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All Journal Jurnal Perikanan dan Kelautan Journal of Environmental Engineering and Sustainable Technology Forum Geografi JFMR (Journal of Fisheries and Marine Research) Environmental Pollution Journal Abdi Geomedisains Jurnal Perikanan dan Kelautan
Seftiawan Samsu Rijal, Seftiawan Samsu
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Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemistry Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Energy Engineering Environmental Science Immunology & microbiology Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mechanical Engineering Medicine & Pharmacology Nursing Physics Social Sciences

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Comparison of Land Surface Temperature During and Before the Emergence of Covid-19 using Modis Imagery in Wuhan City, China Hadibasyir, Hamim Zaky; Rijal, Seftiawan Samsu; Sari, Dewi Ratna
Forum Geografi Vol 34, No 1 (2020): July 2020
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v34i1.10862

Abstract

Coronavirus disease (COVID-19) was firstly identified in Wuhan, China. By 23rd January 2020, China’s Government made a decision to execute lockdown policy in Wuhan due to the rapid transmission of COVID-19. It is essential to investigate the land surface temperature (LST) dynamics due to changes in level of anthropogenic activities. Therefore, this study aims (1) to investigate mean LST differences between during, i.e., December 2019 to early March 2020, and before the emergence of COVID-19 in Wuhan; (2) to conduct spatio-temporal analysis of mean LST with regards to lockdown policy; and (3) to examine mean LST differences for each land cover type. MODIS data consist of MOD11A2 and MCD12Q1 were employed. The results showed that during the emergence of COVID-19 with lockdown policy applied, the mean LST was lower than the mean LST of the past three years on the same dates. Whereas, during the emergence of COVID-19 without lockdown policy applied, the mean LST was relatively higher than the mean LST of the past three years. In addition, the mean LST of built-up areas experienced the most significant differences between during the emergence of COVID-19 with lockdown policy applied in comparison to the average of the past three years.
Perbandingan Kualitas Air Menggunakan Parameter Macroinvertebrates dan Plankton pada Industri Penyedap Rasa Korea dan Jepang Ardiansyah, Fernando; Rijal, Seftiawan Samsu
Environmental Pollution Journal Vol. 3 No. 1: April 2023
Publisher : ECOTON: Ecological Observation and Wetlands Conservation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58954/epj.v3i1.115

Abstract

Sungai merupakan salah satu wilayah yang harus dijaga kelestariannya, oleh karena itu, penelitian ini bertujuan untuk mendapatkan data tentang kualitas air sungai di outlet pembuangan limbah pabrik penyedap mekanan dari korea dan jepang. Hasilnya akan menjadi perbandingan tentang siapa yang lebih mencemari lingkungan. Sampel yang diambil berupa plankton dan Makroinvertebrata (Indeks Kualitas Air) dengan metode pengambilan sampel purposive judgement sampling. Sampel diambil dengan menggunakan plankton net dan jaring biotilik. Air disaring sebanyak 15 liter yang dibagi masing-masing kedalam 3x pengulangan di setiap outlet pabrik penyedap rasa. Hasilnya adalah IKA pada PT Daesang Ingredients yaitu 1.68, PT Ajinomoto 2.25 dan PT Cheiljedang 1.75. Hal ini berbanding terbalik dengan keragaman plankton yang bernilai 2.466 pada PT Daesang Ingredients, 2.1 pada PT Ajinomoto, dan 2.233 pada PT Cheiljedang. Hal ini dikarenakan pada daerah yang tercemar ditemukan beberapa plankton yang mengindikasikan lokasi tersebut sedang tercemar. Kehadiran plankton tersebut dapat membuktikan adanya kontaminasi logam berat dan polutan lain. Plankton tersebut memiliki resistensi yang tinggi terhadap lingkungan teremar.
Study of Coral Reef Distribution in Pejarakan Waters, Bali Using Sentinel-2A Imagery Semedi, Bambang; Rijal, Seftiawan Samsu; Arviani, Dhika Anggi
Jurnal Perikanan dan Kelautan Vol 29, No 1 (2024): February
Publisher : Faculty of Fisheries and Marine, Universitas Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/jpk.29.1.118-124

Abstract

The existence of coral reef ecosystems in Indonesia is a potential marine resource that needs to be preserved due to the many benefits of the coral reef ecosystem. Utilization of Sentinel-2A imagery for coral reef mapping can be done using two approaches, namely pixel-based and object-based. In this study, pixel-based classification and object-based classification are used to determine the dynamics of the distribution of coral reefs in the waters of Pejarakan Village, Bali, during the dry and rainy seasons. The data used are Sentinel-2A image data for 2018, 2020, and 2022 and field data used for the research accuracy test process. Field data was collected using the purposive sampling method, and the accuracy test process was carried out using the confusion matrix method. The data processing results using pixel and object classification show that classification using the object classification method is considered more accurate than pixel classification because it produces an accuracy value of up to 69.4%. Meanwhile, the pixel classification accuracy value is only 61.1%.
SURVEY BOAT PROTOTYPE DESIGN FOR REMOTE AREA Furqon, Muhammad Tanzil; Kadhafi, Muammar; Sunardi, Sunardi; Rijal, Seftiawan Samsu; Tsani, Muhammad Dafa'anh Murya
Journal of Environmental Engineering and Sustainable Technology Vol 8, No 1 (2021)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jeest.2021.008.01.3

Abstract

The water survey activities in remote areas have many challenges, such as cost, transportation to location, access to the location, boat for water survey, manpower, and other factors. This research proposes the method of water survey to overcome the difficulties encountered in surveying in remote areas. The mini boat prototype was designed and fabricated by using a control system to operate in the water. The propulsion power prediction was carried out, by comparison, the similarity to the fullscale ships with 9.5 knots of velocity. Furthermore, the wave-making resistance was simulated by software and confirmed by the trial. The trial has shown that the boat was going well on the water and the measurement equipment in a safe condition. 
Pelatihan Pertolongan Pertama Bagi Nelayan di Pantai Kondang Merak, Kabupaten Malang Setyawan, Fahreza Okta; Aliviyanti, Dian; Yamindago, Ade; Yona, Defri; Fuad, Muhammad Arif Zainul; Isdianto, Andik; Rijal, Seftiawan Samsu; Guntur
Abdi Geomedisains Vol. 4, No. 2, January 2024
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/abdigeomedisains.v4i1.1560

Abstract

Kondang Merak Beach has several community groups that inhabit and manage the beach. One of the local community groups is Bina Karya Mina fishing group. Apart from fishing, which was their main livelihood, this group of fishermen was also proficient in diving and snorkeling. However, due to the lack of training in diving for the fishermen, the diving equipment that is there is not properly utilized. Knowledge about first aid for diving accident victims is also needed not only when a fishermen’s diving accident occurs but can also be used to help tourists when an accident occurs while snorkeling or swimming at the beach. This community service activity aimed to increase the knowledge and skills of the Bina Karya Mina fishing group in terms of diving, especially first aid for accident victims at Kondang Merak Beach, Malang Regency. This activity was divided into three stages of activity, namely the preparation, implementation, evaluation, and reporting stages. The implementation stage of this community service activity was carried out in a hybrid manner, namely socialization material was given online, while practical activities and handover of first aid assistance are carried out offline. Through this activity, it was expected to improve the ability of fishermen in the field of diving. In addition, socialization about first aid kits as supporting equipment to help accident victims was carried out as well so that they could increase the preparedness of fishermen on Kondang Merak Beach in case of an emergency.
Study of Coral Reef Distribution in Pejarakan Waters, Bali Using Sentinel-2A Imagery Semedi, Bambang; Rijal, Seftiawan Samsu; Arviani, Dhika Anggi
Jurnal Perikanan dan Kelautan Vol. 29 No. 1 (2024): February
Publisher : Faculty of Fisheries and Marine, Universitas Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/jpk.29.1.118-124

Abstract

The existence of coral reef ecosystems in Indonesia is a potential marine resource that needs to be preserved due to the many benefits of the coral reef ecosystem. Utilization of Sentinel-2A imagery for coral reef mapping can be done using two approaches, namely pixel-based and object-based. In this study, pixel-based classification and object-based classification are used to determine the dynamics of the distribution of coral reefs in the waters of Pejarakan Village, Bali, during the dry and rainy seasons. The data used are Sentinel-2A image data for 2018, 2020, and 2022 and field data used for the research accuracy test process. Field data was collected using the purposive sampling method, and the accuracy test process was carried out using the confusion matrix method. The data processing results using pixel and object classification show that classification using the object classification method is considered more accurate than pixel classification because it produces an accuracy value of up to 69.4%. Meanwhile, the pixel classification accuracy value is only 61.1%.
Study of Coral Reef Distribution in Pejarakan Waters, Bali Using Sentinel-2A Imagery Semedi, Bambang; Rijal, Seftiawan Samsu; Arviani, Dhika Anggi
Jurnal Perikanan dan Kelautan Vol. 29 No. 1 (2024): February
Publisher : Fakultas Perikanan dan Kelautan Universitas Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/

Abstract

The existence of coral reef ecosystems in Indonesia is a potential marine resource that needs to be preserved due to the many benefits of the coral reef ecosystem. Utilization of Sentinel-2A imagery for coral reef mapping can be done using two approaches, namely pixel-based and object-based. In this study, pixel-based classification and object-based classification are used to determine the dynamics of the distribution of coral reefs in the waters of Pejarakan Village, Bali, during the dry and rainy seasons. The data used are Sentinel-2A image data for 2018, 2020, and 2022 and field data used for the research accuracy test process. Field data was collected using the purposive sampling method, and the accuracy test process was carried out using the confusion matrix method. The data processing results using pixel and object classification show that classification using the object classification method is considered more accurate than pixel classification because it produces an accuracy value of up to 69.4%. Meanwhile, the pixel classification accuracy value is only 61.1%.
Analisis Delineasi Garis Pantai dengan Metode Object-Based Image Analysis di Kabupaten Malang Menggunakan Citra Satelit Planetscope: Analysis of Shoreline Delineation Using Object-Based Image Analysis Method in Malang Regency with Planetscope Satellite Imagery Saphira, Shada; Setyawan, Fahreza Okta; Fuad, M. Arif Zainul; Rijal, Seftiawan Samsu
JFMR (Journal of Fisheries and Marine Research) Vol. 9 No. 1 (2025): JFMR on March
Publisher : Faculty of Fisheries and Marine Science, Brawijaya University, Malang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jfmr.2025.009.01.3

Abstract

Salah satu fenomena alam yang rentan terjadi di wilayah pantai adalah perubahan garis pantai, karena sifat pantai yang dinamis, mengakibatkan wilayah pantai selalu mengalami perubahan. Oleh karena itu, delineasi garis pantai penting untuk dilakukan secara berkala agar garis pantai dapat dipantau secara terus menerus untuk mencegah terjadinya abrasi maupun akresi, juga delineasi garis pantai merupakan hal yang esensial dalam pengelolaan wilayah pesisir berkelanjutan. Penelitian ini berfokus pada delineasi garis pantai berdasarkan metode penginderaan jauh menggunakan Citra Satelit Resolusi Tinggi (CSRT) di Kabupaten Malang, dimana perubahan garis pantai terjadi wilayahnya. Delineasi garis pantai dilakukan dengan menggunakan metode integrasi dari model deep learning, Convolutional Neural Network (CNN), dan Object Based Image Analysis (OBIA). Penelitian ini bertujuan untuk mendapatkan dan mengevaluasi garis pantai dari metode yang digunakan. Didapatkan garis pantai hasil metode OBIA Kabupaten Malang di bagian barat 34.49 km, tengah 51.21 km, dan timur 67.81 km. Nilai overall accuracy yang didapatkan sebesar 83.62% di barat, tengah 80.79%, dan timur 85.06%. Jarak antara garis pantai hasil ekstraksi dan tracking dibandingkan dan didapatkan nilai RMSE di barat sebesar 4.91 meter, tengah 6.62 meter, dan timur 3.68 meter. Hasil tersebut membuktikan bahwa integrasi metode CNN dan OBIA berhasil menciptakan garis pantai dengan akurasi yang baik.   One of the natural phenomena commonly occurring in coastal areas is shoreline change, driven by the coast’s dynamic nature, resulting in coastal areas always experiencing changes. Therefore, delineation of the shoreline is important to be carried out periodically so that the shoreline can be monitored continuously to prevent abrasion and accretion, also delineation of the shoreline is essential in the management of sustainable coastal areas. This research focuses on shoreline delineation based on remote sensing method using High Resolution satellite imagery in Malang Regency, where shoreline changes occur. Shoreline delineation is performed using an integrated method of deep learning models, Convolutional Neural Network (CNN), and Object Based Image Analysis (OBIA). This research aims to obtain and evaluate the shoreline of the method used. The shoreline obtained from OBIA method in Malang Regency is 34.49 km in the west, 51.21 km in the central, and 67.81 km in the east. The overall accuracy value achieved in the western part is 83.62%, the central part is 80.79%, and the eastern part is 85.06%. The distance between the extracted and the tracking shoreline was compared and an overall average RMSE value of 4.91 meters in the western part, 6.62 meters in the middle part, and 3.68 meters in the eastern part. These results prove that the integration of CNN and OBIA methods can successfully create shoreline with good accuracy.
Study of Coral Reef Distribution in Pejarakan Waters, Bali Using Sentinel-2A Imagery Semedi, Bambang; Rijal, Seftiawan Samsu; Arviani, Dhika Anggi
Jurnal Perikanan dan Kelautan Vol. 29 No. 1 (2024): February
Publisher : Fakultas Perikanan dan Kelautan Universitas Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/

Abstract

The existence of coral reef ecosystems in Indonesia is a potential marine resource that needs to be preserved due to the many benefits of the coral reef ecosystem. Utilization of Sentinel-2A imagery for coral reef mapping can be done using two approaches, namely pixel-based and object-based. In this study, pixel-based classification and object-based classification are used to determine the dynamics of the distribution of coral reefs in the waters of Pejarakan Village, Bali, during the dry and rainy seasons. The data used are Sentinel-2A image data for 2018, 2020, and 2022 and field data used for the research accuracy test process. Field data was collected using the purposive sampling method, and the accuracy test process was carried out using the confusion matrix method. The data processing results using pixel and object classification show that classification using the object classification method is considered more accurate than pixel classification because it produces an accuracy value of up to 69.4%. Meanwhile, the pixel classification accuracy value is only 61.1%.
PENENTUAN KESESUAIAN LOKASI MARIKULTUR IKAN KERAPU DI SUMATERA UTARA, INDONESIA MENGGUNAKAN GOOGLE EARTH ENGINE Rijal, Seftiawan Samsu; Bayuaji, Gerardus David Ady Purnama
JFMR (Journal of Fisheries and Marine Research) Vol. 5 No. 2 (2021): JFMR
Publisher : Faculty of Fisheries and Marine Science, Brawijaya University, Malang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jfmr.2021.005.02.21

Abstract

Provinsi Sumatera Utara di Indonesia tercatat telah memproduksi komoditas ekspor yang sangat tinggi untuk Ikan Kerapu. Hal ini harus dipertahankan sebagai upaya menjaga keberlangsungan ekonomi perikanan. Salah satu cara mengembangbiakan Ikan Kerapu adalah dengan marin akuakultur (marikultur) yang sangat bergantung pada ekologi lautan seperti keberadaan klorofil-a, Suhu Permukaan Laut (SPL), Muatan Padat Tersuspensi (MPT) dan topografi kedalaman laut (batimetri). Kondisi ekologi lautan yang sangat mudah berubah menghendaki pemantauan secara berkala. Pada penelitian ini, kami memiliki tujuan pertama yaitu mengetahui kemampuan data penginderaan jauh untuk mengekstraksi parameter - parameter yang digunakan untuk kelayakan lokasi marikultur Ikan Kerapu. Kami menggunakan Landsat 8 untuk mengetahui klorofil-a, SPL dan MPT, sedangkan data batimetri didapatkan dari ETOPO1, sebuah data topografi skala global yang memiliki perekaman permukaan lahan (terrain) hingga dasar lautan. Tujuan kami yang kedua adalah mengetahui keakuratan kesesuaian lokasi marikultur yang dihasilkan oleh pemrosesan citra pada GEE. Hasil penelitian dibandingkan dengan peta referensi mengenai lokasi marikultur yang diperoleh dari Lembaga Penerbangan dan Antariksa Nasional (LAPAN) dan menampilkan hasil pengujian matriks akurasi sebesar 80 %. Hal ini membuktikan data penginderaan jauh dapat digunakan untuk membantu menentukan lokasi marikultur Ikan Kerapu dan GEE adalah platform yang sesuai untuk pemantauan secara berkala dengan kemampuan olah citra melalui komputasi awan sekaligus dapat melakukan analisis penjenjangan bertingkat.
Co-Authors Ade Yamindago Aliviyanti, Dian Andik Isdianto Ardiansyah, Fernando Arviani, Dhika Anggi Bambang Semedi Bayuaji, Gerardus David Ady Purnama Defri Yona Dewi Ratna Sari Fuad, M. Arif Zainul Fuad, Muhammad Arif Zainul Guntur Hamim Zaky Hadibasyir Muammar Kadhafi Muhammad Tanzil Furqon, Muhammad Tanzil Saphira, Shada Setyawan, Fahreza Okta Sunardi Sunardi Tsani, Muhammad Dafa'anh Murya