ANALISA DAN PERANCANGAN SISTEM ABSENSI SISWA BERBASIS WEB DAN SMS GATEWAY

Dalam melakukan pengawasan kehadiran siswa/siswi di sekolah, merupakan kewajiban bersama antara pihak sekolah dengan orang tua/wali siswa. Terkadang ada beberapa siswa yang melakukan kecurangan tidak masuk sekolah tanpa sepengetahuan pihak sekolah atau orang tua/wali siswa. Padahal siswa tersebut berpamitan untuk pergi sekolah, tetapi pada kenyataannya siswa tersebut tidak masuk sekolah. Permasalahan seperti ini tentunya meresakan pihak sekolah ataupun orang tua/wali. Sistem absensi siswa yang dilakukan selama ini masih besifat manual dengan mempertimbangkan juga jumlah mata pelajaran dalam satu semester. Berkaitan dengan permasalahan di atas tentunya pihak orang tua/wali yang putra/putrinya belajar di sekolah, tentunya dapat memantau putra/putrinya masuk untuk mengikuti pelajaran, meninggalkan kelas tanpa izin atau tidak masuk. Memperhatikan permasalah tersebut, diperlukan sistem absensi siswa secara elektronik berbasis web dan sms gateway. Metode yang digunakan dalam membangun sistem ini adalah metode prototipe. Tahapan dalam metode prototipe : pengumpulan kebutuhan, membangun prototyping, evaluasi protoptyping, mengkodekan sistem, menguji sistem, evaluasi sistem dan menggunakan sistem. Tujuan penelitian memberikan kontribusi dalam dunia pendidikan berupa mengelola absensi siswa secara elektronik, dalam upaya peningkatan efisiensi dan efektivitas pengolahan data serta meminimalkan terjadi kesalahan yang dilakukan oleh pengguna sistem

PERANCANGAN PENGOLAHAN ABSENSI SISWA SECARA ELEKTRONIK BERBASIS WEB DAN SMS GATEWAY

Sebagai orang tua/wali yang putra/putrinya belajar di sekolah, tentunya dapat memantau putra/putrinya masuk untuk mengikuti pelajaran, meninggalkan kelas tanpa izin atau tidak masuk. Tentunya hal ini akan sangat meresahkan pihak orang tua ataupun pihak sekolah. Serta pada setiap akhir semester wali kelas disibukkan dengan mengolah absensi siswa yang diterima oleh setiap guru mata pelajaran. Pengolahan absensi siswa yang dilakukan secara semi komputer dengan sejumlah mata pelajaran dan sejumlah siswa pada kelas tersebut tentunya pekerjaan tersebut memerlukan waktu dan biaya yang tidak sedikit. Berkaitan dengan permasalahan di atas peneliti akan merancang sistem pengolahan absensi siswa secara elektronik berbasis web dan sms gateway pada SMKN 1 Kuripan. Bagaimana mengatur hak akses user dalam pengolahan data absensi, melindungi keamanan user, membangun sarana yang mampu menyajikan data absensi siswa yang sesuai dengan kebutuhan siswa dan wali kelas secara cepat dan efisien. Metode yang digunakan dalam membangun sistem ini adalah metode prototipe. Tahapan dalam metode prototipe : pengumpulan kebutuhan, membangun prototyping, evaluasi protoptyping, mengkodekan sistem, menguji sistem, evaluasi sistem dan menggunakan sistem. Penelitian bertujuan memberikan kontribusi dalam dunia pendidikan berupa mengelola absensi siswa secara elektronik, dalam upaya peningkatan efisiensi dan efektivitas pengolahan data serta meminimalkan terjadi kesalahan yang dilakukan oleh pengguna sistem

Indoor Positioning and Navigating System Application Using Wi-Fi with Fingerprinting Method and Weighted K-Nearest Neighbor Algorithm: English

The need for accurate indoor location determination, object tracking, digital maps and indoor travel routes is increasing along with the construction of buildings that have complex and spacious layouts. The current Global Positioning System navigation system is only effective for outdoor use. However, when used indoors it becomes inaccurate due to factors such as signal attenuation and multipath caused by wall obstructions in the building. This study designed an application of Indoor Positioning and Navigating System Using Wi-Fi with Fingerprinting method and Weighted K-Nearest Neighbor algorithm. In the design process, it is necessary to create a fingerprinting database by considering the number of Access points and environmental conditions. Based on the results of the study, the location results of the application show that from floors 1,2, and 3. Floor 1 has a room accuracy result of 89% and a point accuracy of 86% with an average deviation of 1.42 px or 0.9 m, floor 2 has room accuracy results. of 65% and a point accuracy of 70% with an average deviation of 2.43 px or 1.7 m, and the 3rd floor has a room accuracy of 86% and a point accuracy of 68% with an average deviation of 2.27 or 1.5 m. Based on the data above, this application is proven to be able to detect the position of someone in the room with a success percentage on the 1st floor by 90%, the 2nd floor by 55%, and the 3rd floor by 80%

OPTIMASI BLOG DENGAN META TAG UNTUK SEO DAN MONITORINGNYA

Blog as one of the media applicationson the Internethas been used all aroundIndonesia. The user wasnot limited by age,ranging from children to the elderly. A lot of people notrealize that blogs can beoptimizedso thatthe bloggettingtoppositionsin search engines. Metatagwasone ofoptimization techniquesinSearch Engine Optimization (SEO). The main target washow to increaseblogtraffc requests. Afteroptimization, the next stepwasmonitoring, whichaims to determinethe extent to whichthe success ofoptimizationhas been done onSEO.The resultwas ablog sitegettingtoppositionsinthe search enginesandthe monitoring process resultsindicatethat thetitleand content was veryappropriatethat was 100%, description and contentwere alsoappropriatethat was 91%

Quadcopter Stability Control System Using PID And Kalman Filter

Quadcopter is an Unmanned Aerial Vehicle (UAV) that uses 4 motors arranged crosswise as a propulsion system. The quadcopter's capabilities are supported by a main component called the flight controller or control system. The operation of this unmanned aircraft is controlled automatically through a program run from the GCS (Ground Control Station) so that the quadcopter can fly according to the desired destination. The control system is needed to maintain the balance of the quadcopter while flying and maneuvering to remain stable. PID (Proposional Integral Derivative) method as a counterweight when manoeuvring on the y-axis (pitch) and x-axis (roll) and Kalman Filter as processing the resulting sensor output. The results of this study show that setting the value for the proportional constant (Kp), integral constant (Ki) and derivative constant (Kd) determines the quadcopter can fly or maneuver well. The gain values used are Kp of 0.135, Ki of 0.135 and Kd of 0.003. However, the output generated by the gyroscope in pitch and roll still has noise caused by the vibration of the mover during flight and maneuvering. So the Kalman filter is needed to find out the value that is close to the actual output of the gyroscope

Design and Build a System to Minimize the Impact of Toluene Exposure on IoT-Based Workshop Workers

Toluene is one type of organic solvent that is widely used in industry. Organic solvents can have a negative impact on health when exposed to the human body through inhalation (breathing), digestion (swallowing) and adsorption (skin contact). This compound is widely used as a basic material for solvents, dyes, paints, resins, perfumes, nail polish, gasoline, glue, solvent thinner, immersion ink, and printing. The impact on each human will vary depending on the concentration, duration and toxicity of the solvent. The effects of exposure are generally long-term and short-term. Short-term effects include respiratory complaints and eye irritation in exposed humans. An ESP32 microcontroller, HCHO sensor, and DHT11 sensor were used in this study to construct a system to lessen the effects of toluene exposure on workshop personnel. Temperature and humidity sensors picked up by DHT11 have an average value for each node. Each node's average value for the temperature and humidity sensors detected by DHT11 is available. The average error value is categorized as accurate and good for nodes A and B, which are separated by 2 meters and 4 meters, respectively. Due to the DHT11's error rates, the temperature range is 20C and the humidity range is 5% RH

Video Transmission and Navigation System using QR-Code on Quadcopter

In the current era of 4.0 technology, there are many quadcopter applications for testing and usability in life) to monitor the surrounding environment while operating and navigate through the GCS depending on the purpose made. Therefore, the operation of the drone is controlled directly by the operator through certain communication networks such as remote control or automatically through devices that have been previously programmed. This is necessary in order to make it easier to move the drone and monitoring can be done through operator directions or image processing. Image Processing in the form of a QR Code that can provide directions to the drone so that navigation can run smoothly. Research using how the camera detects QR Code will give directions to the drone to navigate to make movements following the QR Code directions in a sequence of numbers so that the final result in the form of video can be viewed via GCS and camera via IP CAM. The results of this study indicate that the drone can detect QR Code and opencv also successfully translates pixels is a distance of 5 meters and navigating based on pixel size with more than 100 pixels, the drone can move automatically to a certain destination. With a distance of 1 meter, it produces 100 pixels on the x-axis and 108 pixels on the y-axis, while for the furthest distance from the QR Code, which is 5 meters, it produces 50 pixels on the x-axis and 80 pixels on the y-axis.

Navigation and Guidance for Autonomous Quadcopter Drones Using Deep Learning on Indoor Corridors

Autonomous drones require accurate navigation and localization algorithms to carry out their duties. Outdoors drones can utilize GPS for navigation and localization systems. However, GPS is often unreliable or not available at all indoors. Therefore, in this research, an autonomous indoor drone navigation model was created using a deep learning algorithm, to assist drone navigation automatically, especially in indoor corridor areas. In this research, only the Caddx Ratel 2 FPV camera mounted on the drone was used as an input for the deep learning model to navigate the drone forward without a collision with the wall in the corridor. This research produces two deep learning models, namely, a rotational model to overcome a drone's orientation deviations with a loss of 0.0010 and a mean squared error of 0.0009, and a translation model to overcome a drone's translation deviation with a loss of 0.0140 and a mean squared error of 0.011. The implementation of the two models on autonomous drones reaches an NCR value of 0.2. The conclusion from the results obtained in this research is that the difference in resolution and FOV value in the actual image captured by the FPV camera on the drone with the image used for training the deep learning model results in a discrepancy in the output value during the implementation of the deep learning model on autonomous drones and produces low NCR implementation values

COVID-19 Disease Diagnosis Expert System with Certainty Factor Method using iOS-Based App

The drop in COVID-19 patients in Indonesia from January to February 2022 made many companies prepare policies to no longer enforce work from home. At the office, we can interact and meet other people directly and it is possible to be exposed to Covid-19 that could potentially become a new wave of COVID-19. This effect poses a serious risk to all people who come into contact with COVID-19-infected individuals or are close to them. The major course of action that may be performed when someone has COVID-19 is self-isolation and tracking anyone who is around or has a health condition associated to COVID-19. We require an iOS-based COVID-19 diagnosis expert system application to track the health status of everyone around us because we are unable to know the health status of everyone. The application uses artificial intelligence technology in the form of an expert system to check health conditions. The expert system replaces the role of the expert with the certainty factor method. This app should be used every time before entering a potentially crowded place to clarify tracking by using maps feature. In addition to COVID-19, this expert system can also diagnose diseases that have the same symptoms as Typhoid Fever and Pneumonia. The results of the expert system are in the form of diagnosing the user's health condition based on the symptoms given with a confidence level of up to 0.9999952130944 or 99.99952130944% for COVID-19, 0.9676 or 96.76% for Typhoid Fever, and 97% for Pneumonia

Quadcopter Take Off and Landing System with Blob Detection Method and Optical Flow

Quadcopter is a type of UAV (Unmanned Aerial Vehicle) which is currently developing and very useful in various fields. With four motors as the main propulsion, the quadcopter has the ability to maneuver, take-off and land vertically in places that have limited space. However, in an autonomous system, the quadcopter is still difficult to operate, one of which is to keep it stable, when in a position where there is minimal GPS signal. Therefore, in this study, we will use the Blob detection method that uses the OpenCV library to determine the landing place and is assisted by an optical flow sensor, aiming to catch roll, pitch and yaw motions. The results of this study indicate that the accuracy of the lidar sensor as a height sensor with an accuracy of 82.16 % is more accurate above 30 cm, the results of distance accuracy for image processing successfully detect up to a height of 600 cm with a light intensity value of around 50-70 lux. optical flow, light intensity and altitude distance greatly affect the motion produced by the quadcopter, but it can still move stably at a minimum value of light intensity of approximately 300 lux at an altitude of 300 cm