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All Journal JOIV : International Journal on Informatics Visualization Faktor Exacta JTERA (Jurnal Teknologi Rekayasa) JURNAL PengaMAS Digital Zone: Jurnal Teknologi Informasi dan Komunikasi TELKA - Telekomunikasi, Elektronika, Komputasi dan Kontrol Jambura Journal of Electrical and Electronics Engineering JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat) Charity : Jurnal Pengabdian Masyarakat JURNAL POLI-TEKNOLOGI Journal of Computer Engineering, Electronics and Information Technology Jurnal Informatika: Jurnal Pengembangan IT
Wirmanto Suteddy
Universitas Pendidikan Indonesia
Aerospace Engineering Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Social Sciences Transportation Other

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Sistem Anti Maling Untuk Rumah Tinggal Menggunakan IoT Bluemix Griffani Megiyanto Rahmatullah; Muhammad Ayat; Wirmanto Suteddy
JTERA (Jurnal Teknologi Rekayasa) Vol 3, No 1: June 2018
Publisher : Politeknik Sukabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31544/jtera.v3.i1.2018.55-62

Abstract

Sistem keamanan rumah merupakan implementasi yang harus dilakukan untuk meningkatkan keamanan dari kejadian yang tidak diinginkan. Beberapa implementasi hanya memberikan notifikasi sederhana berupa alarm dan tidak menjadi bukti yang kuat apabila terjadi pencurian. Salah satu solusi yang dilakukan adalah penempatan kamera untuk memantau keamanan rumah secara real time diintegrasikan dengan penyimpanan cloud. Bluemix merupakan salah satu provider untuk aplikasi cloud yang memiliki layanan pengolahan dan penyimpanan data, akses aplikasi mobile, pengawasan serta Internet of Things (IoT). Sistem yang diimplementasikan adalah integrasi Raspberry Pi dengan layanan Bluemix untuk melakukan pengawasan keamanan rumah dan memberikan notifikasi kepada pengguna. Sistem mendeteksi jarak menggunakan sensor HC-SR04 terhadap objek dan apabila jarak melewati acuan, hal tersebut adalah indikasi terjadinya pencurian. Berikutnya sistem akan menyalakan buzzer sebagai keluaran suara dan mengaktifkan kamera untuk mengambil gambar lalu diunggah ke object storage Bluemix. Langkah berikutnya yaitu layanan IBM push notification memberikan notifikasi ke perangkat Android pengguna. Pengujian dilakukan dengan menghalangi pembacaan sensor sehingga terjadi indikasi pencurian. Hasilnya adalah sistem berhasil menyalakan buzzer, mengambil gambar lalu diunggah ke Bluemix, dan notifikasi berhasil masuk pada Android. Notifikasi diterima oleh file browser pada perangkat Android dan dilakukan sinkronisasi dengan object storage untuk melakukan pengunduhan berkas gambar yang telah diunggah sebelumnya.
PROTOTYPE APPLICATION OF CROWD DETECTION SYSTEM FOR TRADITIONAL MARKET VISITOR BASED ON IOT USING RFID MFRC522 Wirmanto Suteddy; Dastin Aryo Atmanto; Rizki Nuriman; Afila Ansori
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 7 No. 1 (2022)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v7i1.117

Abstract

Crowds of people are the government's concern in dealing with the COVID-19 pandemic because the virus transfers unwittingly from one person to another and transmits it to the closest environment. One of the locations where crowds are difficult to avoid is a traditional market and is thought to be one of the places that have the potential to become the center of the spread of COVID-19. Various efforts made by the government in suppressing crowds have yielded results, but not a few violations that occur are carried out intentionally or unintentionally, one of the efforts to prevent crowd violations is the traditional market visitor detection monitoring system by market management so that market visitors do not violate health protocols and crowds that occur in an area can be avoided. In this study, an IoT-based crowd detection system application prototype uses an RFID sensor MFRC522 as a crowd indicator based on data on the number of visitors entering a kiosk that is recorded in the database and then displayed on the application, this data becomes an indicator of which kiosk other visitors want to go to so that the crowd can be avoided. System functionality testing was carried out with 4 scenarios and system reliability testing through data transmission was carried out 10 times with test data in the form of kiosk id and visitor id sent via a single Transmission Control Protocol (TCP) with a full-duplex communication channel. The test results show that crowd indications can be detected in the application with data transmission speeds reaching 875 KB/s with an average delay of 231.4 ms and a standard deviation of 215 ± 313 ms.
PELATIHAN PEMBUATAN MEDIA PEMBELAJARAN ONLINE INTERAKTIF BERBASIS CHATBOT UNTUK GURU SMA/SMK DI KOTA BANDUNG Ana Rahma Yuniarti; Munawir Munawir; Wirmanto Suteddy; Raditya Muhammad; Mochamad Iqbal Ardimansyah
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Publisher : UNIVERSITAS KHAIRUN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/pengamas.v5i2.4411

Abstract

Grafik kasus COVID-19 yang masih fluktuatif dan tak kunjung usai, membuat pembelajaran secara online memasuki titik jenuh. Berdasarkan hasil survei terhadap 28 guru Sekolah Menengah Atas (SMA) dan Sekolah Menengah Kejuruan (SMK) di Kota Bandung, diketahui bahwa 57% mengalami kendala saat pembelajaran online. Interaksi yang terbatas antara guru dan murid saat pembelajaran online menjadi pangkal permasalahan. Aktivitas tanya-jawab antara murid dan guru menjadi tidak seleluasa ketika pembelajaran di kelas karena beberapa hambatan seperti: kualitas internet yang tidak merata, keterbatasan ruang dan waktu, serta tingkat pemahaman murid dan kualifikasi guru yang beragam. Salah satu solusi yang diusulkan adalah adanya media pembelajaran online berbasis interaktif yang mampu mengatasi permasalahan-permasalahan tersebut. Untuk itu, dalam kegiatan pengabdian masyarakat ini dilakukan pelatihan pembuatan media pembelajaran online interaktif dengan memanfaatkan teknologi chatbot kepada para guru SMA dan SMK di Kota Bandung. Pelatihan dilakukan secara virtual melalui aplikasi zoom dimana peserta mendengarkan pemaparan materi dari narasumber sekaligus praktik langsung cara mengkonfigurasi chatbot sebagai media belajar sesuai kebutuhan. Didapatkan hasil bahwa 82,14% peserta menyatakan bahwa pelatihan berguna bagi mereka serta mengharapkan pelatihan sejenis dapat diselenggarakan kembali ke depannya untuk meningkatkan kapabilitas mereka agar dapat mengimbangi pesatnya perkembangan teknologi di zaman yang serba canggih ini
PELATIHAN PENERAPAN APLIKASI KIDS NOTE SEBAGAI BUKU PENGHUBUNG DIGITAL DI SEKOLAH Ana Rahma Yuniarti; Devi Aprianti Rimadhani Agustini; Wirmanto Sutedy; Kuswanto Kuswanto; Naufal Nurdiansyah; Aulia Putri Cendekia; Bhima Arya Daniswara
Charity : Jurnal Pengabdian Masyarakat Vol 6 No 1a (2023): Special Issue
Publisher : PPM Universitas Telkom

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/charity.v6i1a.5905

Abstract

Berdasarkan instruksi dari Badan Akreditasi Nasional Pendidikan Anak Usia Dini (BAN-PAUD), salah alat yang harus disediakan oleh pihak sekolah adalah Buku Penghubung, sebagai media untuk monitoring dan pelaporan tumbuh kembang siswa kepada orang tuanya. Sekolah Alam Gaharu (SAG) Bandung telah menggunakan Buku Penghubung, namun sistemnya masih tergolong konvensional. Pada sistem konvensional ini ditemukan permasalahan-permasalahan yang mengakibatkan ketidakselarasan antara wali murid dan guru/fasilitator kelas dalam hal monitoring tumbuh kembang anak, seperti: buku yang rentan rusak atau hilang, kurang privasi, tidak real-time dan tidak dapat mengakomodasi file foto/video kegiatan. Dengan kemajuan teknologi pada era sekarang, memungkinkan dilakukan transformasi buku penghubung berbasis kertas menjadi bentuk aplikasi digital berbasis website maupun Android/iOS. Untuk itu, pada kegiatan pengabdian masyarakat ini dikenalkan sebuah aplikasi Buku Penghubung Digital bernama Kids Note. Pelatihan diberikan kepada 50 peserta yang terdiri dari orang tua/wali murid dan guru/fasilitator di Sekolah Alam Gaharu. Berdasarkan survei yang dibagikan pasca kegiatan, didapatkan hasil bahwa 84% peserta memahami cara penggunaan aplikasi Kids Note dan 92% diantaranya menyatakan aplikasi Kids Note mampu mengakomodasi kebutuhan monitoring dan pelaporan tumbuh kembang anak di SAG.
Fault Coverage Testing on the ISCAS’89 S1423 Sequential Circuit using Scan Based Design and Synopsis Tetramax Wirmanto Suteddy; Anugrah Adiwilaga; Dastin Aryo Atmanto
Journal of Computer Engineering, Electronics and Information Technology Vol 1, No 2 (2022): COELITE: Volume 1, Issue 2, 2022
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (646.038 KB) | DOI: 10.17509/coelite.v1i2.43826

Abstract

We tested the ISCAS'89 S1423 series with a scan design method, both non-scan, full-scan, and partial-scan, but for the partial-scan, the method we propose uses a structured random approach. The purpose of this study is to determine the evaluation and performance with the best computational time with the proposed method to produce high fault coverage results. Testing the ISCAS'89 S1423 circuit in the form of verilog was carried out using tetramax synopsis, the partial-scan test requires a strategy in determining the flip flop to be used as a scannable flip flop, the test results using the full scan method produce 100% test coverage and fault coverage, but this method provides gate overhead loss of 24.06% and slower chip performance. To reduce the gate overhead loss, a partial-scan method will be applied with the approach of choosing from 74 DFF which will be used as scannable flip flops, the test with the best results we did through the 37 DFF approach with the highest input obtained test coverage of 98.17% and fault coverage 96.76% with 171.11 CPU Time with gate overhead reduced by 12.03%. The next approach with the best results with the approach of 50 DFF highest output plus DFF which is not self-loop obtained test coverage of 99.24% and fault coverage of 98.47% with gate overhead successfully reduced by 16.26% with CPU Time 43.39.
LPG Gas Leak Detection System and LPG Fire Classification Based on Internet of Things and Artificial Intelligence with Telegram Bot as a Monitoring Tool Adjhi, Dhimaz Purnama; Hanafi, Mohamad Rizal; Suteddy, Wirmanto
Faktor Exacta Vol 17, No 3 (2024)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v17i3.21920

Abstract

LPG gas leaks pose a serious threat in industrial kitchens as they can cause costly fires, both in terms of material and safety. To improve safety, an accurate detection system is required. This research focuses on developing an LPG gas leak detection system and LPG fire classification with Internet of Things and Artificial Intelligence technology. Supported by Telegram Bot as an emergency notification monitoring tool, this system uses MQ-2 sensors to detect LPG gas leaks and ESP32-Cam to classify LPG fires along with Pretrained-model technology such as Cascade Fire Detection on OpenCV Cloud Server. As the output of this system, the use of PWM control and automation oversees regulating the Exhaust Fan according to the detected leakage. FreeRTOS is also used for system task efficiency, and Port Forwarding with Ngrok Local Server allows public access to the ESP32-Cam. System testing was conducted by Black-Box testing, then evaluating the performance of the MQ-2 sensor against 400 ppm and 1500 ppm thresholds for LPG testing distances in open kitchens and closed kitchens, as well as analyzing system response and delay via HTTP protocol. The results demonstrated the system's success in detecting gas leaks, classifying LPG fires and facilitating emergency communication.
Designing A Pdf Malware Detection System Using Machine Learning Salman Abdul Jabbaar Wiharja; Deden Pradeka; Wirmanto Suteddy
Jurnal Poli-Teknologi Vol. 23 No. 1 (2024)
Publisher : Politeknik Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32722/pt.v23i1.6540

Abstract

This research proposes an approach to build malicious PDF detection system using random forest algorithm, focusing the Evasive-PDFMal2022 dataset which is updated and extended with the addition of new datasets. This dataset includes malicious PDF files from CVE and Exploit-DB, non-malicious PDF files, as well as files from private collections and Technically-oriented PDF Collection. Features were extracted using the PDFID tool, resulting in 29 structural features that formed the basis for the Random Forest classification algorithm. Experiments showed that the model trained with the new dataset provided accuracy equivalent to the Evasive-PDFMal2022 model, at 98%, albeit with a small decrease in recall for the benign class. In addition, this research involved the creation of a website for metadata extraction and malicious PDF detection. Recognition goes to the dataset contributors, tool developers, and dataset providers from NIST and Exploit-DB. Overall, this research successfully increased the representation and diversity of the dataset, provided good model training results, improved detection from 3 malicious PDF variants to 13 variants, and created a practical tool for malicious PDF extraction and detection. Nonetheless, further development may be required to improve detection performance in more complex scenarios
Comparative Study of the Effect of Datasets and Machine Learning Algorithms for PDF Malware Detection Wiharja, Salman; Pradeka, Deden; Suteddy, Wirmanto
Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Vol. 15 No. 1 (2024): Digital Zone: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Publisher: Fakultas Ilmu Komputer, Institution: Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/digitalzone.v15i1.19744

Abstract

This research presents an innovative approach to detecting malicious PDFs through machine learning algorithms, focusing on the expansion of the Evasive-PDFMal2022 dataset. The objective is to enhance the accuracy of detecting malicious PDFs by enriching the dataset, augmenting its representation and diversity, and developing a practical tool—a website—for extracting and detecting malicious PDFs. The methodology involves updating and enlarging the dataset with additional malicious PDFs sourced from CVE and Exploit-db, along with non-malicious PDFs from diverse origins. Features are then extracted using the PDFID tool, and these 20 features serve as the foundation for implementing K-Nearest Neighbor (KNN), Random Forest, and Random Committee algorithms. The outcomes demonstrate that the model trained with the expanded dataset achieves a remarkable 99% accuracy, surpassing the performance of models relying solely on the Evasive-PDFMal2022 dataset. Additionally, this research significantly enhances the representation and diversity of the dataset while delivering a practical solution in the form of a website tailored for the extraction and detection of malicious PDFs.
Sistem Monitoring Konsumsi Energi Listrik Berbasis IoT Menggunakan Fuzzy Logic Mamdani Atmanto, Dastin Aryo; Nanditama, Rastra Wardana; Suteddy, Wirmanto; Adiwilaga, Anugrah
TELKA - Telekomunikasi Elektronika Komputasi dan Kontrol Vol 11, No 2 (2025): TELKA
Publisher : Jurusan Teknik Elektro UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/telka.v11n2.151-166

Abstract

Penelitian ini bertujuan mengatasi permasalahan penggunaan energi listrik yang kurang efisien, hal ini disebabkan oleh keterbatasan alat kWh Meter konvensional yang tidak memungkinkan pengguna untuk memantau secara langsung konsumsi energi listrik yang sedang digunakan. Berdasarkan permasalahan tersebut, perlu adanya pemantauan konsumsi energi listrik. Sistem yang dibangun dapat memberikan informasi detail terkait energi harian yang digunakan serta menampilkan grafik visual terkait pemakaian listrik pengguna. Sistem ini memanfaatkan ESP32 dan sensor PZEM004T-100A untuk mengukur data-data listrik yang disajikan menggunakan aplikasi berbasis website secara realtime. Metode fuzzy logic diadopsi untuk memprediksi pemakaian listrik ke dalam kategori hemat, normal, atau boros. Sementara, Real-Time Operating System (RTOS) diterapkan untuk proses monitoring dan komunikasi data yang lebih efisien. Selain itu, sistem ini dibangun dengan adanya robotic arm yang berfungsi untuk meningkatkan aksesibilitas pengguna dalam pengisian token listrik secara otomatis. Berdasarkan pengujian pada seluruh sistem berjalan dengan cukup baik, namun masih terdapat rata-rata nilai kesalahan pada pengukuran tegangan dan arus sensor PZEM004T-100A sebesar 0,27% dan 1,58%, serta nilai kesalahan pada perhitungan algoritma fuzzy sebesar 0,71%. Meskipun demikian, sistem ini berpotensi meningkatkan kesadaran pengguna terhadap konsumsi energi listrik harian, serta efektif dalam mengurangi penggunaan listrik yang tidak efisien, melalui pemanfaatan teknologi terkini dalam pemantauan dan pengelolaan energi listrik. This research aims to overcome the problem of inefficient use of electrical energy, this is caused by the limitations of conventional kWh Meter tools that do not allow users to directly monitor the consumption of electrical energy that is being used. Based on these problems, it is necessary to monitor the consumption of electrical energy. The system built can provide detailed information related to daily energy used and display visual graphs related to user electricity usage. This system utilises ESP32 and PZEM004T-100A sensors to measure electricity data which is presented using a website-based application in real time. Fuzzy logic method is adopted to predict electricity usage into saving, normal, or wasteful categories. Meanwhile, Real-Time Operating System (RTOS) is applied for a more efficient monitoring and data communication process. In addition, this system is built with a robotic arm that serves to increase user accessibility in charging electricity tokens automatically. Based on testing the entire system runs quite well, but there is still an average error value in measuring the voltage and current of the PZEM004T-100A sensor of 0.27% and 1.58%, as well as an error value in the calculation of the fuzzy algorithm of 0.58%. Nonetheless, this system has the potential to increase user awareness of daily electrical energy consumption, and is effective in reducing inefficient electricity use, through the utilisation of the latest technology in monitoring and managing electrical energy.
IoT-based Smart Piggy Bank Design Implementation Using RFID and Telegram Notification Komarudin, Rizal Maulana; Suteddy, Wirmanto; Agustini, Devi Aprianti Rimadhani
Jambura Journal of Electrical and Electronics Engineering Vol 6, No 2 (2024): Juli - Desember 2024
Publisher : Electrical Engineering Department Faculty of Engineering State University of Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjeee.v6i2.26179

Abstract

 Saving is one of the most important things in financial management. Saving is beneficial for the long term for life. In the conventional way, people can save in a closed container or generally use an object called a piggy bank. However, there are still many shortcomings of the current conventional piggy bank, such as having to be disassembled to take the money and it is difficult to monitor the amount of savings in it so that it can only be used once. With the help of technology, these conventional tools can be used better and more efficiently. This smart piggy bank can be integrated with the Telegram when money is inserted so that it becomes more monitored in saving. The money inserted is detected by infrared sensors and color sensors which are then accumulated and sent via Telegram. Previously, there has been similar research in using sensors to detect money and send notifications based on the Internet of Things. This research aims to develop the existing research by integrating some of its features. Testing was conducted using the Black Box method, focusing on the functionality of the device. As a result, the money inserted into the piggy bank can be accumulated properly and monitored via Telegram with a calculation according to the amount of money inserted and can be used by many people because it uses an RFID card that contains user data and savings so that it becomes more efficient and recorded.
Co-Authors Adiwilaga, Anugrah Adjhi, Dhimaz Purnama Afila Ansori Ana Rahma Yuniarti Atmanto, Dastin Aryo Aulia Putri Cendekia Bhima Arya Daniswara Dastin Aryo Atmanto Deden Pradeka Devi Aprianti Rimadhani Agustini Griffani Megiyanto Rahmatullah Hanafi, Mohamad Rizal Komarudin, Rizal Maulana Kuswanto Kuswanto Mochamad Iqbal Ardimansyah Muhammad Ayat Muhammad Fikri Hidayattullah, Muhammad Fikri Munawir Munawir Munawir Munawir Nanditama, Rastra Wardana Naufal Nurdiansyah Putra, Muhammad Taufik Dwi Raditya Muhammad Rizki Nuriman Salman Abdul Jabbaar Wiharja Septiana, Asyifa Imanda Syafia, Anisa Nur Wiharja, Salman