scholarly journals Automatic Cigarette Object Concealment in Video using R-CNN

2021 ◽  
Vol 5 (1) ◽  
pp. 21
Author(s):  
Kadek Utari Widiarsini ◽  
Duman Care Khrisne ◽  
I Made Arsa Suyadnya
Keyword(s):  
Neural Network ◽  
Causes Of Death ◽  
Test Results ◽  
Tobacco Products ◽  
Application Performance ◽  
Nicotiana Rustica ◽  
Heart Attacks ◽  
The Public ◽  
The World ◽  
Lung Infections

Cigarettes are packaged processed tobacco products, produced from the Nicotiana Tabacum, Nicotiana Rustica plants and other species or synthetics that contain nicotine with or without additives. Smoking is known to the public as one of the causes of death in the world that is quite large such as asthma, lung infections, oral cancer, throat cancer, lung cancer, heart attacks, strokes, dementia, erectile dysfunction (impotence), and so on. This research aims to build an application that can recognize cigarettes automatically and conceal pictures so that people especially minors are not affected by cigarettes. The application is built using the Region-based Convolutional Neural Network (R-CNN) method. The study uses images that have cigarette objects in them. The test is carried out to find out the application performance such as the level of application accuracy in recognizing cigarette objects. Based on the test results with a sample of 126 cigarette images, the application built is able to recognize cigarette objects by obtaining an accuracy value of 63%.

scholarly journals PENETAPAN KADAR KAFEIN PADA BUBUK TEH HITAM YANG BEREDAR DI PASAR DELI TUA MENGGUNAKAN SPEKTROFOTOMETRI UV

2020 ◽  
Vol 3 (1) ◽  
pp. 21-28
Author(s):  
DIAN IKA PERBINA MELIALA
Keyword(s):  
Side Effects ◽  
Sampling Method ◽  
Negative Impact ◽  
Black Tea ◽  
The Body ◽  
Test Results ◽  
Ultraviolet Spectrophotometry ◽  
The Public ◽  
Validation Test ◽  
The World

Tea is a drink that is very familiar in the world and is very common in everyday life. Tea is also the most consumed and favored beverage by the public after water. Besides being beneficial, tea also contains compounds that have a negative impact on the body, namely caffeine compounds. Caffeine is an alkaloid of the methylxanthine group which plays a role in increasing the work of psychomotor in the body, and side effects that can be caused are anxiety, irregular heartbeat, difficulty sleeping, tremors, diuresis and others. The purpose of this study was to determine the caffeine content in black tea powder circulating in the Old Deli market. This type of research is descriptive with a purposive sampling method. The analytical method used is qualitative with murexide and quantitative ultraviolet spectrophotometry with a wavelength of 267nm. The results of a qualitative analysis of all positive samples contained caffeine. The average quantitative yield of caffeine in brand A black tea powder was (4,82 ±0,0356)%, B brand black tea powder (4,89 ± 0,0173)% and C brand black tea powder (4,93 ± 0,0531)%. The validation test results obtained linearity r = 0,9984, LOD and LOQ is 0,8074 mcg/ml and 2,6914 mcg/ml ,% recovery = 100,07%, RSD = 0,33%. Based on the results of research conducted, it can be concluded that ultraviolet spectrophotometry can be used to determine caffeine levels in black tea powder.

scholarly journals GAMBARAN KEPATUHAN DIET PADA ANGGOTA PROLANIS SELAMA PANDEMI COVID-19 DI WILAYAH KERJA PUSKESMAS BOJONG 2

2021 ◽  
Vol 16 (1) ◽  
pp. 29-35
Author(s):  
Moh. Khotibul Umam ◽  
Windi Imaningtias ◽  
Nurul Hidayati Listianingrum
Keyword(s):  
Research Method ◽  
Causes Of Death ◽  
Health Workers ◽  
Monitoring Program ◽  
Mortality Rates ◽  
The Public ◽  
Descriptive Research ◽  
The World ◽  
Diet Counseling ◽  
The Right

Non-communicable diseases (NCDs) are the leading causes of death and are responsible for the highest mortality rates in the world and in Indonesia. One of the programs for controlling NCDs especially hypertension and Diabetes at the Public Health Center (PHC) is Prolanis. One of the Prolanis programs is the monitoring of dietary adherence among Prolanis members. A descriptive research design was used as research method. The samples of this study were 34 Prolanis members in Sumurjomblang Bogo Village, the working area of Puskesmas Bojong 2. The results showed that the majority of Prolanis members in Sumurjomblang Bogo did not compliant the right schedule of diet (80%), the right type of diet (60%), and the right number of diet (60 %) for diabetes mellitus and hypertension. This may be due to lack of monitoring from health workers. Therefore, the results of this study are expected for an online diet counseling and monitoring program involving families of prolanis members during covid-19 pandemic.

scholarly journals Detection of Fake Doctored Images used to Circulate Fake News

2020 ◽  
Vol 9 (7) ◽  
pp. 1031-1036
Keyword(s):  
Neural Network ◽  
Network Models ◽  
Machine Learning Techniques ◽  
Fake News ◽  
Neural Network Models ◽  
The Public ◽  
Learning Techniques ◽  
The World ◽  
Classification Of Images

Over the few years the world has seen a surge in fake news and some people are even calling it an epidemic. Misleading false articles are sold as news items over social media, whatsapp etc where no proper barrier is set to check the authenticity of posts. And not only articles but news items also contain images which are doctored to mislead the public or cause sabotage. Hence a proper barrier to check for authenticity of images related to news items is absolutely necessary. And hence classification of images(related to news items) on the basis of authenticity is imminent. This paper discusses the possibilities of identifying fake images using machine learning techniques. This is an introduction into fake news detection using the latest evolving neural network models

scholarly journals Deteksi Parasit Plasmodium pada Citra Mikroskopis Hapusan Darah dengan Metode Deep Learning

2021 ◽  
Vol 9 (2) ◽  
pp. 306
Author(s):  
NOR KUMALASARI CAECAR PRATIWI ◽  
NUR IBRAHIM ◽  
YUNENDAH NUR FU’ADAH ◽  
SYAMSUL RIZAL
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Convolutional Neural Network ◽  
Anopheles Mosquito ◽  
Microscopic Image ◽  
Test Results ◽  
Automatic Diagnosis ◽  
Diagnosis System ◽  
Slowing Down ◽  
The World

ABSTRAKParasit plasmodium merupakan makhluk protozoa bersel satu yang menjadi penyebab penyakit malaria. Plasmodium ini dibawa melalui gigitan nyamuk anopheles betina. Dalam World Malaria Report 2015 menyatakan bahwa malaria telah menyerang sedikit 106 negara di dunia. Di Indonesia sendiri, Papua, NTT dan Maluku merupakan wilayah dengan kasus positif malaria tertinggi. Malaria telah menjadi masalah yang serius, sehingga keberadaan sistem diagnosa otomatis yang cepat dan handal sangat diperlukan untuk proses perlambatan penyeberan dan pembasmian epidemi. Dalam penelitian ini akan dirancang sistem yang mampu mendeteksi parasit malaria pada citra mikroskopis darah menggunakan arsitekur Convolutional Neural Network (CNN) sederhana. Hasil pengujian menunjukkan bahwa metode yang diusulkan memberikan presisi dan recall sebesar 0,98 dan f1-score sebesar 0,96 serta akurasi 95,83%.Kata kunci: parasit, malaria, convolutional neural network, citra mikroskopis ABSTRACTPlasmodium parasites are single-celled protozoan creatures that cause malaria. Plasmodium is carried through the bite of a female Anopheles mosquito. The World Malaria Report 2015 states that malaria has attacked at least 106 countries in the world. In Indonesia itself, Papua, NTT and Maluku are the regions with the highest positive cases of malaria. Malaria has become a serious problem, so the existence of a fast and reliable automatic diagnosis system is indispensable for the process of slowing down the spread and eliminating the epidemic. In this study, a system capable of detecting malaria parasites in microscopic images of blood will be designed using a simple Convolutional Neural Network (CNN) architecture. The test results show that the proposed method provides precision and recall of 0,98, f1-values of 0.96 and accuracy of 95,83%.Keywords: parasites, malaria, convolutional neural network, microscopic image

Smoking

2020 ◽  
pp. 85-104
Author(s):  
Daniel Ashipala ◽  
Nestor Tomas ◽  
Joel M. H. Medusalem
Keyword(s):  
Tobacco Smoke ◽  
Peer Pressure ◽  
Tobacco Product ◽  
Second Hand Smoke ◽  
Contributing Factors ◽  
Tobacco Products ◽  
Smoking During Pregnancy ◽  
The Public ◽  
Quit Smoking ◽  
The World

Smoking involves inhaling, exhaling, holding or otherwise having control over an ignited tobacco product. This practice remains a global budden and deaths caused by smoking-related conditions is believed to have escalated. Many countries in the world have policies in place that regulate the production, transportation, handling and utilization of tobacco products in order to compact this budden of smoking. Despite these effort, various contributing factors of smoking amongst which peer-pressure forms part, are believed to be cause of an increase in the number of new smokers. Nicotine is one of the constituents of tobacco smoke which causes a pleasant feelings which in return contributes to addiction. Cigarette smoke contains thousands of chemicals with some known to be carcinogens. Smoking during pregnancy poses danger to a pregnant mother and her unborn babe as they exchange blood. The public needs to be educated on the danger of smoking, and exposure to second-hand smoke as well as on strategies that one can follow to quit smoking.

scholarly journals World Covid-19 Vaccine Names Classification Using Neural Network Method

2021 ◽  
Vol 1 (1) ◽  
pp. 31
Author(s):  
Kristiawan Nugroho
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Support Vector Machine ◽  
Support Vector ◽  
Neural Network Method ◽  
The Public ◽  
Machine Learning Methods ◽  
The Neural Network ◽  
The World ◽  
Network Method

The Covid-19 pandemic has occurred for a year on earth. Various attempts have been made to overcome this pandemic, especially in making various types of vaccines developed around the world. The level of vaccine effectiveness in dealing with Covid-19 is one of the questions that is often asked by the public. This research is an attempt to classify the names of vaccines that have been used in various nations by using one of the robust machine learning methods, namely the Neural Network. The results showed that the Neural Network method provides the best accuracy, which is 99.9% higher than the Random Forest and Support Vector Machine(SVM) methods.

scholarly journals PENERAPAN ALGORITMA EVOLVING NEURAL NETWORK UNTUK PREDIKSI CURAH HUJAN

2016 ◽  
Vol 1 (1) ◽  
pp. 1-8
Author(s):  
Subhan Panji Cipta
Keyword(s):  
Neural Network ◽  
Flood Control ◽  
Early Stage ◽  
Economic Value ◽  
Weather Forecast ◽  
Decision Makers ◽  
Test Results ◽  
The Public ◽  
Rainfall Prediction ◽  
Better Than

Weather and climate information have contributed as one consideration for decision makers. This arises because the information the weather / climate has economic value in a variety of activities , ranging from agriculture to flood control . From the data obtained implied that the current rainfall prediction not so accurate . Forecasts are often given to the public on a regular basis is the weather forecast , not the amount of rainfall. This study uses an algorithm Evolving Neural Network (ENN) as an approach to predict the rainfall , the data processing and calculations will use MatLab 2009b . The parameters used in this study is time , rainfall , humidity and temperature. The results also compared with the test results and predictions BPNN BMKG. From the results of research conducted from early stage to test and measurement , the application of this ENN has a rainfall prediction with accuracy better than the BPNN and prediction algorithms BMKG.  

scholarly journals ANALISIS SENTIMEN PT TIKI JALUR NUGRAHA EKAKURIR (PT TIKI JNE) PADA MEDIA SOSIAL TWITTER MENGGUNAKAN MODEL FEED FORWARD NEURAL NETWORK

2020 ◽  
Vol 8 (2) ◽  
pp. 103
Author(s):  
Salma Farah Aliyah ◽  
Hasbi Yasin ◽  
Suparti Suparti ◽  
Budi Warsito ◽  
Tatik Widiharih
Keyword(s):  
Neural Network ◽  
Evaluation Model ◽  
Numerical Data ◽  
Test Results ◽  
Feed Forward Neural Network ◽  
The Public ◽  
Freight Forwarding ◽  
Initial Source ◽  
Accuracy Performance ◽  
Fold Cross Validation

In the 2000s until now, e-commerce systems have continued to develop throughout the world and even in Indonesia. PT Tiki Jalur Nugraha Ekakurir (PT Tiki JNE) is a freight forwarding company that provides convenience for the public in carrying out online shopping activities, and shipping other goods. The large volume of shipments makes PT Tiki JNE have several problems in service that have led to several kinds of responses from users. Sentiment analysis on Twitter social media can be an option to see how PT Tiki JNE’s users respond to services that have been provided. These responses are classified into positive sentiments and negative sentiments. In this research data processing is performed using text mining as the initial source of numerical data from document data which will later be classified using the Artificial Neural Network model with the Resilient Backpropagation algorithm. Data labeling is done manually and sentiment scoring. The test results show that the best model obtained is FFNN 867-7-1 by using the evaluation model 10-Fold Cross Validation to get an overall accuracy performance of 80.27%, kappa accuracy of 39.13%, precision of 69.04%, recall of 70.56%, and f-measure of 69.8% which can be interpreted that the model used is quite good. Analysis of the results using wordcloud shows the tendency of opinion sentiment categories depending on the words used in the tweet.

scholarly journals MODEL CNN LENET DALAM PENGENALAN JENIS GOLONGAN KENDARAAN PADA JALAN TOL

2020 ◽  
Vol 12 (2) ◽  
pp. 65
Author(s):  
Anggay Luri Pramana ◽  
Endang Setyati ◽  
Yosi Kristian
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Vehicle Classification ◽  
Test Results ◽  
Field Of Study ◽  
Neural Network Method ◽  
The Public ◽  
Network Method

Research in the field of transportation, especially vehicle classification with various methods, is a widely developed field of study. Vehicles can be categorized by shape, dimension, logo, and  type. The vehicle dataset is also not difficult to find because it is general in nature. Based on the research that has been done, the introduction of group types based on the number of axles with CNN, the dataset is not yet available to the public. In this paper, we discuss the introduction of the types of groups using the Convolutional Neural Network method. The architecture used is the LeNet model. The trial scenario is carried out in 4 stages, namely 25 epochs, 50 epochs, 75 epochs and 100 epochs. Based on the test results, the accuracy obtained continues to increase at 50 epochs and 100 epochs iterations. Starting from an accuracy of 82%, 94% to the highest accuracy of 95%. Likewise in the prediction the data has increased from 80%, 85% to the highest accuracy that can be 86%. From 50 epochs to 75 epochs, the accuracy of both training and testing has decreased.

“All in a Garden Green”: Shakespeare's Staging of Garden Imagery

2019 ◽  
Vol 26 (2) ◽  
pp. 227-252
Author(s):  
Deborah Solomon
Keyword(s):  
Early Modern ◽  
Literary Tradition ◽  
The Public ◽  
The World ◽  
Audience Interaction ◽  
The Many ◽  
Green World

This essay draws attention to the surprising lack of scholarship on the staging of garden scenes in Shakespeare's oeuvre. In particular, it explores how garden scenes promote collaborative acts of audience agency and present new renditions of the familiar early modern contrast between the public and the private. Too often the mention of Shakespeare's gardens calls to mind literal rather than literary interpretations: the work of garden enthusiasts like Henry Ellacombe, Eleanour Sinclair Rohde, and Caroline Spurgeon, who present their copious gatherings of plant and flower references as proof that Shakespeare was a garden lover, or the many “Shakespeare Gardens” around the world, bringing to life such lists of plant references. This essay instead seeks to locate Shakespeare's garden imagery within a literary tradition more complex than these literalizations of Shakespeare's “flowers” would suggest. To stage a garden during the sixteenth and seventeenth centuries signified much more than a personal affinity for the green world; it served as a way of engaging time-honored literary comparisons between poetic forms, methods of audience interaction, and types of media. Through its metaphoric evocation of the commonplace tradition, in which flowers double as textual cuttings to be picked, revised, judged, and displayed, the staged garden offered a way to dramatize the tensions produced by creative practices involving collaborative composition and audience agency.

Sign in / Sign up

Export Citation Format

Share Document