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All Journal SCIENCE TECH: Jurnal Ilmiah Ilmu Pengetahuan dan Teknologi Jurnal Teknologi Informasi dan Komputer J-SAKTI (Jurnal Sains Komputer dan Informatika) Buletin Ilmiah Sarjana Teknik Elektro Mobile and Forensics Jurnal ABDINUS : Jurnal Pengabdian Nusantara J-SAKTI (Jurnal Sains Komputer dan Informatika)
Putra, Wahyu Sukestyastama
Universitas AMIKOM Yogyakarta
Agriculture, Biological Sciences & Forestry Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Neuroscience Social Sciences

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Room Security System Design using ESP32 CAM with Fuzzy Algorithm Putra, Wahyu Sukestyastama; Andy Setyawan
Mobile and Forensics Vol. 3 No. 2 (2021)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/mf.v3i2.5554

Abstract

At this time, security becomes an important thing that must be fulfilled. Especially a room that has valuables. Currently, the average room security only uses conventional methods, which are very easy to break. Therefore, An Intelligent security system is needed to maintain security in a room. An Intelligent security system is a system that can detect everything automatically and can be monitored remotely using the internet or better known as IoT (Internet of Things). This system uses a microcontroller as the primary part of running the system and is supported by several modules such as the PIR infrared motion sensor module, door window magnetic sensor module, camera module, and buzzer alarm module. The door & window magnetic sensor module serves as the first security, which, when the door/window is open, will give a warning via the buzzer alarm module. While the PIR infrared motion sensor module functions as second security which if motion is detected in a room, it will trigger the camera module to take pictures in the room. The results of this system will be sent directly to Android via the Telegram application using a bot. This Telegram bot will send data in text and images from the system to Android directly.
Implementasi Algoritma 2 Step Kalman Filter Untuk Mengurangi Noise Pada Estimasi Data Accelerometer Wahyu Sukestyastama Putra
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 3, No 1 (2019): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (132.364 KB) | DOI: 10.30645/j-sakti.v3i1.108

Abstract

An accelerometer is a useful sensor in technological development. Currently, the accelerometer is found on smartphone devices, navigation devices, and wearable devices. However, processing the sensor output signal into data that can be interpreted is not easy. This is because the output of an accelerometer sensor has significant noise. In this study, the authors are interested in developing an estimation method using a Kalman Filter. Kalman filter is an estimator so it is expected that the sensor data are more resistant to noise interference. In this study, the author innovated the 2 step Kalman filter. The study was conducted because the use of 1 step still has noise on the estimation results. Based on the analysis of the algorithm simulation results, it can be concluded that the Kalman filter 2-step algorithm has good performance in estimating the accelerometer sensor output. When compared with the Kalman filter 1 step algorithm, the Kalman filter 2 step algorithm has a smaller average error estimation and is able to achieve a constant/stable condition faster than the Kalman filter 1 step method
SISTEM DETEKSI KERUSAKAN SENSOR ARUS PADA BATTERY MANAGEMENT SYSTEM (BMS) Wahyu Sukestyastama Putra; Andriyan Dwi Putra
Jurnal Teknologi Informasi dan Komputer Vol 7, No 3 (2021): Jurnal Teknologi Informasi dan Komputer
Publisher : LPPM Universitas Dhyana Pura

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

ABSTRACTCurrent sensor is an expensive sensor on Battery Management Systems (BMS). Curent Information in battery needs to be known to estimate the State of Charge (SoC) with the coulomb counting method. The SoC on the battery is used to determine the overcharging and over-discharge zone. Thus the current information on the battery is very important to know. Problems will occur if the flow information is not obtained accurately. This can occur if the current sensor is damaged. Damage such as data bias, or changes in current sensor characteristics needs to be detected early to avoid misinformation of sensor readings. In this research, a current sensor fault detection algorithm design is performed. The method used is an experimental method by applying current estimation using the battery and Kalman filter models. Estimated current results then compared with current sensor data to determine whether the sensor information is still suitable for use or not. The analysis shows that the algorithm can follow the performance of the current sensor in Coulomb counting operations.Keywords: Bad Sensor Detection; Battery Management System; Recursive Least Square; Kalman Filter;Fault DetectionABSTRAKSensor arus merupakan sensor yang mahal pada Battery Management Systems (BMS). Informasi arus diperlukan untuk melakukan estimasi State of Charge (SoC) dengan menggunakan metode coulomb counting. The SoC pada baterai digunakan untuk menentukan area overcharging dan over-discharge. Dengan demikian informasi arus pada sebuah baterai sangat penting untuk diketahui. Permasalahan akan terjadi jika informasi arus pada baterai tidak dapat diketahui dengan akurat. Kondisi ini dapat terjadi karena sensor arus mengalami kerusakan. Kerusakan tersebut dapat terjadi karena adanya bias data atau perubahan karakteristik dari sensor arus. Kerusahan sensor arus perlu dideteksi lebih dini untuk menghindari kesalahan mengidentifikasi arus yang mengalir. Pada penelitian ini dilakukan desain algoritma untuk mendeteksi kesalahan pada sensor arus. Metode yang dilakukan adalah metode eksperimen dengan melakukan estimasi arus pada baterai menggunakan pemodelan baterai dengan Kalman Filter. Hasil estimasi arus kemudian dibandingkan dengan data sensor arus untuk menentukan apakah informasi dari sensor arus masih layak untuk digunakan atau tidak. Dari analisis yang dilakukan menunjukkan bahwa algoritma dapat mengikuti dapat memprediksi arus dan dapat mengestimasi SoC menggunakan Coulomb Counting.Kata Kunci : Deteksi kerusakan sensor; Battery Management System; Recursive Least Square; Kalman Filter; Deteksi Kesalahan
Implementasi Algoritma 2 Step Kalman Filter Untuk Mengurangi Noise Pada Estimasi Data Accelerometer Wahyu Sukestyastama Putra
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 3, No 1 (2019): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v3i1.108

Abstract

An accelerometer is a useful sensor in technological development. Currently, the accelerometer is found on smartphone devices, navigation devices, and wearable devices. However, processing the sensor output signal into data that can be interpreted is not easy. This is because the output of an accelerometer sensor has significant noise. In this study, the authors are interested in developing an estimation method using a Kalman Filter. Kalman filter is an estimator so it is expected that the sensor data are more resistant to noise interference. In this study, the author innovated the 2 step Kalman filter. The study was conducted because the use of 1 step still has noise on the estimation results. Based on the analysis of the algorithm simulation results, it can be concluded that the Kalman filter 2-step algorithm has good performance in estimating the accelerometer sensor output. When compared with the Kalman filter 1 step algorithm, the Kalman filter 2 step algorithm has a smaller average error estimation and is able to achieve a constant/stable condition faster than the Kalman filter 1 step method
Peningkatan Keterampilan Adaptasi Pengrajin Joglo di Masa Pandemi dengan Strategi Digital Marketing Wahyu Sukestyastama Putra; Taufikkurahman Taufikkurahman
Jurnal ABDINUS : Jurnal Pengabdian Nusantara Vol 5 No 1 (2021): Volume 5 Nomor 1 Tahun 2021
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/ja.v5i1.15219

Abstract

Joglo craftsmen are one of the parties affected by the Covid19 virus. In this service activity, assistance is provided to partners to help survive the pandemic. Mentoring is carried out in the form of online training to improve partners' skills and knowledge. The training provided includes graphic design training, website management training and internet marketing training using Facebook ads. The training process is carried out synchronously and asynchronously. The process of monitoring partner activities in service activities is carried out using the Edpuzzle platform. The results of the analysis of the output of training activities and monitoring of activities carried out can be concluded that the process of transferring knowledge to partners can be carried out even though the activities are carried out online. Synchronous and asynchronous online training needs to be carried out simultaneously to maximize the knowledge transfer process.
Deteksi Anomali Konduktivitas Air Menggunakan Kalman Filter Wahyu Sukestyastama Putra; Muhammad Koprawi; Wahid Miftahul Ashari; Jeki Kuswanto
Buletin Ilmiah Sarjana Teknik Elektro Vol. 4 No. 1 (2022): April
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v4i1.6188

Abstract

Water quality is an essential part of shrimp farming. Data integrity is one of the challenges in building a water conductivity monitoring system. Data read by the sensor should represent the physical conditions that occur. However, some factors can cause abnormal data changes. This abnormal data change can occur due to sensor damage or an attempt to sabotage the pool. In this study, a data anomaly detection algorithm was built using the Kalman filter and standard deviation to solve the problem of determining the normal range of data. The designed algorithm was then tested and evaluated using Arduino nano, Arduino mega, and Wemos D1 Microcontrollers to determine the algorithm's performance on limited computing devices. Based on the data analysis that has been carried out, it is found that the anomaly detection algorithm based on the Kalman filter has an accuracy of 92.5% and can detect anomaly data that occurs with TPF = 1 and FNR = 0 values. The implementation of the detection algorithm on the microcontroller shows that WEMOS D1 (ESP8266) has an excellent average computational speed of 27.99 us. As for the stability of the Arduino Nano (ATMEGA328) and Arduino Mega 2560 (ATMEGA 2560) microcontrollers, the computation time deviation is about 2.8 us. Kualitas air merupakan bagian penting pada budidaya udang. Salah satu tantangan dalam membangun sebuah sistem monitoring konduktivitas air adalah Keutuhan data. Suatu data yang terbaca oleh sensor seharusnya mewakili kondisi fisik yang terjadi. Akan tetapi ada faktor-faktor dapat menyebabkan perubahan data yang tidak wajar. Perubahan data yang tidak wajar ini dapat terjadi karena disebabkan kerusakan sensor maupun adanya upaya sabotase pada kolam. Pada penelitian ini dibangun sebuah algoritma deteksi anomali data menggunakan Kalman filter dan standar deviasi untuk mengatasi masalah penentuan rentang data normal. Algoritma yang dirancang kemudian diuji dan dievaluasi dengan menggunakan Mikrokontroller Arduino nano, Arduino mega dan Wemos D1 untuk mengetahui performa algoritma yang dirancang pada perangkat komputasi terbatas. Berdasarkan analisis data yang telah dilakukan didapatkan hasil bahwa algoritma deteksi anomali berbasis kalman filter memiliki akurasi 92,5% dan dapat mendeteksi data anomali yang terjadi dengan nilai TPF =1 dan FNR=0. Implementasi algoritma deteksi pada mikrokontroller menunjukkan bahwa WEMOS D1 (ESP8266) memiliki rata-rata kecepatan komputasi yang baik yaitu 27,99 us. Sedangkan untuk kestabilan mikrokontroller Arduino Nano (ATMEGA328) dan Arduino Mega 2560 (ATMEGA 2560) memiliki deviasi waktu komputasi sekitar 2,8 us.
Implementasi Web Scraping pada Google Cendekia sebagai Sarana Profiling Penelitian Dosen Muhammad Koprawi; Wahyu Sukestyastama Putra
Science Tech: Jurnal Ilmu Pengetahuan dan Teknologi Vol 9 No 1 (2023): Februari
Publisher : Universitas Sarjanawiyata Tamansiswa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30738/st.vol9.no1.a14188

Abstract

Google Scholar is an online platform that provides access to scholarly literature such as articles, theses, books and conference proceedings from various scientific publishers. As educators or lecturers, they should have scientific research works that can be accessed by anyone at any time. To measure achievement and access to publication of scientific papers quickly and to profiling educators, lecturers or researchers, universities must have a centralized database that comes from a Google Scholar account and can be updated periodically or automatically based on a specified period. To solve this problem, the researcher implements a web scraping technique combined with a cron job as a command that will run a task on a scheduled basis. The method used is the RAD (Rapid Application Development) method which focuses on a fast system development process. This study succeeded in scraping data for 2983 documents, displaying document citation data globally and successfully carrying out an automatic scheduling synchronization process that is set with scheduling configurations every week, every month, every quarter, every semester and every year, and scripts on cron jobs are run every 5 minutes on the server to check if any scheduling is active.
Co-Authors Andriyan Dwi Putra Andy Setyawan Jeki Kuswanto Muhammad Koprawi Taufikkurahman Taufikkurahman Wahid Miftahul Ashari