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All Journal Jurnal Ilmu Komputer dan Informasi Jurnas Nasional Teknologi dan Sistem Informasi JOIV : International Journal on Informatics Visualization Journal of Applied Information, Communication and Technology (JAICT) Jurnal Ilmiah FIFO JIKO (Jurnal Informatika dan Komputer) Jiko (Jurnal Informatika dan komputer) TELKA - Telekomunikasi, Elektronika, Komputasi dan Kontrol Jurnal Abdimas Mandiri Journal of Energy and Electrical Engineering (JEEE) Jurnal Pengabdian UNDIKMA Journal of Computer Engineering, Electronics and Information Technology
Adiwilaga, Anugrah
Universitas Pendidikan Indonesia
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End-To-End Evaluation of Deep Learning Architectures for Off-Line Handwriting Writer Identification: A Comparative Study Wirmanto Suteddy; Devi Aprianti Rimadhani Agustini; Anugrah Adiwilaga; Dastin Aryo Atmanto
JOIV : International Journal on Informatics Visualization Vol 7, No 1 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.1.1293

Abstract

Identifying writers using their handwriting is particularly challenging for a machine, given that a person’s writing can serve as their distinguishing characteristic. The process of identification using handcrafted features has shown promising results, but the intra-class variability between authors still needs further development. Almost all computer vision-related tasks use Deep learning (DL) nowadays, and as a result, researchers are developing many DL architectures with their respective methods. In addition, feature extraction, usually accomplished using handcrafted algorithms, can now be automatically conducted using convolutional neural networks. With the various developments of the DL method, it is necessary to evaluate the suitable DL for the problem we are aiming at, namely the classification of writer identification. This comparative study evaluated several DL architectures such as VGG16, ResNet50, MobileNet, Xception, and EfficientNet end-to-end to examine their advantages to offline handwriting for writer identification problems with IAM and CVL databases. Each architecture compared its respective process to the training and validation metrics accuracy, demonstrating that ResNet50 DL had the highest train accuracy of 98.86%. However, Xception DL performed slightly better due to the convergence gap for validation accuracy compared to all the other architectures, which were 21.79% and 15.12% for IAM and CVL. Also, the smallest gap of convergence between training and validation accuracy for the IAM and CVL datasets were 19.13% and 16.49%, respectively. The results of these findings serve as the basis for DL architecture selection and open up overfitting problems for future work.
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.
Teacher and Student Attendance System at Noor Faqih Usman Foundation Based on RFID Integrated with Raspberry Pi Dhimaz Purnama Adjhi; Mohamad Rizal Hanafi; Rastra Wardana Nanditama; Rifqi Alamsya; Hafidz Rizki Fahriza; Anugrah Adiwilaga
Journal of Computer Engineering, Electronics and Information Technology Vol 2, No 2 (2023): COELITE: Volume 2, Issue 2, 2023
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/coelite.v2i2.59723

Abstract

In educational institutions, tracking attendance is crucial for ensuring effective administration and student engagement. This abstract presents the development of a Teacher and Student Attendance System at the Noor Faqih Usman Foundation, leveraging Radio Frequency Identification (RFID) technology integrated with Raspberry Pi. The proposed system aims to automate the attendance recording process, streamline administrative tasks, and enhance the overall efficiency of attendance management. This can create gaps in the development of data manipulation, data frameworks, and rigid systems. The purpose of this study was to create an RFID-Based Teacher and Student Attendance System integrated with Raspberry Pi. This study was conducted using a quantitative method of study and development study. This RFID-based attendance technology will later replace the role of paper to record the attendance of teachers and students using cards/keychains to make it easier to report attendance; data can be stored in digital form such as Excel, can be accessed via wireless smartphones, interested parties can monitor through the website, and the educational institution will be touched by at least technology. The results showed that the system was able to control the attendance process and succeeded well.
Design and Build an Assessment Platform by Inserting Moodle-Based Cryptographic Methods Deden Pradeka; Anugrah Adiwilaga; Devi Aprianti Rimadhani Agustini; Adi Suheryadi; Rizki Nuriman
Jurnal Nasional Teknologi dan Sistem Informasi Vol 9, No 3 (2023): Desember 2023
Publisher : Jurusan Sistem Informasi, Fakultas Teknologi Informasi, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/TEKNOSI.v9i3.2023.264-270

Abstract

The use of digital platforms in the learning process is increasing, especially in the context of assessment activities. In this context, it is essential to realize that digital platforms can be subject to attack or fraud by irresponsible parties. It is due to the presence of sensitive data and/or restricted to a limited number of authorized persons. Therefore, the protection of data and its security in using digital platforms is very important. To enhance this layer of security in data protection, cryptographic methods play a crucial role in maintaining information security. By applying cryptographic methods to learning platforms for assessment purposes, we can increase the security and integrity of the data involved in the assessment process. This research aims to produce a plugin that can be used on a Moodle-based Learning Management System (LMS). This plugin will provide an additional activity in the form of an assessment activity with an essay exam type. When this plugin is used, all questions and answers will be encrypted into text that is difficult to understand by unauthorized parties when an attack attempt occurs. In this way, the learning platform for assessment purposes can safeguard and protect data from access by irresponsible parties.
Alat Bantu Tuna Netra Berbasis Arduino Uno dan Artificial Intelligence dengan metode YOLO v7 Muhammad Taufik Dwi Putra; Anugrah Adiwilaga; Adelia Clarissa; Anggita Apriliani Putri Gustiansyah; Antonius Didi Kurniadi; Zahra Mumtaz
Jurnal Ilmiah FIFO Vol 15, No 2 (2023)
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/fifo.2023.v15i2.007

Abstract

Pembuatan tongkat ini yaitu untuk memudahkan para penyandang tunanetra mengetahui apa saja objek yang berada di depannya saat tongkat tersebut mendeteksi dengan menggunakan fitur Artificial Intelligence pada tongkat tunanetra yang dilengkapi dengan deteksi objek atau obstacle menggunakan YOLO v7, kemudian fitur pelengkap lainnya adalah tombol Emergency Contact pada alat bantu tunanetra sangat penting dalam situasi darurat serta fitur Answer Back System pada alat bantu tunanetra juga penting untuk membantu para tunanetra menemukan kembali alat bantu tunanetra mereka jika tercecer atau hilang. Metode perancangan sistem alat menggunakan Blok Diagram dan Flowchart. Untuk hasil pengujian dan hasil akhir dalam pembuatan alat ini yaitu Fitur Object Detection telah berfungsi untuk mendeteksi benda dan mengubah teks menjadi suara dan dihubungkan kepada earphone. Fitur Answer Back System untuk memudahkan penyandang tuna netra apabila kesulitan dalam menemukan tongkat. Selain itu, fitur Emergency Contact digunakan untuk mengirimkan pesan pada contact yang telah ditentukan dengan pesan berisi longitude dan latitude lokasi keberadaan tongkat. Hasil dari pengujian tersebut sesuai dengan tujuan dan blok diagram yang dibuat.
Prototype Implementation of Exhaust Fan Control Using Mamdani Fuzzy Logic to Minimize LPG Concentration Mohamad Rizal Hanafi; Dhimaz Purnama Adjhi; Anugrah Adiwilaga
JAICT Vol 9, No 1 (2024)
Publisher : Politeknik Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32497/jaict.v9i1.5300

Abstract

This research aims to design and build a prototype of LPG gas leak detection system using fuzzy logic Mamdani method based on ESP32 with MQ-2 and DHT11 sensors as input and exhaust fan as output or action taken to prevent gas concentration. This research methodology includes literature study, identification and analysis, data collection, design implementation, software and hardware testing, and experiments to verify system performance. The results show that the system can detect LPG leaks and then provide preventive action by adjusting the speed and turning on the exhaust fan. This research is a prototype LPG gas leak detection system using fuzzy logic can be a solution to prevent hazards due to leaking gas. The contribution of this research is to provide alternative data processing methods that can improve the performance of gas sensors and provide responses that are in accordance with environmental conditions.
SISTEM PEMANTAUAN KETINGGIAN PERMUKAAN AIR BERBASIS WIRELESS PADA MODEL MINIATUR BENDUNGAN Adiwilaga, Anugrah; Taufiqurrahman, Imam
Journal of Energy and Electrical Engineering Vol 3, No 1: Oktober 2021
Publisher : Teknik Elektro Universitas Siliwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/jeee.v3i1.3673

Abstract

Pusat Penelitian dan Pengembangan Sumber Daya Air (PUSAIR) merupakan salah satu lembaga litbang milik kementrian PUPR yang memiliki berbagai fungsi beberapa diantaranya adalah penelitian dan pengembangan, pelayanan uji laboratorium dan lapangan, sertifikasi, inspeksi, kalibrasi, dan advis teknis di bidang sumber daya air. Seiring meningkatnya berbagai kegiatan penelitian serta kebutuhan pencatatan data yang praktis, maka PUSAIR mulai meningkatkan kemampuan beberapa alat laboratoriumnya dimana salah satunya adalah mekanisme pencatatan data. Sangat penting untuk melakukan pencatatan hasil pengukuran yang praktis, cepat dan tepat agar para peneliti dapat meningkatkan kualitas dan kapasitas penelitian. Namun kondisinya belum semua alat yang ada mendapatkan digitalisasi, salah satunya alat pembacaan ketinggian permukaan air pada model bendungan yang mana masih menggunakan alat ukur manual dan melibatkan beberapa orang untuk melakukannya serta data yang didapat perlu konversi dari catatan dikertas kepada perangkat lunak spreadsheet. Tujuan penelitian ini adalah merancang dan membuat sistem pemantauan ketinggian permukaan air pada model bendungan secara “realtime” berbasis wireless untuk memudahkan pengguna dalam kegiatan pengambilan data percobaan. Rancangan desain sistem terdiri dari 2 buah perangkat yaitu Sensor Node dan Receiver Node yang diimplementasi menggunakan Sensor Waterlevel Sensor sebagai sensor ketinggian permukaan air, mikrokontroler ATMega328 sebagai pengolah data, Xbee-Pro S2C 2.4 Ghz sebagai modul komunikasi, Buck-Converter, DC power Supply sebagai supply daya, serta LCD 16x2 dan buzzer sebagai indikator. Hasil pengujian system menunjukan bahwa komponen dan modul yang digunakan sudah bekerja sesuai fungsi yang dikendalikan mikrokontroler. Pembacaan ketinggian permukaan air oleh Etape waterlevel sensor mampu membaca dengan rata-rata penyimpangan kurang dari 1%. Pengiriman data berhasil mengirim data sebanyak 100% data ke Receiver Node sesuai dengan harapan dan tanpa adanya gangguan koneksi. Pengguna sistem dapat melakukan pengukuran dan perekaman data ketinggian air secara real time dari ruang pantau tanpa perlu mendatangi model bendungan.
Pelatihan Peningkatan Kemampuan Computational Thingking Guru dengan Media Robotik di SMP Santa Ursula Bandung Munawir; Dwi Putra, Muhammad Taufik; Pradeka, Deden; Adiwilaga, Anugrah; Pararta, Muhammad Salam
Jurnal Abdimas Mandiri Vol. 8 No. 3
Publisher : UNIVERSITAS INDO GLOBAL MANDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jam.v8i3.4704

Abstract

Tujuan dari dilaksanakannya pengabdian ini adalah untuk meningkatkan kemampuan berpikir komputasional guru di SMP Santa Ursula Bandung. Metode-metode yang diterapkan dalam pengabdian ini meliputi ceramah, praktik langsung, dan diskusi interaktif. Sebanyak 25 guru diikutsertakan dalam pelatihan ini, dan evaluasi kegiatan dilakukan menggunakan instrumen yang disediakan melalui Google Form yang kemudian dianalisis secara deskriptif. Hasil dari pengabdian ini menunjukkan adanya peningkatan capaian hasil belajar siswa yang diajarkan dengan penerapan ilmu teknologi robotika. Dengan analisis uji normalitas menggunakan N-Gain, didapatkan peningkatan pada nilai-nilai yang berkaitan dengan kompetensi siswa dalam pembelajaran. Para siswa cenderung lebih aktif dan mudah memahami konsep-konsep pelajaran ketika diberikan pemeragaan menggunakan robot. Hal ini ditunjukkan dengan rata-rata nilai efektivitas N-Gain di angka 40%. Dengan dilaksanakannya pelatihan ini, diharapkan para guru dapat menerapkan ilmu teknologi robotika sebagai media pembelajaran dalam kegiatan belajar mengajar di kelas. Penerapan teknologi ini tidak hanya membantu siswa memahami materi pelajaran dengan lebih baik, tetapi juga mempersiapkan mereka untuk menghadapi tantangan di era digital. Pelatihan ini juga diharapkan dapat meningkatkan kompetensi guru dalam mengintegrasikan teknologi dalam proses pembelajaran, sehingga menciptakan lingkungan belajar yang lebih interaktif dan inovatif. Dengan demikian, tujuan utama dari pengabdian ini dapat tercapai, yaitu meningkatkan kualitas pendidikan melalui pemanfaatan teknologi yang tepat guna.
DESIGN OF MICROSLEEP DETECTION SYSTEM IN 32-BIT MICROCONTROLLER-BASED MOTORISTS WITH RANDOM FOREST METHOD Maqdis, Syiva Awaliyah; Adiwilaga, Anugrah; Munawir, Munawir
JIKO (Jurnal Informatika dan Komputer) Vol 7, No 2 (2024)
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v7i2.8539

Abstract

The number of motorcycle accidents has increased rapidly every year. Many occur due to drowsiness or fatigue because motorists force themselves to keep driving. The state of fatigue while driving is also known as microsleep. To overcome this problem, we propose a design of a prototype system that can be installed on the helmet of a motorized user so that the driver is more alert when driving a vehicle. This system utilizes machine learning technology with the Random Forest algorithm with two prediction results: prediction 1, which means the motorcyclist is tired, or prediction 0, which means the motorcyclist is in a normal state, embedded in the ESP32 microcontroller, and a tilt sensor that can detect signs of drowsiness in motorists. This system design will use the MPU6050 sensor to measure changes in the angle of the motorcyclist's head. The microcontroller will process the data obtained to identify head changes that indicate the possibility of drowsiness. If it occurs, the buzzer will beep as a warning to warn the driver to take a short break. The test results in drowsiness conditions with an angle of 10°–30° resulted in 100% accuracy, and normal conditions only at an angle of 0°–6° resulted in 100% accuracy. The result of the developed system is expected to reduce the number of accidents caused by drowsiness
YOLOv11 Model as a Smart Solution for Waste Identification and Classification in Automated Waste Management System Permana, Muhammad Fajar Jati; Gani, Julio Caesar Ray Bakar; Fauzan, Naufal Ahmad; Adiwilaga, Anugrah
Jurnal Ilmu Komputer dan Informasi Vol. 18 No. 2 (2025): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Informatio
Publisher : Faculty of Computer Science - Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21609/jiki.v18i2.1490

Abstract

Urbanization and population growth present significant challenges for efficient and sustainable waste management. This research develops an IoT-based intelligent system for waste classification and management utilizing RFID technology, ESP32, a camera, an ultrasonic sensor, and the YOLOv11 object detection model. The system accurately identifies three categories of waste: organic, inorganic, and hazardous. The classification process is automated, incorporating user identification via RFID, servo-controlled bin lid operation, and capacity monitoring through an ultrasonic sensor. Data management is facilitated through a mobile application and a website, which provide user guidance and support for administrators. Test results indicate that the system achieves an average accuracy of 87.5% in the mAP50-95 evaluation, with specific accuracies of 89.0% for inorganic waste, 86.0% for hazardous waste, and 87.0% for organic waste. Despite these results, challenges remain, including object detection errors related to background interference. Future research should focus on enhancing the dataset and implementing data encryption to improve model accuracy and information security. This system demonstrates significant potential for enhancing waste management efficiency and promoting sustainable environmental practices.
Co-Authors Abdurrahman, Hammam Adelia Clarissa Adi Suheryadi Anggita Apriliani Putri Gustiansyah Antonius Didi Kurniadi Atmanto, Dastin Aryo Dastin Aryo Atmanto Dastin Aryo Atmanto Deden Pradeka Devi Aprianti Rimadhani Agustini Dhimaz Purnama Adjhi Dhimaz Purnama Adjhi Fauzan, Naufal Ahmad Gani, Julio Caesar Ray Bakar Hafidz Rizki Fahriza Ikhsaniyah, Najwa Imam Taufiqurrahman Maqdis, Syiva Awaliyah Mohamad Rizal Hanafi Munawir Munawir Nanditama, Rastra Wardana Nugraha, Wildan Tisna Surya Nuriman, Rizki Pararta, Muhammad Salam Permana, Muhammad Fajar Jati Putra, Muhammad Taufik Dwi Rastra Wardana Nanditama Rifqi Alamsya Rizki Nuriman Suheryadi, Adi Sundari, Firda Rosela Wirmanto Suteddy Zahra Mumtaz