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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer Depik Jurnal Ilmu-Ilmu Perairan, Pesisir dan Perikanan Depik Jurnal Ilmu-Ilmu Perairan, Pesisir, dan Perikanan
Kris Handoko
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Computer Science & IT Earth & Planetary Sciences Education Engineering

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Monitoring the endemic ornamental fish Pterapogon kauderni in Bokan Kepulauan, Banggai marine protected area, Indonesia Samliok Ndobe; Kris Handoko; Deddy Wahyudi; Moh. Yasir; Yulina Irawati; Wendy Alexander Tanod; Abigail Mary Moore
Depik Vol 9, No 1 (2020): April 2020
Publisher : Faculty of Marine and Fisheries, Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (880.877 KB) | DOI: 10.13170/depik.9.1.15363

Abstract

Abstract. The Banggai cardinalfish Pterapogon kauderni is a species of national and international conservation concern. Established in November 2019, the Banggai marine protected area (MPA) in Central Sulawesi, Indonesia covers most of the endemic range of this ornamental fish. The third repeat survey (T2 monitoring) under the National Action Plan for Banggai Cardinalfish Conservation (NAP-BCFC) was carried out in October 2019 at eight sites in the Bokan Kepulauan region within the MPA. The T2 monitoring used the standard NAP-BCFC belt transect method. Data were collected on P. kauderni abundance (by size class: recruits, juveniles, adults) and microhabitat (sea urchins, sea anemones, hard corals, and others). Data were evaluated with respect to the T0 (2017) survey and T1 (2018) monitoring at the same sites, as well as previous surveys in 2004 (2 sites) and 2012 (4 sites). The data show wide between-site variation in P. kauderni and microhabitat parameters, with one subpopulation at very high risk of extirpation. Trends included declines over time in P. kauderni, sea urchin and sea anemone abundance, with an increase since 2017 in hard coral microhabitat use by adult P. kauderni. We recommend evaluation of other P. kauderni populations in Bokan Kepulauan and specific site or zone-based actions. However, we conclude that the most urgent priority for P. kauderni conservation in Bokan Kepulauan is protection of key microhabitat through a moratorium on sea urchin and sea anemone collection in P. kauderni habitat.  Keywords: Banggai cardinalfish, endangered species, marine conservation, microhabitat, monitoring, ornamental fishery, CITES
Monitoring the endemic ornamental fish Pterapogon kauderni in Bokan Kepulauan, Banggai marine protected area, Indonesia Samliok Ndobe; Kris Handoko; Deddy Wahyudi; Moh. Yasir; Yulina Irawati; Wendy Alexander Tanod; Abigail Mary Moore
Depik Vol 9, No 1 (2020): April 2020
Publisher : Faculty of Marine and Fisheries, Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13170/depik.9.1.15363

Abstract

Abstract. The Banggai cardinalfish Pterapogon kauderni is a species of national and international conservation concern. Established in November 2019, the Banggai marine protected area (MPA) in Central Sulawesi, Indonesia covers most of the endemic range of this ornamental fish. The third repeat survey (T2 monitoring) under the National Action Plan for Banggai Cardinalfish Conservation (NAP-BCFC) was carried out in October 2019 at eight sites in the Bokan Kepulauan region within the MPA. The T2 monitoring used the standard NAP-BCFC belt transect method. Data were collected on P. kauderni abundance (by size class: recruits, juveniles, adults) and microhabitat (sea urchins, sea anemones, hard corals, and others). Data were evaluated with respect to the T0 (2017) survey and T1 (2018) monitoring at the same sites, as well as previous surveys in 2004 (2 sites) and 2012 (4 sites). The data show wide between-site variation in P. kauderni and microhabitat parameters, with one subpopulation at very high risk of extirpation. Trends included declines over time in P. kauderni, sea urchin and sea anemone abundance, with an increase since 2017 in hard coral microhabitat use by adult P. kauderni. We recommend evaluation of other P. kauderni populations in Bokan Kepulauan and specific site or zone-based actions. However, we conclude that the most urgent priority for P. kauderni conservation in Bokan Kepulauan is protection of key microhabitat through a moratorium on sea urchin and sea anemone collection in P. kauderni habitat.  Keywords: Banggai cardinalfish, endangered species, marine conservation, microhabitat, monitoring, ornamental fishery, CITES
Monitoring the endemic ornamental fish Pterapogon kauderni in Bokan Kepulauan, Banggai marine protected area, Indonesia Samliok Ndobe; Kris Handoko; Deddy Wahyudi; Moh. Yasir; Yulina Irawati; Wendy Alexander Tanod; Abigail Mary Moore
Depik Vol 9, No 1 (2020): April 2020
Publisher : Faculty of Marine and Fisheries, Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13170/depik.9.1.15363

Abstract

Abstract. The Banggai cardinalfish Pterapogon kauderni is a species of national and international conservation concern. Established in November 2019, the Banggai marine protected area (MPA) in Central Sulawesi, Indonesia covers most of the endemic range of this ornamental fish. The third repeat survey (T2 monitoring) under the National Action Plan for Banggai Cardinalfish Conservation (NAP-BCFC) was carried out in October 2019 at eight sites in the Bokan Kepulauan region within the MPA. The T2 monitoring used the standard NAP-BCFC belt transect method. Data were collected on P. kauderni abundance (by size class: recruits, juveniles, adults) and microhabitat (sea urchins, sea anemones, hard corals, and others). Data were evaluated with respect to the T0 (2017) survey and T1 (2018) monitoring at the same sites, as well as previous surveys in 2004 (2 sites) and 2012 (4 sites). The data show wide between-site variation in P. kauderni and microhabitat parameters, with one subpopulation at very high risk of extirpation. Trends included declines over time in P. kauderni, sea urchin and sea anemone abundance, with an increase since 2017 in hard coral microhabitat use by adult P. kauderni. We recommend evaluation of other P. kauderni populations in Bokan Kepulauan and specific site or zone-based actions. However, we conclude that the most urgent priority for P. kauderni conservation in Bokan Kepulauan is protection of key microhabitat through a moratorium on sea urchin and sea anemone collection in P. kauderni habitat.  Keywords: Banggai cardinalfish, endangered species, marine conservation, microhabitat, monitoring, ornamental fishery, CITES
Implemantasi Mask R-CNN pada Perhitungan Tinggi dan Lebar Karang untuk Memantau Pertumbuhan Transplantasi Karang Alkhalis, Naufal; Husaini, Husaini; Haekal Azief Haridhi; Maretna, Cut Nadilla; Nur Fadli; Haditiar, Yudi; Nanda, Muhammad; Ulfah, Maria; Kris Handoko; Intan Malayana; Arsa Cindy Safitri
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 11 No 3: Juni 2024
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.938374

Abstract

Indonesia merupakan negara kepulauan dengan terumbu karang yang tinggi dan keanekaragaman hayati laut yang kompleks. Namun, setidaknya 45% dari terumbu karang di Indonesia dalam kondisi terancam disebabkan oleh beberapa faktor seperti ulah manusia, perubahan iklim, lingkungan sekitar, lambatnya laju pertumbuhan dan lain sebagainya. Transplantasi karang telah menjadi salah satu pendekatan yang dilakukan untuk konservasi. Penelitian ini mengimplementasikan algoritma Mask Region-based Convolutional Neural Network (Mask R-CNN) dengan Pustaka Detectron2 dalam deteksi dan segmentasi objek untuk menghitung tinggi dan lebar karang transplantasi melalui citra. Metode penelitian melibatkan pengumpulan dataset, pembagian dataset, anotasi dataset, implementasi model, evaluasi model, dan mengitung laju pertumbuhan karang. Implementasi model melibatkan 7 backbone segmentasi instance dengan jadwal laju pembelajaran sebesar 3 kali. Hasil penelitian menunjukkan bahwa dari ketujuh backbone yang diuji X101-FPN dan R101-DC5 menghasilkan presisi dan recall yang lebih baik. Selisih Average Presision (AP) antara kedua model terbaik tersebut untuk segmentasi mask pada Intersection over Union (IoU) maksimum sebesar 2,2% sedangkan untuk deteksi box sebesar 5,8%. Sedangkan selisih Average Recall (AR) untuk segmentasi mask sebesar 8,3% dan deteksi box sebesar 5,2%. Hasil segmentasi X101-FPN dipilih untuk mengukur tinggi dan lebar karang yang telah di transplantasi, sehingga dapat digunakan untuk memantau laju pertumbuhan dari transplantasi karang.
Implementasi Mask R-Cnn Pada Perhitungan Persentase Tutupan Karang Untuk Memantau Ekosistem Terumbu Karang Maretna, Cut Nadilla; Husaini; Haridhi, Haekal Azief; Alkhalis, Naufal; Nur Fadli; Haditiar, Yudi; Nanda, Muhammad; Ulfah, Maria; Kris Handoko; Intan Malayana; Arsa Cindy Safitri
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 12 No 4: Agustus 2025
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.124

Abstract

Terumbu karang memiliki peranan penting bagi kehidupan di laut. Namun, ekosistem terumbu karang sangat rentan mengalami kerusakan karena sejumlah faktor seperti aktivitas manusia, perubahan iklim, lambatnya laju pertumbuhan dan sebagainya. Upaya pelestarian terumbu karang telah dilakukan, namun pemantauan masih minim. Oleh karena itu, pemantauan ekosistem terumbu karang perlu ditingkatkan untuk mengetahui kondisi terumbu karang sebenarnya. Persentase tutupan karang adalah indikator yang perlu diketahui sebagai penentuan tingkat kehidupan terumbu karang. Proses pemantauan terumbu karang saat ini masih dilakukan secara konvensional, sehingga proses pemantauan tidak efisien dan perolehan informasi mengenai persentase tutupan karang membutuhkan waktu yang panjang. Penelitian ini mengimplementasikan algoritma Mask Region Convolutional Neural Network (Mask R-CNN) pada library Detectron2 untuk melakukan deteksi dan segmentasi objek tutupan karang pada ekosistem terumbu karang dengan menggunakan citra terumbu karang sebagai input. Model yang digunakan untuk segmentasi instance pada citra terumbu karang ini dilatih dengan menggunakan backbone Residual Network (ResNet) dan Residual Networks Next (ResNeXt) yang terdapat pada library Detectron2. Model backbone dievaluasi berdasarkan matriks presisi dan recall. Hasil penelitian menunjukkan ResNeXt101-FPN merupakan backbone terbaik dalam menghasilkan segmentasi. Hasil proses segmentasi tersebut kemudian digunakan untuk menghitung persentase tutupan karang. Berdasarkan hasil perhitungan, persentase tutupan karang dengan data yang diuji adalah sebesar 86,06%. Dengan demikian, proses perhitungan persentase tutupan karang untuk memantau ekosistem terumbu karang dapat dilakukan dengan efisien dan informasi mengenai persentase tutupan karang dapat diperoleh dalam waktu yang singkat.   Abstract Coral reefs have an important role for life in the sea. However, coral reef ecosystems are very vulnerable to damage due to a number of factors such as human activities, climate change, slow growth rates and so on. Efforts to preserve coral reefs have been made, but monitoring remains minimal. Therefore, coral reef ecosystem monitoring needs to be enhanced to assess their actual condition. The percentage of coral cover is an indicator that needs to be known as a determination of the life rate of coral reefs. The current coral reef monitoring process is still carried out conventionally, so the monitoring process is inefficient and obtaining information about the percentage of coral cover takes a long time. This study implements the Mask Region Convolutional Neural Network (Mask R-CNN) algorithm in the Detectron2 library to detect and segment coral cover objects in coral reef ecosystems using coral reef images as input. The model used for instance segmentation on coral reef images was trained using the Residual Network (ResNet) and Residual Networks Next (ResNeXt) backbones, which are available in the Detectron2 library. The backbone model is evaluated based on precision and recall matrices. The results show that ResNeXt101-FPN is the best backbone in producing segmentation. The results of the segmentation process are then used to calculate the percentage of coral cover. Based on the calculation results, the percentage of coral cover with the tested data was 86.06%. Thus, the process of calculating the coral cover percentage to monitor coral reef ecosystems can be carried out efficiently and information about the coral cover percentage can be obtained in a short time.
Co-Authors Abigail Mary Moore Alkhalis, Naufal Arsa Cindy Safitri Deddy Wahyudi Haditiar, Yudi Haekal Azief Haridhi Haridhi, Haekal Azief Husaini Husaini Husaini Intan Malayana Maretna, Cut Nadilla Maria Ulfah Moh. Yasir Nanda, Muhammad Nur Fadli Samliok Ndobe Wendy Alexander Tanod Yudi Haditiar Yulina Irawati