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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Journal of Telematics and Informatics Jurnal sistem informasi, Teknologi informasi dan komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) Infotech Journal Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Komputer Terapan JITK (Jurnal Ilmu Pengetahuan dan Komputer) JOURNAL OF APPLIED INFORMATICS AND COMPUTING Justek : Jurnal Sains Dan Teknologi Jurnal Sisfokom (Sistem Informasi dan Komputer) JURNAL TEKNOLOGI DAN OPEN SOURCE Jurnal Manajemen Informasi Kesehatan Indonesia (JMIKI) Building of Informatics, Technology and Science GUYUB: Journal of Community Engagement Jurnal Teknologi Informasi Cyberku COREAI: Jurnal Kecerdasan Buatan, Komputasi dan Teknologi Informasi Nusantara Journal of Computers and its Applications JAR'S (Journal of Advanced Research in Informatics) Babakti : Journal of Community Engangement JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Fathorazi Nur Fajri
Universitas Nurul Jadid
Religion 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 Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Public Health Social Sciences Transportation Other

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Digital Fish Image Segmentation Using U-Net for Shape Feature Extraction Fathorazi Nur Fajri; Mohammad Dzikrillah; Ahmad Khairi
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 7 No. 2 (2024): Jurnal Teknologi dan Open Source, December 2024
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v7i2.3968

Abstract

Segmentation of digital images of fish is an important challenge in image processing in the field of marine biology and aquaculture. Extraction of fish shape features through image segmentation can improve accuracy in species identification and fish population monitoring. The U-Net method, which is based on deep learning, has been proven effective in medical image segmentation and is beginning to be applied in fish image segmentation. This study aims to develop a fish digital image segmentation method using U-Net architecture for accurate and efficient fish shape feature extraction. The dataset used consists of 500 fish images of various shapes and sizes collected from various sources. The fish images were processed using a U-Net artificial neural network, which was trained and tested to obtain the best segmentation results, with evaluation using Intersection over Union (IoU). The segmentation results show that the U-Net method can produce precise segmentation, with a high degree of accuracy in extracting fish shape features. Evaluation of the segmentation metrics resulted in an IoU value of 0.88, indicating excellent performance in distinguishing the fish object from the background and accurately mapping the fish shape. The fish digital image segmentation method using U-Net is effective for fish shape feature extraction and can be applied in fish species identification and aquatic ecosystem monitoring.
DEVELOPMENT OF VT-UNUJA APPLICATION AS A WEBVR-BASED CAMPUS ENVIRONMENT INTRODUCTION MEDIA Miftahul Huda; Fathorazi Nur Fajri; Maulidiansyah Maulidiansyah
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 10 No. 3 (2025): JITK Issue February 2025
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v10i3.5945

Abstract

Conventional campus introductions are often limited in providing an immersive experience to prospective students, especially for those who cannot attend in person. This encourages the need for technology-based solutions that can overcome these limitations. This research develops a WebVR-based VT-UNUJA application as a campus introduction media that offers an interactive experience with 360-degree panoramic image features, hotspot descriptions, navigation, and voice-over. The purpose of this research is to create an application that can increase user understanding of campus locations and facilities more efficiently and easily accessible. The test results show that this application is effective in improving user understanding, with a high level of satisfaction with the ease of use and interactivity of the application. The benefits of this research are to contribute in improving campus professionalism in presenting information digitally, as well as providing innovative alternatives for other educational institutions in supporting the orientation process for prospective students.
Penerapan Machine Learning untuk Penentuan Mata kuliah Pilihan pada Program Studi Informatika Fathorazi Nur Fajri; Abu Tholib; Wiwin Yuliana
Jurnal Teknik Informatika dan Sistem Informasi Vol 8 No 3 (2022): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v8i3.3990

Abstract

Informatics study program at Nurul Jadid University does not have a general concentration of knowledge, so that sometimes the selection of elective courses by students is not quite right. This study aims to classify the concentration of knowledge with a data mining approach which can then be used as a recommendation for selecting elective courses by students. In this study, we implement a machine learning algorithm to provide recommendations to students regarding what interests are more suitable to be taken based on the values ​​of prerequisite courses in previous semesters. Student data was obtained from the Head of the Center for Data and Information Systems (PDSI) at Nurul Jadid University with 70 student data from Nurul Jadid University batch 2018. The machine learning algorithm used is Neural Network with Python programming language, the tools used are Google Collab. At the beginning of data collection, then pre-processing is carried out to prepare the dataset in order to get good results, and model training is carried out. After training on the model, then further testing is carried out on the model to determine the performance of the model. The result of the accuracy value in the training model process is 0.83 or 83% and the accuracy of the test data is 0.79 or 79%.
Pengembangan Sistem Identifikasi Ancaman Keamanan pada Sistem Penerimaan Mahasiswa Baru dengan Framework Laravel Halimi, Ahmad; Fajri, Fathorazi Nur; Rizal, Fathur
COREAI: Jurnal Kecerdasan Buatan, Komputasi dan Teknologi Informasi Vol 6, No 1 (2025): Kecerdasan Buatan dalam Meningkatkan Efisiensi Bisnis
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/coreai.v6i1.11537

Abstract

Perkembangan transformasi digital yang semakin pesat telah digitalisasi mendorong institusi pendidikan mengadopsi sistem Penerimaan Mahasiswa Baru (PMB) berbasis web. Namun, sistem ini rentan terhadap berbagai serangan siber seperti SQL Injection, XSS, dan bot attack. Penelitian ini bertujuan mengembangkan keamanan berbasis Laravel yang mampu mendeteksi dan menangkal ancaman tersebut secara otomatis. Metode yang digunakan adalah Research and Development (R&D), melalui tahap studi pendahuluan, perancangan, pengembangan, pengujian, dan evaluasi. Middleware yang dikembangkan memiliki fitur validasi input, deteksi pola serangan berbasis regex, pembatasan permintaan, logging aktivitas, serta geo-tracking. Hasil pengujian menunjukkan middleware mampu mendeteksi dan memblokir seluruh simulasi serangan dengan tingkat keberhasilan 100%, tanpa menurunkan performa sistem secara signifikan. Evaluasi pengguna juga menunjukkan peningkatan kepercayaan terhadap sistem PMB yang lebih aman dan tangguh. Penelitian ini membuktikan bahwa integrasi keamanan berbasis dapat menjadi solusi efektif untuk melindungi aplikasi web akademik dari ancaman siber.
Edukasi Cyber untuk Peningkatan Literasi Digital: Menuju Desa Smart People Fajri, Fathorazi Nur; Moh. Dzikrillah; Ahmad Khairi
Babakti: Journal of Community Engangement Vol. 2 No. 1 (2025): April
Publisher : Universitas Singaperbangsa Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35706/babakti.v2i1.67

Abstract

Kegiatan Pengabdian kepada Masyarakat (PKM) di Desa Karanganyar bertujuan meningkatkan literasi digital masyarakat, khususnya dalam penggunaan media sosial yang bijak dan bertanggung jawab. Program ini penting karena tingginya penggunaan media sosial belum diimbangi pemahaman tentang keamanan, etika, dan dampak negatif seperti hoaks dan cyberbullying. Edukasi ini dirancang untuk mewujudkan Desa Karanganyar sebagai "Desa Smart People" yang adaptif terhadap perkembangan teknologi. Analisis situasi menunjukkan rendahnya literasi digital dan minimnya edukasi formal di desa tersebut. Untuk mengatasi tantangan ini, diterapkan metode berupa ceramah, diskusi interaktif, simulasi praktis, serta pendampingan pasca-program. Keberhasilan kegiatan ini didukung oleh partisipasi aktif pemerintah desa dan tokoh masyarakat. Hasil program menunjukkan peningkatan signifikan dalam pemahaman peserta terkait literasi digital, bahaya hoaks, dan pentingnya menjaga privasi. Perubahan perilaku masyarakat terlihat dalam sikap yang lebih selektif terhadap informasi yang disebarkan. Program ini juga mendorong pemanfaatan media sosial untuk promosi produk lokal dan pariwisata desa. Secara keseluruhan, program ini meletakkan dasar transformasi digital di Desa Karanganyar dan dapat direplikasi untuk membangun masyarakat yang cerdas teknologi di desa lain.
Co-Authors Abd Rahman Abdur Rohman Sholeh Abu Tholib Afiqur Rahman Agung Maulana Agung Wahyu Firdaus Ahmad Khairi Ahmad Khairi Arie Wahyudi Arifah, Indah Inayatul Azizi, Moh. Rusli Dewi Sholehatin Diyah Ayu Aprilingga Fadli Hidayat, M. Noer Fajrullah Fajrullah Gulpi Qorik Oktagalu Pratamasunu Habibah Habibah Hadiyanto, Ridwan Halimatus Sa'diya Halimi, Ahmad Hasbul Bahar Ibadi, Suhdil Indri Ratna Sugianti Jasri, Moh. Kamil Malik Khairi, Ahmad Khoirun Nisa' Matbulul Khairi Maulana, Agung Maulidiansyah Maulidiansyah Miftahul Huda Milzamah Elvi Laily Moh. Budi Utomo Setiawan Moh. Dzikrillah Mohammad Dzikrillah Muafi Muafi Muhammad Fadil Hasan Muhammad Roziqin Musfiroh Musfiroh Nadiyatus Sholihah Nurul Hidayattun Nasyihin Priambodo, Wahyu Galih Puji Kurnia Sari Purwanto Purwanto Purwanto, Zendi Ari Ricardus Anggi Pramunendar Rizal, Fathur Shodiq, Wali Jafar Siti Aisyah Suci Rahayu Agustini Suhdil Ibadi Syaiful . Syaiful Syaiful Uky Oktavia Risti Permatasari Uswatun Hasanah Wahab Sya’roni Wali Ja’far Shudiq Warda, Faridatul Wiwin Yuliana Yaqin, Moh. Ainol Yuliana, Wiwin Zainal Arifin Zainal Arifin