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All Journal ComEngApp : Computer Engineering and Applications Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) TEKNIK INFORMATIKA Teknika Jurnal Teliska Proceedings of KNASTIK Elkom: Jurnal Elektronika dan Komputer PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Prosiding SNATIF Teknika: Jurnal Sains dan Teknologi Annual Research Seminar SMATIKA Jurnal Ampere Proceeding of the Electrical Engineering Computer Science and Informatics PROtek : Jurnal Ilmiah Teknik Elektro Jurnal Informatika Upgris Tech-E International Journal of Artificial Intelligence Research JURNAL MEDIA INFORMATIKA BUDIDARMA VOLT : Jurnal Ilmiah Pendidikan Teknik Elektro Indonesian Journal of Artificial Intelligence and Data Mining JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal TIPS : Jurnal Teknologi Informasi dan Komputer Politeknik Sekayu Jurnal Teknologi Sistem Informasi dan Aplikasi Jurnal RESISTOR (Rekayasa Sistem Komputer) Explore IT : Jurnal Keilmuan dan Aplikasi Teknik Informatika Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Qua Teknika Jurnal Fokus Elektroda : Energi Listrik, Telekomunikasi, Komputer, Elektronika dan Kendali Jurnal Teknologi Informasi dan Pendidikan Building of Informatics, Technology and Science Jurnal Informatika dan Rekayasa Elektronik bit-Tech Indonesian Journal of Electrical Engineering and Computer Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) International Journal of Advances in Data and Information Systems Jurnal Teknik Informatika (JUTIF) Fokus Elektroda: Energi Listrik, Telekomunikasi, Komputer, Elektronika dan Kendali) Advance Sustainable Science, Engineering and Technology (ASSET) Aptekmas : Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian Masyarakat Bangsa Enrichment: Journal of Multidisciplinary Research and Development Prosiding Seminar Hasil Penelitian dan Pengabdian Kepada Masyarakat Jurnal Pengabdian Masyarakat Sultan Indonesia Journal of Environment and Sustainability Education JEPEmas: Jurnal Pengabdian Masyarakat (Bidang Ekonomi) Jurnal Pengabdian Masyarakat Mentari
Ade Silvia Handayani
Politeknik Negeri Sriwijaya
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Journal : Building of Informatics, Technology and Science

 1 
Penerapan EfficiencyNet Untuk Pembuatan Model CNN Pada Klasifikasi Bahasa Isyarat Putri, Amanda Kanaya; Suroso, Suroso; Handayani, Ade Silvia
Building of Informatics, Technology and Science (BITS) Vol 6 No 2 (2024): September 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i2.5592

Abstract

This study discusses the application of EfficientNet architecture in developing a Convolutional Neural Network (CNN) model for sign language classification. Sign language is a vital communication method for the deaf community, but automatic recognition remains a challenge in the field of computer vision. One of the primary issues is the limitation in accuracy and efficiency of models in recognizing complex variations of sign language in real-world conditions. EfficientNet, known for its computational efficiency, is used as a backbone to build a CNN model that can classify sign language letter patterns with high accuracy while remaining lightweight. The dataset used in this study is American Sign Language (ASL) with data augmentation techniques to enhance the variety and quality of the dataset. The dataset comprises 14,740 images of sign language letter patterns from various angles and lighting conditions. Experimental results show that the EfficientNet-based model developed achieves training and validation accuracies of 98.40% with a more efficient model size and inference time. This study demonstrates the significant potential of using EfficientNet in developing sign language classification systems that can be applied to devices with limited resources, such as mobile applications and edge computing. These findings are expected to improve accessibility and social inclusion for the deaf and speech-impaired communities. Thus, this research not only contributes to the field of pattern recognition technology but also to efforts to enhance the quality of life for individuals with communication disabilities through the development of effective and efficient assistive tools.
Implementasi IoT dan Sensor Termal untuk Mitigasi Kebakaran Hutan dan Lahan dengan Penentuan Koordinat Br Ginting, Nurul Devani; Handayani, Ade Silvia; Sarjana, Sarjana
Building of Informatics, Technology and Science (BITS) Vol 6 No 2 (2024): September 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i2.5594

Abstract

Forest fires are a serious environmental problem, causing ecosystem damage, air pollution and economic losses. Effective monitoring and mitigation of forest fires requires early detection and tracking of hotspots that have the potential to become fire centers. This research proposes the implementation of Internet of Things(IoT) technology and thermal sensors to detect forest fires through point coordinate mapping using the triangulation method. The method used involves the installation of thermal sensors and NEO-6 GPS modules. The thermal sensor measures the ambient temperature in real-time, while the GPS module provides precise coordinate data in (latitude and longitude). Data from the sensors is transmitted to the ThingSpeak platform via the IoT network, where further analysis is performed to identify hot spots. A triangulation method is then applied to map the position of the hot spot. This research aims to develop a forest fire monitoring system capable of detecting and mapping hotspots in real-time, thus enabling quick and effective mitigation actions. The results obtained from this research show that the system can determine the position of hotspots with coordinate accuracy (latitude and longitude) within a margin of error of less than 5 meters.
Analisis Deteksi Mata Kantuk Di Wajah Pengemudi Menggunakan Support Vector Machine (SVM) Berbasis Citra Real-Time Maharani, Ullya Dwi; Handayani, Ade Silvia; Lindawati, Lindawati
Building of Informatics, Technology and Science (BITS) Vol 6 No 2 (2024): September 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i2.5701

Abstract

Traffic accidents in Indonesia are a serious issue with a high number of fatalities, and one of the main causes is microsleep, which is a brief moment of sleep while driving. To address this problem, this research has developed a sleePIness detection system based on the Internet of Things (IoT) using a Raspberry PI and a webcam, utilizing the Support Vector Machine (SVM) algorithm. The system is designed to detect the driver’s eye condition and provide a warning through a buzzer if the eyes are closed for more than 3 seconds. The research results indicate that the SVM model with a polynomial kernel has a training accuracy of 85.04%, demonstrating its ability to classify eye data into "opened" and "closed" categories. Evaluation with various SVM kernels, including linear, radial basis function (RBF), and polynomial, shows that the polynomial kernel performs the best with an accuracy of 85%, precision of 86%, and recall of 85% in detecting closed eyes. Although the system is effective in real-time detection of driver sleePIness, challenges remain with lighting conditions and camera positioning. Further testing is needed to improve the reliability and accuracy of the system in various situations. By providing early warnings to drivers, this system has significant potential to enhance road safety and prevent accidents caused by drowsiness.
Penerapan Algoritma Random Forest untuk Memprediksi Curah Hujan pada Masa Mendatang di Daerah Berpotensi Banjir Aswarisman, Novie Rahmadani; Handayani, Ade Silvia; Hadi, Irawan
Building of Informatics, Technology and Science (BITS) Vol 6 No 2 (2024): September 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i2.5593

Abstract

Palembang, as one of the largest cities in Indonesia, regularly experiences severe flooding problems every year. Flooding not only disrupts the daily activities of residents, but also causes significant economic losses and social impacts. To solve this problem, it is crucial to have an in-depth understanding of flooding patterns and some of the factors that influence them. The purpose of this research is to apply highly efficient Machine Learning (ML) technology for the prediction analysis of future flood-prone areas. The integration of ML can help in identifying patterns, predicting risks, and making more accurate decisions in flood mitigation. In an effort to achieve this goal, the CRISP-DM (Cross-Industry Standard Process for Data Mining) methodology will be applied to ensure the research is conducted systematically and comprehensively. Therefore, research on the analysis of mapping flood-prone areas in Palembang using ML is essential to provide a fairly effective and efficient solution to the long-standing flooding problem. With the CRISP-DM approach, it is expected that this research can produce an accurate and reliable prediction model by integrating the Random Forest algorithm as a regression model, and provide long-term benefits for flood risk management in Palembang and several other cities in Indonesia that experience similar problems.
Rancang Bangun Kontrol Air Conditioner Otomatis Menggunakan Algoritma Propotional Integral Derivative (PID) Berbasis Internet of Things Sinaga, Putri; Enri, Jon; Handayani, Ade Silvia
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.5690

Abstract

An efficient and responsive air conditioning control system is essential for maintaining thermal comfort as well as energy efficiency in a room. This research develops an AC control system based on the number of people entering or leaving the room using the PID (Proportional-Integral-Derivative) algorithm integrated with Internet of Things technology through the Blynk platform. Infrared proximity and temperature sensors are used to detect the number of people in the room and measure the room temperature. This data is then processed by the ESP32 microcontroller which runs the PID algorithm to generate a control signal that will adjust the AC temperature towards the setpoint. This system allows the AC temperature to be dynamically adjusted based on changes in the number of people in the room, which is expected to optimize energy consumption. In addition, integration with Blynk allows real-time monitoring and control of the system through a smartphone app, providing users with greater flexibility and control. The trial results show that the system is able to respond to changes in the number of people and maintain the room temperature within comfortable limits (setpoint). As such, it offers an effective solution for smarter room temperature management.
Co-Authors A. Rahman AA Sudharmawan, AA Aan Sugiyanto Abdul Rakhman Abdurahman Abdurrahman Abu Hasan Aditya, M Rizky Vira Afifah, Luthfia Afiifa Aaliyah Maharani Agung, Muhammad Zakuan Ahmad Taqwa Ahmad Taqwa Al Fatur Sayid Al-Kausar, Jefri Albertia Youlanda Alfarizal, Niksen Ali Nurdin Ali Nurdin Ali Nurdin Alquratu SeptriaPS, Annies Amperawan Amperawan Andry Meylani Angguna, Welan Mauli Anisah Fadhilah Arinaullah, Nabiel Aryanti Aryanti Asriyadi Asriyadi Aswarisman, Novie Rahmadani Auditra Faza Amira Az-zahra, Maudhy Banu Putri Pratiwi Br Ginting, Nurul Devani Btari Puspa Yahya C. Ciksadan Carlos R Sitompul Ciksadan Ciksadan Ciksadan, Ciksadan Destra Andika Destra Andika Pratama Devi Indah Pujiana Dewi, Tresna Dody Novriansyah DWI RAMADHANI Dzikrillah, Muhammad Ekawati Prihatini Ekawati Prihatini Elisa Islami Putri Emilia Hesti Endri, Jon Endri, Jon Enri, Jon Evelina Evelina Evelina Evelina Evelina, Evelina Faisal Damsi Farid Jatri Abiyyu Faris, Fakhri Al Farozi, Ahmad Felia, Okta Felisia Talitha Aprilia Firdaus Firdaus Hani Marta Putri Harlasyanti, Dewi Ekha Hertani Indah Lestari Hetty Meileni Hj. Lindawati Husni, Nyayu Latifah Ibnu Ziad, Ibnu Ihsan Mustaqiim Inayah, Cantika Tri Irawan Hadi Irawan Hadi Irdayanti, Yeni Irma Salamah Irsyadi Yani Iryadi Yani Iryadi Yani, Iryadi Iskandar Lutfi Jon Endri Kaila, Afifah Syifah Kinasih, Ayu Antika Sekar Kurniawan, M Lutfi Leni Novianti Linda Wati Lindawati Lindawati M Arief Rahman M. Ardiansyah M. Ilham Akbar M. Sobri Maharani, Ullya Dwi Mardiani, Mega Marieska Lupikawaty Martinus Mujur Rose Masayu Anisah Maysya Ayu, Ghina Medina Nadila Prima Putri Mega Hasanul Huda Meranda, Arganda Meutia Deli Rachmawati Mieska Despitasari Moh. Heri Kurniawan Mohammad Fadhli Msy Aulia Hasanah Muhamad Rizki Harahap Nabila, Puspita Aliya Nasron Nasron Nasron Nasron Nofriyanti, Duwi Novriansyah, Dody Nur Agustini Nur Hopipah Nurhajar Anugraha Nyanyu Latifah Husni Nyayu Latifah Nyayu Latifah Husni Nyayu Latifah Husni Nyayu Latifah Husni Nyayu Latifah Husni Nyayu Latifah Husni, Nyayu Latifah Oktariani, Clara Permata Sari, Mira Permatasari, Rosmalinda Plowerita, Sanyyah Pratama, Destra Andika Prihatini, Ekawati Putra, Muhammad Rizki Ganda Putra, Yogie Dwi Putri, Amanda Kanaya Rahman, M Arief Rahman, M. Arief Rakhman, M Arief Rakhman, M.Arief Rasyad, Sabilal Riska Handayani Riswal Hanafi Siregar Rivaldo Arviando Rizkiyanti, Shally Rizky Vira Robi Robi Rosita, Ella Rossi Passarella Rumiasih Rumiasih Rumiasih Rumiasih Rumiasih Rumiasih Sabilal Rasyad Sabilal Rasyad Safitri, Rahmi Dian Salsabillah, Farhah Sanyyah Plowerita Sarjana Sarjana Sarjana, Sarjana Sehatiningsih, Ambar Selamat Muslimin Sinaga, Putri Sitangsu Sitangsu Siti Chodijah Siti Nurmaini Sitompul, Carlos R Sobri, M. Sopian Soim Sopian Soim Sopian Soim, Sopian Sri Chodidjah Sugiyanto, Aan Suroso Suroso Suroso Suroso suzan zefi Syauqiyah, Khansa Ghazalah Taqwa, Ing Ahmad Tarmidi Tarmidi Theresia Enim Agusdi Tresna Dewi Tresna Dewi Ulandari, Monica Wahyu Caesarendra Wahyuni, Devi Widya, Afni Rara Wildan Putra Pratama Wirayudha, Ikhwan Adhi Yani, Iryadi Yeni Irdayanti Yudi Wijanarko