Judul: Sensor Submersible untuk Mengestimasi Tinggi Muka Air di Lahan Gambut Provinsi Jambi
Abstrak: Peatland fires have become a serious issue in peatland management. One of the factors that influence peatland fires is the decreasing groundwater level. Therefore, there is a need to monitor the groundwater level (GWL) in real time. The data collected is GWL data derived from submersible sensor, and manual readings. The GWL found in peatlands in Tangkit Baru village experiences an increase when precipitation is increasing, in contrast to peatlands in Pematang Rahim village where the GWL still decrease although there is a quite heavy rain occurred. The t-test results on the GWL sampling comparison show a value of 0.052, more than 0.05, indicating there is no difference between the two measurements method. The comparison between submersible sensor and manual measurements is similar to each other, with a difference of around 0.1-1 cm, thus brings the important of sensors maintenance in order to provide an accurate measurement. The NDWI resulted from cloud free image may provide better result, however to relate the NDWI and GWL may need some further analysis and modelling effort.
Keyword: Peatlands, NDWI, sensors, groundwater level

Judul: Temporal Data Imputation Model for Peatland Groundwater Level
Abstrak: Lahan gambut adalah akumulasi tumbuhan mati yang terdekomposisi penuh selama lebih dari ribuan tahun dan dapat menyimpan karbon, memproduksi oksigen serta mengatur tingkat air. Tinggi muka air (TMA) menjadi indikator penting dalam peringatan kebakaran lahan dan hutan (karhutla). Sistem Pemantau Air Lahan Gambut (Sipalaga) sudah menjadi sistem yang digunakan untuk merekam TMA kelembaban gambut, dan tingkat curah hujan. Penelitian ini menggunakan data Sipalaga berstasiun di Rimba Panjang. Namun data yang digunakan masih mengandungi banyak missing value yang harus ditangani. Penelitian ini berfokus untuk membandingkan metode rekonstruksi data TMA lahan gambut menggunakan Last Observation Carried Forward, Next Observation Carried Forward, Interpolation, Weighted Moving Average, Kalman filter, K-nearest Neighbor Imputation, dan Simple Averaging Ensemble. Data yang sudah direkonstruksi dievaluasi menggunakan Long-Short Term Memory. Hasil terbaik yang diperoleh adalah menggunakan Stacked LSTM dengan unit 64 dan 128, dengan metode Spline Interpolation menghasilkan MSE 0.00012, MAE 0.00822 dan R2 0.95316. Hasil penelitian ini diharapkan dapat membantu prediksi TMA lahan gambut sebagai peringatan dini karhutla di Indonesia., Peatlands are accumulations of dead plants that have fully decomposed over thousands of years that can store carbon, produce oxygen and regulate water levels. The groundwater level (GWL) is an important indicator for forest fires. The Sistem Pemantau Air Lahan Gambut (Sipalaga) has become a system used to record GWL, peatland moisture, and rainfall levels at peatland locations. This study will use data from Sipalaga stationed at Rimba Panjang. However, the data used still contains many missing values that must be addressed. This research will focus on comparing methods of reconstructing peatlands’ GWA data using Last Observation Carried Forward, Next Observation Carried Forward, Weighted Moving Average, Interpolation, Kalman filter, K-nearest Neighbor Imputation and Simple Averaging Ensemble. Reconstructed data will be evaluated with Long-Short Term Memory predictions. The best model made in this study is using Stacked LSTM with 64 and 128 units using Spline Interpolation resulting MSE 0.00012, MAE 0.00822 dan R2 0.95316. The results of this study are expected to help predict the TMA of peatlands as an early warning of forest and land fires in Indonesia.
Keyword: LSTM, forest fire, groundwater level, peatland, reconstruction

Judul: Sintesis Flavon dari Fenol dan Benzoil Klorida
Abstrak: Flavone is a class of flavonoid, commonly found in plants with wide bioactivity spectrum. A widely used flavone synthesis route is through acidcatalyzed oxidative cyclization of β-diketone. In this study, unsubstituted flavone had been synthesized via 5-step from phenol, with 22% yield and successfully increased the yield of previous study on Fries rearrangement of phenyl acetate and benzoylation of o-HAP steps. Phenol was acetylated resulting 93% phenyl acetate. AlCl3-catalyzed Fries rearrangement in 1.5 hour and at 120 °C converted phenyl acetate into o-hydroxyacetophenone (o-HAP) with 40% yield. AlCl3 as catalyst produced o-HAP with higher and reproducible yield compared with BF3·Et2O and ZnCl2. Benzoylation of o-HAP followed by Baker-Venkataraman rearrangement of the ester product using KOH in dried pyridine produced β-diketone 1-(2- hydroxyphenyl)-3-phenylpropane-1,3-dione. The yield of ester and β-diketone were 71% and 85%, respectively. Finally, oxidative cyclization of β-diketone with sulphuric acid as catalyst produced 99% of flavone. The flavone product had been characterized spectroscopically and its melting point as well.
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