Embedded Device pada Smarthome System Berbasis IoT untuk Pengoperasian Pintu Gerbang Terkendali melalui Smartphone

This research was motivated by a number of shortcomings in previous similar studies, mainly related to the selection of sensors, the selection of application for operation, and the absence of backup power in the system, so that manufacturing and development were carried out for the acquisition of an embedded device as a control unit. The availability of this control unit is part of the smart-home system based on the Internet of Things (IoT) for gateway controllers, via smartphones with a one-time password mechanism. The research objectives include (i) the manufacture of control units and programming based on Arduino IDE and (ii) verification and validation tests. The realization of the control unit is carried out through assembling a number of electronic devices, making motherboards, re-functionalizing of the miniature gates, and integrated wiring equipped with embedded programs. The performance of the control unit is measured by providing verification tests in the form of simulations based on the Proteus application and validation tests assisted by the Telegram Bot application when conditions are given to the gate when it is opened, closed, or the lock is in a lock/unlocked state. The performance of the control unit developed, in the form of increasing the speed of the gate opening and closing process, implementing one-time passwords for operating security, and the availability of internal backup power. Recommendations for further research, more emphasis is placed on the creation of various control units that are integrated into the smart-home system platform. 

Substraksi Latar Menggunakan Nilai Mean Untuk Klasifikasi Kendaraan Bergerak Berbasis Deep Learning

Moving object detection systems have been widely used in everyday life. Currently, research in the field of background subtraction is still being carried out to achieve maximum accuracy results. This study aims to model the background subtraction of an image using the mean value with the concept of non-overlapping block. Furthermore, the background abstraction results will be used in deep learning-based moving object detection. Specifically, the input image will be divided into several blocks, then the mean value of each block will be calculated to later produce a binary block (binary map). The binary blocks that have been generated will be used as input for background modeling. The background model aims to separate moving objects from the background in the input image. The resulting moving object (object localization) will be sent to the object classification stage using deep learning. The dataset used in this study is CDNet 2014. The results of the study were able to produce a more accurate moving object detection system. Quantitative tests carried out resulted in an accuracy of above 90%

Automation Storage System Based On SCADA Using PLC CP1H and CP1L

The warehousing system is a means of supporting production activities and industrial operations that function to store goods to be distributed, which are still using a manual system and must adapt to technological developments. The problem that often arises in the warehousing system that is still done manually is that the flow of goods into the warehouse is not well organized, and this makes it difficult when the goods are about to be removed, so it requires a longer search time. Previous research has shown actual data on storage racks that use Arduino Mega as a controller and VB as an interface, but there is no actual data on the state of the lifter or the selection of lifter movement speed modes to facilitate operators in monitoring and operating goods storage. Control systems with industry standards greatly affect the effectiveness and optimization of the production process. Based on these problems, this research aims to simplify the managerial and monitoring process in the warehouse with a prototype of automatic multilevel storage using PLC CP1H and CP1L as system control and Wonderware Intouch as an interface with the SCADA system. The prototype has 12 cells, and each cell can accommodate 2 boxes; each cell is distinguished by the height and color of the box. In testing this research, the SCADA system can work optimally. The interface is capable of displaying the actual data of the rack with a success rate of 100%, the hardware error rate is less than 1%, and the interface can display the actual data on the state of the lifter

Rancang Bangun AirMouse Menggunakan Sarung Tangan Bersensor Berbasis ESP32

Digital interactions are still commonly using indirect media such as mouse and keyboard to provide user input in the form of two-dimensional data. Therefore, to provide intuition in virtual interactions, it is possible to add media that can draw directly in the air or a flat surface that will track hand movements and overall finger position. In this research, we try to track hand movements in real time by capturing the position of the hand and finger curvature using a wearable sensor equipped with an Inertial Measurement Unit (IMU) sensor and a flex sensor installed by the user. Then the system will identify the position of the user's finger bending. and the location indicated by the sensors installed to move the cursor on the screen and simulate left-click and right-click hand movements as with a traditional mouse. By using this system, users can interact with the computer more naturally and get the accuracy of cursor movement with the accuracy of finger movement translation reaching more than 85% and the translation of hand movements to mouse cursor movements is on average 73% for shapes that use straight lines. and 23.4% on curved lines such as circles and other shapes

Robot Beroda Pendeteksi Gas Karbon Monoksida dan Metana Berbasis IoT Menggunakan Metode Finite State Machine dan Fuzzy Logic

Occupational Safety and Health (K3) is an important requirement needed in mining. This is because activities in mining have great risks and are associated with unpredictable natural conditions. One of them is the leakage of hazardous gas at the mine site caused by mining activities. This article proposes a wheeled robot to detect carbon monoxide gas and methane gas based on the Internet of Things (IoT) using Finite State Machine (FSM) and Fuzzy Logic. The finite state machine (FSM) in this study is used as a control of the robot’s movement, while fuzzy logic is used as a safety classification of the readable state of dangerous gases. The results showed that the system was capable of detecting gas and the information is successfully sent to a web server. In addition, the use of lidar can detect obstacles around the robot. 

Deteksi Gestur Tangan Berbasis Pengolahan Citra

Hand sign language is a medium of communication for people with disabilities (deaf and speech impaired). However, in social practice, persons with disabilities may have to communicate with non-disable persons who do not understand sign language. These problems can be overcome with the help of translators or normal people learning sign language through existing media such as videos. Unfortunately, this method will probably cost a lot of money and time. In respons to this issue, the present study designed a sistem to detect hand gestures based on image processing. The method used is the You Only Look Once (YOLO) algorithm. The YOLO algorithm can detect and classify objects at once without being influenced by the light intensity and background of the object. This algorithm is a deep learning method that is more accurate than other deep learning methods. From this research, the system can detect and classify hand gestures with different backgrounds, light intensity, and distances with an accuracy rate above 90%

A Usability Analysis of QODE: Qurbani Web Application System

Qurbani is an Islamic ritual animal sacrifice that is carried out during Eid-Adha; one of the two major Muslim holidays. In Indonesia, every village normally has one mosque that takes charge of organizing any related Qurbani activities, from collecting money, creating slaughter schedule, to distributing the meat for the recipients. The current management of these activities is done manually and by hand, which can potentially have errors. Therefore, this research aims to develop and evaluate the usability of a web-based application that will in part take care of Qurbani-related activities. This application is designed and developed using the Scrum methodology. The application as successfully developed and its functionalities are as expected based on design. The application was then evaluated using System Usability Scale (SUS) with 10 respondents. The application obtained the average score of 91.25 which falls into A or excellent category

Measurement of Ankle Brachial Index with Oscillometric Method for Early Detection of Peripheral Artery Disease

Peripheral Arterial Disease (PAD) is a blood vessel disease caused by blockage or plaque accumulation around the artery walls. PAD is included in the category of diseases that are often diagnosed too late and affect more severe cases, such as the death of certain tissues or body parts. The Ankle Brachial Index (ABI) is an accurate non-invasive method for diagnosing PAD, in practice, ABI is usually performed in certain hospitals and is still difficult to find due to limited tools. Therefore, a tool is made that can detect the condition of a person's PAD based on the ABI value. The tool is made using two MPX5050GP sensors to detect oscillometric pulses, a DC pump and solenoid valve as an actuator to pump and deflate the cuff, ADS1115 as an external ADC to increase the accuracy of sensor readings, as well as an LCD and buzzer as tool indicators. The output is displayed in the form of a print out from a thermal printer, with an emergency stop that functions as a safety system to power off the supply when a failure occurs in the measurement process. Oscillometric method is used to detect systolic and diastolic pressure. The accuracy of the tool is 95.5%. This accuracy result is obtained by comparing the readings of systolic and diastolic values using a sphygmomanometer which is commonly used

Seleksi Fitur dan Perbandingan Algoritma Klasifikasi untuk Prediksi Kelulusan Mahasiswa

Students are a major part of the life cycle of a university. The number of students graduating from a university often has a small ratio when compared to the number of students obtained in the same academic year. This small student graduation rate can be caused by several aspects, such as the many student activities accompanied by economic aspects, as well as other aspects. This makes it mandatory for a university to have a model that can take into account whether the student can graduate on time or not. One of the main factors that determine the reputation of a university is student graduation on time. The higher the level of new students at a university, with the same ratio, there must also be students who graduate on time. An increase in the number of student data and academic data occurs if many students do not graduate on time from all registered students. So that it will affect the image and reputation of the university which can later threaten the accreditation value of the university. To overcome this, we need a model that can predict student graduation so that it can be used as policy making later. The purpose of this study is to propose the best classification model by comparing the highest level of accuracy of several classification algorithms including Naïve Bayes, Random Forest, Decision Tree, K-Nearest Neighbor (K-NN) and Support Vector Machine (SVM) to predict student graduation. In addition, the feature selection process is also used before the classification process to optimize the model. The use of feature selection in this model with the best features using 12 regular attribute features and 1 attribute as a label. It was found that the classification model using the Random Forest algorithm was chosen, with the highest accuracy value reaching 77.35% better than other algorithms

Rancang Bangun Alat Pengukur Jarak Tempuh Lari Laun Menggunakan Sensor Inertial Measurement Unit (IMU) Berbasis Mikrokontroler

Jogging is a form of trotting or running at a slow or leisurely pace. So far, the measurement of running distance is determined by wearables Global Positioning System (GPS) and pedometers. The use of wearables with GPS commonly used by joggers cannot be used in indoor conditions. In addition, the use of a pedometer for measuring the number of steps cannot calculate the specific distance due to the inconsistency of human footsteps. This study aims to design a device to measure the distance traveled in jogging. To measure the distance traveled in a run, an Inertial Measurement Unit (IMU) sensor can be used with a linear acceleration output then reduce the measurement noise by using a Kalman Filter. The acceleration signal is processed into a velocity signal and the velocity signal is processed into a distance signal through integration. From the results of the prototype design, it is able to measure a distance of 25m with an error of 0.78%, a distance of 50m with 0.53% and a distance of 75m with 0.22%.