Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management)
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Developing a Decision Tree Algorithm for Detecting Agroforestry and Monoculture Coffee Plantations Using Landsat 8 Imagery: A Case Study inBandung Regency, Indonesia
No full textKopi arabika merupakan komoditas unggulan di Kabupaten Bandung, Provinsi Jawa Barat, Indonesia, yang memiliki potensi pengembangan yang besar dengan menggunakan sistem penanaman agroforestri. Oleh karena itu, penelitian ini bertujuan untuk mendeskripsikan pengembangan algoritma pohon keputusan dengan mengkombinasikan variabel spektral yang berasal dari citra Landsat 8 dan variabel sosio-geo-biofisik. Variabel yang dikaji meliputi citra sintetis dan faktor sosio-geo-fisik, seperti elevasi, kemiringan lereng, jarak dari jalan dan sungai, jarak dari permukiman, kepadatan penduduk, jarak dari desa, dan peta tutupan lahan yang ada. Algoritma decision tree machine learning (DTML) dikembangkan untuk mendeteksi distribusi spasial penanamn kopi agroforestri dan kopi monokultur di Kabupaten Bandung. Parameter pohon keputusan yang diuji untuk mengidentifikasi bobot masing-masing variabel adalah gain ratio, information gain, dan gini indeks. Sementara itu, metode brute force diterapkan untuk memilih variabel yang paling signifikan dalam model. Hasil penelitian menunjukkan bahwa variabel yang paling signifikan untuk mengidentifikasi agroforestry dan monokultur kopi adalah kombinasi dari variabel spektral, biogeofisik, dan tutupan lahan, dengan kriteria terbaik adalah information gain. Penggunaan peta penggunaan dan tutupan lahan yang ada merupakan variabel yang paling berpengaruh dalam model. Dalam konteks ini, akurasi keseluruhan (OA) yang diperoleh adalah 84,65%, dengan akurasi kappa (KA) sebesar 82,60%.Data on the potential of coffee commodities in Bandung Regency is still mixed with data on other commodities. Therefore, the study aims to develop an algorithm that provides accurate spatial information through maps for both coffee plantations in agroforestry and monoculture systems. This study integrates the data derived from remotely sensed data and data derived using socio-geobiophysical aspects, such as elevation, slope, distance from the road and rivers, proximity of the settlements, population density, proximity of villages, and a visually-based land-use-land cover map. The importance value for each variable was computed using several criteria, such as information gain, Gini index, and gain ratio. Meanwhile, the brute force method was applied to select the most significant variables in the model. The study found that the most significant variables for identifying coffee agroforestry and monoculture were ARVI, EVI, GARI, NRGI, and VDVI, as well as DEM, slope, proximity to roads, and visual-based LULC, using the criterion of information gain. The use of existing land-use and cover maps was the most influential variable in the model. The algorithm achieved an overall accuracy (OA) of 84.65% and a kappa accuracy (KA) of 82.60%. Based on overall accuracy and high kappa accuracy, the maps produced facilitate local governments and cooperatives in planning specific interventions for coffee-producing areas, supporting policies related to sustainable agriculture, climate-smart agroforestry expansion, and supply chain traceability
Monitoring Forest Cover Change and Encroachment Risk Mapping Using the Normalized Difference Fraction Index (NDFI): A Case Study of Gunung HalimunSalak National Park, Indonesia
No full textGunung Halimun Salak National Park (GHSNP) is one of the most biodiversity-rich protected areas in Java, yet it remains highly vulnerable to deforestation and forest degradation. This study examines forest cover dynamics from 1994 to 2024 and projects village-level encroachment risk for 2034. Landsat 5 TM, Landsat 7 ETM+, and Landsat 8–9 OLI imagery were processed in Google Earth Engine to generate the Normalized Difference Fraction Index (NDFI) using spectral mixture analysis of GV, NPV, soil, and shade fractions. Changes in NDFI (ΔNDFI) were used to classify degradation, deforestation, regrowth, and intact forest. Encroachment risk mapping was modeled using a 3 × 3 kernel neighborhood with two analytical approaches: the sum of risk weight and the majority of risks around. Forest cover declined by 19,424 ha between 1994 and 2004, largely driven by illegal encroachment linked to governance uncertainty in 2003. An increase of 6,678 ha during 2004–2014 reflects the impact of restoration initiatives and strengthened area protection, although a subsequent decline of 1,992 ha occurred between 2014 and 2024 due to renewed encroachment. Model evaluation indicates low predictive performance for both kernel methods (Precision 4%). Despite this limitation, areas of elevated risk consistently appeared along forest edges near settlements and footpath access routes. Citorek Kidul was identified as the village most susceptible to encroachment in 2034. Improving the accuracy of encroachment prediction will require the integration of socio-economic drivers and advanced machine-learning approaches capable of capturing the complex and non-linear patterns of forest encroachment.
Spatial and Quantitative Analysis of Historical Pollution Incidents: Sulfur Dioxide Emissions from Copper Smelting during Japan\u27s Modernization Era
No full textDuring Japan’s modernization and westernization over a century ago, copper mining and smelting became a key export industry. However, the resulting sulfur dioxide emissions caused significant damage to crops and forests. Due to the limited availability of historical environmental records, this study utilizes the atmospheric dispersion simulation tool AIST-ADMER, developed by the National Institute of Advanced Industrial Science and Technology, to reconstruct pollution patterns associated with the Besshi Copper Mine in Ehime Prefecture. We assess the plausibility of the simulated dispersion patterns by examining their correlation with historical records of environmental damage and compensation. The results reveal a moderate correlation between simulated sulfur dioxide concentrations and compensation levels, whereas the correlation with recorded damage is relatively weak. Regression analysis further indicates that compensation amounts are significantly associated with both concentration levels and the proportion of forest land use. Applying this model to counterfactual scenarios, we estimate that relocating the smelting facilities to alternative sites, such as a coastal onshore site or a mountainous inland area which could have increased compensation payments by approximately three and five times, respectively. These findings shed light on how corporate decisions shaped responses to environmental damage and compensation, highlighting the complex trade-offs companies faced in managing pollution under evolving social and environmental pressures. This research fills a significant gap in the literature by establishing a quantitative framework that links simulated pollution patterns with historical evidence, enabling a deeper understanding of past environmental impacts and corporate responses
Enhancing Performance Production Forest Inventory in Java Using LiDAR Technology
Full text linkForest inventory (FI) is an essential process for assessing the quality and quantity of forest resources, forming the foundation for strategic planning and sustainable management. Terrestrial methods (sampling / census), remote sensing methods, or a combination of these can be used to obtain this data and information. This study explores the application of LiDAR technology to improve forest inventory practices in plantation forests (teak and pine) in Java, Indonesia. LiDAR sensors, deployed via drones and handheld devices, were tested in several Perum Perhutani Forest Management Unit compartments, which were the locations of proof of concept (PoC). PoC is a testing process to prove the feasibility of a concept or methodology before it is implemented. The results showed that LiDAR-based inventories provide superior accuracy compared to traditional methods, with data showing strong alignment with ground-truth measurements. These results underscore the potential of LiDAR technology to revolutionize FI practices and inform sustainable forest management strategies in Java and beyond. The use of this technology in natural forests where the variety of tree species is more diverse certainly requires further study
Potential for Developing Access to Safe Drinking Water in the Highlands Area (Case Study: Bogor City, Indonesia)
Full text linkThe need for water in Indonesia is not directly proportional to its availability. This challenge is not limited to rural areas but also affects urban areas like Bogor City. Since 2004, Regional drinking water company of Bogor City has been classified as healthy and is a pilot city for the prime drinking water zone program alongside two other Indonesian cities. This research aims to assess Bogor City\u27s potential for safe drinking water development, considering the physical environment, readiness of the drinking water system, social conditions, and economic conditions of the community. The methodology used is mixed with a quantitative approach via spatial analysis. The physical environment variable yielded 4 classifications: high potential, potential, moderate potential, and low potential. The very potential classification was dominant in 45 sub-districts. The drinking water system readiness had 4 classifications: potential, moderate potential, low potential, and no potential, with the moderate potential dominating in 51 sub-districts. The community social condition had 4 classifications: potential, moderate potential, low potential, and no potential, with the low potential dominating in 36 sub-districts. The community economic condition variable resulted in 4 classifications. Moderate potential dominates in 29 sub-districts. Bogor City has moderate potential for developing access to safe drinking water. The key factors for this classification are the community\u27s social and economic conditions, as well as the drinking water system\u27s readiness
Land Use Change and Future Prediction in Banggai Islands Regency, Central Sulawesi, Indonesia
Full text linkLand use and land cover (LULC) changes can influence policies in a region due to economic and social conditions caused by population growth. The objective of this study is to analyze and map LULC changes in 2002, 2012, and 2022 using the Random Forest approach on Google Earth Engine, and to predict land use in 2042 using Markov-CA, thereby supporting the provision of accurate and sustainable policy data related to LULC in Banggai Islands Regency. This method can provide accurate information about the spatial distribution of rational LULC, balancing development demands with sustainable environmental protection. The study\u27s results indicate that LULC has undergone significant changes from 2002 to 2022. There has been an increase in plantation land, open land, and settlements originating from forest and scrubland. Predictions of LULC changes in 2042 show an increase in plantations, settlements, and open land, while other land uses are declining. Effective land use policies require spatial planning that considers the potential andlimitations of land, as well as the space needs for residential, agricultural, and forest areas. This approach will facilitate the application of land conservation principles in sustainable, balanced agricultural and non-agricultural development in Banggai Islands Regency
Influence of Sociodemographic, Knowledge, and Behavior of DKI Jakarta People on Willingness To Pay for Disposable Mask during the Covid-19 Pandemic
Full text linkThe use of masks is recommended to reduce the risk of widespread spread of the Covid-19 virus, but because of its use in high quantities in a short time, it has an impact on the high waste of disposable masks. The problem of high waste of masks that is not accompanied by good management is it has the potential to pollute the environment and disposable masks are included in the type of hazardous medical waste so that they require special waste management. The purpose of this study is to analyze the relationship between the sociodemographic characteristics of the people of DKI Jakarta and the Willingness to Pay (WTP) for disposable mask waste management to determine the WTP price for disposable mask waste management. The survey was conducted in DKI Jakarta Province by distributing questionnaires and obtained a total sample of 356 respondents. Furthermore, the analysis method used, the first is logistic regression analysis to determine the variables of sociodemographic characteristics that affect individual WTP. The next analysis method is to calculate WTP using the Contingent Valuation Method (CVM) and the question model with the Double Bounded dichotomous method. Based on the results, it is known that the dependent variables that can increase the WTP value are income (Δ+ 23.6%, p ≤ 0.05), type of healing treatment (Δ+ 100%, p ≤ 0.1), and knowledge (Δ+ 125.9%, p ≤ 0.01), where a value of Rp 28,578 is ideal for the cost of managing disposable mask waste.Dampak penyebaran virus Covid-19 di seluruh dunia sejak awal tahun 2020 berdampak pada anjuran pembatasan social dan penggunaan masker untuk menutupi hidup dan mulut. Penggunaan masker dianjurkan untuk menurunkan risiko penyebaran virus Covid-19 yang meluas namun sebab penggunaannya dalam jumlah yang tinggi pada waktu yang singkatm berdampak pada tingginya limbah dari masker sekali pakai. Permasalahan yang terjadi adalah tingginya limbah masker yang tidak diiringi oleh pengelolaan yang baik berdampak pada timbulan masker yang berpotensi mencemari lingkungan serta masker sekali pakai termasuk ke dalam jenis limbah medis B3 sehingga membutuhkan pengelolaan limbah secara khusus. Tujuan dari penelitian ini adalah analisis hubungan karakteristik sosiodemografi masyarakat DKI Jakarta terhadap Willingness to Pay (WTP) pengelolaan limbah masker sekali pakai untuk menentukan harga WTP pengelolaan limbah masker sekali pakai. Survey dilakukan di Provinsi DKI Jakarta dengan pembagian kuesioner dan didapatkan total sampel sebanyak 356 responden. Selanjutnya metode analisis yang digunakan, yang pertama adalah analisis regresi logistic untuk mengetahui variable karakteristik sosiodemografi yang berpengaruh pada WTP individu. Metode analisis selanjutnya yaitu untuk perhitungan WTP menggunakan metode perhitungan Contingent Valuation Method (CVM) dan model pertanyaan dengan metode Double Bounded Dichotomus. Hasil analisis adalah pendapatan, penanganan penyembuhan, dan pengetahuan signifikan berpengaruh pada keputusan WTP individu dengan hasil perhitungan nilai WTP untuk pengelolaan limbah masker sebesar Rp 30.771. Kesimpulan dari penelitian ini adalah nilai WTP sangat dipengaruhi oleh pendapatan, penanganan penyembuhan, dan pengetahuan dimana nilai sebesar Rp 30.771 ideal untuk biaya pengelolaan limbah masker sekali pakai
Nesting Site Preference of Tarsius fuscus in Bantimurung Bulusaraung National Park, South Sulawesi
Full text linkTarsius fuscus merupakan salah satu primata terkecil di dunia endemik Sulawesi Selatan. T. fuscus sebagai satwa liar cenderung memilih sarang pada lokasi dengan kriteria tertentu. Sarang memiliki peran penting pada habitat satwa liar yang berkaitan dengan anti-predator, tempat tidur, dan reproduksi. Penelitian mengenai preferensi sarang T. fuscus sangat penting dilakukan dengan tujuan untuk menganalisis pemilihan sarang T. fuscus dan faktor yang mempengaruhinya. Penelitian ini dilakukan di Resort Mallawa, Taman Nasional Bantimurung Bulusaraung, Sulawesi Selatan pada bulan Juli hingga Agustus 2021. Metode yang digunakan adalah observasi langsung ke titik bersarang T. fuscus. Data biotik dan abiotik dicatat pada setiap lokasi perjumpaan baik secara langsung maupun melalui bantuan analisis GIS. Preferensi sarang T. fuscus ditentukan dengan perhitungan PCA dan indeks Neu. Terdapat 7 parameter yang mempengaruhi preferensi sarang T. fuscus yaitu tutupan lahan, substrat sarang, tinggi sarang dari tanah, jarak dari pemukiman, kelerengan, ketinggian, dan jarak dari sungai.Tarsius fuscus is one of the smallest primates in the world endemic to South Sulawesi. T. fuscus as a wildlife is thought to tend to choose nests in places with certain criteria. Nests have an important role in wildlife habitats related to anti-predator, sleeping, and reproductive functions. Research on T. fuscus nesting preferences is important to do with the aim of analyzing T. fuscus nesting preferences and the factors that influence them. This research was conducted at the Mallawa Resort, Bantimurung Bulusaraung National Park, South Sulawesi from July to August 2021. The method used was direct observation of T. fuscus nesting points. Biotic and abiotic data are recorded at each of these points either by direct measurement or with the help of GIS. T. fuscus nesting preference was determined by PCA calculation and Neu index. There are 7 parameters that influence the preferences of T. fuscus nesting sites, namely land cover, nest substrate, the height of the nest from ground level, distance from settlements, slope, elevation, and distance from rivers
Annual litterfall Production in the Medium-high Tides Mangrove Area of Angke Kapuk Protected Forest
Full text linkProduksi serasah di ekosistem mangrove sangat penting bagi komunitas mangrove. Ia juga memiliki peran penting dalam menyumbangkan karbon ke muara di daerah tropis. Tujuan dari penelitian ini adalah untuk mengetahui produksi serasah mangrove di kawasan Hutan Lindung Angke Kapuk, Indonesia yang mempunyai tipe pasang surut medium high tides, dan bagaimana faktor lingkungan mempengaruhi produksi serasah. Metode yang digunakan untuk menangkap serasah di hutan dalam jangka waktu tertentu adalah dengan metode perangkap serasah dengan menggunakan 34 buah perangkap serasah ukuran masing-masing 1 x 1 meter dan ukuran mata jaring 1 mm yang disebar secara teratur dan digantung diatas ketinggian pasang surut maksimum. Sampah yang terperangkap dipilah menjadi daun, ranting, komponen reproduksi, dan komponen lainnya. Litterfall dipanggang dalam oven bersuhu 105 oC selama 24 jam dan ditimbang berat keringnya. Produksi tahunan serasah mangrove pada daerah pasang sedang-tinggi adalah 761,37 g m-2. Daun merupakan komponen yang paling dominan dalam serasah mangrove. Tidak terdapat korelasi yang signifikan antara produksi serasah dengan curah hujan bulanan, sedangkan korelasi antara produksi serasah dengan kecepatan angin hanya mempengaruhi bagian reproduksi yang dipengaruhi secara signifikan oleh kecepatan angin.Litterfall production in the mangrove ecosystem is essential for the mangrove community. It also has an essential role in contributing carbon to estuaries in the tropics. This study aimed to determine the mangrove litterfall production in the Angke Kapuk Protected Forest area, Indonesia, which has a medium-high tide tidal type, and how environmental factors affect the litterfall production. The method used to catch litterfall in the forest for a certain period was the litter-trap method with 34 litter-traps size 1 × 1 meter each and a mesh size of 1 mm spread out systematically and suspended above the maximum tidal height. The trapped litterfall was sorted into leaves, twigs, and reproductive components. Litterfall was baked in an oven at 105 oC for 24 hours, and the dry weight was weighed. The annual production of mangrove litterfall in the medium-high tides area is 761.37 g m2. Leaves were the most dominant component of mangrove litterfall. There is no significant correlation between litterfall production and monthly rainfall, while the correlation between litterfall production and wind speed only affects reproductive parts significantly affected by wind speed
Relationship Between Environmental Knowledge, Pro-Environmental Attitude, and Pro-Environmental Behavior of Employees (Study at PT X)
Full text linkSeiring dengan berkembangnya industri di Indonesia terdapat dampak lingkungan yang menimbulkan kerugian. Salah satu yang mengakibatkan munculnya dampak lingkungan adalah perilaku peduli lingkungan yang tidak sesuai masih dilakukan. Salah satu yang dapat mewujudkan perilaku peduli lingkungan adalah adanya sikap peduli lingkungan dan pengetahuan lingkungan yang baik. Tujuan penelitian ini untuk mengetahui kaitan pengetahuan lingkungan, sikap peduli lingkungan dan perilaku peduli lingkungan. Partisipan dalam penelitian ini adalah berjumlah 63 orang, teknik sampling yang digunakan adalah probability sampling, yaitu menggunakan teknik simple random sampling. Pada penelitian ini menggunakan alat ukur kuesioner, kuesioner ini digunakan untuk mengetahui tingkat pengetahuan lingkungan, sikap peduli lingkungan dan perilaku peduli lingkungan responden. Data yang didapat menggunakan uji normalitas, lienaritas dan uji multikolinearitas. Untuk mengetahui hubungan antara variabel maka dilakukan pengkategorian dari data dan dianalisis dengan menggunakan uji Chi Square. Dari hasil pengolahan data dapat disimpulkan bahwa terdapat hubungan antara masa kerja dengan pengetahuan lingkungan, kemudian hasl juga menunjukkan tidak ada hubungan yang signifikan antara pengetahuan lingkungan, sikap peduli lingkungan dan perilaku peduli lingkungan.The rapid industrialization has led to environmental degradation, exacerbated by a lack of pro-environmental behavior. This study aimed to analyze the correlation between environmental knowledge, pro-environmental attitudes, and pro-environmental behavior within the industrial sector. The study was conducted at the workshop of PT X, an Indonesian mining services company with operations across the country. A quantitative research method was employed using simple random sampling to select respondents who completed questionnaires. The data were analyzed using a product moment correlation coefficient test. The results indicated no significant correlation between environmental knowledge, pro-environmental attitudes, and pro-environmental behaviors. However, a significant relationship was found between years of service and the level of environmental knowledge among participants. This suggests that knowledge and attitudes alone are insufficient to promote pro-environmental behavior. Further research is needed to identify these factors and design more effective interventions to promote sustainable industrial practices and mitigate the negative impacts of industrialization.