analysis and Power BI in conducting literature reviews. This methodology bolsters our understanding of RBV and KBV, offering small and medium-sized enterprises a beneficial instrument to traverse these intricate theories. The study suggests that future research could broaden the application of this methodological approach to encompass other strategic management theories.
Characteristics of Multi-Class Suicide Risks Tweets Through Feature Extraction and Machine Learning Techniques
Authors: Lim Yan Qian , Loo Yim Ling
Published: December 2023

This paper presents a detailed analysis of the linguistic characteristics connected to specific levels of suicide risks, providing insight into the impact of the feature extraction techniques on the effectiveness of the predictive models of suicide ideation. Prevalent initiatives of research works had been observed in the detection of suicide ideation from social media posts through feature extraction and machine learning techniques but scarcely on the multiclass classification of suicide risks and analysis of linguistic characteristics' impact on predictability. To address this issue, this paper proposes the implementation of a machine learning framework that is capable of analyzing multiclass classification of suicide risks from social media posts with extended analysis of linguistic characteristics that contribute to suicide risk detection. A total of 552 samples of a supervised dataset of Twitter posts were manually annotated for suicide risk modeling. Feature extraction was done through a combination of feature extraction techniques of term frequency-inverse document frequency (TF-IDF), Part-of-Speech (PoS) tagging, and valence-aware dictionary for sentiment reasoning (VADER). Data training and modeling were conducted through the Random Forest technique. Testing of 138 samples with scenarios of detections in real-time data for the performance evaluation yielded 86.23% accuracy, 86.71% precision, and 86.23% recall, an improved result with a combination of feature extraction techniques rather than data modeling techniques. An extended analysis of linguistic characteristics showed that a sentence's context is the main contributor to suicide risk classification accuracy, while grammatical tags and strong conclusive terms were not.
Multi-Temporal Factors to Analyze Indonesian Government Policies regarding Restrictions on Community Activities during COVID-19 Pandemic
Authors: Fachri Pane Syafrial , Adiwijaya Adiwijaya , Dwi Sulistiyo Mahmud , Akbar Gozali Alfian
Published: December 2023

Concerning the implementation of the government policy regarding the Restriction of Community Activities (PPKM) during the COVID-19 pandemic era, there are still discrepancies in the economic sector and population mobility. This issue emerges due to irrelevant data and information in one region of Indonesia. The data differences should be carefully solved when implementing the PPKM policy. Besides, the PPKM must also pay attention to some specific factors related to the real conditions of a region, such as the data on the epidemiology of COVID-19, economic situations, and population mobility. These three are called Multi Factors. Then, based on the data, COVID-19 has a specific spreading period that cannot be repeated and thus is called temporal. Therefore, using the Multi-Temporal Factors approach to identify their correlation with the PPKM policy by applying Machine Learning, such as the Multiple Linear Regression model and Dynamic Factors, is essential. This research aims to analyze the characteristics and correlations of the COVID-19 pandemic data and the effectiveness of the government's policy on community activities (PPKM) based on the data quality. The results show that the accuracy of the multiple linear regression models is 84%. The Dynamic Factor shows that the five most important factors are idr_close, positive, retail_recreation, station, and healing. Based on the ANOVA test, all independent variables significantly influence the dependent one. The linear multiple regression models do not display any symptoms of heteroscedasticity. Thus, based on the data quality, the implementation of PPKM by the government has a practical impact.
Correlation of advanced glycation end products (AGEs) intake with prehypertension incidence among adults
Authors: Yan Loriza Sativa
Published: December 2023

Background : The incidence of prehypertension in adults has a threefold risk of developing hypertension and triggering heart disease when compared to other ages population. This study aimed to correlate the intake of advanced glycation end products (AGEs) with the incidence of prehypertension in adults in Kota Jambi.

Method : A cross-sectional study using the correlation method with a sample of 134 people aged 21 â€“ 59 years who came for treatment at the Tanjung Pinang Public Health Center, Kota Jambi  and sample selected by purposive sampling. Data collected by using a questionnaire and analyzed by Spearman rank.

Results : a strong relationship between AGEs intake and prehypertension (p = 0.000; r: 0.725)

Conclusion  AGEs intake has a correlation with the incidence of prehypertension in adults.
Effectiveness of Kinesio Video and Pelvik Roxing Exercise Video on Reducing Back Pain of Third Trimester Pregnant Women
Authors: Herinawati Herinawati , Lilis Dewi Nopiska , Osvinarti Osvinarti , Novita Nesi , Iksaruddin Iksaruddin
Published: December 2023

Background: Back pain in pregnant women is a common problem that is often experienced during pregnancy, especially in the third trimester.  Back pain in pregnant women not only interferes with the mother's quality of life, but can also affect fetal well-being and the delivery process. In an effort to address the problem of back pain in pregnant women, various physical therapy methods have been developed. Two methods that have gained attention are Kinesio techniques and Pelvic Roxing Exercises.

Method: This research is a quantitative research with a pre-experimental study that uses a one group pretest-posttest design with no control group. The sample of this study was third trimester pregnant women at PMB Latifah and PMB Zainab Jambi City as many as 60 pregnant women. The sampling technique used purposive sampling technique. This research instrument is a questionnaire. Data were analyzed using the mann whitney test.

Results: The results showed that in the Kinesia Taping therapy group it was known that before being given Kinesio Taping treatment, the scale of back pain felt by respondents was 67% feeling moderate pain and 33% feeling severe pain controlled. After being given Kinesio Taping, the pain scale felt by respondents was 57% feeling mild pain and 43% feeling moderate pain. In the Pelvic Roxing Exercise therapy group, it is known that before being given Pelvic Roxing Exercise therapy, the scale of back pain felt by respondents is 9% feeling mild pain, 70% moderate pain and 21% severe pain controlled. After being given Pelvic Roxing Exercise therapy, the scale of back pain felt by respondents was 77% mild pain and 235 moderate pain. The results of the mann whitney test obtained p-value = 0.041, p-value <0.05 so that there is a significant difference between the results after kinesio taping and pelvic roxing exercise interventions

Conclusion: Based on the results of the study, it can be concluded that there are differences in the scale of back pain in third trimester pregnant women before being given kinesio taping therapy and pelvic roxing exercise with after being given kinesio taping therapy and pelvic roxing exercise.
The The Influence Of Early Children's Dental Health Monitoring Books On Parents' Knowledge In Az-Zahra Islamic Kindergarten, Jambi City
Authors: Febrianti Sri , Muliadi Muliadi , Suhartono Suhartono
Published: December 2023

Background: The results of the 2018 Basic Health Research (Riskesdas) show that the prevalence of caries in the 3-4 year age group is 81.5% and the caries prevalence in the 5-9 year age group is 92.6%. The average def-t for the age group 3-4 years was 6.2 and the average def-t for the 5-year age group was 8.1. Research conducted on all kindergarten students in Malalayang District showed that the prevalence of primary tooth caries was 90% with an average index def-t = 6.99.Method: The design in this study used a pre-experimental one group pre-test posttest. There were 30 samples in the study that met the inclusion and exclusion criteria. Results: The statistical test output shows that the p-value of knowledge is 0.000. Because the value 0.000 < 0.05, the hypothesis is accepted, which means there is a difference between the dental health knowledge scores for the pre-test and post-test.Conclusion: Monitoring books can increase parents' knowledge in Az-Zahra Islamic Kindergarten, Jambi City
Development of Nursing Clinical Supervision Application
Authors: Ernawati Ernawati , Damayantie Netha , Mursidahdewi Mursidahdewi , Muliyadi Muliyadi
Published: December 2023

ABSTRACT

 

Nursing services require an effective and efficient nursing management system, so that nursing resources can be directed to produce quality nursing services, one of which is through nursing supervision. Supervision is a personal observation of functions or activities, in the nursing care process, and delegations of functions or activities to maintain accountability and evaluate nursing care appropriately.

This research aims to develop a clinical supervision application to improve the quality of implementation of nursing supervision in Jambi city hospitals. Clinical supervision research is designed with an application as guidance and information for room heads, team leaders, and implementing nurses in carrying out clinical supervision so that it can improve the quality of nursing supervision in hospitals.

Research design with a mixed methods approach, namely qualitative research on conceptual development and quantitative research used in the product development and testing phases. The research procedure uses analysis-design & development-formative evaluation steps with the Dick and Carey procedure. The research was carried out in three hospitals in Jambi City, namely Abdul Manap Hospital, Bratanata Hospital, and Bhayangkara Hospital Jambi in April - August 2023 with the research subjects being all room heads totaling 16 people and team leaders totaling 24 people.

 There is a difference in user knowledge about nursing supervision before and after the development of the Android-based clinical nursing supervision educational application with a p-value of 0.000 < 0.005.

The model for developing nursing clinical supervision applications using the Dick and Carey learning design approach is a systematic learning design model for developing effective and efficient learning programs. Nursing clinical supervision educational applications can be applied in hospitals by room heads in carrying out supervision in inpatient rooms.

 

Keywords: Development, education, clinical supervision, nursing
The Comparison of the Sunscreen Activity of Ethanol Extracts and Fractions from Robusta Coffee (Coffea canephora) Leaves using UV Spectrophotometer Method
Authors: Krisyanella Krisyanella , Meinisasti Resva , Muslim Zamharira , Salasa Alfrida Monica , Baharyati Delta
Published: December 2023

Background: The development of sunscreen preparations has led to the use of natural ingredients as active substances. Robusta coffee leaves (Coffea canephora) contain alkaloids, flavonoids, saponins, tannins and steroids. From previous research the SPF value of its ethanol extract at 150 ppm was 12,989 (Maximum protection). The sunscreen activity of its fractions need to be determined, to find out which one has the highest potential sunscreen activities

Method: Sunscreen activity examination was carried out in vitro using a UV spectrophotometer. The concetntration of each fraction used was 150 ppm.

Results: The N-hexane, ethyl acetate and butanol fractions have sunscreen activity with extra protective power, SPF values respectively were 6.006, 7.609, and 8.046. This activities arises from the content of flavonoids, phenolics and tannins. While the remaining water fraction has the lowest protective activity, with SPF value 3.985 and only contain tannin. Compared to Its ethanol extract, the ethanol extract has better sunscreen activit, because at a 150 ppm it has  SPF value 12.989 (Maximum sunscreen activity)

Conclusion: the sunscreen activity of this fraction is lower than its  ethanol extract. The ethanol extract of robusta coffee leaves has more potential to be developed into a sunscreen preparation.

Keywords: ; Robusta coffee leaves ; Fraction ; SPF Value
Formulation and Activity Test of Foot Spray from Sungkai Leaf Extract (PeronemacanescensJack) as an Antibacterial that Causes Foot Odor
Authors: Perawati Santi , Wulandari Aprilia , Aryani Silvi Febri , Andani Hasma
Published: December 2023

Background : Sungkai is one of the medicinal plants used by the Suku Anak Dalam Tribe in Jambi to treat infectious diseases. Sungkai leaves contain secondary metabolites including alkaloids, flavonoids, terpenoids, steroids and tannins. Tannins and terpenoids are metabolites that have potential as antifungal , antibacterial and antiviral so they can be used in the cosmetics and pharmaceutical industries. Some bacterial infections can cause foot odor which can reduce a person's self-confidence. The aim of this research was to test Sungkai leaf extract which was formulated in foot spray dosage form to treat bacteria that cause foot odor, namely Staphylococcus epidermidis and Pseudomonas aeruginosa .

Method : This research begins with the extraction stage of Sungkai leaves using the maceration method using 96% ethanol, then the resulting extract is continued with phytochemical screening testing, formulating the foot spray, and testing the antibacterial activity of foot spray. Antibacterial testing using by disc diffusion method, preparation of foot spray formulation using several series concentrations of Sungkai leaf extract there are 15% (F1), 20% (F2), and 25% (F3), and than followed by evaluation of foot spray formula includes organoleptic tests, pH tests , stability tests , irritation tests and liking tests.

Results : Antibacterial activity of foot spray for both bacteria is in the medium category with average values of 7.29 and 7.11. The statistical test results at a p value of 0.05 show a significant difference between F0, FP, and F1.

Conclusion : Based on the research that has been carried out, it can be concluded that foot preparation spray from Sungkai leaf extract is effective as an antibacterial especially for (F3) which contain an extract concentration of 25%.

                                     

Keywords :Extract, sungkai leaves, foot spray , Peronema canescensJack, Pseudomonas aeruginosa And Staphylococcus epidermidis .