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All Journal Jurnal Ilmu Komputer dan Informasi Jupiter Jurnal Buana Informatika Jurnal Informatika dan Teknik Elektro Terapan Register: Jurnal Ilmiah Teknologi Sistem Informasi SemanTIK : Teknik Informasi Jurnal Teknologi Sistem Informasi dan Aplikasi Jurnal Informatika dan Rekayasa Perangkat Lunak Community Development Journal: Jurnal Pengabdian Masyarakat Community Empowerment Jurnal Sains Teknologi dan Sistem Informasi Jurnal Media Informasi Teknologi Journal of Information Systems and Technology (JISTech) Mekongga: Jurnal Pengabdian Masyarakat Media of Computer Science JROCK (Journal Research on Computing Knowledge)
Yuwanda Purnamasari Pasrun
Universitas Sembilanbelas November Kolaka
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Public Health Social Sciences Other

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Journal : Jurnal Informatika dan Teknik Elektro Terapan

 1 
PENERAPAN METODE NAÏVE BAYES DALAM KLASIFIKASI KESEGARAN IKAN BERDASARKAN WARNA PADA CITRA AREA MATA Mutmainnah Muchtar; Yuwanda Purnamasari Pasrun; Rasmiati Rasyid; Nisa Miftachurohmah; Mardiawati Mardiawati
Jurnal Informatika dan Teknik Elektro Terapan Vol 12, No 1 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i1.3879

Abstract

As a maritime nation, fish is a staple in the Indonesian diet, rich in nutrition and a crucial protein source. It is imperative to maintain the freshness of fish to ensure the quality of fish production. However, the practice of mixing fresh and non-fresh fish poses a serious threat to consumer health and diminishes the overall quality of fish production. Therefore, the development of an automated and efficient method is necessary to distinguish between fresh and non-fresh fish. This research proposes the application of the Naïve Bayes method in classifying fish freshness based on color analysis in the eye area image. This approach involves the extraction of entropy features after segmenting fish images using the RGB and YCbCr color models. A total of 40 datasets of fish eye images were used for training and testing the model. The research results indicate that the proposed classification method achieved an accuracy rate of 97.5%. This success signifies the potential of the color analysis method and entropy features in distinguishing levels of fish freshness. These findings contribute to the development of automated techniques for monitoring and processing fish quality in the fisheries industry.
PERBANDINGAN JARAK EUCLIDEAN, CITYBLOCK, MINKOWSKI, CANBERRA, DAN CHEBYSHEV DALAM SISTEM TEMU KEMBALI CITRA BATIK Muchtar, Mutmainnah; Zainuddin, Noorhasanah; Sajiah, Adha Mashur; Ningsi, Nurfitria; Pasrun, Yuwanda Purnamasari
Jurnal Informatika dan Teknik Elektro Terapan Vol 12, No 3S1 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i3S1.5324

Abstract

Batik is a highly valuable cultural heritage in Indonesia, showcasing a rich diversity of motifs with deep meaning and aesthetics. To enhance the accessibility and utilization of batik collections, an efficient image retrieval system is essential. This study compares distance measurement methods in a batik image retrieval system: Euclidean, Cityblock, Minkowski, Canberra, and Chebyshev, using a combination of color and texture features. The dataset comprises 50 types of batik images. The results show that the Cityblock method achieves the highest Mean Average Precision (MAP) of 97.71, followed by Canberra with MAP 96.87. The Euclidean method also performs well with a MAP of 94.56, while Minkowski and Chebyshev have lower MAP values of 92.93 and 90.89, respectively. Chebyshev experiences the largest MAP drop when images are rotated (5.98), while Cityblock demonstrates the best resistance to rotation with the smallest MAP drop (1.51). This research successfully developed a Content-Based Image Retrieval (CBIR) system with a GUI in MATLAB and suggests integrating the latest image processing and machine learning techniques for further enhancement.
Co-Authors Abdul Malik Aliniy Aliniy Amaliya Nurani Basyarah Andi Tenri Sumpala, Andi Tenri Anjar Pradipta Ariani, Irma Chastine Fatichah Djafar Djafar Eka Novarida Fathur Rahman Rustan Haryati Haryati Hasidu, La Ode Abdul Fajar Ilayani, Ilayani Indar Ismail Jamaluddin Jayanti Yusmah Sari Jayawarsa, A.A. Ketut Jimsan Jimsan Johar Nur Iin Jumadil Nangi, Jumadil La Ode Hasnuddin S. Sagala La Sudarman Mardiawati Mardiawati Maulana, Sahrul Muh Iskandar Z. A Muh Nurtanzis Sutoyo Muh. Ihsan Sarita Muhammad Syaiful Muliyadi Muliyadi Mutmainnah Muchtar Nanik Suciati Nasarudin Nasarudin Natalis Ransi Nirsal Nisa Miftachurohmah Noorhasanah Zainuddin Novi Aulya Nur Fajriah Muchlis Nur Fajriah Muchlis, Nur Fajriah Nurfitria Ningsi Phradiansah ., Phradiansah Rabiah Adawiyah Rabiah Adawiyah, Rabiah Rahmat Karim Rasmiati Rasyid Riska Risnawati Rizal Adi Saputra Sajiah, Adha Mashur Sarimuddin, Sarimuddin Suharsono Bantun Sutardi Sutardi Wa Ode Nur Aisyah Yuandi, Intan Anuggrah