Abstract:The purpose of this research is to analyze the Collaborative Governance Regime (CGR) in the management of residents affected by the post-earthquake, tsunami and liquefaction disasters in Palu City. The research method used…
ed is a qualitative approach with Miles and Huberman 2014 data analysis consisting of: data collection, data condensation, data presentation, and drawing conclusions. From the research conducted, it can be concluded that the Collaborative Governance Regime (CGR) in handling disaster-affected residents after the earthquake, tsunami and liquefaction disasters have not run optimally. This is because there are components in the Collaborative Governance Regime (CGR) cycle that are not going well.
Abstract:The increased integration of operational technology (OT), Internet of Things (IoT), and business IT systems has allowed sophisticated attackers to circumvent isolated security features and launch cross-platform assaults.…
Current fragmented techniques, with discrete detectors monitoring Modbus, Kubernetes, MQTT, or other domain-specific protocols, cannot handle cross-system risks. These methodologies overlook 68% of multi-vector marketing that uses both physical and digital channels. This study introduces a transfer learning architecture to integrate detection capabilities by correlating threats across protocols, devices, and settings. The architecture generates a unified feature space that extracts behavioral semantics from industrial control system logs, cloud telemetry, network traffic, and device-level signals to produce protocol-agnostic threat representations. Adversarial domain adaptation and semantic graph embeddings enable cross-domain knowledge transfer with minimum retraining. Security teams may now discover kill chains like infected cloud containers preceding illegal PLC command execution every 23 minutes. Validated against real-world attack datasets from water treatment facilities (OT) and cloud infrastructure (IT), the system achieved 93.4% cross-platform attack recall, a 41.3 percentage point improvement over prior methodologies. It reduced OT data labeling by 89% and false positives by 93.5%. This paradigm shift transforms threat correlation from a reactive, domain-specific process to adaptive intelligence, boosting resilience for critical infrastructure, industrial ecosystems, and smart environments facing cyber-physical hazards. The framework's practical validation in energy, industry, and vital infrastructure shows its importance in protecting an increasingly linked world.
Abstract:Abstract:Corona virus is a type of influenza virus or a common virus that causes infection of the nose, sinuses or upper throat. The Covid-19 virus in humans is most commonly transmitted from an infected person to another…
r in a number of ways. This virus can be transmitted easily through the air by coughing and sneezing. However, it can also be through direct contact such as shaking hands, touching objects and so on. Indonesia is one of the countries where the spread of the corona 19 virus is relatively fast. This virus also causes the death of victims, therefore education is needed related to preparedness during the Covid 19 Pandemic. This activity was held in Tempursari village, Magelang Regency for 1 month (June 2020) involving 1 assistant lecturer and 4 students of the Guidance and Counseling study program. Muhammadiyah University of Magelang as a companion for counseling and simulations related to proper hand washing and the use of proper masks. This service activity is expected for the community to have insight into the dangers of Covid 19 and have skills related to proper hand washing procedures and the use of proper masks so that they can reduce the spread of Covid 19, especially in Magelang district.
Keywords: alert response; covid pandemic 19; wash hands
Abstrak:Virus Corona merupakan sejenis virus influenza atau virus umum yang menyebabkan infeksi pada hidung, sinus atau tenggorokan bagian atas.Virus Covid-19 pada manusia paling umum menular dari orang yang terinfeksi ke orang lain melalui berbagai cara. Virus ini dapat menular dengan mudah melalui udara dengan batuk dan bersin. Namun, bisa juga melalui kontak langsung seperti berjabat tangan, menyentuh benda dan lain sebagainya. Indonesia merupakan salah satu negara yang penyebaran Virus Covid-19 terhitung cepat. Virus ini juga menyebabkan kematian terhadap korban, karena itu perlu adanya edukasi terkait tanggap siaga dalam masa Pandemi Covid 19. Kegiatan ini dilaksankan di desa Tempursari Kabupaten Magelang selama 1 bulan ( juni 2020) dengan melibatkan 1 dosen pendamping dan 4 mahasiswa program studi Bimbingan dan Konseling Universitas Muhammadiyah Magelang sebagai pendamping penyuluhan dan simulasi terkait cuci tangan yang benar dan penggunaan masker yang tepat. Kegiatan pengabdian ini diharapkan masyarakat memiliki wawasan terkait bahaya covid 19 dan memiliki ketrampilan terkait tata cara cuci tangan yang benar dan penggunaan masker yang tepat sehingga dapat menekan penyebaran Covid-19 khususnya di kabupaten Magelang.
Kata kunci: cuci tangan; pandemi covid-19; tanggap siaga
Abstract:Abstract: Malaria remains a major global health problem, particularly in tropical countries such as Indonesia. Accurate early diagnosis is essential for reducing malaria-related morbidity and mortality. Conventional microscopic…
oscopic examination is time-consuming, highly dependent on expert personnel, and prone to human error. This study compares the performance of two Convolutional Neural Network (CNN) architectures, ResNet-50 and DenseNet-121, for malaria image classification. The Cell Images for Malaria dataset provided by the National Institutes of Health (NIH) through Kaggle was used, consisting of 27,558 microscopic blood cell images categorized into Parasitized and Uninfected classes. The dataset was divided into 80% training data and 20% testing data. Image preprocessing included resizing to 224 × 224 pixels, normalization, labeling, and data augmentation using RandomFlip, RandomRotation, RandomZoom, and RandomContrast. Experimental results showed that the ResNet-50 model trained for 100 epochs achieved the highest performance, with an accuracy of 95.54% and precision, recall, and F1-score of 0.96. The confusion matrix indicated 5,272 correctly classified images out of 5,510 testing samples. These findings demonstrate that ResNet-50 outperformed DenseNet-121 and has strong potential for supporting accurate, reliable, and efficient computer-aided malaria diagnosis based on microscopic blood smear images.
Keywords: computer-aided diagnosis; convolutional neural network (CNN); densenet-121; early detection; image classification; malaria; microscopic blood smear images; resnet-50;
Abstrak : Malaria masih menjadi masalah kesehatan global yang serius, terutama di negara tropis seperti Indonesia. Diagnosis dini yang akurat sangat penting untuk menurunkan angka morbiditas dan mortalitas. Metode konvensional berupa pemeriksaan mikroskopis memiliki keterbatasan karena memerlukan waktu yang relatif lama, bergantung pada tenaga ahli, dan berpotensi menimbulkan kesalahan manusia. Penelitian ini bertujuan membandingkan kinerja arsitektur Convolutional Neural Network (CNN) yaitu ResNet-50 dan DenseNet-121 dalam klasifikasi citra malaria. Dataset yang digunakan berasal dari Cell Images for Malaria yang disediakan oleh National Institutes of Health (NIH) melalui platform Kaggle, terdiri dari 27.558 citra dengan pembagian 80% data latih, 20% data validasi. Tahap praproses meliputi cleaning, resizing citra menjadi 224×224 piksel, normalisasi, labeling, serta data augmentasi menggunakan RandomFlip, RandomRotation, RandomZoom, dan RandomContrast. Hasil pengujian menunjukkan bahwa model ResNet-50 pada epoch 100 memperoleh akurasi sebesar 95,54% dengan nilai precision, recall, dan F1-score masing-masing sebesar 0,96. Confusion matrix menunjukkan jumlah prediksi benar sebanyak 5.272 dari total 5.510 data uji. Hasil ini menunjukkan bahwa arsitektur CNN mampu mengklasifikasikan citra malaria dengan tingkat akurasi yang tinggi dan memiliki kemampuan generalisasi yang baik terhadap data baru. Penelitian ini memberikan kontribusi dalam evaluasi performa arsitektur CNN untuk mendukung pengembangan sistem diagnosis malaria berbasis citra mikroskopis yang lebih cepat dan akurat.
Kata kunci: convolutional neural network (CNN); citra mikroskopis hapusan darah; densenet-121; diagnosis berbantuan komputer; deteksi dini; klasifikasi citra; malaria; resnet-50
Abstract:Abstract: Hospitals play an important role in examining the scan results of patient data infected with the Covid 19 virus. However, there are problems when processing the scan results, namely that sometimes errors occur…
in the scan data, causing many failures and delays in sending data to the Health Office. The purpose of this study is to build a Desktop-based decision support system application that can facilitate hospitals in selecting the eligibility of the scan results of Covid 19 patient data. The urgency in examining the scan results of Corona patient data is a very pressing public health issue, because the long-term impact is very significant for patients. Thus, a scientific discipline is needed that can support the decision-making process, namely the Decision Support System using the Preference Selection Index (PSI) method. PSI is a simple and easy calculation method, based on statistical concepts without having to determine attribute weights. The results of this method are clear and firm values based on the level of strength of the rules applied. The results of the research conducted on the PSI process can be concluded that valid Covid 19 patient data is Recap File I with a value of 0.2042 which is declared valid and accepted.
Keywords: covid-19; decision support system; PSI
Abstract:Abstract: This research aims to develop a method for detecting leaf spot disease in oil palm seedlings using Convolutional Neural Network (CNN). Leaf spot disease in oil palm seedlings can hinder growth and production. CNN…
NN has proven effective in image processing and classification, particularly in plant disease detection. In this study, we utilized a dataset of images containing oil palm seedling leaves infected with leaf spot disease and healthy leaves. We performed data processing, built a CNN model, and conducted hyperparameter tuning. The test results demonstrate that the developed CNN model achieves high accuracy in recognizing and distinguishing between oil palm seedling leaves infected with leaf spot disease and healthy ones. This research contributes to the development of plant disease detection technology that can support economic growth in the oil palm plantation sector.
Keywords: Convolutional Neural Network, image processing, leaf spot disease detection, oil palm seedlings.
Abstrak: Penelitian ini bertujuan untuk mengembangkan metode deteksi penyakit bercak pada bibit kelapa sawit menggunakan Convolutional Neural Network (CNN). Bibit kelapa sawit yang terinfeksi penyakit bercak dapat menghambat pertumbuhan dan produksi kelapa sawit. Metode CNN telah terbukti efektif dalam pengolahan citra dan klasifikasi, khususnya dalam deteksi penyakit pada tanaman. Dalam penelitian ini, kami menggunakan dataset citra daun bibit kelapa sawit yang terinfeksi penyakit bercak dan yang normal. Kami melakukan processing data, membangun model CNN, dan melakukan tuning hyperparameter. Hasil pengujian menunjukkan bahwa model CNN yang dikembangkan memiliki akurasi yang tinggi dalam mengenali dan membedakan citra daun bibit kelapa sawit yang terinfeksi penyakit bercak dan yang normal. Penelitian ini memberikan kontribusi dalam pengembangan teknologi deteksi penyakit tanaman yang dapat mendukung pertumbuhan ekonomi di sektor perkebunan kelapa sawit.
Kata kunci: bibit kelapa sawit, Convolutional Neural Network, deteksi penyakit bercak, pengolahan citra.
Abstract:Abstract : Coconut plantation palm has a very strategic role in the development of the Indonesian economy. Coconut palm that is processed becomes oil cook and material burn. To produce product quality derivatives from coconut…
conut palm this needs proper handling in its maintenance. On plantation coconut palm lots were found to cause coconut infected palm disease, so this will hinder productivity of the plantation. Handling is not appropriate to coconut infected palm disease and can result in losses that don't little. To overcome the problem, they make it a system android based expert. System experts can diagnose disease with detect the symptoms shown coconut palm moment attacked disease, so taking decision for handling furthermore will be more accurate that will impact on results maximum harvest.
Keywords : android; coconut palm; disease; system expert.
Abstrak : Perkebunan kelapa sawit memiliki peranan yang sangat strategis dalam pembangunan ekonomi Indonesia. Kelapa sawit ini banyak diolah menjadi minyak masak dan bahan bakar. Untuk menghasilkan produk turunan yang berkualitas dari kelapa sawit ini maka membutuhkan penanganan yang tepat dalam pemeliharaannya. Pada perkebunan kelapa sawit banyak ditemukan kasus kelapa sawit yang terserang penyakit, sehingga hal ini akan menghambat produktivitas perkebunan. Penanganan yang tidak tepat terhadap kelapa sawit yang terserang penyakit dapat mengakibatkan kerugian yang tidak sedikit. Untuk mengatasi masalah tersebut dibuatlah sistem pakar yang berbasis android. Sistem pakar dapat mendiagnosis penyakit dengan mendeteksi gejala-gejala yang ditunjukan kelapa sawit saat terserang penyakit, sehingga pengambilan keputusan untuk penanganan selanjutnya akan lebih akurat yang akan berdampak pada hasil panen yang maksimal.
Kata Kunci : android; kelapa sawit; penyakit; sistem pakar.
Abstract:This research uses Pre-Experimental Design without control group with One Group Pretest-Posttest Design. The study was conducted in March 2021 in two districts that were confirmed to be inhabited by COVID-19 positive residents…
idents (Johan Pahlawan District and Meureubo District), West Aceh, Indonesia. Statistical analysis used: Hand-washing is one way to prevent COVID-19 transmission. This is essential because in this global pandemic, every community has the opportunity to catch COVID 19. The research objective was to determine the effectiveness of WASH educational collaboration on farmers as an attempt to COVID-19 prevention. The population in the study is all farmers who live in these mentioned districts. There were 37 farmers in total. The sampling method used total sampling, namely 37 farmers who live in the areas that are confirmed to have positive patients of COVID 19. Data were analyzed using Univariate, Bivariate (Dependent T-test) and Multivariate with using logistic regression. The result shows that there is a significant influence between the collaboration of WASH Education on farmers as an effort to prevent COVID-19 with a statistical test value of P-Value <0.05. Collaboration on WASH education for farmers is very influential in preventing COVID-19. It is hoped that cross-sectoral involvement and roles can be maintained so that COVID 19 prevention behavior through WASH can continue to be applied. Educative collaboration of WASH impacts on the behaviour alteration toward farmers who live in the area confirmed to be infected by COVID 19.
Abstract:A wound is an injury where the skin is torn, cut or punctured, or a blunt force trauma causes a contusion. The use of honey as a wound treatment has been widely used, but the comparison of accelerated wound healing using…
three types of honey originating from Indonesia is not yet known. From the results of the study that on days 1 to 7 the MD-NTT group could reduce exudate weight better than the MD-JW, MD-KLM, and K-MD. The conclusion in this study is that the use of honey originating from NTT can be an alternative to healing acute wounds infected with bacteria.