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All Journal Jurnal Teknologi dan Sistem Komputer Jurnal Sustainable: Jurnal Hasil Penelitian dan Industri Terapan Jurnal ABDINUS : Jurnal Pengabdian Nusantara Journal of Computer Networks, Architecture and High Performance Computing Jurnal Anugerah: Jurnal Pengabdian Kepada Masyarakat Bidang Keguruan dan Ilmu Pendidikan Journal of Maritime Empowerment Journal of Information Systems and Technology (JISTech) TENANG : Teknologi, Edukasi, dan Pengabdian Multidisiplin Nusantara Gemilang
Hayaty, Nurul
Computer Science Department, Engineering Faculty, Universitas Maritim Raja Ali Haji
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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SISTEM KLASIFIKASI JENIS KERANG BERDASARKAN CITRA CANGKANG MENGGUNAKAN SUPPORT VECTOR MACHINE (SVM) Adinda; Seffi Rozahana; Nadia Ayu Putri Priyani; Apriliani Putri; Irsyad Widiansyah; Nurul Hayaty
Sustainable Vol 13 No 2 (2024): Jurnal Sustainable : Jurnal Hasil Penelitian dan Industri Terapan
Publisher : Fakultas Teknik Universitas Maritim Raja Ali Haji

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31629/hdnn8e89

Abstract

This study aims to build an automatic classification system to identify shellfish types based on shell images by applying the Support Vector Machine (SVM) algorithm. This study classifies three types of shellfish, namely blood cockles with the scientific name Anadara granosa, green mussels (Perna viridis), and scallops (Amusium pleuronectes). Image data was obtained from the internet and each class consisted of 150 images, so the total dataset was 450 images. The research stages include image pre-processing to normalize image size and quality, feature extraction to obtain visual information in the form of texture (with GLCM), color (RGB histogram), and shape (Canny edge detection), and classification using SVM. This application is web-based and functions to receive uploaded shellfish images from users and provide automatic shellfish type recognition results. The test results show that the developed SVM model is able to classify shellfish types with high accuracy, reaching 93,83%. This research is expected to contribute to the development of digital shellfish species identification technology to support the fields of fisheries, marine resource conservation, and marine biota research. 
Penggunaan Convolutional Neural Network (CNN) untuk Menentukan Kesegaran Ikan Bawal Putih Hanisa; Delima Pakpahan; Qoriah Rahmadiah Ismail; Wulan Novitasari; Nurul Hayaty; Kartika, Amelia
Sustainable Vol 13 No 1 (2024): Jurnal Sustainable : Jurnal Hasil Penelitian dan Industri Terapan
Publisher : Fakultas Teknik Universitas Maritim Raja Ali Haji

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31629/qgfm2430

Abstract

Ikan bawal putih (Pampus argenteus) merupakan salah satu komoditas yang menjadi andalan yang memiliki nilai ekonomi tinggi dan banyak diekspor dalam keadaan beku. Namun, ikan sangat rentan terhadap kerusakan, sehingga kesegarannya merupakan faktor penting yang mempengaruhi kualitas dan harga jual. Penelitian ini bertujuan untuk mengembangkan sistem untuk mengklasifikasikan tingkat kesegaran ikan bawal putih dengan menggunakan metode Convolutional Neural Network (CNN). Citra kepala ikan dipilih sebagai data masukan, yang telah diproses menjadi ukuran 1700x1700 piksel dan disesuaikan dengan resolusi 224x224 piksel sebelum dimasukkan ke dalam model. Arsitektur CNN yang diterapkan terdiri atas tiga lapisan konvolusi dengan penggabungan Max-Pooling, Dropout, Flatten, dan Dense Layer. Proses pelatihan ini berhenti pada epoch ke-30 setelah model mencapai performa yang optimal  dan menghasilkan akurasi pelatihan sebesar 85%, akurasi validasi sebesar 80%, dan akurasi data uji sebesar 81,2%. Hasil evaluasi menunjukkan bahwa model dapat mengklasifikasikan ikan segar dengan baik (precision 0.865, recall 0.938), cukup memuaskan untuk ikan tidak segar (precision 0.788, recall 0.854), dan kurang efektif untuk ikan yang kurang segar (recall 0.646). Secara keseluruhan, model CNN ini menunjukkan kinerja yang cukup baik dan dapat digunakan sebagai alat bantu untuk secara otomatis mendeteksi tingkat kesegaran ikan bawal putih (Pampus argenteus).
Klasifikasi Tingkat Kesegaran Cumi-Cumi (Loligo vulgaris) Menggunakan Metode Support Vector Machine Berbasis Citra Digital Aprizal, Danyi; Simatupang, Seli Octaria; Hayaty, Nurul
Sustainable Vol 13 No 2 (2024): Jurnal Sustainable : Jurnal Hasil Penelitian dan Industri Terapan
Publisher : Fakultas Teknik Universitas Maritim Raja Ali Haji

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31629/frctg379

Abstract

 Determining the freshness level of squid (Loligo vulgaris) is crucial to ensure the quality and safety of seafood products. This study develops an automatic classification system based on digital image processing using the Support Vector Machine (SVM) algorithm. The freshness categories are divided into three classes: Fresh, Not Fresh, and Spoiled. The images used were preprocessed through cropping, resizing to a uniform size, augmentation, and color space conversion. Feature extraction involved color features (RGB and HSI) and texture features (using the Gray Level Co-occurrence Matrix or GLCM). The SVM model was trained using the RBF kernel and evaluated on a separate test dataset to measure its classification performance. The results showed that combining color and texture features significantly improved the accuracy, reaching 87.65% on the test data. As a practical implementation, the system was developed into a graphical user interface (GUI) using MATLAB, enabling users to predict squid freshness directly. This study demonstrates that the proposed method has promising potential as an early solution for digital and efficient quality control in the seafood industry. 
PENINGKATAN PEMAHAMAN MASYARAKAT MELALUI SOSIALISASI PENGELOLAAN SAMPAH BERBASIS OBSERVASI SAMPAH DI MANGROVE DOMPAK Idris, Fadhliyah; Hidayati, Jelita Rahma; Hayaty, Nurul; Koenawan, Chandra Joei; Yandri, Falmi; Kurniawan, Rika; Nugraha, Aditya Hikmat; Sadam, Sadam; Aditianda, Said Rully; Anjani, Poppy Yulia; Aulia, Hillyatul; Arifatin, Ilil; Achmadiyah, Soneta
Jurnal Pemberdayaan Maritim Vol 8 No 1 (2025): Journal of Maritime Empowerment
Publisher : Lembaga Penelitian, Pengabdian Masyarakat, dan Penjaminan Mutu, Universitas Maritim Raja Ali Haji

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31629/jme.v8i1.7700

Abstract

Permasalahan sampah laut di kawasan pesisir, termasuk ekosistem mangrove di Dompak, semakin memprihatinkan dengan dominasi sampah plastik dan keberadaan mikroplastik. Rendahnya kesadaran masyarakat dalam pengelolaan sampah mendorong perlunya kegiatan sosialisasi yang terarah dan berbasis data lapangan. Kegiatan ini bertujuan untuk meningkatkan pemahaman masyarakat melalui sosialisasi pengelolaan sampah sekaligus melakukan observasi jenis sampah di ekosistem mangrove Dompak. Metode yang digunakan meliputi sosialisasi dengan pre-test dan post-test untuk mengukur perubahan pemahaman masyarakat, serta pengamatan langsung komposisi sampah ukuran makro dan mikro di lokasi penelitian. Hasil uji Wilcoxon menunjukkan adanya perbedaan signifikan antara nilai pre test dan post test, sedangkan uji N-Gain menghasilkan peningkatan pemahaman masyarakat tentang pengelolaan sampah sebesar 66,67% pada kategori sedang. Observasi lapangan memperlihatkan bahwa sampah plastik mendominasi hingga 80% dari total komposisi sampah makro, sedangkan mikroplastik yang terdeteksi pada sedimen didominasi oleh tipe film sebesar 85%. Temuan ini mengindikasikan bahwa sosialisasi yang dilakukan efektif dalam meningkatkan pemahaman masyarakat tentang pengelolaan sampah, namun pencemaran plastik di ekosistem mangrove Dompak masih tinggi sehingga memerlukan tindak lanjut berupa aksi nyata dan penguatan pengelolaan sampah secara berkelanjutan.
CRYPTOGRAPHY OF CHACHA20 and RSA ALGORITHMS for TEXT SECURITY Dzahabi, Ziad Yasqi; Hayaty, Nurul; Bettiza, Martaleli
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 1 (2025): Article Research January 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i1.5345

Abstract

The purpose of this study is to apply the ChaCha20 and RSA cryptographic algorithms to enhance text security and safeguard data from unauthorized access, data breaches, and cyberattacks such as man-in-the-middle or replay attacks. ChaCha20, a symmetric encryption algorithm, is employed for generating efficient and secure keystreams, while RSA, an asymmetric algorithm, is used for encrypting numeric keys or messages. The integration of these two algorithms ensures robust data protection from various digital threats. The choice of this title stems from the growing urgency to prioritize data security in the digital era, especially given the increasing incidents of data leaks that often lead to significant consequences. This research focuses on analyzing the implementation of both algorithms in encryption and decryption processes, as well as evaluating their effectiveness in preserving data confidentiality and integrity. The findings of this study demonstrate that the ChaCha20 and RSA implementations effectively secure data, with the encryption and decryption processes functioning as intended. To further validate the system’s robustness, simulated attacks were conducted, and the results confirmed the system's ability to prevent unauthorized access. This research not only contributes to the development of reliable data security solutions but also highlights opportunities for future improvements. Enhancing algorithm efficiency and optimizing encryption runtime are potential areas for further exploration. By addressing these challenges, the study aims to pave the way for more robust and efficient cryptographic solutions in the evolving landscape of digital security.
Pelatihan dan Pendampingan E-Commerce bagi UMKM di Batam: Membangun Ekosistem Digital yang Berkelanjutan Nurul Hayaty; Nola Ritha
TENANG : Teknologi, Edukasi, dan Pengabdian Multidisiplin Nusantara Gemilang Vol. 1 No. 1 (2024): Juni
Publisher : Perhimpunan Ahli Teknologi Informasi dan Komunikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Kegiatan pengabdian masyarakat ini bertujuan untuk meningkatkan kemampuan Usaha Mikro, Kecil, dan Menengah (UMKM) di Batam dalam memanfaatkan e-commerce sebagai strategi pemasaran digital yang efektif. Melalui pelatihan intensif dan pendampingan berkelanjutan, pelaku UMKM diberikan pemahaman mengenai konsep e-commerce, cara membuat dan mengelola toko online, serta strategi pemasaran melalui platform digital. Hasil dari kegiatan ini menunjukkan bahwa para pelaku UMKM mampu mengadopsi teknologi e-commerce dengan baik, yang terbukti dari peningkatan penjualan sebesar 15-30% setelah program pendampingan. Meskipun beberapa peserta menghadapi tantangan dalam mempelajari aspek teknis di awal, dukungan pendampingan memungkinkan mereka untuk mengatasi kendala tersebut dan secara bertahap membangun ekosistem digital yang berkelanjutan. Pelatihan ini berhasil mendorong transformasi digital UMKM di Batam dan diharapkan dapat memberikan dampak positif jangka panjang bagi perekonomian daerah.
Memajukan Ekowisata Bahari Dengan Memanfaatkan Media Teknologi Informasi Di Desa Pengudang, Bintan, Kepulauan Riau Bachtiar, Ibnu Kahfi; Hayaty, Nurul; Rathomi, Radzi; Hekso, Anton; Nurfalinda, Nurfalinda
Jurnal ABDINUS : Jurnal Pengabdian Nusantara Vol 3 No 2 (2020): Volume 3 Nomor 2 Tahun 2020
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/ja.v3i2.13867

Abstract

One potential tourism segment in the Riau Islands is attractions managed by local communities on the coast such as the Pengudang Bintan Mangrove in Pengudang Village, Riau Islands. Most of these attractions are not widely known outside the Riau Islands because of promotions that have not been explored maximally. By conducting a survey, a study of literature, and an analysis of a series of problems, website design was made as a solution. The website is equipped with questionnaires and visitor charts so that managers can conduct an empirical analysis to set targets and goals going forward. In addition to the website also made a profile of attractions on one of the famous traveller sites like TripAdvisor. The results of reviews of tourists visiting various tourist objects, become the basis of most tourists to decide to choose a tourist location.
Co-Authors Achmadiyah, Soneta Adinda Aditianda, Said Rully Aditya Hikmat Nugraha Anjani, Poppy Yulia Apriliani Putri Aprizal, Danyi Arifatin, Ilil Aulia, Hillyatul Bachtiar, Ibnu Kahfi Chahyadi, Ferdi Chandra Joei Koenawan Cut Putri Khairani Delima Pakpahan Dzahabi, Ziad Yasqi Fadhliyah Idris Faiz Arrafi Falmi Yandri Halta Putra Ash Sidiq Hanisa Hekso, Anton Irfan Ibrahim Irsyad Widiansyah Jelita Rahma Hidayati Julia, Rini Hervianti Kartika, Amelia Kirana Putri Fercia Kurniawan, Rika M Afief Anugrah M. Mudaffarsyah M. Wisnu Adjie Pramudya Marcel Wangnandra Martaleli Bettiza Matulatan, Tekad Maulana Fitra Ramadhani Muhamad Radzi Rathomi Muhammad Azza Al Kausar Muhammad Noval Muhammad Ridho Nadia Ayu Putri Priyani Nikentari, Nerfita Nola Ritha Nurfalinda, Nurfalinda Obi Luter Sihombing Pratama, Eko Imam Putri Suci Renita Qoriah Rahmadiah Ismail Ridho Ramadhan Ritha, Nola Sadam, Sadam Seffi Rozahana Simatupang, Seli Octaria Wulan Novitasari