PENDAMPINGAN PENGGUNAAN WEBSITE PELAYANAN ONLINE BAGI STAF PERANGKAT DESA TEGALREJA DI KABUPATEN BREBES

Website merupakan salah satu bagian penting dari sebuah sistem informasi, yang berfungsi sebagai media informasi, sarana publikasi dan media interaksi. Pelayanan yang ada di Desa Tegalreja saat ini masih menggunakan sistem manual, yang mengharuskan pegawai desa melakukan pelayanan di balai desa. Pelayanan di Desa Tegalreja tidak optimal karena jam kerja pegawai desa dibatasi untuk menghindari kerumunan sehingga proses permohonan berbagai surat menyurat menjadi lama dan terhambat. Tujuan dari Penelitian ini adalah menghasilkan sebuah website pelayanan online desa, yang dapat membantu semua masyarakat yang membutuhkan informasi dan Layanan Kemasyarakatan Desa Tegalreja, Kecamatan Banjarharjo, Kabupaten Brebes. Dengan adanya website ini, diharapkan pelayanan desa bisa menjadi lebih optimal. Metode ceramah dan praktik digunakan untuk memberikan pengetahuan dan pemahaman tentang penggunaan website pelayanan online desa. Peserta juga diajak untuk berdiskusi agar lebih mengenal dan termotivasi untuk memanfaatkan dan menggunakan website pelayanan online desa agar pelayanan desa menjadi lebih optimal. Penelitian ini menghasilkan sebuah website pelayanan online desa, yang dapat membantu semua masyarakat yang membutuhkan informasi dan Layanan Kemasyarakatan Desa Tegalreja. Pada website ini terdapat menu yang dapat membantu pelayanan desa untuk masyarakat seperti menu cek data diri, layanan, saran pembangunan dan inventaris hasil pembangunan. Dengan adanya website ini, diharapkan pelayanan desa menjadi lebih optimal

PENGARUH KUALITAS PRODUK, HARGA DAN PELAYANAN TERHADAP KEPUASAN PELANGGAN (STUDI KASUS PADA RUMAH MAKAN MEGA MULIA CABANG DELIMA PEKANBARU)

Kepuasan pelanggan adalah aspek penting dan menjadi kunci untuk menjalankan bisnis yang sukses, kepuasan merupakan fungsi dari perbedaan antara kinerja yang dirasakan dengan harapan. Harapan pelanggan dapat dibentuk oleh pengalaman masa lampau, komentar dari kerabatnya serta janji akan informasi pemasar dan saingannya. Pelanggan yang puas akan setia lebih lama, kurang sensitif terhadap harga dan memberi komentar yang baik tentang perusahaan Tujuan dari penelitian ini adalah untuk mengetahui pengaruh kualitas produk, harga dan pelayanan terhadap kepuasan pelanggan rumah makan mega mulia cabang Delima Pekanbaru. Penelitian ini menggunakan metode kuantitatif. Populasi dalam penelitian ini adalah pelanggan rumah makan mega mulia cabang Delima pekanbaru. Teknik pengambilan sampel dalam penelitian ini menggunakan purposive sampling dengan rumus lemeshow sehingga jumlah sampel dalam penelitian ini berjumlah 97 orang. Teknik analisis data yang digunakan adalah analisis regresi linear berganda. Hasil penelitian menunjukkan bahwa kualitas produk, harga dan pelayanan berpengaruh positif dan signifikan terhadap kepuasan pelanggan rumah makan mega mulia cabang Delima Pekanbaru

Pengembangan Model untuk Mendeteksi Kerusakan pada Terumbu Karang dengan Klasifikasi Citra

The abundant biodiversity of coral reefs in Indonesian waters is a valuable asset that needs to be preserved. Rapid climate change and uncontrolled human activities have led to the degradation of coral reef ecosystems, including coral bleaching, which is a critical indicator of coral health conditions. Therefore, this research aims to develop an accurate classification model to distinguish between healthy corals and corals experiencing bleaching. This study utilizes a specialized dataset consisting of 923 images collected from Flickr using the Flickr API. The dataset comprises two distinct classes: healthy corals (438 images) and bleached corals (485 images). These images have been resized to a maximum of 300 pixels in width or height, whichever is larger, to maintain consistent sizes across the dataset. The method employed in this research involves the use of machine learning models, particularly convolutional neural networks (CNN), to recognize and differentiate visual patterns associated with healthy and bleached corals. In this context, the dataset can be used to train and test various classification models to achieve optimal results. By leveraging the ResNet model, it was found that a from-scratch ResNet model can outperform pretrained models in terms of precision and accuracy. The success in developing accurate classification models will greatly benefit researchers and marine biologists in gaining a better understanding of coral reef health. These models can also be employed to monitor changes in the coral reef environment, thereby making a significant contribution to conservation and ecosystem restoration efforts that have far-reaching impacts on life.Comment: in Indonesian languag

Global burden of cardiovascular diseases and risk factors, 1990–2019: update from the GBD 2019 study

Cardiovascular diseases (CVDs), principally ischemic heart disease (IHD) and stroke, are the leading cause of global mortality and a major contributor to disability. This paper reviews the magnitude of total CVD burden, including 13 underlying causes of cardiovascular death and 9 related risk factors, using estimates from the Global Burden of Disease (GBD) Study 2019. GBD, an ongoing multinational collaboration to provide comparable and consistent estimates of population health over time, used all available population-level data sources on incidence, prevalence, case fatality, mortality, and health risks to produce estimates for 204 countries and territories from 1990 to 2019. Prevalent cases of total CVD nearly doubled from 271 million (95% uncertainty interval [UI]: 257 to 285 million) in 1990 to 523 million (95% UI: 497 to 550 million) in 2019, and the number of CVD deaths steadily increased from 12.1 million (95% UI:11.4 to 12.6 million) in 1990, reaching 18.6 million (95% UI: 17.1 to 19.7 million) in 2019. The global trends for disability-adjusted life years (DALYs) and years of life lost also increased significantly, and years lived with disability doubled from 17.7 million (95% UI: 12.9 to 22.5 million) to 34.4 million (95% UI:24.9 to 43.6 million) over that period. The total number of DALYs due to IHD has risen steadily since 1990, reaching 182 million (95% UI: 170 to 194 million) DALYs, 9.14 million (95% UI: 8.40 to 9.74 million) deaths in the year 2019, and 197 million (95% UI: 178 to 220 million) prevalent cases of IHD in 2019. The total number of DALYs due to stroke has risen steadily since 1990, reaching 143 million (95% UI: 133 to 153 million) DALYs, 6.55 million (95% UI: 6.00 to 7.02 million) deaths in the year 2019, and 101 million (95% UI: 93.2 to 111 million) prevalent cases of stroke in 2019. Cardiovascular diseases remain the leading cause of disease burden in the world. CVD burden continues its decades-long rise for almost all countries outside high-income countries, and alarmingly, the age-standardized rate of CVD has begun to rise in some locations where it was previously declining in high-income countries. There is an urgent need to focus on implementing existing cost-effective policies and interventions if the world is to meet the targets for Sustainable Development Goal 3 and achieve a 30% reduction in premature mortality due to noncommunicable diseases

ANALISIS PENGARUH KEPUASAN GAJI DAN KEPUASAN KERJA TERHADAP TURNOVER PADA PEGAWAI PT. ASURANSI ASEI INDONESIA

ANALISIS PENGARUH KEPUASAN GAJI DAN KEPUASAN KERJA TERHADAP TURNOVER PADA PEGAWAI PT. ASURANSI ASEI INDONESIA

bahasa inggris

Class imbalance is a serious problem that disrupts the process of semantic segmentation of satellite imagery in urban areas in Earth remote sensing. Due to the large objects dominating the segmentation process, small object are consequently limited, so solutions based on optimizing overall accuracy are often unsatisfactory. Due to the class imbalance of semantic segmentation in Earth remote sensing images in urban areas, we developed the concept of Down-Sampling Block (DownBlock) to obtain contextual information and Up-Sampling Block (UpBlock) to restore the original resolution. We proposed an end-to-end deep convolutional neural network (DenseU-Net) architecture for pixel-wise urban remote sensing image segmentation. this method to segmentation the small object in satellite imagery.The accuracy of the small object class in this study was further improved using our proposed method. This study used data from the Massachusetts Buildings dataset using Dense U-Net method and obtained an overall accuracy of 84.34%.  Class imbalance is a serious problem that disrupts the process of semantic segmentation of satellite imagery in urban areas in Earth remote sensing. Due to the large objects dominating the segmentation process, small object are consequently limited, so solutions based on optimizing overall accuracy are often unsatisfactory. Due to the class imbalance of semantic segmentation in Earth remote sensing images in urban areas, we developed the concept of Down-Sampling Block (DownBlock) to obtain contextual information and Up-Sampling Block (UpBlock) to restore the original resolution. We proposed an end-to-end deep convolutional neural network (DenseU-Net) architecture for pixel-wise urban remote sensing image segmentation. this method to segmentation the small object in satellite imagery.The accuracy of the small object class in this study was further improved using our proposed method. This study used data from the Massachusetts Buildings dataset using Dense U-Net method and obtained an overall accuracy of 84.34%

PERANCANGAN ALAT BANTU KOMUNIKASI PASIEN STROKE BERAT MENGGUNAKAN GESTURE RECOGNITION TERINTEGRASI INTERNET OF THINGS

Salah satu penyakit penyebab disabilitas tertinggi di dunia adalah stroke. Sebagian besar penderita pascastroke mengalami penurunan fungsi motorik yang membuat pasien sulit untuk beraktivitas sehari-hari, terutama dalam berkomunikasi. Berdasarkan masalah tersebut, perlu adanya alat yang mampu membantu penderita pascastroke dalam berkomunikasi sehari-hari terutama dalam menyampaikan kebutuhan yang rutin dilakukan seperti makan, minum, berpindah, dan penggunaan toilet (activities of daily living) menggunakan anggota tubuh yang masih bisa digerakkan oleh penderita. Penelitian ini bertujuan untuk membuat alat bantu komunikasi sehari-hari penderita pascastroke menggunakan gesture recognition yang terhubung internet. Pada penelitian ini digunakan kamera sebagai masukan citra gerakan dan mikrokomputer Raspberry Pi untuk mengolah hasil tangkapan citra kamera menggunakan computer vision dan mengirimkannya ke aplikasi Android menggunakan internet. Metode yang digunakan pada penelitian ini yaitu eksperimen terencana yang diawali dengan identifikasi masalah, studi pustaka, perancangan desain produk, integrasi sistem, verifikasi dan validasi produk. Berdasarkan hasil pengujian, alat yang telah dibuat berfungsi dengan baik, notifikasi perubahan gerakan (activities of daily living) pasien dapat terkirim ke aplikasi Android saat pasien ingin beraktivitas. Pengembangan penelitian selanjutnya diharapkan mampu menyesuaikan kecakapan gerak motorik pasien yang masih berfungsi seperti raut wajah, gerakan kepala, dan lain-lain secara mudah serta penambahan berbagai jenis aktivitas pada alat sesuai dengan kebutuhan pasien. One of the highest causes of disorder in the world is stroke. Most post-stroke sufferers experience a decrease in motor function which makes it difficult for patients to carry out daily activities, especially communicating. Based on these problems, it is necessary to have a tool that can help post-stroke sufferers in communicating daily, especially in conveying routine needs such as eating, drinking, moving, and using the toilet (daily activities) using limbs that can still be moved by sufferers. This study aims to create a daily communication tool for post-stroke sufferers using gesture recognition connected to the internet. In this study, a camera was used as motion image input, and a Raspberry Pi microcomputer to process camera image captures using computer vision and send them to an Android application using the internet. The method used in this study is a planned experiment that begins with problem assistance, literature study, product design, system integration, product verification, and validation. Based on the test results, the tool that has been made functions properly, and notifications of changes in the patient's movements (activities of daily living) can be sent to the Android application when the patient wants to move. The development of further research is expected to be able to adjust the patient's motoric abilities that are still functioning such as facial expressions, head movements, etc

The role of interoperability dimensions in building information modelling

Building Information Modelling (BIM) is a paradigm shift from the traditional Architecture, Engineering, and Construction (AEC) industry practices to digital construction delivery processes. BIM provides the capabilities of cost reduction, increase quality, enhanced productivity, and on-time delivery. Despite the numerous advantages of BIM, its adoption in AEC is vulnerable to confrontation. Data interoperability is often cited as a significant barrier to BIM adoption; there is a limited focus on other dimensions of interoperability. In other research areas, such as information systems and electronic government, the evolution of interoperability construct is debated beyond data interoperability. These dimensions of interoperability have yet to be explored in the AEC industry. This research article aims to introduce the BIM Interoperability Adoption Model (BIAM). For this purpose, we investigate the interoperability in multiple dimensions according to the European Interoperability framework and develop BIM Interoperability Model with factors affecting each interoperability dimension. BIAM offers a comprehensive assessment of technical, organizational, semantic, and legal interoperability in intra –organizational AEC units, inter-organizational AEC, and BIM partner organizations and assists as a model in assessing the level of compliance and maturity interoperability. BIAM is proposed to work as a link between the organizational, semantic, legal, and technical factors to determine the interoperability issues in the early stages of BIM adoption. The BIAM model addresses interoperability factors and provides recommendations and specifications to help AEC firms to collaborate more effectively by improving interoperability activities, organizational mapping processes, and improving legal coordination. Furthermore, opportunities for future research related to BIM interoperability are discussed, and addressing these aspects of interoperability will make collaborative project delivery well informed, more structured, and effective

Smart Asissistive Device: Alat Bantu Komunikasi Pasien Stroke Berat Dengan Gesture Recognition Berbasis Internet Of Things

Stroke is the highest cause of disability in the world. Most post-stroke patients experience a decrease in motor function and make the patient experience difficulties in carrying out daily activities so that they need assistance from a companion. As a result of dysartia experienced by patients, companions need to be on guard all the time by the patient's side to anticipate the patient's needs. This makes patient companions have limitations in carrying out their daily activities. Based on these problems, an innovative communication tool for post-severe stroke patients was created with gesture recognition based on the Internet of Things. This tool can assist patients in communicating their needs appropriately while at the same time making patient companions remain productive because there is no need to stand guard accompanying patients as long as they are not needed. The research method used is a planned experiment beginning with problem identification, literature study, product design, system integration, product verification and validation. Based on data analysis, the system is functioning properly, successfully sending daily activity notifications to the accompanying Android application when the patient wants to move. This tool is very useful for post-stroke patients as a tool to communicate their needs, and is also useful for companions so that time for caring for patients is not wasted. For further development, this tool can adjust the patient's motoric abilities that are still functioning, such as head movements, facial expressions, etc., as well as adding various types of activities to the tool.Stroke merupakan penyakit penyebab disabilitas tertinggi di dunia. Sebagian besar pasien pasca stroke mengalami penurunan fungsi motorik dan membuat pasien mengalami kesulitan dalam menjalani aktivitas sehari-hari sehingga membutuhkan bantuan pendamping. Akibat disartia yang dialami pasien menjadikan pendamping perlu berjaga sepanjang waktu di sisi pasien untuk mengantisipasi kebutuhan pasien. Hal tersebut membuat pendamping pasien memiliki keterbatasan dalam menjalani aktivitasnya sehari-hari. Berdasarkan masalah tersebut, maka dibuatlah inovasi alat bantu komunikasi pasien pasca stroke berat dengan gesture recognition berbasis Internet of Things. Alat ini dapat membantu pasien dalam mengomunikasikan kebutuhannya secara tepat sekaligus membuat pendamping pasien tetap produktif karena tidak perlu berjaga mendampingi pasien selama tidak dibutuhkan. Metode penelitian yang digunakan adalah eksperimen terencana diawali identifikasi masalah, studi pustaka, perancangan desain produk, integrasi sistem, verifikasi dan validasi produk. Berdasarkan analisis data, sistem berfungsi dengan baik, berhasil mengirimkan notifikasi perubahan gerakan (daily activity) ke aplikasi Android pendamping saat pasien ingin beraktivitas. Alat ini sangat bermanfaat untuk pasien pasca stroke sebagai alat bantu komunikasi kebutuhannya, serta bermanfaat pula bagi pendamping agar waktu penjagaan pasien tidak terbuang sia-sia. Untuk pengembangan selanjutnya alat ini dapat menyesuaikan kemampuan gerak motorik pasien yang masih berfungsi seperti gerakan kepala, raut wajah, dan lain-lain serta penambahan berbagai jenis aktivitas pada alat