Asuhan kebidanan continuity of care (coc) pada ny. “j” dibidan praktik mandiri lismarini palembang

The World Health Organization (WHO) states that the maternal mortality rate in 2017 is 462/100.000 KH, the maternal mortality rate in indonesia according to the 2017 (SDKI) is still high at 305/100.000 KH, the maternal mortality rate in palembang city in 2018 is 4 people from 126,837 KH and maternal mortality rate in the lismarini independent midwife practice in 2019 was 0 people. One of the efforts to reduce maternal mortality and infant mortality is to carry out continuity of care (COC) midwife care, namely continuity of care (COC) midwife care for Mrs.J starting from pregnancy, childbirth, newborns, postpartum and neonatus in the independent midwife practice of lismarini. This final project report provides midwifery care continuity of care (COC) to Mrs.J in the independent midwife practice of lismarini since mart 28 marce 2021 in the second trimester starting from pregnancy, child birth, new borens, post partum and neonatus. The data collection technique data. The midwifery method used was the midwifery continuity of care (COC) approach and used the SOAP method. The results of care obtained from midwifery continuity of care (COC) for Mrs.J in pregnancy, child birth from the 1st to the 4st stage of new borns 6 hours and 7 days post partum and neonatus. The scope of physiology felt by the mother stomach pain radiating to the waist. The conclusion is based on the assessment of the data, Mrs J is cooperative and there are no problems. The advice given to the patient is expected to always maintain the health of herself and her baby and keep in touch with the midwife

Design and Development Augmented Reality Application to Introduce the Potential of Sudaji Village in Bali Using the Design Thinking Method

Indonesia is a country that has diversity, both in terms of ethnicity, customs, religion, and language. One of them is the island of Bali, the island of Bali is one of the parameters of Indonesian tourism. Data on the high number of tourist visits to Bali before the pandemic increased. This is what affects the economy in Bali. However, due to the COVID-19 pandemic, tourists visiting Bali have decreased. In an effort to increase the economy due to the pandemic in the tourism sector, the Province of Bali continues to develop villages in Bali into tourist villages. One of them is Sudaji Village, Sudaji Village is included in the top 50 Indonesian tourist villages, the current digitization in the form of websites, YouTube, Instagram, Tiktok, Facebook which is used to provide information about the potential that exists in the village. However, the digitization is still not enough to encourage tourists to know about Sudaji Village, especially domestic tourists. This is evidenced by the results of interviews with five domestic tourists, stating that they have never heard of tourism in Sudaji Village, Bali. In the development of digital villages in Sudaji Village, namely using Augmented Reality (AR). Augmented Reality (AR) is a technology that has a lot of potential to be developed in various fields. This study uses the design thinking method with 5 stages, namely empathize to find out about the problems of potential users, define to define problems from the data that has been obtained, ideate, which is to create solutions or ideas based on existing problems, prototypes make products from the results of the previous stages, and the fifth stage, namely testing carried out by 5 potential users to get an SUS score of 82 which is included in the A value with excellent information

Ant Colony Optimization for Resistor Color Code Detection

In the early stages of learning resistors, introducing color-based values is needed. Moreover, some combinations require a resistor trip analysis to identify. Unfortunately, a resistor body color is considered a local solution, which often confuses resistor coloration. Ant Colony Optimization (ACO) is a heuristic algorithm that can recognize problems with traveling a group of ants. ACO is proposed to select commercial matrix values to be computed without preventing local solutions. In this study, each explores the matrix based on pheromones and heuristic information to generate local solutions. Global solutions are selected based on their high degree of similarity with other local solutions. The first stage of testing focuses on exploring variations of parameter values. Applying the best parameters resulted in 85% accuracy and 43 seconds for 20 resistor images. This method is expected to prevent local solutions without wasteful computation of the matrix

Development of Human Facial Expression Game for Autism Children Using Design Thinking Method

Facial expression is one of the important factors in interacting and communicating activities. People can know the emotions and feelings of the interlocutor through their facial expressions. However, this can be difficult while doing interactions with children with autism. These limitations become obstacles in socializing for children with autism because not everyone can understand their feelings. To overcome this problem, a study was proposed with the title "Development of a Game for Recognizing Human Facial Expressions for Children with Autism Using Design Thinking Methods". The existence of this research is expected to help children with autism to learn facial expressions according to the emotions they feel and can improve their social skills. The method used in this study is the Design Thinking method which consists of 5 stages, namely Empathize, Define, Ideate, Prototype, and Test

ADAPTIVE ANT COLONY OPTIMIZATION BASED GRADIENT FOR EDGE DETECTION

Ant Colony Optimization (ACO) is a nature-inspired optimization algorithm which is motivated by ants foraging behavior. Due to its favorable advantages, ACO has been widely used to solve several NP-hard problems, including edge detection. Since ACO initially distributes ants at random, it may cause imbalance ant distribution which later affects path discovery process. In this paper an adaptive ACO is proposed to optimize edge detection by adaptively distributing ant according to gradient analysis. Ants are adaptively distributed according to gradient ratio of each image regions. Region which has bigger gradient ratio, will have bigger number of ant distribution. Experiments are conducted using images from various datasets. Precision and recall are used to quantitatively evaluate performance of the proposed algorithm. Precision and recall of adaptive ACO reaches 76.98 % and 96.8 %. Whereas highest precision and recall for standard ACO are 69.74 % and 74.85 %. Experimental results show that the adaptive ACO outperforms standard ACO which randomly distributes ants

Emotion Recognition using Fisher Face-based Viola-Jones Algorithm

In the form of the image integral, this primitive feature accelerates the performance of the Viola-Jones algorithm. However, the robust feature is necessary to optimize the results of emotion recognition. Previous research [11] has shown that fisher face optimized projection matrix in the low dimensional features. This feature reduction approach is expected to balance time-consuming and accuracy. Thus we proposed emotion recognition using fisher face-based Viola-Jones Algorithm. In this study, PCA and LDA are extracted to get the fisher face value. Then fisher face is filtered using Cascading AdaBoost algorithm to obtain face area. In the facial area, the Cascading AdaBoost algorithm re-employed to recognize emotions. We compared the performance of the original viola jones and fisher face-based viola jones using 50 images on the State University of Malang dataset by measuring the accuracy and time-consuming in the fps. The accuracy and time-consuming of the Viola-Jones algorithm reach 0.78 and 15 fps, whereas our proposed methods reach 0.82 and 1 fps. It can conclude that the fisher face-based viola-jones algorithm recognizes facial emotion as more accurate than the viola-jones algorithm

Design and Development an Augmented Reality Pop-Up Earth Application Using the Design Thinking Method

The importance of providing information about planet earth to users is one of the reasons for conducting this research, because humans are living beings who play an important role in protecting the earth so that various information and knowledge about planet earth are needed. To get this information, the smartphone is one of the tools used as a medium of information. Through the use of this technology, researchers convey information using an interactive pop-up application in the form of three dimensions. To realize the interactive application, researchers use markerless-based augmented reality technology, so that users can use it without any limitations of space and time.The development method used in this research is the design thinking method consisting of 5 stages, namely empathize, define, ideate, prototype, and test. The testing phase in this study uses blackbox testing, validation tests carried out by experts, and a usability scale system carried out by potential users to determine the level of satisfaction when using the application. The results of the Pop-Up Earth application test show that the application is in grade A or the excellent category with an average SUS score of 82.5% and can run well as expected. Experts state that this application is valid for use with an average value of 98.3% for the delivery of application media and 87.5% for the delivery of application information. It is hoped that the Pop-Up Earth application can provide various information about planet earth to users interactively and informatively.

The Improved Artificial Neural Network Based on Cosine Similarity in Facial Emotion Recognition

In this study, we present the improved artificial neural network based on cosine similarity in facial emotion recognition. We apply a shifting window that employs neural network for two concurrent processes consisting of face detection and emotional recognition. In order to prevent the slow and futile computations, non-face areas need to be filtered from neurons on each network layer, thus we propose the improved artificial neural network based on cosine similarity. Cosine similarity is employed to bypass the process of non-face areas in neural network. The accuracy of the proposed method reaches 0.84, while the accuracy of the original neural network method reaches 0.74. It can be concluded that our methods work accurately.proposed method is superior to the state-of-the-art algorithms

Optimization of 2D-CNN Setting for the classification of covid disease using Lung CT Scan

RT-PCR is considered the best diagnostic tool. Previous studies have demonstrated the reliability of CNN in classifying classifications, but CNN requires a lot of training data. Meanwhile, at the CT Scan clinic, patients are limited. Therefore, exploration of 2D-CNN settings is proposed to optimize CNN performance on limited data. We compare: (1) activation models, (2) output shapes per layer, (3) dropout layers, and (4) early stopping values. The test results show that RELU activation is better than Sigmoid. Rescaling (128x128) is better for scala (64x64) and (256x256) which affects the output shape model of each layer. In this learning stage, the use of dropouts in the CNN architecture achieves robust accuracy than the architecture that ignores dropouts. The use of 15 early stoppings is better than other values compared. 20 images of pneumonia and 20 images of covid have been tested using the proposed method and achieved 87.50% accuracy, 80.00% precision, 100% recall, and 99.89% F1-Score. Our method is superior to the the comparison method in terms of accuracy, precision, recall, and f1-score, which achieves 85%, 70%, 100%, and 82.35%, respectively

SISTEM PENDUKUNG KEPUTUSAN PRODUKSI BERBASIS FUZZY PADA SISTEM INFORMASI JUAL BELI MOBIL BEKAS

Sistem informasi jual beli merupakan salah satu jenis sistem informasi yang difungsikan untuk mengendalikan,mengontrol,dan memonitor aktifitas jual beli sebuah perusahaan. Bagaimanapun, proses kontrol jumlah barang membutuhan rekomendasi jumlah produksi yangdiolah secara otomatis, cepat dan dianalisis berdasarkan data statistika yang dimiliki perusahaan tersebut. Untuk itu, pada penelitian ini, diusulkan pengembangan sistem pendukung keputusan produksi berbasis Fuzzy pada sistem informasi jual beli. Jumlah produksi diperoleh secara otomatis berdasarkan perbandingan antara jumlah stok yang tersedia dan jumlah penjualanyang terjadi dalam jangka bulanan. Stok atau persediaan barang dan jumlah penjualan dikomputasi dengan tahapan: (1) fuzzyfikasi, (2) pembentukan aturan, (3) inferensi, dan (4) defuzzyfikasi. Data yang digunakan dalam penelitian ini adalah data penjualan mobil bekas padamobilhandal.com. Kecepatan performa Fuzzy dalam memberikan keputusan diuji sebanyak sepuluh kali percobaan menggunakan dua spesifikasi laptop yang berbeda.Hasil pengujian menunjukkan rata-rata kecepatan algoritma Fuzzy adalah 1.79 detik. Berdasarkan hasil tersebut, dapat disimpulkan bahwa algoritma Fuzzy memberikan keputusan jumlah produksi secara cepat