Search

Student attendance is a system used for tracking student activity in school. Many methods are used to develop student attendance systems, such as Quick Response (QR) Code systems, Radio Frequency Identification (RFID) systems, fingerprint systems, and so on. The COVID-19 pandemic has driven technological development, especially in the student attendance system. Measuring human surface body temperature has become a protocol that must be done before entering school. Student attendance systems need to expand the function not only for attendance but also for monitoring student surface body temperature. This research aims to improve student attendance systems by adding surface body temperature measurements and recording during student presence. Recording data can be done by using the internet of things. Student presence data will be sent to school databases throughout the internet. This system uses RFID technology for student presence and a non-contact thermal sensor for temperature measurement. According to data research, non-contact thermal sensors provide a temperature reading with an average error of 1.69%, a minimum error value of 0.96%, and a maximum error value of 2.57% with a range error value of 0.35°C – 0.95°C. RFID test shows that the optimum distance for the system to read an RFID card is 0 – 2cm. The System also successfully sent presence data to the student school database through the internet. This study concludes that developed systems can track student attendance by recording the student’s surface body temperature while in presence. Further work will be focused on managing data networks if this system is used with many users in the school.

Ikan lele salah satu komoditas unggulan yang saat ini masih terus dikembangkan oleh pemerintah Indonesia untuk meningkatkan produksi pada sektor perikanan. Pada prakteknya, para pembudidaya ikan lele masih melakukan pemantauan pakan secara konvensional yaitu dengan cara mendatangi kolam ikan. Permasalahanan yang sering terjadi dikarenakan kebutuhan pakan harian harus sesuai dengan pemberian pakan harian dan jadwal pemberian pakan. Hal ini lah sebagai penghambat aktivitas para pembudidaya yang menyebabkan waktu menjadi tidak efektif dan effisien. Berdasarkan permasalahan tersebut penelitian ini akan merancang sebuah sistem dengan memanfaatkan sensor Loadcell HX711 dan motor servo yang berfungsi untuk memantau dan mengontrol pemberian pakan ikan lele, dengan memanfaatkan google firebase sebagai database dan aplikasi Android sebagai kontrol dan monitoring yang terintegrasi dengan Module Wifi Nodemcu ESP8266. Akurasi yang dihasilkan sensor loadcell untuk pakan ikan sangat baik yaitu sebesar 97,573%. Akurasi yang dihasilkan motor servo yaitu sebesar 98,237%. Hasil perhitungan QoS berupa Throughput yang dihasilkan sebesar 0,000120026 kbps dan merupakan kategori Buruk pada TIPHON. Packet Loss yang dihasilkan sebesar 0,012% dan merupakan kategori Sangat baik pada TIPHON. Delay yang dihasilkan sebesar 297,986 ms merupakan kategori Bagus dalam TIPHON. Kata kunci: Internet of Things, Nodemcu ESP8266, Loadcell HX711, Motor servo, Android. Abstract Catfish is one of the leading commodities currently being developed by the Indonesian government to increase production in the fisheries sector. In practice, catfish farmers still carry out conventional feed monitoring by visiting fish ponds. The problem that often occurs is due to daily feed requirements which must be in accordance with the feeding schedule and daily feeding. This becomes an obstacle for cultivator activity which causes time to be ineffective and inefficient. Based on these problems, this study will design a system using Loadcell sensors and servo motors that function to monitor and control catfish feeding, by utilizing Google Firebase as a database and an Android application as control and monitoring integrated with the Wifi Module Nodemcu ESP8266. The accuracy of the loadcell sensor for fish feed is very good, which is 97.573%. The accuracy of the servo motor is 98.237%. The result of QoS calculation in the form of Throughput generated is 0.000120026 kbps and is a Bad category on TIPHON. The resulting Packet Loss is 0.012% and is a very good category on TIPHON. The resulting delay of 297.986 ms is in the Good category in TIPHON. Keywords: Internet of Things, Nodemcu ESP8266, Loadcell HX711, Motor servo, Android

Indonesia merupakan negara yang sebagian besar penduduknya mempunyai mata pencaharian dari sektor pertanian. Teh adalah salah satu komoditi pertanian yang pengelolaannya cukup luas di Indonesia dan berumur panjang. Teh merupakan tanaman yang hidup pada suhu 130C – 150C dan kelembaban >70% pada siang hari. Perkebunan teh yang luas menimbulkan sulitnya melakukan monitoring suhu dan kelembaban tanah lahan tersebut, sehingga peneliti ingin merancang sebuah alat yang dapat memonitoring lahan perkebunan tersebut secara jarak jauh. Peneliti membuat alat untuk mengetahui suhu dan kelembaban tanah yang ada pada lahan perkebunan teh, dengan menggunakan sensor DHT11 dan sensor soil moisture YL-69 yang terhubung dengan mikrokontroller ESP32 untuk mempermudah monitoring. Akurasi yang dihasilkan dari sensor DHT11 baik, nilai rata-rata error rate pada pagi hari yaitu 1,04%, nilai rata-rata error rate pada siang hari yaitu 2,09% dan nilai rata-rata error rate pada malam hari yaitu 1,53%. Akurasi yang dihasilkan sensor YL-69 cukup baik, terdapat 3 kategori kondisi tanah yaitu kering dengan nilai kurang dari 70%, lembab jika dirange 70% sampai 90%, dan basah jika diatas nilai 90%. Didapatkan nilai rata-rata RSSI terkecil yaitu sebesar -100,2. Sedangkan nilai rata-rata SNR yaitu sebesar -3,3, dan selanjutnya nilai delay yang diterima oleh perangkat yaitu mempunyai nilai rata-rata sebesar 14 detik. Kata kunci: ESP32, DHT11, YL-69, SNR, RSSI. Abstract Indonesia is a country where most of the population has a livelihood from the agricultural sector. Tea is one of the agricultural commodities whose management is quite extensive in Indonesia and has a long life. Tea is a plant that lives at a temperature of 130C – 150C and humidity> 70% during the day. Extensive tea plantations make it difficult to monitor the temperature and soil moisture of the land, so researchers want to design a tool that can monitor the plantation land remotely. Researchers made a tool to determine the temperature and soil moisture in tea plantations, using a DHT11 sensor and a YL-69 soil moisture sensor connected to the ESP32 microcontroller to facilitate monitoring. The accuracy of the DHT11 sensor is good, the average error rate in the morning is 1.04%, the average error rate during the day is 2.09% and the average error rate at night is 1, 53%. The accuracy produced by the YL-69 sensor is quite good, there are 3 categories of soil conditions, namely dry with a value of less than 70%, moist if in the range of 70% to 90%, and wet if above 90%. The smallest RSSI average value was obtained, which was -100.2. While the average value of SNR is -3.3, and then the delay value received by the device has an average value of 14 seconds. Keywords: ESP32, DHT11, YL-69, SNR, RSSI.

Pada pemeliharaan ikan didalam akuarium membutuhkan perawatan guna menjaga kelangsungan hidup ikan dan vegetasi air yang terdapat didalamnya. Selain rutinitas pemberian pakan, nilai parameter lingkungan akuarium juga perlu selalu diawasi dan dijaga pada rentang tertentu. Tujuan utama yang ingin dicapai untuk memonitoring pH dan kekeruhan pada akuarium sehingga kualitas air akuarium bisa terjaga. pH yang baik untuk ikan hias di akuarium yaitu lebih dari 7 dan kurang dari 8, kemudian kekeruhan yang baik untuk ikan hias di akuarium yaitu dibawah 25 ntu. Pada penelitian ini menggunakan mikrokontroler NodeMCU ESP32 digunakan sebagai pusat kendali sistem, kemudian sensor pH untuk mendeteksi nilai pH air, kem Pada pemeliharaan ikan didalam akuarium membutuhkan perawatan guna menjaga kelangsungan hidup ikan dan vegetasi air yang terdapat didalamnya. Selain rutinitas pemberian pakan, nilai parameter lingkungan akuarium juga perlu selalu diawasi dan dijaga pada rentang tertentu. Tujuan utama yang ingin dicapai untuk memonitoring pH dan kekeruhan pada akuarium sehingga kualitas air akuarium bisa terjaga. pH yang baik untuk ikan hias di akuarium yaitu lebih dari 7 dan kurang dari 8, kemudian kekeruhan yang baik untuk ikan hias di akuarium yaitu dibawah 25 ntu. Pada penelitian ini menggunakan mikrokontroler NodeMCU ESP32 digunakan sebagai pusat kendali sistem, kemudian sensor pH untuk mendeteksi nilai pH air, kemudian sensor turbidity untuk mendeteksi nilai kekeruhan air, kemudian Buzzer berfungsi sebagai alarm dan yang terakhir LCD berfungsi untuk menampilkan hasil dari pembacaan sensor tersebut. Pada penelitian ini metode yang digunakan yaitu metode regresi linear untuk mengetahui keakuratan dari pembacaan sensor pH. Pada penelitian ini terdapat pengujian sensor turbidity untuk menguji hasil sensor, pengujian sensor pH untuk menguji nilai ADC / tegangan output dan akurasi sesnsor pH, Pengujian regresi linear pada sensor pH dan pengujian QOS untuk mengetahui beberapa nilai parameter diantara lain delay, throughput, packet loss dan jitter. Pada sistem ini digunakan android ntuk monitoring dan notifikasi dengan implementasi internet of things. Berdasarkan hasil pengujian pada sensor pH dengan kondisi pH 4,2, 7,1 dan 9,4, pada pembacaan sensor dengan kondisi pH 9,4 tingkat rata-rata errornya yaitu 2%. Namun setelah diuji denngan metode regresi linier dengan persamaan y=-0,2540+1,0468X nilai rata-rata errornya menjadi 0%, dapat disimpulkan bahwa metode regresi linier dapat diterpakan pada penelitian ini. Pada hasil pengujian QOS delay didapatkan nilai rata-rata pengujian delay sebesar 975,9470 ms dimana termasuk dalam kategori jelek, packet loss didapatkan rata-rata sebesar 15,126 % dimana termasuk dalam kategori sedang, throughput didapatkan rata-rata sebesar 694,661 bit/s dimana termasuk dalam kategori sangat bagus dan Jitter didapatkan rata-rata sebesar 473,9918 ms dimana masuk dalam kategori jelek. Kata kunci : Akuarium, Sensor pH, Sensor Turbidity, NodeMCU ESP32, Buzzer, LCD.

Pemantauan kualitas udara dalam gudang elektronik sangat penting untuk menjaga kesehatan manusia dan kualitas barang elektronik. Penelitian ini bertujuan untuk memantau nilai densitas debu pada suatu ruangan khususnya pada gudang elektronik, dan mengetahui hubungan antara densitas debu, suhu, dan kelembaban. Metode yang digunakan dalam penelitian ini adalah eksperimen dan uji statistik. Dan untuk uji statistik yang digunakan menghasilkan bahwa tidak ada hubungan antara densitas debu dan suhu hal ini dibuktikan dengan nilai chi-square hitung (0,265) lebih kecil dari chi-square tabel (1,645) dan tidak ada hubungan antara densitas debu dan kelembaban hal ini dibuktikan dengan nilai chi-square hitung (0,1023) lebih kecil dari chi-square tabel (1,645). Tingkat debu pada Gudang Elektronik Depo Pelita pada tanggal 22 juli 2021 sampai dengan 30 Juli 2021 memiliki rata-rata 0,13 mg/m3 atau 130 µg/m3. Hasil penelitian ini yaitu debu tidak dapat dipengaruhi oleh suhu dan kelembaban melainkan dipengaruhi oleh aktifitas yang berada disekitar.

This paper discussed the method of navigation and robot formation in a swarm using the Local Positioning System (LPS) which was applied to the mobile robot's differential steering platform. Navigation and formation of robots in swarm robotics could run well because of the presence of robot position coordinates. In the outdoor application of coordinates, the position of the robot could be obtained easily using the Global Positioning System (GPS), but GPS had drawbacks in indoor applications. In indoor use, signals from satellites were difficult to obtain and inaccurate for use with relatively short distances. In coordinate research, positioning used LPS which was built using Bluetooth Low Energy (BLE). LPS with BLE was successfully built with simple resources and at a low price but had optimal performance. The LPS accuracy built with BLE and the regression algorithm had an error of 4.33% on the X-axis, and 2.67% on the Y-axis. The robot formation utilized a combination of proximity sensors and position coordinates obtained from LPS. The proximity sensor served to detect obstacles that hold the robot towards a predetermined target. The combination of navigation algorithms and swarm formation robotics was proven to be faster at finding targets compared to a single robot.

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.

Pada pengiriman data, sinyal yang diterima oleh antena penerima pasti tidak sama dengan sinyal yang dikirim oleh antena pengirim. Pada penelitian ini, teknik K-Means Clustering diaplikasikan untuk proses pengembalian data bit sebagai fungsi demodulasi pada konstelasi M-Ary yang sebelumnya telah terganggu oleh noise dan fading di jaringan pita lebar. Modulasi digital yang digunakan dalam penelitian ini yaitu 16 QAM. Simulasi dilakukan pada kanal ideal (AWGN) menggunakan teknik multicarrier Filter Bank Multicarrier Offset QAM (FBMC OQAM) dengan equalizer Zero Forcing (ZF) dan tanpa ZF. Kinerja dari demapper k-means dievaluasi menggunakan Silhouette Coefficient menghasilkan sistem FBMC OQAM dengan penggunaan ZF memiliki kinerja lebih baik daripada sistem FBMC OQAM tanpa penggunaan equalizer . Seperti BER FBMC OQAM ZF pada SNR 0 dB hingga SNR 20 dB mengalami penurunan sebesar 0,3849, sedangkan pada FBMC OQAM memiliki BER yang relatif stabil. Selain mengalami penurunan pada parameter BER, sistem FBMC OQAM ZF mengalami peningkatan pada kapasitas kanal yang dihasilkan.

Fever is one of the symptoms of a person with Covid-19. Body temperature must be checked e before entering crowded areas such as schools, offices, shops, and hospitals. It is a mandatory protocol that must be done. One of the tools that can be used to check body temperature is a thermal camera. Thermal cameras have the disadvantage of a high temperature reading error. This is because the thermal camera used has a low resolution. This study aims to reduce the value of the temperature reading error on the thermal camera using the linear regression method. The linear regression method is able to reduce the error rate of temperature readings by 5.27% at 36 ° C reading. The reduction in reading error also occurred by 5.27% at 37 ° C and 6.44% at 38 ° C. Based on the results obtained, this study shows that linear regression can be applied to thermal cameras and provides a decrease in the error rate of temperature readings on thermal cameras

Currency is an item humans require as a medium of exchange in transactions, including those with vision impairments. It can be challenging for certain blind people to identify currencies. This research aimed to help blind people identify nominal currency when in the transaction. Deep Learning with the CNN algorithm and preprocessing with a sequential model were used in this research. This algorithm is modeled as neurons in the human brain that communicate and learn patterns. Data collecting, preprocessing, testing, and evaluation are this research stage. Six hundred eighty-one datasets are used, consisting of IDR 50.000, IDR 75.000, and IDR 100.000. Model testing was carried out with different iterations of 5, 10, 15, and 20 epochs. Different epoch values will affect the time it takes the model to learn, but the length of the learning process will result in more accurate models. The highest result obtained from all epoch tests is 100%. The class prediction results for the 69 test data show that they can be predicted based on the actual class, indicating that the model is adequate. The results of this classification might be used to construct a smartphone app that would assist visually challenged people in recognizing the nominals.

Communication channels that are affected by various disturbances will cause a high Bit Error Rate (BER). To maximize the performance of the channel in the future, Filter Bank Multicarrier (FBMC) technique is used as a renewal of Orthogonal Frequency Division Multiplexing (OFDM). FBMC has better spectrum efficiency properties due to the nature of orthogonality which only divides bandwidth for sub-channels. The purpose of the research was to knowing the performance of FBMC Offset QAM (FBMC O-QAM) which has a variation of modulation levels of 4-QAM, 16-QAM, and 64-QAM. The Zero Forcing (ZF) method is used to detect the original signal sent by the transmitting antenna. System performance in this study was measured by parameter Bit Error Rate (BER) and channel capacity. The results showed that the FBMC O-QAM system with ZF has decreased BER value on each modulation. At the time of modulation 4 QAM has a BER value of 0.0008945 with an SNR value of 20 dB. Modulation 16 QAM also experienced the same thing when the SNR value of 20 dB has BER value of 0.001856, and at modulation 64 QAM has BER value of 0.01766 at a SNR of 20 dB. Besides decreasing the BER parameters, the FBMC O-QAM ZF system has own characterize in channel capacity. For the 4-QAM has 4.808 b/s/Hz, 16-QAM has 4.627 b/s/Hz, and 64-QAM has 3.903 b/s/Hz at SNR 20 dB. It conclude that 4-QAM has a best channel capacity enhancement. The value of channel capacity generated based on simulations using Zero Forcing shows an increase in value along with an increase in SNR, but has a smaller value compared to channel capacity in theory.

Pakcoy is a type of vegetable plant belonging to the Brassica family. Pakcoy plants can be cultivated using hydroponic techniques, namely plant cultivation techniques without soil media. The advantage of cultivating Pakcoy plants using hydroponic techniques is that it does not require a large area of ​​land, so it is easy to apply in the yard. However, cultivation with hydroponic techniques has drawbacks such as farmers need to make regular observations to determine the harvest readiness of each plant. This causes a lack of effectiveness of farmers in cultivating Pakcoy plants. With the development of Machine Learning technology, a model can classify the maturity of Pakcoy plants based on digital image data. By applying the Support Vector Machine (SVM) Algorithm, the Machine Learning model can learn to classify a digital image of Pakcoy plants with the category "Small" to represent immature Pakcoy plants and "Large" to represent mature Pakcoy plants which results in an accuracy level of above 79%. It can be concluded that Machine Learning can be implemented in Pakcoy cultivation activities to support hydroponic farmers. &nbsp, Tanaman Pakcoy merupakan tanaman jenis tanaman sayur yang tergolong dalam keluarga sawi. Tanaman Pakcoy dapat dibudidayakan dengan teknik hidroponik, yaitu teknik budidaya tanaman tanpa media tanah. Keunggulan budidaya tanaman Pakcoy menggunakan teknik hidroponik adalah tidak memerlukan lahan yang luas sehingga, mudah diterapkan di halaman rumah. Namun budidaya dengan teknik hidroponik memiliki kekurangan diantaranya petani perlu melakukan pengamatan secara rutin untuk menentukan kesiapan panen setiap tanaman. Hal ini menimbulkan kurangnya efektifitas petani dalam membudidayakan tanaman Pakcoy. Adanya perkembangan teknologi Machine Learning, sebuah model dapat mengklasifikasi kematangan tanaman Pakcoy berdasarkan data citra digital. Dengan menerapkan Algoritma Support Vector Machine (SVM), model Machine Learning dapat belajar mengklasifikasi sebuah citra digital tanaman Pakcoy dengan kategori “Kecil” untuk mewakili tanaman Pakcoy belum matang dan “Besar” untuk mewakili tanaman Pakcoy sudah matang yang menghasilkan tingkat akurasi mencapai di atas 79%. Dapat disimpulkan bahwa Machine Learning dapat diimplementasikan pada kegiatan budidaya tanaman Pakcoy untuk mendukung petani hidroponik.

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.

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.

Coronavirus disease (COVID-19) is a disease that disrupts the respiratory tract and infects many people. However, until now, there is still no cure. Therefore a robot service is proposed to minimize direct contact between nurses and patients who are equipped with PPE (Personal Protective Equipment). Robot Service is a robot carrying logistics for patients in the Isolation Room. The robot is expected to be able to help medical personnel work and reduce the risk of medical personnel being exposed to the virus while in the Isolation Room. This robot has a feature to rotate and move along the hospital hallway, using either automatic or normal mode. This robot is also equipped with an Omni infrared camera that can see the environmental conditions around the robot so that it can make it easier for operators to run this robot with a Wi-Fi communication system. With this robot, medical workers can deliver the needs of patients without having to meet face to face, so that the risk of being exposed to the virus can be reduced. Keywords: Coronavirus, Hospital, Medical Personnel, Robot Abstrak Coronavirus disease (COVID-19) is a disease that disrupts the respiratory tract and infects many people. However, until now, there is still no cure. Therefore a robot service is proposed to minimize direct contact between nurses and patients who are equipped with PPE (Personal Protective Equipment). Robot Service is a robot carrying logistics for patients in the Isolation Room. The robot is expected to be able to help medical personnel work and reduce the risk of medical personnel being exposed to the virus while in the Isolation Room. This robot has a feature to rotate and move along the hospital hallway, using either automatic or normal mode. This robot is also equipped with an Omni infrared camera that can see the environmental conditions around the robot so that it can make it easier for operators to run this robot with a Wi-Fi communication system. With this robot, medical workers can deliver the needs of patients without having to meet face to face, so that the risk of being exposed to the virus can be reduced. Kata Kunci: Coronavirus, Hospital, Medical Personnel, Robot

Sistem kendali daya sangat berkaitan dengan masalah interferensi antar user pada jaringan homogen femtocell . Kendali daya juga dapat menjaga baterai perangkat supaya hemat dalam penggunaan daya. Bentuk kendali daya terpusat ( centralized power control atau disingkat CPC) digunakan dalam penelitian ini dengan analisis unjuk kerja berdasarkan metode penyelesaian menggunakan algoritma solusi yang layak ( feasible solution ). Dengan menguji kelayakan nilai vektor daya, solusi yang layak dapat dicapai jika user mempunyai nilai daya non-negatif ( non-negative power vector ), yang berarti bahwa SINR target dapat tercapai dan sistem dapat diterapkan. Studi ini difokuskan pada single channel dan multi-channel yang diterapkan pada multi-user . Hasilnya menunjukkan bahwa saat kondisi sistem tersebut feasible maka semua daya user bernilai positif dan semua user mampu mencapai signal to noise ratio (SINR) target yang ditentukan yakni 13 dB untuk skema 5 user dan 9,5 dB untuk skema 10 user . Pada kondisi infeasible , daya user pada power vector ada yang bernilai negatif dan beberapa user tidak mencapai SINR target. Pada penggunaan channel bersama, penambahan user akan menurunkan SINR yang diterima user . Semakin kecil ukuran user group maka semakin tinggi SINR yang dapat dicapai. Hal ini dikarenakan interferensi antar user yang semakin kecil.

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.

Kanal komunikasi sistem Filter Bank Multicarrier (FBMC) melakukan pengiriman dan penerimaan sebuah sinyal informasi melalui pengelompokan simbol pada bagian penerima ( receiver ). FBMC merupakan salah satu metode yang lebih baik dibandingkan Ortoghonal Frequency Division Multiplexing (OFDM) dalam proses modulasi karena sifat orthogonalitas yang membagi bandwidth untuk sub-saluran tetangga. Penggunaan modulasi Offset Quadrature Amplitude Modulation (OQAM) yang memiliki kestabilan sistem lebih baik dari QAM biasa dimana OQAM lebih kuat terhadap efek dispersi serta mampu memperbaiki proses decision dan memiliki kecepatan yang tinggi. Algoritma deteksi simbol yang digunakan adalah metode Zero Forcing (ZF). Istilah dari pengelompokan pada sisi penerima ini biasa disebut dengan demapper . Penelitian ini berfokus pada unjuk kerja K-NN ( K-Nearest Neighbor ) clustering yang menggantikan fungsi demapper FBMC pada biasanya. Demapper K-NN menggunakan metode Euclidean Distance yang mengelompokkan bit-bit dari blok diagram pasca pengolahan OQAM menuju diagram 16 QAM. Parameter unjuk kerja sistem pada penelitian ini yaitu diukur dengan Signal to Noise Ratio (SNR) terhadap Bit Error Rate (BER) dan kapasitas saluran. Hasil penelitian menunujukan FBMC OQAM ZF demapper K-NN memiliki nilai BER lebih baik dibandingkan yang tidak menggunakan ZF. Peningkatan nilai SNR yang digunakan dapat menghasilkan nilai kapasitas kanal yang semakin meningkat.

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.