Analisis Situasi Masalah Kesehatan Di Kota Depok

Indonesia faces a double burden, and the significant increase number of non-communicable diseases also unresolved infectious diseases. Depok City is one of the cities directly adjacent to the capital city of Indonesia. With various health problems occurs, it is necessary to perform a situation analysis to determine the priority health problems in Depok City. This activity uses a descriptive observational design with qualitative and quantitative approaches. The study involves officials at the Depok City Health Office and the Head of the Puskesmas within a total of twenty-eight respondents. Scoring and ranking calculated using the PAHO-adapted Hanlon method with the Basic Priority Rating (BPR) formula. Based on the results of problem identification, ten health problems were obtained: Maternal Mortality Rate, Immunization, Tuberculosis (TBC), Human Immunodeficiency Virus/Acquired Immunodeficiency Syndrome, Coronavirus Disease 2019 (Covid-19), Dengue Hemorrhagic Fever, Upper Respiratory Tract Infection, Hypertension, Diabetes Mellitus. and people with severe mental disorders. The results of the assessment of health problems placed Covid-19 (BPR: 58.44), followed by tuberculosis (BPR: 54.34) and Immunization (BPR: 53.66) as the three main priority health problems in Depok City.

Contrast modification for pre-enhancement process in multicontrast rubeosis iridis images

Existing researchers for rubeosis iridis disease focused on image enhancement as a collective group without considering the multi-contrast of the images. In this paper, the pre-enhancement process was proposed to improve the quality of iris images for rubeosis iridis disease by separating the image into three groups; low, medium and high contrast. Increment, decrement and maintenance of the images’ original contrast were further operated by noise reduction and multi-contrast manipulation to attain the best contrast value in each category for increased compatibility prior subsequent enhancement. As a result, this study proved that there have three rules for the contrast modification method. Firstly, the histogram equalization (HE) filter and increasing the image contrast by 50% will achieve the optimum value for the low contrast category. Experimental revealed that HE filters successfully increase the luminance value before undergoing the contrast modification method. Secondly, reducing the 50% of the image contrast to achieve the optimum value for the high contrast category. Finally, the image contrast was maintained for the middle contrast category to optimise contrast. The mean square error (MSE) and peak signal-to-noise ratio (PSNR) of the outputs were then calculated, yielding an average of 18.25 and 28.87, respectively

A review of technologies for heart attack monitoring systems

Every year, approximately 1.35 million people die in car accidents. One of the causes of traffic accidents is a heart attack while driving. Common heart attack warning signs are pain or discomfort in the chest or one or both arms or shoulders, light-headedness, faintness, cold sweat, and shortness of breath. When having a heart attack, a car driver has strong pain in the centre or left side of the chest. Current technology for heart attack detection is based on sensory signal properties such as the electrocardiogram (ECG), heart rate and oxygen saturation (SpO2). This paper is intended to give the readers an overview of technologies for heart attack monitoring system that has been used at the hospital, at the home and in the vehicle. The result shows that ECG, heart rate and SpO2 properties are mostly used by numerous researchers for heart attack monitoring systems at hospitals. Meanwhile, many researchers developed a system by using heart rate, ECG, SpO2 and images as properties for heart attack monitoring systems at home. Existing technologies for heart attack monitoring systems in the vehicle used heart rate and ECG as properties in a system. However, there are no review papers yet on heart attack monitoring systems using image processing in vehicles. We believe that researchers and practitioners will embrace this technology by addressing image processing in the heart attack monitoring system in vehicles

Implementing book-end division approach using classpoint to energize electrical and electronics engineering student engagement

This study investigates the efficacy of using ClassPoint in improving student engagement during class and its impact on academic performance among electrical and electronics engineering students by using student engagement framework that established by technology-enhanced learning (TEL) environment microsystem. To achieve this objective, five instructors teaching various courses incorporated ClassPoint into their classes. Then, quantitative data on student engagement and academic performance were collected via surveys. The student’s comments are extracted from university teaching evaluation survey (EPAT) for thematic analysis. The descriptive analysis revealed a significant increase in student engagement after ClassPoint was implemented. Furthermore, students appreciated the use of ClassPoint features such as slide-drawing, multiple choice questions, and word clouds during classes. Survey results also show students have greater attentiveness, active participation, and improved interactions with their peers and instructors. Likert scale responses indicate positive correlation between the use of ClassPoint and students’ enhanced performance in class discussions, idea integration, increased interest in learning, and improved classroom dynamics. Moreover, thematic analysis shows the empowering of five element in TEL microsystem with ClassPoint increase the student engagement. This study highlights ClassPoint's effectiveness in creating an inclusive and interactive learning environment, thus, transforming teaching methods for electrical and electronics engineering students

Hand segmentation for chest pain behaviour of a car driver in vehicle by using fusion watershed and blob analysis

Hand segmentation is an important identification of chest pain behaviours among drivers. Chest pain is an early detection of heart-related diseases. Among the many methods in hand segmentation, YCbCr is determined as the most effective colour space to detect the colour of human skin. The threshold applied technique has great robustness in skin colour detection and segmentation of human body objects such as the face, arm, hands and neck through the undertaking of blob analysis. However, one of several obstacles in hand segmentation which resulted in its low accuracy rate of 62% is identified to be an existing connection between the hands and face regions. This connection problem is specifically overcome by the introduction of a fusion watershed technique with blob analysis. As an effective technique for image segmentation, watershed transform would separate the connected area into multiple regions. The conducted analysis then confirmed the hand as the smallest area across other separated regions. Enhanced execution of hand segmentation was subsequently achieved through extraction of the hand region via the output of the fusion watershed by the employment of blob analysis. Experimental results ultimately confirmed a higher accuracy rate of 75% through the employment of the fusion technique

Kelulut honey-filled pots detection using image processing based techniques

Kelulut bee is one of the stingless bee species in Malaysia, which is not dangerous to human. Honey from Kelulut bee can be used for the treatment of a variety of illness. The awareness of honey nutrition in our health makes it received high demands from the consumers. Traditionally, beekeepers did the manual inspection to check the honey-filled pots by using the straw or needle. The high demand from the consumers and the greater size of Kelulut beehive make it impractical to check manually all the honeypots which are time-consuming. The hygiene of the collected honey is also important to produce a good quality of honey. Hence, an automated honey-filled pots detection system is proposed to overcome these limitations. The proposed system will reduce the time consuming and less prone to error of the wrong estimation of honey-filled pots. MATLAB software is used to process the image of the Kelulut beehive which is challenging due to the overlapped honeypots in the image. Using the proposed algorithm, it can detect whether the pots filled with honey or not by using image processing techniques and it will analyse the image which represents the percentage amount of honey in the beehives

Development of IoT based smart sorting recycle bin using raspberry Pi3 B+

Nowadays, the expansion in population and settlement pollutes the environment due to the community’s laid-back attitude; this problem raises the authorities’ management expenses and causes environmental concerns. As a result, the goal of this initial work is to create an automated system for sorting the recycle bin with both local and distant monitoring indicators using the Raspberry Pi3 B+. The locally accessible resources were used to design and fabricate the IoT-based smart recycle container. The system was driven by a 5 V/2 A rechargeable battery that powered the recycle container. It was also made to distinguish between three different types of garbage: paper, metal, and plastic. As a result, the system was able to recognise the different types of materials that were thrown into the recycle bin. Simultaneously, the user can use their smartphone to check the status of the recycle bin. In conclusion, the development of this IoT-based smart recycle bin can help to ensure that the surrounding area is clean and environmentally friendly

Comparative study on hyperspectral image enhancement for low illumination outdoor scenes images

Hyperspectral image is rich with information because it contains spatial and spectral properties of specific objects. However, the image quality may be affected by low lighting conditions caused by non-uniform illumination environments, uncontrollable weather, which tends to darken outdoor scenes. Difficulty arises for high order image processing modalities such as detection, classification and tracking. In this paper, a comparative study was conducted to identify the most appropriate enhancement method for outdoor scenes. Four techniques were investigated: Bio-Inspired Multi-Exposure Fusion (BIMEF), Dehazing, Illumination Estimation, and Multi-deviation Fusion (MF). Experiments revealed that BIMEF is the best approach with the lowest lightness of error

Comparative study for cursor detection at endoscopic images for telepointer

Communication over the internet is a common practice among computer users. A pointer is an essential tool for effective communication, pointing to a landmark or an intended object. Telepointer have become an important gadget for telemedicine to pinpoint the exact location of lesions, especially for endoscopic images. The endoscopic image will be displayed on the monitor at the surgeon's site, and the same view will be displayed at the remote expert site. However, the challenges for endoscopic images are the unconscious movement of the tissues in the endoscopic images, uniform texture, and varied illumination, which make it hard to keep track of the intended object. In this paper, a comparative study to detect the cursor over the endoscopic images was explored. RGB color space and HSV color space were used for comparative study. Experimental results revealed that HSV color space works well for cursor detection with an accuracy of 99.59%