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All Journal Jurnal Silvikultur Tropika (JST) Jurnal Penelitian Hutan Tanaman Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering)
Supriyanto Supriyanto
Institut Pertanian Bogor
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Decision Sciences, Operations Research & Management Earth & Planetary Sciences Energy Engineering Environmental Science Social Sciences

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PENGEMBANGAN METODE PENILAIAN KESEHATAN HUTAN RAKYAT SENGON (Miq.) Barneby & J.W. Grimes) Rahmat Safe'i; Hardjanto Hardjanto; Supriyanto Supriyanto; Leti Sundawati
Jurnal Penelitian Hutan Tanaman Vol 12, No 3 (2015): JURNAL PENELITIAN HUTAN TANAMAN
Publisher : Pusat Penelitian dan Pengembangan Hutan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (934.781 KB) | DOI: 10.20886/jpht.2015.12.3.175-187

Abstract

Kriteria dan indikator, khususnya kesehatan hutan untuk Pengelolaan Hutan Lestari (PHL) baru dikembangkan terhadap hutan alam dan hutan tanaman; sedangkan untuk hutan rakyat belum dikembangkan. Penelitian ini bertujuan untuk mengembangkan metode penilaian kesehatan hutan rakyat sengon ( (Miq.) Falcataria moluccana Barneby & J.W. Grimes) berbasis indikator indikator ekologis kesehatan hutan. Studi kasus ini dilakukan pada klaster plot Forest Health Management (FHM) hutan rakyat monokultur sengon di Wilayah Provinsi Lampung. Hasil penelitian menunjukkan bahwa tingkat kesehatan hutan rakyat sengon dapat dinilai dengan menggunakan metode FHM dengan indikator prioritas adalah produktivitas, kualitas tapak, dan vitalitas. Dalam pengembangan metode penilaian kesehatan hutan rakyat sengon dapat menggunakan nilai tertimbang dan nilai skor darimasingmasing indikator prioritas tersebut.
PENILAIAN KESEHATAN SUMBER BENIH Shorea spp. DI KHDTK HAURBENTES DENGAN METODA FOREST HEALTH MONITORING Kurniawati Purwaka Putri; Supriyanto Supriyanto; Lailan Syaufina
Jurnal Penelitian Hutan Tanaman Vol 13, No 1 (2016): JURNAL PENELITIAN HUTAN TANAMAN
Publisher : Pusat Penelitian dan Pengembangan Hutan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (721.095 KB) | DOI: 10.20886/jpht.2016.13.1.37-48

Abstract

ABSTRACTThe healthy of forest ecosystem is one of the criteria for assessing sustainable forest management (SFM) The healthy stands is also general requirement of seed sources. Forest Health Monitoring (FHM) is an intensive method for monitoring and assessing ecosystem health. The indicators of FHM are site quality, tree vitality, productivity and biodiversity. The research aimed to assess the health status of seed sources stands of Shorea spp. in Forest Area for Special Purposes Haurbentes based on FHM method. The results showed that the site quality was high for CEC, pH was low, the distribution of diameter at breast height were 39.3-66.1 cm, the level of tree damage was low,the crown condition was unhealthy, and the diversity of tree species was low. The health status of Shorea spp. seed source stand in FASPHaurbentes was fair and could appointed as a seed source with identified seed stands level.Keywords:Forest health, seed source, Shorea spp., sustainabilityABSTRAKKesehatan ekosistem hutan adalah salah satu kriteria penilaian pengelolan hutan yang lestari. Kesehatan ekosistem hutan juga menjadi dasar penunjukan sumber benih. Forest Health Monitoring (FHM) adalah metode yang dapat digunakan untuk pemantauan dan penilaian kondisi kesehatan ekosistem secara intensif. Indikator ekologis yang dinilai adalah kualitas tapak, vitalitas pohon, produktivitas dan biodiversitas. Metode penelitian menggunakan proses jaringan analitik. Tujuan penelitian adalah menilai status kesehatan tegakan sumber benih Shorea spp. di KHDTK Haurbentes berdasarkan metode FHM. Hasil penelitian menunjukkan bahwa kualitas tapak berdasarkan nilai kapasitas tukar kation (KTK) tergolong tinggi, pH tanah tergolong rendah, diameter pohon antara 39,3-66,1 cm, tingkat kerusakan pohon termauk rendah, kondisi tajuk tidak sehat dan dan keragaman jenis pohon termasuk kategori rendah. Status kesehatan sumber benih Shorea spp. di KHDTK Haurbentes tergolong sedang dan layak ditunjuk sebagai sumber benih dengan kelas tegakan benih teridentifikasi. Kata kunci:Kelestarian, kesehatan hutan, Shorea spp., sumberbenih
Utilization of Rice-Hush Charcoal to Improve Growth of Jabon Seedlings (Anthocephalus cadamba (Roxb.) Miq) on Subsoil Media. Supriyanto Supriyanto; Fidryaningsih Fiona
Jurnal Silvikultur Tropika Vol. 1 No. 1 (2010): Jurnal Silvikultur Tropika
Publisher : Departemen Silvikultur, Fakultas Kehutanan dan Lingkungan, Institut Pertanian Bogor (IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j-siltrop.1.1.%p

Abstract

Bio-charcoal has been used widely in agriculture and forestry, especially in seedling production. It is not only as a source of fuel energy but the charcoal can also be used as a soil amandment for improving soil properties as an effort to improve crop growth and land rehabilitation. The purpose of this study was to determine the effect of adding rice-husk charcoal amendment to Jabon seedlins  grown in the subsoil media. Treatment was provided in the form of five doses of rice-husk charcoa lthose were 0% (control), 2.5%, 5%, 7.5% and 10% (v / v) with 10 replicates, each treatment consisted of  3 units. The number of media (subsoil)treatment was 2 / 3 the volume polybag size 10 x 15 cm. Observations showed that the amandment of rice-husk charcoal to the subsoil improved significantly on height and the total dry weight (biomass) of Jabon seedlings compared to controls. The amandment of rice-husk charcoal 5% (v / v) in the subsoil produced the best growth of Jabon seedlings or increasd  from  27.42% to 65.64% for total dry weight (biomass) compared to control.
The Effects of Rootone-F Plant Growth Regulators on the Growth of Duabanga mollucana. Blume Cuttings Supriyanto Supriyanto; Kaka E. Prakasa
Jurnal Silvikultur Tropika Vol. 2 No. 2 (2011): Jurnal Silvikultur Tropika
Publisher : Departemen Silvikultur, Fakultas Kehutanan dan Lingkungan, Institut Pertanian Bogor (IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j-siltrop.2.2.%p

Abstract

Wood shortage supply from natural forest effected the running of wood-based industry. Therefore forestry entrepreneurs began to switch from also growing tree species to fast growing tree species. Duabanga moluccana Blume is one type of native tree in Indonesia who can growing  fast and have good characteristics for industrial raw materials. Multiplication of Duabanga mollucana can be planting by seeds and also by vegetative propagation. Shoot and stem cuttings is one alternative was to obtain plantation in sufficient quantities and in sort time. The addition of plant growth regulators (Rootone - F) was expected to increase the percentage of rooted materials cuttings and the survival percentage.
Prediction of Phenotypic Parameters of Sugarcane Plants Based on Multispectral Drone Imagery and Machine learning Febri Hasskavendo; Mohamad Solahudin; Supriyanto Supriyanto; Slamet Widodo
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol 13, No 4 (2024): December 2024
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v13i4.1182-1195

Abstract

Measuring phenotypic parameters is important in evaluating the productivity of sugarcane. Existing manual measurements are considered less efficient, so a better alternative method is needed. This research aims to explore the potential of using multispectral drone imagery and machine learning to estimate phenotypic parameters of sugarcane plants that are efficient, accurate, inexpensive, and support sustainable agricultural practices. Spectrum data captured by drones, namely Green, Red, RedEdge and NIR are used as inputs to estimate phenotypic parameters including brix value, number of stands, stem diameter, and plant height. Based on the results of machine learning model development, the ANN algorithm model is most effective in predicting Brix Value with R2 0.74 and RMSE 0.06 and number of stands with R2 0.68 and RMSE 2.13. All models could not predict stem diameter and plant height well. The best model to predict plant height was obtained by RF algorithm with R2 0.53 and RMSE 14.09. SVR algorithm was the best model to predict plant diameter with R2 0.39. and RMSE 0.49. This indicates that the effectiveness of an algorithm depends on the specific parameter being predicted and there is no dominant algorithm for all phenotypic parameters. Keywords: Machine learning, Multispectral drone imagery, Phenotypic parameter, Plant productivity, Sugarcane.
Co-Authors Febri Hasskavendo Fidryaningsih Fiona Hardjanto Hardjanto Kaka E. Prakasa Kurniawati Purwaka Putri Lailan Syaufina Leti Sundawati Mohamad Solahudin Rahmat Safe’i Slamet Widodo