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All Journal Jurnal Belantara Journal of Tropical Marine Science Journal of People, Forest And Environment
Rudi Hilmanto
Jurusan Kehutanan, Fakultas Pertanian, Universitas Lampung
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Earth & Planetary Sciences Education Environmental Science

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Komposisi Vegetasi Mangrove Di Pulau Pahawang, Provinsi Lampung Annisa Putri Nabila; Indra Gumay Febryano; Rahmat Safe’i; Rudi Hilmanto
Journal of Tropical Marine Science Vol 5 No 2 (2022): Journal of Tropical Marine Science
Publisher : Universitas Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (262.101 KB) | DOI: 10.33019/jour.trop.mar.sci.v5i2.3272

Abstract

The composition of mangrove vegetation on small islands is very important related to its sustainability. The purpose of this study was to determine the composition of mangrove vegetation on Pahawang Island, Lampung Province. Data collection was carried out based on the Forest Health Monitoring (FHM) technique on the mangrove FHM plot cluster. Data analysis by calculating relative frequency, relative dominance, and relative density to get the Important Value Index (INP). The results showed that three species were found that compose the composition of mangrove forest vegetation, namely Rhizophora mucronata, Rhizophora stylosa, and Rhizophora apiculata. The INP values of each species were Rhizophora mucronata of 160,83%, Rhizophora stylosa of 71,54%, and Rhizophora apiculata of 67,64%. In general, the type of Rhizophora mucronata has a wide distribution and has an impact on forest stability. Therefore, Rhizophora mucronata plays an important role as a plant that is resistant to ocean currents due to coastal land erosion, where various marine biota live, absorbs carbon dioxide gas (CO2) and produces oxygen (O2) in that location. The government is expected to carry out mangrove protection activities, so that the function of the mangroves is maintained properly.
FAKTOR-FAKTOR YANG MENDORONG MASYARAKAT DESA LABUHAN RATU VII IKUT SERTA DALAM KEMITRAAN KONSERVASI DI TAMAN NASIONAL WAY KAMBAS Intan Maharani Safitri; Susni Herwanti; Indra Gumay Febryano; Rudi Hilmanto; Kuswandono Kuswandono; Rusdianto Rusdianto
Jurnal Belantara Vol 6 No 2 (2023)
Publisher : Forestry Study Program University Of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jbl.v6i2.895

Abstract

One of the alternative solution to resolve conflict between communities and conservation area managers is conservation partnership scheme.  This study aims to explain the factors that encourage communities to participate in conservation partnership programs in villages around the national park.  This study uses a qualitative approach, where data collection is carried out by in-depth interviews, observations, and documentation studies.  The collected data is then analyzed to see the factors that encourage communities to participate in conservation partnerships.  This study indicates that there are several factors that encourage the community to participate in the program.  The first factor is public awareness on the importance of forests, which sparks the will to conserve and protect them.  Other factors that the community can obtain are: increased income, permanent jobs, access to assistance and funding from third parties.  The community is greatly assisted in terms of the economy after participating in the conservation partnership program activities. Illegal activities, and land fires have been significantly reduced in the Way Kambas National Park area.  This shows that the Conservation Partnership in Labuhan Ratu VII Village is starting to succeed, therefore this program can be implemented in other villages.  Way Kambas National Park managers should carry out ongoing mentoring and consultation activities in every village around the national park, so that more people will join the conservation partnership program.
IDENTIFIKASI TUTUPAN LAHAN TERBUKA HIJAU DI KOTA MADYA BANDAR LAMPUNG MENGGUNAKAN ALGORITMA MACHINE LEARNING MODEL GAUSSIAN MIXTURE MODEL (GMM) Muhammad Rofi; Trio Santoso; Rudi Hilmanto; Gunardi Djoko Winarno
Journal of People, Forest and Environment Vol. 5 No. 1 (2025): Mei
Publisher : University of Lampung

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

Abstract

Pertumbuhan kota yang pesat di Kota Madya Bandar Lampung mendorong kebutuhan akan pemantauan dan pengelolaan lahan terbuka hijau (RTH) secara efektif. RTH memiliki peran vital dalam menjaga keseimbangan ekosistem dan kualitas lingkungan perkotaan. Penelitian ini bertujuan untuk mengidentifikasi tutupan lahan terbuka hijau menggunakan pendekatan machine learning dengan algoritma Gaussian Mixture Model (GMM). Data citra satelit resolusi menengah digunakan sebagai basis pengolahan spasial, yang kemudian diproses melalui tahapan pra-pemrosesan seperti koreksi geometrik dan peningkatan citra. GMM diterapkan untuk melakukan klasifikasi tak terawasi terhadap jenis tutupan lahan berdasarkan spektrum nilai piksel. Hasil analisis menunjukkan bahwa algoritma GMM mampu memetakan area RTH dengan akurasi yang cukup tinggi, dan memberikan informasi spasial yang mendukung perencanaan kota berkelanjutan. Studi ini menegaskan potensi penggunaan metode machine learning dalam pemetaan tutupan lahan secara efisien dan adaptif di wilayah urban.
PENGGUNAAN BERBAGAI INDEKS VEGETASI UNTUK PENGENALAN CEPAT DAN AKURAT PERUBAHAN TUTUPAN LAHAN MANGROVE DI KECAMATAN LABUHAN MARINGGAI KABUPATEN LAMPUNG TIMUR Muhammad Agung Permana; Rudi Hilmanto; Trio Santoso; Indriyanto Indriyanto
Journal of People, Forest and Environment Vol. 5 No. 1 (2025): Mei
Publisher : University of Lampung

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

Abstract

Ekosistem mangrove memiliki fungsi ekologis yang penting, antara lain sebagai penahan abrasi, habitat biota perairan, penyerap karbon, serta penunjang ekonomi masyarakat pesisir. Namun kawasan mangrove di Kecamatan Labuhan Maringgai mengalami degradasi serius akibat konversi lahan, abrasi pantai, dan tekanan aktivitas masyarakat pesisir yang tidak terkendali. Pemantauan kondisi mangrove dapat dilakukan dengan memanfaatkan teknologi penginderaan jauh. Penelitian ini bertujuan untuk membandingkan kinerja indeks vegetasi NDVI, GNDVI, dan SAVI dalam mendeteksi kerapatan tutupan lahan mangrove secara cepat dan akurat, serta melakukan reklasifikasi dan estimasi perubahan luas tutupan mangrove periode 2013–2025. Penelitian ini dilakukan pada bulan Februari 2025 di Kecamatan Labuhan Maringgai, Kabupaten Lampung Timur, Lampung. Metode yang digunakan meliputi analisis citra satelit Landsat 8 dengan pengolahan NDVI, GNDVI, dan SAVI, dilengkapi validasi lapangan melalui Ground Truth Point (GTP). Hasil penelitian menunjukkan bahwa NDVI dengan model regresi cubic memiliki akurasi tertinggi dalam mendeteksi kerapatan mangrove dengan nilai R² sebesar 0,978 dan F sebesar 237,969. Sementara itu, GNDVI dan SAVI lebih efisien menggunakan model linear karena sederhana namun stabil. Reklasifikasi peta indeks vegetasi menunjukkan bahwa tutupan mangrove di Kabupaten Lampung Timur mengalami dinamika yang fluktuatif, dengan peningkatan pada tahun 2015–2017 namun penurunan drastis sejak 2019 hingga mencapai titik terendah pada 2025 akibat tekanan antropogenik dan abrasi pantai.
Co-Authors Annisa Putri Nabila Gunardi Djoko Winarno Indra Gumay Febryano Indra Gumay Febryano Indriyanto Indriyanto Intan Maharani Safitri Kuswandono Kuswandono Muhammad Agung Permana Muhammad Rofi Rahmat Safe'i Rusdianto Rusdianto Santoso, Trio Susni Herwanti