The Role of Balanced Nutrition for the Recovery of COVID-19 Patients Undergoing Self-Isolation

Coronavirus (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus. Not all COVID-19 patients are reported to have severe symptoms. There are also patients who are asymptomatic or with mild symptoms who only need rest and self-isolation. Self-isolation is an attempt to separate a person confirmed COVID-19 with or without symptoms, from a healthy person which aim is to reduce the risk of transmission. Nutritional intake in patients with COVID-19 includes energy needs from macronutrient, micronutrients, fluids and electrolytes. A balanced diet can support a strong immune system and help fight viral infections. In this activity, the method used was whatsApp media or android /web-based applications. Patients are classified into 3 groups, namely asymptomatic groups or mild symptoms, without decreased oxygen saturation (green group), patients with moderate symptoms, oxygen saturation still above 95% (yellow group), patients with severe symptoms and saturation below 95% (red group). Virtual consultations are conducted with the aim of reminding a balanced nutrition intake in patients, guiding cough techniques and warning signs of COVID-19. This activity provided lunch support consisting of rice, vegetables, animal protein, side dishes and fruit that can hasten healing from COVID-19

Pencegahan Stunting dengan Pemberian Susu Kambing pada Balita di Dusun Ketawang Magelang

Stunting adalah kondisi gagal tumbuh pada Balita yang diakibatkan kekurangan gizi kronis sehingga anak menjadi pendek dibandingkan dengan anak usianya. Angka Stunting di Indonesia pada tahun 2022 masih di atas 21%, dan ditargetkan dapat turun di angka 14% di tahun 2024. Anak dengan stunting memiliki tubuh lebih pendek dari anak normal seusianya dan mengalami keterlambatan dalam berpikir yang dapat menimbulkan kerugian ekonomi bagi negara sebesar 2-3 persen dari Produk Domestik Bruto (PDB) per tahun. Tujuan dari pengabdian ini adalah meningkatkan kesadaran orangtua tentang pentingnya protein hewani, salah satunya dengan susu kambing untuk diberikan pada balita dalam mencegah dan menanganI stunting. Susu kambing memiliki kelebiihan seperti mudah diabsorbsi, tidak menggumpal, memiliki risiko kecil dalam menimbulkan alergi pada anak. Susu kambing memiliki globula lemak yang lebih kecil dan asam lemak rantai pendek dan menengah (MCT) yang lebih pendek daripada susu sapi, dan memiliki kemampuan metabolisme yang baik untuk menyediakan energi pada proses pertumbuhan anak. Metode pengabdian ini meliputi pemberian susu kambing pada balita dan pemberian edukasi pada orangtua balita tentang gizi seimbang pada balita. Kegiatan dilaksanakan di dusun Ketawang Magelang. Pelaksanaan kegiatan ini mendapat respons yang baik dari orangtua Balita maupun kader Kesehatan setempat. Diperlukan kegiatan berkelanjutan sebagai pendampingan dalam membantu orangtua Balita untuk memberikan makanan yang sesuai dengan kebutuhan tumbuh kembang buah hatinya. Stunting is a condition of failure to thrive in toddlers caused by chronic malnutrition so that children are short compared to their age. The stunting rate in Indonesia in 2022 is still above 21% and is targeted to decrease to 14% in 2024. Children with stunting have shorter bodies than normal children of their age and experience delays in thinking which can cause economic losses to the country of 2 -3 percent of Gross Domestic Product (GDP) per year. The purpose of this service is to increase parental awareness about the importance of animal protein, one of which is goat's milk to be given to toddlers in preventing and treating stunting. Goat's milk has advantages such as being easily absorbed, does not clot, and has a small risk of causing allergies in children. Goat's milk has smaller fat globules and shorter short and medium-chain fatty acids (MCT) than cow's milk and has a good metabolic ability to provide energy for the child's growth process. This service method includes giving goat milk to toddlers and providing education to parents of toddlers about balanced nutrition for toddlers. The activity was carried out in the Ketawang village, Magelang. The implementation of this activity received a good response from toddlers' parents and local health cadres. Continuous activities are needed as assistance in helping parents of toddlers to provide food that is by the needs of the growth and development of their children

Klasifikasi Kemampuan Kognitif Pembelajar Pada Permainan Matematika Berbasis Metode Backpropagation Neural Network

Mengklasifikasikan profil pembelajar siswa merupakan suatu kebutuhan dalam dunia pendidikan. Klasifikasi tersebut bisa meliputi kemampuan kognitif maupun gaya belajar dari seorang siswa. Kemampuan kognitif siswa dalam belajar di sekolah sangat penting untuk diketahui perkembangannya agar seorang pengajar dapat mengevaluasi kegiatan belajar mengajar yang dilakukan telah sesuai dengan yang diharapkan atau belum. Dengan menerapkan metode jaringan saraf tiruan, diharapkan hasil klasifikasi dapat menunjukkan angka galat yang sedikit. Penelitian ini mengklasifikasikan profil pembelajar dari segi kemampuan kognitifnya. Klasifikasi ini diharapkan dapat memudahkan pengajar dalam menilai kemampuan anak didiknya serta mengevaluasi kegiatan belajar mengajar di dalam kelas. Dengan cara membandingkan keluaran sistem dengan keluaran hasil tes tulis siswa, didapatkan nilai selisih akar kuadrat (RMSE) senilai 0.295 ===================================================================================================== Classify student learner profile is a necessity in education sector. Such classification includes cognitive ability and learning style of the student. The student cognitive skill in learning at school is very important to note its development so that a teacher can evaluate the studying and teaching methods that have been done. By applying Artificial Neural Network method, expected results of classification can show a small error. This research classify student cognitive ability. This classify is expected to help teacher in assessing student ability and also evaluate the studying and teaching methods at class. Student cognitive ability can be classified in this research with RMSE value 0.29

Penerapan Fuzzy Tsukamoto pada Alat Deteksi Penyakit Hipoksemia, Hipotermia, Hipertensi, dan Diabetes untuk Health Care Kiosk

Most of people in Indonesia need fast, right, and accurate health medical service. But as we know in hospital takes many time just for check our health condition. This research make a Health Care Kiosk for medical check up, without using a doctor, so that kiosk can detect many deseases automatically. This research focused on 4 deseases such as hypothermia, hypoxemia, hypertension and diabetes. System using Embedded PC for data processing automatically. There are many medical sensor such as thermometer, heart rate sensor, blood pressure sensor, SPO2 sensor, and glucometer sensor for check health condition. System can make a decision if that patient healthy or not automatically because it uses fuzzy method for that decision. The result of this paper is this system can detect every deseases and that error for each sensor are body temperature has 1.05% error, oxygen level has 1.90% error, heart rate has 5.78% error, blood pressure sistolic has 4.16% error, blood pressure diastolic has 4.87% error and glucosa level in blood has 4.01% error. This system integrated with database MySQL for save that result. The accuracy from fuzzy method is 100% right and fuzzy tsukamoto can process input well.Most of people in Indonesia need fast, right, and accurate health medical service. But as we know in hospital takes many time just for check our health condition. This research make a Health Care Kiosk for medical check up, without using a doctor, so that kiosk can detect many deseases automatically. This research focused on 4 deseases such as hypothermia, hypoxemia, hypertension and diabetes. System using Embedded PC for data processing automatically. There are many medical sensor such as thermometer, heart rate sensor, blood pressure sensor, SPO2 sensor, and glucometer sensor for check health condition. System can make a decision if that patient healthy or not automatically because it uses fuzzy method for that decision. The result of this paper is this system can detect every deseases and that error for each sensor are body temperature has 1.05% error, oxygen level has 1.90% error, heart rate has 5.78% error, blood pressure sistolic has 4.16% error, blood pressure diastolic has 4.87% error and glucosa level in blood has 4.01% error. This system integrated with database MySQL for save that result. The accuracy from fuzzy method is 100% right and fuzzy tsukamoto can process input well

Teaching English Vocabulary to Young Learners via Augmented Reality Learning Media

This research aims to investigate the effect of teaching English vocabulary to young learners via Augmented Reality learning media. The subject of this research was 12 students of grade 1 elementary school. Due to strict health protocols during COVID-19 outbreak, the testing phase was done in students' respective homes accompanied by their parents using cell phones. Vocabulary illustrated in 30 three-dimensional objects and their written form were generated through cell phone’s scanning. A quiz consisted of 54 multiple choice questions was provided after the interactive learning experience. Both the vocabulary and quiz were refer to Thematic English Exploration for Grade 1 book. The results showed that learning vocabulary using AR application was able to increase the mean evaluation score by 0.77%. This application is effective in helping students improve their English language skills as approved by 76% of parents. The AR application was also approved by 59% of parents that it was easy to use. The AR application is proven to be convenience for students to learn English vocabulary interactively and feasible to be used as learning media

Deteksi Microaneurysm Pada Mata Sebagai Langkah Awal Untuk Penentuan Diabetic Retinophaty Menggunakan Pengolahan Citra Digital

Diabetic Retinopathy is a microvascular complication of diabetes mellitus. According to WHO (World Health Organization), there are more than 347 billion people who suffer from diabetes. This disease will become the seventh leading cause of death in the world in 2030. Based on research in Indonesia, it is estimated that there are 42.6% of diabetic retinopathy. Therefore, this final project plans a system to assist doctors in identifying diabetic retinopathy through its characteristics, namely microaneurysm. This system begins with an input retinal image from the fundus camera. Then the input will be processed in preprocessing to increase the contrast using the green channel. The next stage is segmentation. This is used to detect candidates from blood vessels and microaneurysms that use morphology operations. The next step is feature extraction, where it uses the features of glcm and white pixels detected in the image resulting from segmentation. The value of the white pixels and the values in the glcm feature are used as parameters in determining whether the classification process will be used as a determination of a Diabetic Retinopathy image or not. The success rate of the system using the SVM (Support Vector Machine) method is 88.4%

Automatic Detection of Fetal Head and Fetal Measurement on Birth Time Estimation

Fetal biometry in ultrasound (USG) is a routine activity that can be used to determine the gestational age of a baby. Accuracy is needed when measurements are made. However, the low quality of ultrasound images and manual measurement that takes a long time and give rise to many different variations of values from each doctor or sonographer. Thus the measurement results obtained are less accurate. From these problems, the development of automatic detection and measurement of the fetal head is needed. One of them is by using a learning-based system method that will carry out the training process using Haar training to get features. The training process with the Haar method uses positive image data as objects and negative images as background. Haar training data that have been obtained, then used to detect fetal head objects automatically. Detection results are then processed to separate the object from the background image, which is then carried out the segmentation process to obtain the fetal head and fetal femur. Then the segmentation method used is Integral Projection to get the fetal head circumference and Find Contour to get the fetal femur. The parameters used to determine gestational ages are biparietal diameter and femur length. Based on experiments that have been done, obtained an accuracy rate of 97.77% using the proposed method for estimating gestational age automatically. Measurements are obtained by comparing the results of the doctor's diagnosis using manual measurements on an ultrasound machine

Pemetaan Usaha Budidaya Perikanan Air Tawar Di Wilayah Kabupaten Dati II Malang

Wilayah Kabupaten Malang merupakan suatu kawasan yang permintaan akan produk-produk perikanannya cukup besar. Perkembangan konsumsi ikan perkapita masyarakat Kabupaten Malang pada tahun 1997 dan I998 adalah 14,02 dan 14,23 kg/perkapita/tahun, sedangkan target nasional 22,5 kg/perkapita/tahun. Untuk pemenuhan kebutuhan tersebut masyarakat Kabupaten Malang mengusahakan dengan berbagai cara disamping produksi ikan dari kawasan sendiri juga mendatangkan dari Iuar daerah . Kawasan ini memiliki potensi sumber daya alam yang potensial khususnya kawasan subur dan perairan umum yang bisa dimanfaatkan untuk tujuan pemenuhan protein hewani masyarakat. Tujuan Penelitian ini adalah (1) memetakan usaha budidaya perikanan air tawar di wilayah Kabupaten Malang (2) menentukan daerah-daerah yang sangat mendukung untuk usaha budidaya air tawar (3) sebagai upaya identifikasi potensi dan komoditas budidaya air tawar di Kabupaten Malang. Penelitian ini dilakukan dengan metode survey di 35 kecamatan di Kabupaten Malang. Teknik pengambilan data dengan pengumpulan data primer dam sekunder. Data primer dianalisa melalui pendekatan produksi dengan nilai LQ, pendekatan agroekosistem, agrobisnis dan pendekatan kebijakan dengan pemberian nilai skor. Dari analisa tersebut didapatkan daerah-daerah yang sangat mendukung untuk usaha - usaha budidaya air tawar. Dari hasil penelitian yang diiakukan dapat dikemukakan hal-hal sebagai Berikut: I. Daerah-daerah yang sangat mendukung untuk usaha budidaya a. Kolam meliputi : Kecamatan Batu, Singosari, Lawang, Wajak dan Turen b. Mina padi meliputi : Kecamatan Ngajum dan Turen. c. Karamba meliputi : Kecamatan Batu, Junrejo, Singosari, Lawang, Pakis, Wajak, Turen, Kepanjen, Ngajum d. Jaring apung meliputi : Kecamatan kalipare, sumberpucung dan Pagak 2. Sistem budidaya (teknologi ) yang berkembang di wilayah Kecamatan-kecamatan Kabupaten Malang antara Iain ; Kolam ( I00 % ), mina padi ( 37,14 % ), Karamba ( 28,85 % ) dan Jaring apung ( 8,57 % ). 3. Sedangkan komoditas ikan yang telah dibudidayakan wilayah Malang antara lain meliputi , ikan Lele ( 94,28 %), Tombro (57,l4 %), Nila ( 37,14 %), Gurami ( 20,0% ), Katak ( 25,7l%) dan Ikan Hias dan lain-Iain( 11,42 %)

Implementation of Myo Armband on Mobile Application for Post-stroke Patient Hand Rehabilitation

Medical rehabilitation is one of the efforts to restore motor function of post-stroke patients, but the biggest factor that makes patients quickly restore motor function by active patient movement exercises. The movement in question is the movement carried out every day outside medical rehabilitation at the hospital. On the other hand, patients are reluctant to do therapy independently outside the hospital, because there is no tool that supports patients to do so. So, we need a device that helps patients to do therapy independently. The device is connected to Myo Armband to read the gestures of the patient by looking at the EMG signal from the patient's hand. Then the system performs matching gestures during therapy with EMG signal data that has been trained. The motion matching is done by calculating the Euclidean distance between the two EMG signal data obtained from the Myo Armband device. From the results of the tests carried out, the accuracy of movement matching results obtained an average accuracy of 89.67 percent for flexion-extension gestures and 82 percent for pronation-supination gestures. It can be concluded that Myo Armband in the Mobile Application can be used for Rehabilitation of post stroke patient hands