One of the issues of current attendance system is not being able to record employees who working outside the office. This work discussed a solution designed to solve common operational project problems, especially in ...
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One of the issues of current attendance system is not being able to record employees who working outside the office. This work discussed a solution designed to solve common operational project problems, especially in attendance and tasklist management activity in companies who has employee working outside of the office. Considering the number of employees who have to visit various places, conventional attendance system is no longer feasible as be the solution. Similar problem occured in tasklist management, with so many employees to manage in different places will make it difficult for Project Manager to assign task and monitor the progress. Based on the problems, solusion was then designed using SDLC Waterfall using the field research data. This research conclude that by using the proposed application, complexity can be reduced and effectiveness can be improved in performing day-to-day operational task and make sure that they can be monitored. Moreover, the number of employee who responsible to make reports of projects and attendance can be reduced about 50%.
As we already know, the IoT (Internet of Thing) system has developed and is used in many fields, such as agriculture, security, industry etc. The IoT system requires real time monitoring and this is one of the problem...
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As we already know, the IoT (Internet of Thing) system has developed and is used in many fields, such as agriculture, security, industry etc. The IoT system requires real time monitoring and this is one of the problems that exists today. Transfering data from the sensor via the internet network to a monitoring device must be less than 300 ms. One process that can cause non-fulfillment of these requirements is a method for displaying the data on a monitor. There are several methods for delivering data from the sensor to a monitor. This paper has been compared between two methods, namely the polling method and the websocket method. The experiment was conducted to compare these two method. The result obtained that the websocket method was better in presenting real time data compared to the polling method. It can be shown in bandwidth usage and memory usage. In the experiment was found that the average of bandwidth usage is 478KB for polling method, and 91KB for web socket method in web based and the memory consumption of websocket less as much as 16% compared to polling method. In android smartphone the average bandwidth usage is 5.1 KB for web socket method and 15 KB for polling method and the memory consumption of websocket less as much as 22% compared to polling method.
Indonesia's crude palm oil (CPO) production from year to year continues to increase, at the end of 2020 it reached 17.35 million tons, up 3.6% from the previous year. Increasing production will result in more CPO ...
Indonesia's crude palm oil (CPO) production from year to year continues to increase, at the end of 2020 it reached 17.35 million tons, up 3.6% from the previous year. Increasing production will result in more CPO stock and require good storage. The storage process that occurs is to maintain the temperature of the CPO so that the quality is not damaged. This temperature regulation is still done manually and raises the risk of work accidents. The purpose of this research is to create a temperature control system and automatic volume measurement that can be monitored from a smartphone. The manufacture of a control system used ESP8266 NodeMCu microcontroller, temperature sensor, proximity sensor, and 1000-Watt heater. programming used the Arduino IDE and C++. The result of this study was an IoT CPO Storage Tank design equipped with sensors and microcontrollers. The temperature was measured with the DS18B20 sensor had a data accuracy of 99.19% while the volume measured with the HC-SR04 sensor had an accuracy of 99.78%. Data obtained from the sensor could be seen through the Thingspeak application from a computer or smartphone.
Leveraging topological properties in the response of electromagnetic systems can greatly enhance their potential. Although the investigation of singularity-based electromagnetics and non-Hermitian electronics has cons...
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The effectiveness and efficiency of the operation of oil palm plantations are considered to be the most crucial factor to develop the productivity and profitability of the palm oil business. One of the major obstacles...
The effectiveness and efficiency of the operation of oil palm plantations are considered to be the most crucial factor to develop the productivity and profitability of the palm oil business. One of the major obstacles for the plants to optimally produce crops based on their capacity is caused by the presence of noxious weeds in the plantation area. However, weed control via chemical processes may potentially harm the surrounding environment if it is not properly managed. Therefore, an automatic system to assist the farmers to identify and control the weeds is required to minimize harmful impacts on the environment. Machine Learning (ML) and Artificial Intelligence (AI)-based systems provide powerful tools to perform such tasks. In this work, we aim for an ML-based system design to perform an automatic weed recognition task. The methodology can provide an effort for environmental sustainability in oil palm plantations. The weed identification involves the description, the local names, and tolerance class of the weeds as well as suggestions to control them. The flow of this work consists of weed and herbicide data acquisition, data labeling, model configurations, and data training. Further, the proposed system can be adopted as an android-based application in mobile devices that can deploy the trained model to predict weed category in both real-time and non-real-time tasks.
Electrostatic discharges (ESD) can release large amounts of energy to products and humans, causing product failure and pain, respectively. In this research, we elucidate the electrostatic charge generation, and discha...
ISBN:
(数字)9781728130767
ISBN:
(纸本)9781728130774
Electrostatic discharges (ESD) can release large amounts of energy to products and humans, causing product failure and pain, respectively. In this research, we elucidate the electrostatic charge generation, and discharge phenomena in real polyvinyl chloride (PVC) based electrical tape factory, which is primarily operated by the roll to roll manufacturing process. We perform the electrostatic potential measurement to identify the critical process of charge generation and to eliminate static charge at the source in order to prevent incidents caused by electrostatic discharge to operators or staff in the winding process. We also perform a numerical simulation-based finite element method (FEM) that provides modeling of an induced electric field, allowing the electrostatic discharge. The maximum potential is ~20 kV measured at 25 mm, indicating that the meter was induced by the electric field approximately ~0.8 MV/m, corresponding to surface charges density is ~ 10 μC/m 2 . Therefore, we introduced the ionization emitter bar in this case because it is feasible to install to the current infrastructure of the tested factory. The ionization emitter appears to reduce the electrostatic charge deposited on the PVC surface ~ 30% of the original charges. Therefore, installing a charge-dissipation technology at a proper location or combining with other methods, the electrostatic charge generation can be minimized even in roll to roll process.
Deep learning (DL) has significantly advanced various industries, including semiconductors, by providing sophisticated methods for analyzing emerging device data. Transfer learning (TL), a prominent DL topology, lever...
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With the recent rapid development of the Internet of Vehicles and autonomous driving technology, the demand for digital vehicle identification has also increased. Coupled with the gradual maturity of quantum technolog...
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ISBN:
(数字)9798350389210
ISBN:
(纸本)9798350389227
With the recent rapid development of the Internet of Vehicles and autonomous driving technology, the demand for digital vehicle identification has also increased. Coupled with the gradual maturity of quantum technology, the Internet of Vehicles, which mainly uses wireless communication technology for data transmission, will face the threat of quantum computing and privacy issues. This research proposes the Vehicle Forensics Cloud System (VFCS), a framework combining post-quantum cryptography and blockchain technology to address these issues and provide a comprehensive solution for vehicle digital forensics.
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