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Estimation Model of Ramin (Gonystylus bancanus) Standing Stock in Peat Swamp Forest: Case Study in Sumatra and Kalimantan Samsuri, Samsuri; Jaya, I Nengah Surati; Lastini, Tien; Purnama, Edwin Setia
Journal of Sylva Indonesiana Vol. 1 No. 01 (2018): Journal of Sylva Indonesiana
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (534.674 KB) | DOI: 10.32734/jsi.v1i01.422

Abstract

Multiple sampling technique was applied to estimate ramin (Gonystylus bancanus) standing stock in peat swamp forest by combining imagery analysis (phase I) and field measurement (phase II). The objectives of this research were to obtain (1) estimation model of stand volume, (2) estimation model of G. bancanus standing stock, and (3) volume of standing stock of G. bancanus in Sumatera and Kalimantan peat swamp forests. The research was conducted in peat swamp forest of Sumatera and Kalimantan Island. ALOS AVNIR image interpretation was completed to obtain crown density and used as independent variable for developing stand volume model. Cluster sampling was used to obtain field data from circle sample plot of 0.1 ha and square sample plot of 0.25 ha. Spatial analysis was conducted to map and calculate standing stock of G. bancanus for Sumatera and Kalimantan Island. Estimation model of stand volume was V bf = 0.1851 C field1.05234 (R 2 =0.62) for Sumatera peat swamp forest and V bf = 3.1163 e 0.041 Cfield (R 2 = 0.62) for Kalimantan peat swamp forest, respectively. We estimated that standing stock of G. bancanus of peat swamp forest in Sumatra and Kalimantan was 5% and 2.3% of the total stand volume, respectively. Base on both the estimation models, standing stock of G. bancanus in Sumatera peat swamp forest was 15,351,063 m 3 and in Kalimantan peat swamp forest was 6,004,874 m 3 .
Developing a Spatial Mathematical Model for Assessing the Rate of Natural Forest Changes Dahlan, Dahlan; Jaya, I Nengah Surati; Saleh, Muhammad Buce; Puspaningsih, Nining; Affan, Muzailin
Aceh International Journal of Science and Technology Vol 12, No 1 (2023): April 2023
Publisher : Graduate School of Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13170/aijst.12.1.31703

Abstract

Establishing a spatial mathematical model that uses diverse data types such as ratio data, interval data, and ordinal and nominal data is a challenge. This paper describes how the mathematical model of the rate of natural forest cover change was developed by considering the causes and/or driving forces that come from the society's biophysical and/or socioeconomic aspects. The main objective of this research is to establish a spatial mathematical model using the environmental and socioeconomic variables that play a significant role in determining the rate of natural forest cover change. From a number of variables considered in the analysis, coupled with any other reason, the rate of natural forest cover change (y), in units of ha per year), this study found that there are 10 potential variables, namely the proximity of the road (x4), the proximity of the river (x5), the proximity of the settlement (x6), proximity from the regency capital (x8), the proximity of the capital city of the district (x9), proximity of the edge of the forest in 2015 (x11), the proximity of the plantation area in 2009 (x12), the proximity of the plantation in 2015 (x13), slope class (x16), and elevation class (x17). The standardization process successfully transformed the non-ratio data type into a ratio data type. Using the standardized data, the study obtained spatially mathematical models that are reliable in estimating the rate of forest cover change, namely y = 0.017 + 0.00040x9 with SR of 17.3% and R2 is 88.0%. The study concludes that the most significant factor affecting the natural forest cover change in the study site is the proximity from sub-district capital (x9). Therefore, a spatial mathematical model can facilitate the government in monitoring forest cover.
Separabilitas Spektral Beberapa Jenis Pohon Menggunakan Citra Compact Airborne Spectograph Imager (CASI): Studi Kasus di Kebun Raya Bogor Jaya, I Nengah Surati
Jurnal Manajemen Hutan Tropika Vol. 8 No. 2 (2002)
Publisher : Institut Pertanian Bogor (IPB University)

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Abstract

CASI (Compact Airborne Spectrometer Imager) data was examined to classrfi 20 tree species. The numerical taxonomy using nearest neighbor hierarchical classification method was applied to cluster the spectral reflectance of those species of interest. The study shows promising results expressing the abiliry of CASI image to discriminate 20 tree species. To get a better result of discriminating 20 species, the number of bands used should be more than eight bands. Using combination of less than eight bands caused some class pairs "inseparable". From the cluster analysis, the study also found that there is no relationship between botanical taxonomy of the species and their spectral reflectance. The tree species that belong to the same genus or family could not have similar spectral reflectance.
Study on the Use of Small Format Non-Metric Aerial Photos For Establishing Aerial Teak Stand Volume Table (A case study in Randublatung Forest Management Unit, PT.Perhutani Unit I, Central Java) Cahyono, Agung Budi; Jaya, I Nengah Surati; Pratomosunu, Bambang Sapto
Jurnal Manajemen Hutan Tropika Vol. 7 No. 2 (2001)
Publisher : Institut Pertanian Bogor (IPB University)

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Abstract

Penelitian ini mengkaji tentang pemanfaatan foto udara non-metrik format kecil (SFNAP) guna menyusun tabel volume udara tegakan jati (aerial stand volume table of teak wood) di KPH Randublatung, Perum Perhutani Unit I, Jawa Tengah. Sebagai perbandingan, pengkajian terhadap penggunaan potret udara metrik konvensional (CAP) juga dilakukan. Hasil penelitian menunjukkan bahwa secara teknis SFNAP layak digunakan untuk mengestimasi potensi tegakan sebagaimana ditunjukkan oleh hasil tes statistik. Model terbaik untuk estimasi volume tegakan jati menggunakan SFNAP di lokasi penelitian adalah V = 52,4 – 0,469 C (r2 = 76,2%), sedangkan model terbaik menggunakan CAP adalah V = 32,4 – 0,246 C (r2 = 69,1%).
Analisis Spasial Degradasi Hutan dan Deforestasi: Studi Kasus di PT. Duta Maju Timber, Sumatera Barat Mulyanto, Lukman; Jaya, I Nengah Surati
Jurnal Manajemen Hutan Tropika Vol. 10 No. 1 (2004)
Publisher : Institut Pertanian Bogor (IPB University)

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Abstract

This study develops a predictive model on forest degradation and deforestation in Duta Maju Timber concession area West Sumatera during 1999 and 2002 period. The study found that the likelihoods of the forest degradation and deforestation are significantly affected respectively by distance from villages/settlement centers (X1), distance from rivers/streams (X3), distance from public road/logging roads (X2) and the age of logged over forest (X4). The probality of forest changes was negatively correlated with the distance from the villages and the age of logged over forest. While the rest variables (X3 and X2) are positively correlated. The best predictive model obtained for predicting forest degradation and deforestation was the logistic model (y =(10-7,64).X4-23,565.X1-6,889 . X35,505. X23,712) having considerably high coefficient correlation.
Prediksi Kebutuhan Hutan Kota Berbasis Oksigen di Kota Padang, Sumatera Barat Septriana, Diana; Indrawan, Andry; Dahlan, Endes Nurfilmarasa; Jaya, I Nengah Surati
Jurnal Manajemen Hutan Tropika Vol. 10 No. 2 (2004)
Publisher : Institut Pertanian Bogor (IPB University)

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Abstract

The study describes a method for predicting urban forest area in Padang City based upon oxygen needs. The result shows that the needs of urban forest in Padang City increase continously, mainly due to the increase of industries. Since the year 2002, the spatial analysis also found that the significant increase of the urban forest need occurred in Lubuk Kilangan disctrict, i.e., approximately 368,88 hectares per year. In the year 2020, the estimate needs of urban forest in all Padang City are 14,894.61 hectares. This need is approximately 53% of the area. Furthermore, the extent of urban forest is still sufficient for supplying oxigen up to the year 2020. However, it is also the spatial analysis shows that urban forest (vegetated area) are not evenly distributed in the centers of economic activities (e.g. settlement, industries, shopping centre, etc). Key words : ,
Evaluasi Kerusakan Tegakan Tinggal Akibat Pemanenan Menggunakan Landsat 7 ETM+ di HPH PT Sari Buana Dumai Provinsi Riau Susilawati; Jaya, I Nengah Surati
Jurnal Manajemen Hutan Tropika Vol. 9 No. 1 (2003)
Publisher : Institut Pertanian Bogor (IPB University)

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Abstract

This paper describes the use of Landsat 7 ETM+ for evaluating logged over stand condition. The digital classification and spatial analysis were performed to identity degree of stand damage and their spatial distribution. The study found that Landsat 7 ETM+ images were powerful to identify logged over stand damage having Kappa and overall accuracies more than 99%, as well as interclass separability more than 1900 (good). There is also a spatial relationship between the stand damage and distance from the logging road.
Kajian Teknis Penggunaan Citra IKONOS dan CASI dalam Rangka Inventarisasi Hutan: Studi Kasus di Kebun Raya Bogor Jaya, I Nengah Surati
Jurnal Manajemen Hutan Tropika Vol. 9 No. 2 (2003)
Publisher : Institut Pertanian Bogor (IPB University)

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Abstract

This study examined the capability of high-resolution imageries for identifying tree species. The IKONOS and CASI (Compact Airborne Spectrographic Imager) data were examined to digitally identify 20 tree species and estimating stand density. The numerical taxonomy using nearest neighbor hierarchical classification method was applied to cluster the spectral reflectance of those species of interest. Although the panchromatic band of IKONOS and CASI have the same spatial resolution, the study shown that CASI provided better performance than IKONOS in discriminating 20 tree species of interest. The finer spectral and spatial resolution of CASI significantly improved the quantitative discrimination ability. Inversely, the IKONOS imagery was fail to digitally identify tree species. However, the study shows that both the IKONOS and CASI images are capable to be used to estimate the stand density. To get a better result of discriminating 20 species using CASI image, the number of bands hould be used more than eight bands. Otherwise, some "inseparable" class pairs could exist.
Application of Random Forest Algorithm to Analyze the Confidence Level of Forest Fire Hotspots in Riau Peatland Unik, Mitra; Sukaesih Sitanggang, Imas; Syaufina, Lailan; Surati Jaya, I Nengah
Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Vol 15 No 2 (2025): Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (JPSL)
Publisher : Pusat Penelitian Lingkungan Hidup, IPB (PPLH-IPB) dan Program Studi Pengelolaan Sumberdaya Alam dan Lingkungan, IPB (PS. PSL, SPs. IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jpsl.15.2.255

Abstract

Forest fires pose a significant challenge in Riau Province, Indonesia, especially in peatland areas. This study employs the Random Forest (RF) algorithm to analyze the confidence levels of hotspots, aiming to predict potential fire occurrences and improve fire management strategies. The research focuses on peatlands spanning 3.86 million ha, using key variables such as NDVI, surface temperature, and peat thickness derived from satellite data. The model achieved an average AUC of 0.732 and a classification accuracy of 70.3%, with medium-confidence hotspots demonstrating the best predictive performance (AUC: 0.707, F1-score: 0.804). However, the model struggled with low-confidence hotspots, reflecting challenges in distinguishing less prominent patterns in the data. Compared to other methods, RF demonstrates strong potential in handling complex environmental datasets, making it a valuable tool for hotspot prediction. This study contributes to understanding forest fire risks in peatlands and provides actionable insights for improving preparedness and mitigation efforts.
Exploration of Data Handling Techniques to Improve PM2.5 Prediction Using Machine Learning Unik, Mitra; Sitanggang, Imas Sukaesih; Syaufina, Lailan; Jaya, I Nengah Surati
International Journal of Electronics and Communications Systems Vol. 5 No. 1 (2025): International Journal of Electronics and Communications System
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ijecs.v5i1.25687

Abstract

Particulate matter (PM₂.₅) is one of the most dangerous air pollutants because it can penetrate the respiratory system and cause serious health problems. Amidst the limitations of a real-time and comprehensive air quality monitoring system, a data-driven predictive approach is needed that can accurately project PM₂.₅ concentrations. This study aims to develop a PM₂ concentration prediction model using the Random Forest Regressor (RFR) algorithm optimised through a series of data pre-processing techniques. The pre-processing techniques include outlier detection with four methods (Isolation Forest, Autoencoder ANN, OCSVM, IQR) and missing value handling using three approaches (Spline Cubic Interpolation, Nearest Point Interpolation, Data Removal). The daily data used covered 12 environmental variables (including rainfall, temperature, relative humidity, AOD, and NDVI) from the period of March 2022 to March 2023, with PM₂.₅ as the target. The RFR model was built with 100 decision trees and 10-fold cross-validation to improve accuracy. Results showed the combination of IQR (outlier detection) and data deletion (missing values) produced the best performance with RMSE 0.082, MAE 0.027, and R² 0.886. The most influential variables were temperature (TEMP), relative humidity (RHU), and evapotranspiration (ET). This research contributes to the development of an accurate air quality prediction model, supporting the mitigation of PM₂.₅ pollution impacts on public health
Co-Authors Abdul Rosyid Adelia Juli Kardika Adhiguna, Agasta Agung Budi Cahyono Agung Budi Cahyono Agus P. Kartono Ahyar Gunawan Andry Indrawan Anita Zaitunah Anita Zaitunah Antonius B Wijanarto Antonius B Wijanarto Antonius B Wijanarto Bambang Hero Saharjo Bambang Sapto Pratomosunu Bejo Slamet Beni Iskandar Boedi Tjahjono Bramasto Nugroho Budi Kuncahyo Cecep Kusmana Dahlan Dahlan Dahlan Dahlan Darwo Darwo Darwo Darwo Dede Dirgahayu Dewayany Sutrisno Dewayany Sutrisno Diana Septriana Dito Cahya Renaldi Dito Cahya Renaldi Dwi Noventasari Dwi Putra Apriyanto Dwi Shanty Apriliani Gunadi Elias Elias Ema Kurnia ENDANG SUHENDANG Endang Suhendang Endang Suhendang Suhendang Endes Nurfilmarasa Dahlan Eva Achmad F Gunarwan Suratmo Fahmi Amhar Faid Abdul Manan Fairus Mulia Fairus Mulia Farida H. Susanty, Farida H. Farida Herry Susanty Farida Herry Susanty Florentina Sri Hardiyanti Purwadhi Hanifah Ikhsani Hardian, Dwika Hardjanto Hardjanto Hardjanto Hariaji Setiawan Haryo Tabah Wibisono Hasriani Muis Hendrayanto . Hendri Nurwanto Hermanu Triwidodo Herry Purnomo Herry Purnomo Hidayat Pawitan I Gusti Bagus Wiksuana Iin Arianti Imas Sukaesih Sitanggang Irdika Mansur Ismail HJ Hashim Israr Albar Ita Carolita Iwan Gunawan Jarunton Boonyanuphap Kartodihardjo, Hariadi Kukuh Murtilakono Kukuh Murtilaksono Kukuh Murtilaksono Kukuh Murtilaksono Kusnadi Lailan Syaufina LILIK BUDIPRASETYO Liu Qian Liu Qian Lukman Hakim Lukman Mulyanto M. Bismark Makin Basuki Marlina, Etty Moch. Anwar Muhammad Ardiansyah Muhammad Buce Saleh Muhammad Ikhwan Mulyaningrum Mulyaningrum Muzailin Affan Muzailin Affan N Nurhendra Naik Sinukaban Naik Sinukaban Nanin Anggraini Nining Puspaningsih Nitya Ade Santi Nitya Ade Santi Nitya Ade Santi Nitya Ade Santi Nobuyuki Abe Nurdin Sulistiyono Omo Rusdiana Oteng Haridjaja Oteng Haridjaja Patrich Phill Edrich Papilaya Pratiwi Pratiwi Pratiwi Pratiwi Purnama, Edwin Setia R Assyfa El Lestari Rahimahyuni Fatmi Noor'an Robert Parulian Silalahi Rudi Ichsan Ismail Samsuri Samsuri Samsuri Samsuri Samsuri, Samsuri Sendi Yusandi Sigit Nugroho Soedari Hardjoprajitno Sri Wahyuni Suria Darma Tarigan Susilawati Suyadi Suyadi Suyadi Suyadi Syamsu Rijal Tatang Tiryana Teddy Rusolono Tien Lastini Tien Lastini Tirta Negara Tirta Negara Tomi Yuwono Tomi Yuwono, Tomi Unik, Mitra Uus Saepul Mukarom Wang Xuenjun Wang Xuenjun Wibisono, Haryo Tabah Wibisono, Haryo Tabah Wibisono, Haryo Tabah Widi Atmaka Widyananto Basuki Aryono Wijanarto, Antonius B. Wijanarto, Antonius B. Yadi Setiadi YANTO SANTOSA Zhang Yuxing