Search

Intisari— Air merupakan salah satu kebutuhan dasar bagi tubuh manusia. Badan Pusat Statistik (BPS) menyatakan kebutuhan air di Indonesia mencapai 3.242.458 (ribu m3) yang terdiri dari 108.559 (ribu m3) untuk pelanggan sosial, 2.543637 (ribu m3) untuk pelanggan non niaga, 426.267 (ribu m3) untuk pelanggan niaga dan industri, dan 173.995 (ribu m3) untuk pelanggan khusus. Permintaan air bersih yang begitu banyak tidak lepas dari kebutuhan dasar manusia untuk minum. Depot air minum isi ulang merupakan salah satu Industri yang berkembang dalam distribusian air minum. Pandemi COVID – 19 menyebabkan industri depot air minum isi ulang sebagai salah satu potensi penyebaran virus. Hal ini tidak lepas dari adanya interaksi antara pelayanan isi ulang dan beli air minum isi ulang. Indsutri depot air minum isi ulang membutuhkan sebuah inovasi untuk dapat berkembang di bagian otomatisasi. Penelitian ini bertujuan untuk merancang, membuat, dan menguji sistem otomatisasi dalam pembayaran di depot air minum isi ulang menggunakan uang koin yang beredar di Indonesia. Data pengujian berdasarkan penelitian menunjukkan bahwa alat yang dirancang dan dibuat dapat di implementasikan untuk depot air minum isi ulang. Tingkat akurasi dari alat yang dibuat adalah 97,38% dan tingkat kepresisianya adalah 89,50%. Dari penelitian ini dapat disimpulkan bahwa alat yang dibuat mampu menjadi sistem pembayaran otomatis untuk depot air minum isi ulang di masa pandemi COVID – 19. Abstract— Water is basic needs for human body. Badan Pusat Statistik (BPS) shows that water necessity in Indonesia reach out 3.242.458 (thousand m3) consist of 108.559 (thousand m3) for social needs, 2.543637 (thousand m3) for non commercial needs, 426.267 (thousand m3) for commercial and industry needs, and 173.995 (thousand m3) for special customer needs. Clean water needs is very much because of basic human needs to drink. COVID – 19 pandemic makes many refillable drink water industry is one of the many industry that cause virus spread. Refillable drink water industry service makes interaction from shopkeeper with buyer. This condition makes refillable drink water industry need an inovation to survive. Refillable drink water industry need otomation for payment process. This research aims to designing, make, and test payment automation system for refillable drink water industry using coins. Test result according to the research shows that the development device can be implement in refillable drink water industry. Research shows that accuracy device is 97,38% and 89,50% for the precission. According to the research can conclude that device payment system for refillable drink water industry can inmpelent in COVID – 19 pandemic.

Improving efficiency and quality in farming activities is important reason of developing technology to support agriculture. Technology in agriculture such as image processing, Internet of Things (IoT), Artificial Intelligence, Big Data, and Artificial Lighting gives increasing trends. Artificial lighting technology has high impact to support agriculture in an area that has low sun light intensity such as in rainy season. Farmer has a difficulty to cultivating plant especially in early stage in rainy season. This problem happen because of the intensity of sun light is very minimum. Artificial lighting is a technology to solve early stage cultivating problem in rainy season. This technology can support agriculture for cultivating plant with minimum sun light. Artificial lighting contains light emitting diode (LED) that is laid out as an array. This research goal is to make an artificial lighting prototype to support early stage cultivating. Pakcoy is a plant that used to observe artificial lighting impact for early stage Pakcoy cultivation. This research shows Pakcoy plant placed in the prototype gives significant growth compared with a plant which placed in low light room. Pakcoy plant in artificial lighting gives 2 4 leaves, the height is 1.5 5cm, and from 18 seeds 10 is grow. This research can conclude that artificial lighting prototype can support early stage Pakcoy cultivation.

Heart rate abnormalities can lead to many cardiovascular diseases such as heart arrythmia, heart failure, heart valve disease and many more. Some cardiovascular disease can cause death. Abnormalities signal feature can be seen using electrocardiogram. Electrocardiogram is an electric signal record from heart activity. Normal heart and abnormal heart have a different electrocardiogram signal pattern. This research is aim to detect abnormality from heart rate using electrocardiogram abnormality signal feature. Abnormality signal pattern can be used to classify normal and abnormal heart rate. Abnormality feature consists of P signal condition, R signal condition, P R interval rate, and double R interval. Electrocardiogram data that used in this study is obtain from MIT-BIH Arrythmia database. 20 electrocardiogram data have been used to see detection and classification performance while classifying normal and abnormal heart rate. Research result shows that feature based has 90.00% in accuracy, 90.00%in precision, and 90.00% in sensitivity while classify normal and abnormal heart rate. Research result can conclude that abnormality feature can be used to classify normal and abnormal heart rate. This method can be used for embedded system device that has limitation in memory and size.

The development of wireless technology has penetrated in femtocell communication systems, where this communication system is very flexible to develop. However, with many networks running simultaneously, which is called a heterogeneous network, a combination of macrocell and femtocell networks, interference between networks is unavoidable. To resolve this interference, it can be done with adaptive power control techniques by the user. Adaptive power control can be achieved through the use of Game Theory and also known as Power Control Game (PCG). By determining the appropriate utility function, the optimal power is obtained when using the power update iteration process. The results show that in the Proposed method when it reaches a convergent condition, both femto users and macro users are able to reach SINR that exceeds the target SINR of 5.496 for femto users and 10.04 for macro users. Meanwhile, the Distributed Power Control (DPC) method is only able to achieve the SINR user value which is the same as the target SINR, which is 5 and 10 for femto users and macro users, respectively. The Proposed method produces a higher SINR value for the user than the DPC method so that in terms of achieving the target SINR, it is possible to conclude that the Proposed approach is superior to the DPC.

Phonocardiogram (PCG), one of the auscultation-based technique used as a diagnostic method of the heart condition, is a patient’s heart sound recording. The simplicity, non-invasive, and passive brings an advantage to implement this method as a diagnosis system. Nevertheless, PCG recordings are often interrupted by various sources, for instance, noise from the surrounding environment, respiratory or lung sounds, power disturbances, and movement of the surrounding skin, so inhibit the PCG implementation as a diagnosis method. Therefore, it requires an appropriate method to eliminate the noise that exists in the PCG signals. To get an appropriate method in the PCG system, we compare the Empirical Mode Decomposition (EMD) and Double-Density Discrete Wavelet Transform (DD-DWT) method as a denoising system to minimize the noise effect in the PCG signal. Observation of the system performance used thirty data from the normal heart sound added by the additive white Gaussian noise (AWGN), and the performance parameter used signal-to-noise ratio (SNR) and mean square error (MSE). Based on the result, we obtained the best SNR value of 25.55 dB for the EMD method and SNR value of 18.19 dB for DD-DWT. Also, we perceived the best MSE value of 0.01% for the EMD method, and 0.42% for the DD-DWT. The results obtained show that the denoising process using the EMD method is better than the DD-DWT to implement in the PCG signal.

Thermogun is non-contact thermometer to examine people whom body temperature above 37°C that is used to screening human body temperature while entering public areas such as schools, offices, and supermarkets. Thermo gun is widely used yet not effective because it measuring single point around body or face which cannot represent whole body. Thus, the development of thermal camera is important. This research focusing on development of low-cost and low-resolution thermal camera to replace thermo gun. Thermal camera measure 36°C, 37°C, 38°C object temperature and gives accuracy respectively 99.38%, 99.39% 99.41%. Therma camera not only give high accuracy but also high precision. The precision for same temperature respectively 35.01 ± 0.63 when measure 36°C object temperature, 36.55 ± 0.26 when measure 37°C object temperature, and 37.27 ± 0.49 when measure 38°C object temperature. This result is satisfied and good enough to examine human body temperature.

A pair of blood vessels inside of the human neck that serves to deliver blood to the brain is called carotid artery. Cholesterol in human body can form plaque, causes blockage to carotid artery that evoke atherosclerosis, stroke and heart disease which is a dangerous disease that can lead to death. If in certain long time it is not discovered, carotid artery will rupture. In clinical practice, the availability of ultrasound is wide also it is a low cost method to observe plaque in carotid artery. Unfortunately, ultrasound plaque images in carotid artery is diverse, noisy and not easy to be identified. It is also hard to develop computational techniques for recognizing plaque from ultrasound images. Therefore, it is a challenge to develop an optimal method that can be implemented in computer system to recognize plaque from ultrasound images. One method from many techniques available in pattern recognition is a feature extraction which can be obtained from various ways. In this work, A Gabor wavelet which is one of the powerful method in feature extraction is applied to recognize plaque characteristics. However a Gabor wavelet feature extraction will result a huge data, therefore to reduce the data dimension, the Principal Component Analysis (PCA) is applied to reduce such huge data. The result of this method for recognize plaque in carotid artery is satisfied with 100% recognition rate by using 8 orientations and 3 scales bank of Gabor with 100% eigenvectors configuration. In this research we used 24 carotid artery training images.