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"Mangrove merupakan ekosistem penting di kawasan pesisir karena memiliki fungsi ekologi dan ekonomi. Namun, perubahan iklim dan aktivitas manusia yang berlebih menyebabkan ekosistem mangrove terancam mengalami kerusakan dan degradasi. Degradasi yang terjadi terindikasi dari adanya perubahan komposisi spesies penyusun berupa kehadiran dan dominasi tumbuhan perdu (understory plant). Adanya tumbuhan perdu tersebut dapat memberikan informasi kondisi mangrove yang bias karena tumbuhan lapisan bawah perdu dengan tutupan kanopi yang rapat menghasilkan nilai NDVI yang tinggi. Tutupan kanopi tinggi tetapi kerapatan pohon < 1000 pohon /ha dikategorikan sebagai kawasan mangrove rusak. Sehingga jika tanpa ada informasi kerapatan pohon maka ekosistem tersebut akan menjadi terlihat baik kondisinya. Ketersediaan informasi yang kurang tentang kerapatan pohon yang mendorong penggunaan parameter tunggal tutupan kanopi yang dapat menyebabkan kebijakan yang salah. Oleh karena itu, kehadiran tumbuhan lapisan bawah perlu dideteksi baik secara umum maupun terperinci sampai komposisi spesies. Penelitian ini bertujuan membuat metode deteksi tumbuhan lapisan bawah perdu di hutan mangrove menggunakan Indeks Mangrove dan NDVI, dan Menganalisis secara spektrometri untuk identifikasi 21 spesies mangrove di Taman Nasional Berbak Sembilang Sumatera Selatan, dengan menggunakan spektral Landsat-8. Penggunaan dua kanal sintesis secara bersama yaitu Indeks Mangrove dan NDVI dapat mendeteksi keberadaan tumbuhan perdu, karena bias yang disebabkan oleh tutupan kanopi rendah bisa dihilangkan. Informasi detail spasial sebaran spesies mangrove masih diperlukan, sebagai pengganti parameter kerapatan pohon dalam penentuan kriteria kondisi mangrove, atau menambah kriteria. Spesies mangrove yang ditemukan di lokasi penelitian secara spektral mampu dibedakan dengan baik dari data pengukuran reflektan menggunakan spektrometer pada spektrum Landsat-8.

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Mangroves are an important ecosystem in coastal areas because they have ecological and economic functions but are threatened by degradation due to natural and human factors. Degradation causes changes in the composition of species composition, in the presence and dominance of understory plants that did not previously exist. This provides biased information on mangrove conditions because understory plants with dense canopy cover produce high NDVI values. High canopy cover with a tree density of <1000 trees/ha was categorized as a damaged mangrove area. The limited availability of tree density information drives using a single parameter for canopy cover and will generate a mistake in national policy decisions. Therefore, the presence of understory plants must be detected in general and in detail in terms of the species composition. The aim of this study was to develop a method for detecting mangrove forest shrubs using the Mangrove Index and NDVI, and spectrometry analysis for identification of 21 mangrove species in Berbak Sembilang National Park using Landsat-8 spectrum. Using two synthetic channels together, namely, the Mangrove Index and NDVI, can detect the presence of understory plants, so it can be used to minimize canopy cover bias. Detailed spatial information on mangrove species distribution is still needed as a substitute for tree density parameters if the area has high NDVI. The mangrove species found at the research location were spectrally well-discriminated by the reflectance measurement data using a spectrometer on the Landsat-8 spectrum"

"The atmospheric effects reduction in this study which covers path radiance effect decrement and ground reflectivity extraction of Landsat MSS Data.When radiation travels through the atmosphere, energy is attenuated through scattering and absorption, an enhanced due to atmospheric emission and path radiance. Ground reflected radiance, from which information is extracted for remote sensing application,is altered by the atmosphere when it reaches the satellite. Besides that, radiance reflected by the background area surrounding the target may also reach thesatellite. Therefore, the effects of atmosphere on Landsat data must be reduced, before data processing for any purposes.The effective reflectivity which is observed from the satellite can be computed as a function of ground reflectivity. Relation between the effective reflectivity and ground reflectivity is linear approximately.Land cover classification which is processed by Maximum Likelihood method is used in this study, in order to evaluate the atmospheric effects reduction method."

"ABSTRAKVegetasi mangrove memiliki fungsi, manfaat serta peranan penting terhadap wilayah pesisir dan masyarakat yang tinggal di dalamnya. Penelitian ini dilakukan dengan tujuan untuk mengetahui persebaran vegetasi mangrove serta mengetahui perubahan luas vegetasi mangrove di Estuari Perancak dalam kurun waktu 10 tahun, serta mengetahui tingkat kehijauan vegetasi mangrove serta parameter lingkungan vegetasi mangrove saat ini, yaitu salinitas dan kondisi substrat. Metode yang digunakan adalah metode penginderaan jauh untuk dapat melihat persebaran dan perubahan luas vegetasi mangrove dengan melakukan klasifikasi terbimbing supervised pada citra satelit SPOT tahun 2007 dan 2017. Hasil dari penelitian menunjukkan adanya penambahan luasan vegetasi mangrove di Estuari Perancak sebesar 18,7 hektar dengan tingkat kehijauan yang meningkat pula. Selain persebaran dan tingkat kehijauan, parameter lingkungan yang turut diamati adalah salinitas dan kondisi substrat, dimana nilai salinitas rata-rata 31,54 ppt dan kondisi substrat yang cukup baik tidak banyak sampah.

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ABSTRACTVegetation of mangrove has a function, benefit and important role to coastal area and society that live in it. The purpose of this research is to know the distribution of mangrove vegetation, the change of mangrove vegetation area in Perancak Estuari area within 10 years, and to know the level of greenness and environmental parameters of mangrove vegetation salinity and substrate condition. To see the distribution and change of mangrove vegetation area, supervised classification is used on SPOT satellite imagery in 2007 and 2017. The result shows that the addition of mangrove vegetation area in Perancak Estuari area is 18.7 hectares with also increasing greenishness level. In addition to the distribution and greenness, the observed environmental parameters are salinity and substrate conditions, where the average salinity value is 31.54 ppt and the substrate conditions are good not much waste."

"ABSTRAKDelta bersifat dinamis dan selalu berubah bentuk akibat interaksi dari sungai danlaut. Delta Ci Punagara sejak tahun 1972 selalu bertambah luas, sehinggaberpotensi berubah bentuk secara spasial. Tujuan penelitian untuk menganalisisperubahan spasial delta dan faktor-faktor yang mempengaruhinya. Berdasarkanoverlay peta tahun 1972, 1994, dan 2015 terjadi abrasi dan akresi di delta,sehingga mengubah bentuk delta dari Irreguler menjadi Bird-Foot. Arus dangelombang yang sejajar garis pantai menyebabkan abrasi dan menghasilkanwilayah akresi. Pasang surut yang kecil cenderung membangun pantai.Peningkatan debit Ci Punagara diikuti peningkatan sedimentasi akibat perubahanpenggunaan tanah terutama menipisnya hutan menyebabkan daratan deltabertambah luas.

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ABSTRACTand the sea. Delta Ci Punagara since 1972 become broader, potentially deformspatially. The aim of research to analyze the spatial changes in the delta and thefactors that influence it. Based overlay maps in 1972, 1994 and 2015 occurred inthe delta erosion and accretion, thereby transforming the delta of the irregularinto Bird-Foot. Currents and waves are parallel to the shoreline causing abrasionand produce accretion region. Small tidal tends to build up the beach. Increaseddischarge of Ci Punagara followed by increased sedimentation due to changes inland use, especially depletion of forests leads expanding inland delta."

"This research was aimed at first, studying and comparing between the accuracies of the geometrically and non-geometrically corrected digital Landsat data; and second, evaluating these classification accuracies to ascertain the possibility of using them as an input into the process of building up a geographical information system. The method used was digital land use classification by applying the data’s maximum likelihood algorithm in the two approaches. The first approach involved classification prior to geometric correction (reference) and the second classification after geometric correction (transformed result). Analysis was then carried out through the overlay technique between the frst and the second results. It is found that an error matrix depicting individual and overall accuracies and omissions and commission of errors. Result shows that the overall accuracy of land use classification after the correction is >80%. However, this overall accuracy varied according to the technique applied. But the choice of which technique to be used depends on the average increase and decrease in area. As such, the use of the nearest neighbor interpolation, bilinear interpolation and cubic convultion techniques resulted into an areal increase of 19.54%, 24.80%, and 24.93% and a reduction of 17.17%, 24.60%, and 27.87% respectively."

"Two multi-temporal as well as multi-sensor data of LANDSAT MSS (1979) and MOS (1991) were used for Mangrove Forest change detection in Tg. Karawang, West Java. About 13,986 hectare decrease of total volume of the Mangrove Forest were detected for 12 years from 1979 to 1991. Procedures for change detection of vegetated areas employed in this study were detected by post-classification differencing technique. Landsat MSS image was registered to MOS image after the extraction of the test area from the each original image. A land cover classification image of the Landsat MSS in 1979 was produced by the supervised maximum likelihood classification method, another land cover classification image of the MOS Data 1991 was produced by the same method."

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Pertambangan menjadi sektor penting yang berperan dalam mendukung pembangunan dan perekonomian Indonesia. Salah satu perusahaan tambang terbesar di dunia adalah PT Freeport Indonesia yang terletak di Kabupaten Mimika, Papua. Dalam operasi pertambangannya, PT Freeport Indonesia menghadapi sejumlah masalah lingkungan, salah satunya adalah perubahan lahan bervegetasi menjadi lahan tandus yang minim vegetasi. Kerusakan lingkungan hidup yang terjadi akibat aktivitas pertambangan dapat dipulihkan melalui kegiatan reklamasi. Reklamasi lahan di wilayah pertambangan memerlukan waktu dalam jangka panjang untuk mencapai struktur dan fungsi ekosistem yang berkembang, stabil, dan matang sehingga diperlukan monitoring perubahan kondisi tutupan vegetasi di lahan bekas tambang menggunakan teknologi yang efektif dan efisien, yaitu penginderaan jauh. Dalam penelitian ini, citra penginderaan jauh yang digunakan adalah citra Sentinel-2 yang dikumpulkan dari tahun 2016 hingga 2023 untuk mendapatkan distribusi nilai indeks tutupan vegetasi (NDVI) dan tingkat kehijauan vegetasi di Area Reklamasi Grasberg. Variabel yang digunakan untuk menganalisis perubahan tutupan vegetasi selama proses revegetasi di Area Reklamasi Grasberg adalah indeks vegetasi (NDVI), jenis vegetasi, tahun reklamasi, ketinggian, kemiringan lereng, dan arah lereng. Penelitian ini menunjukkan bahwa semakin bertambah waktu reklamasi, maka semakin bertambah luas area yang tertutupi vegetasi dengan tingkat kehijauan sedang dan tinggi yang ditunjukkan dari hasil regresi linier yang bernilai posistif. Perubahan tutupan vegetasi di Area Reklamasi Grasberg menunjukkan tren peningkatan tutupan vegetasi seluas 379,66 hektar atau 98,71% dari total luas area reklamasi dan sisanya mengalami tren penurunan berdasarkan hasil analisis tren Sen’s Slope+Mann Kendall. Perubahan tutupan vegetasi di Area Reklamasi Grasberg tidak dipengaruhi oleh jenis vegetasi karena karakteristik vegetasi di area tersebut cenderung sama. Sedangkan perubahan tutupan vegetasi di Area Reklamasi Grasberg berdasarkan hasil uji korelasi dipengaruhi oleh faktor kondisi topografi. Ketinggian wilayah tidak menunjukkan pengaruh yang kuat terhadap tutupan vegetasi tetapi kemiringan lereng yang curam akan memicu terjadinya tingkat kehijauan tutupan vegetasi yang rendah dan sebaliknya. Sedangkan vegetasi yang berada di lereng yang menghadap ke arah timur memiliki tingkat kehijauan yang tinggi karena mendapatkan penyinaran matahari yang cukup. Pemantauan perubahan tutupan vegetasi di area reklamasi bekas tambang sangat bermanfaat untuk kebijakan pengelolaan lahan di area pertambangan dan perencanaan reklamasi.

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Mining is an important sector that plays a role in supporting Indonesia's development and economy. One of the largest mining companies in the world is PT Freeport Indonesia, located in Mimika Regency, Papua. In its mining operations, PT Freeport Indonesia faces a number of environmental problems, one of which is the change of vegetated land into barren land with minimal vegetation. Environmental damage caused by mining activities can be restored through reclamation activities. Land reclamation in mining areas takes a long time to achieve a developed, stable and mature ecosystem structure and function so that it is necessary to monitor changes in vegetation cover conditions in post-mining land using effective and efficient technology, namely remote sensing. In this research, the remote sensing images used were Sentinel-2 images collected from 2016 to 2023 to obtain the distribution of vegetation cover index (NDVI) and vegetation greenness in the Grasberg Reclamation Area. The variables used to analyze changes in vegetation cover during the revegetation process in the Grasberg Reclamation Area are vegetation cover index (NDVI), vegetation type, reclamation year, elevation, slope, and slope direction. This study shows that as the reclamation time increases, the area covered by vegetation with medium and high greenness levels increases, as shown by the positive linear regression results. Changes in vegetation cover in the Grasberg Reclamation Area show an increasing trend covering 379.66 hectares or 98.71% of the total reclamation area and the others show a decreasing trend based on the results of Sen's Slope+Mann Kendall trend analysis. Changes in vegetation cover in the Grasberg Reclamation Area are not influenced by vegetation type because the characteristics of vegetation in the area tend to be the same. Meanwhile, changes in vegetation cover in the Grasberg Reclamation Area based on the results of the correlation test are influenced by topographic conditions. The elevation of the area does not show a strong influence on vegetation cover but steep slopes will trigger a low level of vegetation cover greenness and vice versa. The vegetation on the east-facing slope has a high level of greenery because it gets enough sunlight. Monitoring changes in vegetation cover in ex-mining reclamation areas is very useful for land management policies in mining areas and reclamation planning."

"Beras merupakan bahan pangan pokok dengan tingkat kebutuhan tinggi di kawasan Asia Tenggara, termasuk Indonesia yang menjadi produsen padi terbesar di kawasan ini. Sektor pertanian, khususnya produksi padi, berperan penting dalam mendukung misi Sustainable Development Goals (SDGs) untuk mencapai ketahanan pangan. Namun, tantangan seperti alih fungsi lahan dan perubahan iklim mengancam keberlanjutan produksi padi, termasuk di Kabupaten Indramayu, salah satu lumbung padi utama di Jawa Barat. Untuk mendukung pengelolaan lahan pertanian yang berkelanjutan, pemetaan padi berbasis pengindraan jauh menjadi solusi yang efisien, memanfaatkan teknologi satelit seperti Sentinel-2 dan Landsat-8. Penelitian ini bertujuan untuk memetakan distribusi padi di Kabupaten Indramayu dengan mengintegrasikan metode Convolutional Neural Network (CNN) untuk ekstraksi fitur spektral-temporal dan algoritma Extreme Gradient Boosting (XGBoost) untuk klasifikasi. Hasil penelitian menunjukkan bahwa skema fitur terbaik, yaitu kombinasi data Raw Spectral Bands dengan NDVI, menghasilkan tingkat Overall Accuracy tertinggi sebesar 98,90%. Selain itu, metrik evaluasi lainnya seperti Recall, Precision, dan F1-Score juga menunjukkan hasil tertinggi, masing-masing sebesar 98,90%, yang mencerminkan kemampuan model yang konsisten dalam membedakan area padi dan non-padi. Model CNN-XGBoost menunjukkan kinerja yang lebih baik dibandingkan model CNN murni, dengan akurasi yang lebih tinggi dan hasil evaluasi yang lebih optimal. Dengan memanfaatkan data multispektral dan multitemporal dari kedua satelit, penelitian ini memberikan kontribusi signifikan dalam mendukung pengambilan keputusan berbasis data untuk pengelolaan pertanian yang berkelanjutan, sekaligus memperkuat upaya ketahanan pangan nasional.

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Rice is a staple food with high demand in Southeast Asia, including Indonesia, which is the largest rice producer in the region. The agricultural sector, particularly rice production, plays a crucial role in supporting the Sustainable Development Goals (SDGs) for achieving food security. However, challenges such as land conversion and climate change threaten the sustainability of rice production, including in Indramayu Regency, one of the main rice granaries in West Java. To support sustainable agricultural land management, rice mapping based on remote sensing provides an efficient solution, utilizing satellite technologies such as Sentinel-2 and Landsat-8. This study aims to map the distribution of rice in Indramayu Regency by integrating the Convolutional Neural Network (CNN) method for spectral-temporal feature extraction and the Extreme Gradient Boosting (XGBoost) algorithm for classification. The results show that the best feature scheme, a combination of Raw Spectral Bands and NDVI, achieves the highest Overall Accuracy of 98.90%. Additionally, other evaluation metrics such as Recall, Precision, and F1-Score also show the highest values, each at 98.90%, reflecting the model's consistent ability to distinguish between rice and non-rice areas. The CNN-XGBoost model outperforms the pure CNN model, with higher accuracy and better evaluation results. By utilizing multispectral and multitemporal data from both satellites, this study significantly contributes to data-driven decision-making for sustainable agricultural management, while strengthening national food security efforts."

"Penelitian bertujuan mengevaluasi pelaksanaan pemeriksaan jarak jauh BPK berdasarkan panduan pemeriksaan jarak jauh yang dikeluarkan oleh BPK pada awal pandemi COVID 19 tahun 2020 dan 2021. Analisis dilakukan dengan mengevaluasi dokumen pemeriksaan, pengamatan atas pelaksanaan pemeriksaan dan wawancara. Hasil penelitian pemeriksaan jarak jauh telah direncanakan dan dilaksanakan sesuai dengan panduan, sehingga hasil pemeriksaan tetap berkualitas. Pemeriksaan dengan metode jarak jauh tidak mengurangi ketepatan waktu penyusunan laporan hasil pemeriksaan sehingga prosedur pemeriksaan jarak jauh tetap dapat dipertahankan pada pasca Covid.

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This study aims to evaluate the implementation of the BPK remote audit based on the remote audit guide issued by the BPK at the beginning of the COVID 19 pandemic in 2020 and 2021. The analysis was conducted by evaluating the audit document, observing the audit implementation, and interviewing. The results show that the remote audit had been planned and carried out by the guidelines so that the audit results remain of high quality. Auditing with the remote method does not affect the timeliness of preparing audit reports so that remote audit procedures can still be maintained post-Covid."

"ABSTRAKMangroves in Indonesia have a large enough area, but in the last 3 decades the area has been reduced to 40%. Besideshaving a function as a coastal protector, mangroves are also able to maintain the quality of the waters around it. Currently, the construction of a reclamation island in Jakarta Bay is being carried out which will have an impact on the surroundingmangrove forests. Therefore, the purpose of this study was to identify the impact of island reclamation in Jakarta Bay onsedimentation and mangrove growth in surrounding area. This research was conducted with literature studies, vegetation analysis, water quality analysis and also spatial analysis with WorldView-2 satellite imagery. The results showed that the mangrove forests on the coast of North Jakarta, especially in the Muara Angke area tend to increase, especially in the reclaimed island area. The mangrove stands increase by approximately 1.32 ha / year. The density and stem diametersvary in 5 locations. Oxygen levels at the study site are very low but the existing mangrove forests can absorb dissolved heavy metals. The results of the study also show that the area that has the potential to be planted with mangroves is 30 ha. Overall, the sedimentation process helps expand mangrove forests naturally while the bad quality of water does not significantly affect the development of mangroves. On the contrary, the existing mangrove is able to keep the stability of the water quality in surrounding area."