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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 Smatika Jurnal : STIKI Informatika Jurnal
Ade Silvia Handayani
Politeknik Negeri Sriwijaya
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Journal : bit-Tech

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Analysis of Frequency Spectrum in Digital Image Transmission Using Orthogonal Frequency Multiplexing Sarjana Sarjana; Ade Silvia Handayani; Devi Wahyuni
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.2749

Abstract

Accurate and efficient data transmission is increasingly essential due to the growing reliance on digital communication, particularly for multimedia content such as images. Orthogonal Frequency Division Multiplexing (OFDM) provides high bandwidth efficiency and strong noise resilience by transmitting data over multiple orthogonal subcarriers. Despite its advantages, limited studies have explored how modulation schemes influence frequency-domain characteristics during image transmission under different noise conditions. This study addresses that gap by evaluating digital image transmission through OFDM using Binary Phase Shift Keying (BPSK) and Quadrature Phase Shift Keying (QPSK) modulation. The objective is to compare spectral performance across various signal-to-noise ratio (SNR) levels. A grayscale image is converted into a binary stream, modulated using BPSK and QPSK, and processed through an OFDM system with 512 subcarriers and a 25% cyclic prefix. The signals are transmitted through an Additive White Gaussian Noise (AWGN) channel at SNR values of 0 dB, 5 dB, and 10 dB. Power Spectral Density (PSD) is measured using the Welch method with a Hamming window, 50% overlap, and 1024-point Fast Fourier Transform (FFT). The results show that increasing SNR improves spectral sharpness, reduces the noise floor, and enhances symmetry. BPSK offers better performance in noisy conditions, while QPSK is more efficient in high-SNR environments. These findings provide practical insight for optimizing modulation choices in OFDM-based image transmission systems where spectral efficiency and noise robustness must be balanced.
Multi-Step GRU Model for River Water Level Prediction with IoT Sensors Ahmad Satrio Perdana; Ade Silvia Handayani; Ciksadan Ciksadan; Carlos RS; Asriyadi Asriyadi
bit-Tech Vol. 8 No. 2 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i2.2846

Abstract

The Simpang Lima PUPR Pump Station on Jalan Radial, Palembang, serves as a critical drainage point for the largest water discharge in the downstream area, making the surrounding region highly vulnerable to surface runoff and flooding, especially during short-duration high-intensity rainfall events. This study aims to develop a 24-hour ahead multi-step river water level prediction model using the Gated Recurrent Unit (GRU) algorithm, powered by real-time data from Internet of Things (IoT) sensors installed at the pump station. The collected dataset spans from June to July and includes water level, rainfall, temperature, humidity, and barometric pressure. The data was preprocessed through normalization before being used as input to the GRU model. The GRU-based prediction model demonstrated strong performance with a Mean Squared Error (MSE) of 0.394, Root Mean Squared Error (RMSE) of 0.628, coefficient of determination (R²) of 0.99, and Nash-Sutcliffe Efficiency (NSE) of 0.9853. These results indicate high predictive accuracy and model reliability. The proposed model has strong potential for integration into early warning dashboards to support flood mitigation strategies and improve the operational efficiency of pump stations in high-risk urban zones. Additionally, this research offers a data-driven framework for the Ministry of Public Works and Housing (PUPR) to design real-time, predictive flood control systems. The approach can optimize pump operations, enhance emergency response planning, and guide drainage infrastructure improvements. Furthermore, it promotes climate-resilient flood adaptation policies and serves as a model for smart technology deployment in other Indonesian cities.
Comparative Analysis Of Random Forest and Naive Bayes for Flood Classification Using Sentinel-1 SAR Clara Silvia Rotua Aritonang; Ade Silvia Handayani; Suroso Suroso; Wahyu Caesarendra; Asriyadi Asriyadi
bit-Tech Vol. 8 No. 2 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i2.2852

Abstract

This research introduces a framework for classifying flood inundation utilising Sentinel-1 Ground Range Detected (GRD) radar imagery alongside machine learning algorithms.  Radar backscatter values from pre- and post-event Sentinel-1 images were processed with SNAP and QGIS to extract spatial features and change indicators in decibel (dB) format.  The tabular dataset, comprising 500,000 samples that equally represent flooded and non-flooded areas, was utilised for model training. Two models, Random Forest and Naive Bayes, were assessed for their classification efficacy.  The Random Forest model demonstrated exceptional performance, attaining an accuracy of 99.81%, precision of 99.75%, recall of 99.67%, and an F1-score of 99.71%.  Naive Bayes achieved an accuracy of 52.63%, with precision and F1-score notably impacted by elevated false positive rates, although recall was 86.36%.  Analysis of confidence distribution indicated that Random Forest exhibited low-confidence errors at the decision boundary, whereas Naive Bayes demonstrated confident misclassifications. Analysis of computation time indicated that Naive Bayes required less than 0.1 seconds per run, whereas Random Forest completed training in under 3 minutes.  The trade-off between speed and reliability underscores the appropriateness of Random Forest for operational flood mapping applications.  This research provides a practical comparison of classification models utilising open-access radar data and establishes a dependable pipeline for pixel-level flood identification.
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 Satrio Perdana 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 Aryanti Aryanti Asriyadi Asriyadi 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 Carlos RS Ciksadan Ciksadan Ciksadan Ciksadan Ciksadan, Ciksadan Clara Silvia Rotua Aritonang Destra Andika Destra Andika Pratama Devi Indah Pujiana Devi Wahyuni Dewi, Tresna Dody Novriansyah DWI RAMADHANI Dzikrillah, Muhammad Ekawati Prihatini Ekawati Prihatini Elisa Islami Putri Ella Rosita 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 Ghina Maysya Ayu 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 Leni Novianti Linda Wati Lindawati Lindawati M Arief Rahman M Arief Rahman M Lutfi Kurniawan M. Ardiansyah M. Ilham Akbar M. Sobri Maharani, Ullya Dwi Mardiani, Mega Marieska Lupikawaty Martinus Mujur Rose Masayu Anisah 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 Nabiel Arinaullah 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 Suroso Suroso suzan zefi Syauqiyah, Khansa Ghazalah Taqwa, Ing Ahmad Tarmidi Tarmidi Theresia Enim Agusdi Tresna Dewi Tresna Dewi Ulandari, Monica Wahyu Caesarendra Wahyu Caesarendra Widya, Afni Rara Wildan Putra Pratama Wirayudha, Ikhwan Adhi Yani, Iryadi Yeni Irdayanti Yudi Wijanarko