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All Journal JOIN (Jurnal Online Informatika) Sistemasi: Jurnal Sistem Informasi JOIV : International Journal on Informatics Visualization Indonesian Journal of Electrical Engineering and Computer Science Tridharmadimas: Jurnal Pengabdian Kepada Masyarakat Jayakarta Jurnal Pengabdian Ibnu Sina Jurnal Pengabdian Masyarakat Bangsa SWAGATI: Journal of Community Service
Ferda Ernawan
Program Pasca Sarjana Magister Teknik Informatika, Universitas Dian Nuswantoro,Semarang 50131
Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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Data Science untuk Karang Taruna : Menggali Peluang Bisnis dan Pengembangan Karir melalui Eksplorasi Data Gata, Windu; Hermaliani, Eni Heni; Manik, Lindung P.; Ernawan, Ferda
Jurnal Pengabdian Masyarakat Bangsa Vol. 2 No. 5 (2024): Juli
Publisher : Amirul Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59837/jpmba.v2i5.1046

Abstract

Di era revolusi 4.0 ini, data science semakin populer di berbagai sektor industri, berfungsi sebagai alat penting untuk mengonversi data menjadi informasi berharga. Karir sebagai data scientist dan data analyst adalah dua profesi yang sangat potensial di masa depan, sehingga masyarakat harus terus mengupgrade diri agar terus berkembang mengikuti pertumbuhan ilmu pengetahuan saat ini. Bagi Karang Taruna, diselenggarakannya kegiatan ini dapat memberikan wawasan keilmuan terkait data science dan manfaatnya sebagai peluang bisnis dan pengembangan karir anggotanya. Adapun metode  pelaksanaan pelatihan dan kronologis kegiatan abdimas dimulai dengan tahap persiapan yaitu menggali permasalahan yang dihadapi lanjut mengajukan izin penyelenggaraan. Tahap selanjutnya dari kegiatan ini dimulai dengan pembukaan, diikuti oleh presentasi materi, diskusi interaktif, dan sesi tanya jawab. Setelah itu, proses monitoring dan evaluasi dilakukan melalui penyebaran kuesioner untuk mendapatkan umpan balik. Kegiatan ditutup dengan acara penutupan resmi. Program pengabdian ini berhasil memperluas wawasan peserta mengenai teknologi modern dan menekankan pentingnya ilmu data di era digital untuk mengidentifikasi peluang bisnis dan mengembangkan karir. Kompetensi dasar yang diperoleh dapat terus diasah melalui tools-tools ilmu data lainnya dimasa depan.
A set of embedding rules in IWT for watermark embedding in image watermarking Hafidz, Muhammad Afnan; Ernawan, Ferda; Bakar, Suraya Abu; Fakhreldin, Mohammad
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 3: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i3.pp1512-1520

Abstract

The development of new technologies has made image watermarking crucial in the digital era to preserve and protect illegal distribution of images against unauthorized users. This paper presents a robust image watermarking technique that employs a set of embedding rules in the three-level of integer wavelet transform (IWT). The proposed method aims to achieve high robustness of image watermarking while maintaining the imperceptibility. The proposed scheme divides the red and green layers into non-overlapping 16×16 blocks. Three levels of IWT are applied to obtain 2×2 LL sub-band, four coefficients of IWT are then modified based on the proposed set of rules for embedding watermark. The experimental results demonstrate a comparison of the proposed embedding and the existing methods. The proposed scheme produced an average NC value of 0.965 against the median filter. The results also showed the imperceptibility of the the image with a PSNR of 45.1760 db and SSIM of 0.9995.
Dual image watermarking based on NSST-LWT-DCT for color image Avivah, Siti Nur; Ernawan, Ferda; Mat Raffei, Anis Farihan
Indonesian Journal of Electrical Engineering and Computer Science Vol 35, No 2: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v35.i2.pp907-915

Abstract

Advanced internet technology allows unauthorized individuals to modify and distribute digital images. Image watermarking is a popular solution for copyright protection and ensuring digital security. This research presents an embedding scheme with a set of conditions using non-subsampled Shearlet transform (NSST), lifting wavelet transform (LWT), and discrete cosine transform (DCT). Red and green channels are employed for the embedding process. The red channel is converted by NSST-LWT. The low-frequency area (LL) frequency is then split into small blocks of 8×8, each partition block is then transformed by DCT. The DCT coefficient of (3,4), (5,2), (5,3), (3,5), called matrix M1, and (2,5), (4,3), (6,2), (4,4), called matrix M2 are selected for singular value decomposition (SVD) process. With a set of conditions, the watermark bits are incorporated into those singular values. The green channel is cropped to get the center image before splitting into 4×4 pixels. The block components are then selected based on the least entropy value for the embedding regions. The selected blocks are then computed using LWT-SVD. A set of conditions for U(1,1) and U(2,1) are used to incorporate the watermark logo. The experimental findings reveal that the suggested scheme achieves high imperceptibility and resilience under various evaluating attacks with an average peak signal-to-noise ratio (PSNR) and correlation value (NC) values are up to 43.89 dB and 0.96, respectively.
PELATIHAN PEMANFAATAN AI UNTUK MENUNJANG PENINGKATAN LITERASI DIGITAL Pardede, Hilman F; Riana, Dwiza; Kurniawati, Laela; Ernawan, Ferda; Na'am, Jufriadif
TRIDHARMADIMAS: Jurnal Pengabdian Kepada Masyarakat Jayakarta Vol 4 No 2 (2024): PKM-TRIDHARMADIMAS (Desember 2024)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/tridharmadimas.v4i2.1719

Abstract

. Dengan adanya perkembangan teknologi informasi dan komunikasi yang semakin meningkat saat ini, memiliki keterampilan literasi digital menjadi suatu kebutuhan mendesak untuk mempersiapkan generasi muda menghadapi tantangan teknologi. Artificial intelligent hadir untuk membantu pekerjaan manusia hingga dapat menyelesaikan tugasnya dengan cepat, tepat, efektif dan efisien, bukan untuk menggantikan pekerjaan manusia. Mitra dalam program ini adalah Jaringan Pemuda dan Remaja Indonesia (JPRMI) DKI Jakarta. JPRMI DKI Jakarta bertempat di Jl. Jend. Basuki Rachmat No.1A, RT.1/RW.9, Bidara Cina, Kecamatan Jatinegara, Kota Jakarta Timur, Daerah Khusus Ibukota Jakarta 13410. JPRMI merupakan organisasi sosial dengan keanggotaan pemuda masjid di wilayah DKI Jakarta. Permasalahan yang selama ini dihadapi oleh mitra adalah kesulitan dalam memberikan pengarahan kepada peserta terkait bagaimana pemanfaatan AI untuk menunjang peningkatan literasi digital. Solusi untuk mitra dalam mengatasi permasalahan tersebut adalah memberikan pelatihan pemanfaatan AI untuk menunjang peningkatan literasi digital. Berdasarkan permasalahan tersebut Fakultas Teknologi Informasi Universitas Nusa Mandiri akan menyelenggarakan Tri Dharma Perguruan Tinggi yaitu kegiatan pengabdian masyarakat dengan tema Pelatihan Pemanfaatan AI untuk Menunjang Peningkatan Literasi Digital. Kegiatan PKM ini bertujuan untuk mengembangkan pengetahuan dan wawasan peserta terkait pemanfaatan AI untuk menunjang peningkatan literasi digital, dengan luaran yang ditargetkan dari kegiatan ini adalah publikasi release dan submit ke jurnal nasional
SOSIALISASI KESADARAN KEAMANAN SIBER PADA BADAN SANTUNAN YATIM KELURAHAN PONDOK CINA DEPOK Riana, Dwiza; Ernawan, Ferda; Na'am, Jufriadif; Pardede, Hilman Ferdinandus; Hasanah, Riyan Latifahul
Jurnal Pengabdian Ibnu Sina Vol. 4 No. 1 (2025): Januari 2025
Publisher : LPPM Universitas Ibnu Sina

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36352/j-pis.v4i1.848

Abstract

ABSTRAK Perkembangan teknologi informasi dan komunikasi selain membawa manfaat tapi juga berdampak dengan munculnya tindak pidana baru dalam bidang teknologi. Modus kejahatan dalam bidang teknologi (cyber chrime) mengikuti alur yang terjadi dalam sistem digital. Lima jenis penipuan yang sering terjadi yaitu, penipuan berkedok hadiah, pinjaman digital ilegal, pengiriman tautan yang berisi malware atau virus, penipuan berkedok krisis keluarga, dan investasi ilegal. Dalam rangka melaksanakan kegiatan Tri Dharma Perguruan Tinggi yaitu Pengabdian kepada Masyarakat, Fakultas Teknologi Informasi Universitas Nusa Mandiri menyelenggarakan pelatihan dengan tema “Sosialisasi Kesadaran Keamanan Siber pada Badan Santunan Yatim Kelurahan Pondok Cina Depok”. Kegiatan ini bertujuan untuk meningkatkan kesadaran peserta akan pentingnya keamanan siber serta menambah wawasan mengenai keamanan siber. Luaran pengabdian kepada masyarakat berupa press release yang ditayangkan di Nusa Mandiri News serta artikel jurnal. Kata Kunci: keamanan siber, pengabdian kepada masyarakat, sosialisasi ABSTRACT The development of information and communication technology not only brings benefits but also has an impact on the emergence of new criminal acts in the field of technology. The mode of crime in the field of technology (cyber crime) follows the flow that occurs in digital systems. The five types of fraud that often occur are, fraud under the guise of gifts, illegal digital loans, sending links containing malware or viruses, fraud under the guise of family crises, and illegal investments. In order to carry out the Tri Dharma of Higher Education activities, namely Community Service, the Faculty of Information Technology, Nusa Mandiri University held training with the theme "Socialization of Cyber ​​Security Awareness in the Orphan Compensation Agency, Pondok Cina Village, Depok". This activity aims to increase participants' awareness of the importance of cyber security and increase their insight into cyber security. The output of community service is in the form of press releases published in Nusa Mandiri News and journal articles. Keywords: cyber security, community service, socialization
Fast image watermarking based on signum of cosine matrix Ernawan, Ferda; Adi, Prajanto Wahyu; Liew, Siau-Chuin; Sarwoko, Eko Adi; Winarno, Edy
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 3: March 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i3.pp1383-1391

Abstract

In the field of image watermarking, the singular value decomposition has good imperceptibility and robustness, but it has high complexity.  It divides a host image into matrices of U, S, and V. Singular matrix S has been widely used for embedding and extracting watermark, while orthogonal matrices of U and V are used in decomposition and reconstruction. The proposed signum of cosine matrix method is carried out to eliminate the generation of the three matrices at each block and replace it with a signum of cosine matrix. The proposed signum of cosine matrix is performed faster on the decomposition and reconstruction. The image is transformed into a coefficient matrix C using the signum matrix. The C matrix values are closer to the S value of singular value decomposition which can preserve high quality of the watermarked image. The experimental results show that our method is able to produce similar imperceptibility and robustness level of the watermarked image with less computational time.
Pelatihan Penggunaan Aplikasi Administrasi RT/RW Berbasis Website Pada PKK RW 06 Tegal Parang Mampang Hermaliani, Eni Heni; Gata, Windu; Manik, Lindung Parningotan; Ernawan, Ferda
SWAGATI : Journal of Community Service Vol. 1 No. 2 (2023): July
Publisher : Universitas AMIKOM Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24076/swagati.2023v1i2.1100

Abstract

Kehidupan bermasyarakat pada tingkatan paling bawah diatur melalui Permendagri nomor 5 tahun 2007 yang mengatur tentang pembentukan Rukun Warga dan Rukun Tetangga. Untuk dapat menjalankan fungsi dan perannya dengan baik pada revolusi 4.0 ini, pemerintah diharapkan dapat beradaptasi dengan perkembangan teknologi untuk menyelesaikan dan memenuhi kebutuhan masyarakat melalui penggunaan aplikasi berbasis teknologi pada pelayanan publik. Dalam rangka melaksanakan kegiatan tri dharma perguruan tinggi yaitu pengabdian kepada masyarakat, Fakultas Teknologi Universitas Nusa Mandiri menyelenggarakan pelatihan penggunaan aplikasi administrasi RT RW berbasis website yang bertujuan guna memberikan cara dan langkah-langkah penggunaan aplikasi administrasi RT RW yang dapat digunakan oleh pengurus RW 06 dan RT yang berada dibawah RW 06. Pelatihan ini diselenggarakan bekerjasama dengan mitra yaitu PKK RW 06 Kelurahan Tegal Parang Kecamatan Mampang Prapatan. Dengan adanya aplikasi, dapat memberikan pelayanan administrasi kepada masyarakat dengan lebih cepat dan tepat.
Generative Adversarial Networks In Object Detection: A Systematic Literature Review Mat Raffei, Anis Farihan; Suakanto, Sinung; Hamami, Faqih; Ismail, Mohd Arfian; Ernawan, Ferda
JOIN (Jurnal Online Informatika) Vol 10 No 1 (2025)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v10i1.1576

Abstract

The intersection of Generative Adversarial Networks (GANs) and object detection represents one of the most promising developments in modern computer vision, offering innovative solutions to longstanding challenges in visual recognition systems. This review presents a systematic analysis of how GANs are transforming these challenges, examining their applications from 2020 to 2025. The paper investigates three primary domains where GANs have demonstrated remarkable potential: data augmentation for addressing data scarcity, occlusion handling techniques designed to manage visually obstructed objects, and enhancement methods specifically focused on improving small object detection performance. Analysis reveals significant performance improvements resulting from these GAN applications: data augmentation methods consistently boost detection metrics such as mAP and F1-score on scarce datasets, occlusion handling techniques successfully reconstruct hidden features with high PSNR and SSIM values, and small object detection techniques increase detection accuracy by up to 10% Average Precision in some studies. Collectively, these findings demonstrate how GANs, integrated with modern detectors, are greatly advancing object detection capabilities. Despite this progress, persistent challenges including computational cost and training stability remain. By critically analyzing these advancements and limitations, this paper provides crucial insights into the current state and potential future developments of GAN-based object detection systems.
Exploring Blockchain and AI in Digital Banking: A Literature Review on Transactions Enhancement, Fraud Detection, and Financial Inclusion Pramudito, Dendy; Na’am, Jufriadif; Ernawan, Ferda
Sistemasi: Jurnal Sistem Informasi Vol 14, No 3 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i3.5231

Abstract

This paper explores the integration of Blockchain and Artificial Intelligence (AI) in the realm of digital banking, focusing on enhancing transaction efficiency, preventing fraud, and promoting financial inclusion. Utilizing a literature review methodology, this study synthesizes existing research to identify the synergistic effects of these two transformative technologies. Blockchain offers a decentralized, secure framework for transactions, while AI enhances data analysis and decision-making capabilities. The findings reveal that the combined application of Blockchain and AI can significantly streamline banking operations, reduce the incidence of fraud through advanced predictive analytics, and extend financial services to underserved populations. A comparison followed on case studies of successful digital banks that e taken advantage of AI and Blockchain technologies. In order to validate the results, industry experts and banking professionals were interviewed qualitatively to find out on the one hand where the opportunities lie and on the other where the challenges are when doing this implementation. Furthermore, the research highlights the challenges and limitations of implementing these technologies, including regulatory hurdles and the need for robust cybersecurity measures. By addressing these issues, financial institutions can leverage Blockchain and AI to create a more secure, efficient, and inclusive banking environment. This study not only fills a critical research gap but also provides practical recommendations for banking practitioners and policymakers. Ultimately, the integration of Blockchain and AI is poised to redefine digital banking, ensuring that technological advancements contribute to a more equitable financial landscape.
Comparative Analysis of Robust Imputation Techniques for Enhancing Cervical Cancer Prediction with Missing Data Mizan, Muhammad Thaqiyuddin; Ernawan, Ferda; Kasim, Shahreen; Erianda, Aldo; Mohd Fauzi, Abdullah Munzir
JOIV : International Journal on Informatics Visualization Vol 9, No 5 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.5.4501

Abstract

Handling missing data is a critical challenge in machine learning applications, as it can significantly affect the accuracy and reliability of predictive models. Addressing this issue is crucial for developing robust systems that can deliver high-performance results. This study provides a comparative analysis of the robust imputation technique for cervical cancer prediction with incomplete information. This study has investigated the importance of robust imputation techniques, particularly Soft Imputer, in addressing missing data challenges and enhancing model performance. This study investigates the impact of various imputations across five distinct approaches: KNN imputer, PCA imputer, MICE imputer, XGBoost imputer, LightGBM imputer, and feature selection methods. These imputation data are tested on several machine learning models such as Random Forest (RF), Extreme Gradient Boosting (XGB), Decision Tree (DT), Support Vector Classifier (SVC), Logistic Regression (LR), Extra Trees Classifier (ETC), CatBoost Classifier, Stochastic Gradient Descent (SGD), and Gradient Boosting (GB) for improving classification accuracy of cervical cancer prediction. The evaluation reveals that the soft imputer method achieves a balanced and effective handling of missing data, significantly improving the reliability of the models. Among the tested methods, LightGBM and XGBoost deliver strong results, each achieving an average accuracy of 96.91%. MICE demonstrated the lowest average accuracy at 95.94%, although it still performs reliably in managing missing data. The findings provide valuable insights for enhancing predictive accuracy in future work by integrating advanced imputation strategies for high-dimensional and complex datasets.
Co-Authors Aldo Erianda, Aldo Avivah, Siti Nur Bakar, Suraya Abu Dendy K. Pramudito Dwiza Riana Edy Winarno Eko Adi Sarwoko Eni Heni Hermaliani, Eni Heni Fakhreldin, Mohammad Faqih Hamami Gata, Windu Hafidz, Muhammad Afnan Hasanah, Riyan Latifahul Ismail, Mohd Arfian Laela Kurniawati, Laela Liew, Siau-Chuin Lindung Parningotan Manik Manik, Lindung Parningotan Mat Raffei, Anis Farihan Mizan, Muhammad Thaqiyuddin Mohd Fauzi, Abdullah Munzir Na'am, Jufriadif Na’am, Jufriadif Pardede, Hilman F Pardede, Hilman Ferdinandus Prajanto Wahyu Adi, Prajanto Wahyu Puspita, Kartika Shahreen Kasim, Shahreen Sinung Suakanto Yuris Alkhalifi