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Abstrak :
ABSTRAK
Tanaman pisang merupakan tanaman khas daerah tropis yang dapat dengan mudah dijumpai dimana saja tanpa mengenal musim. Sampai saat ini di Indonesia pemanfaatan tanaman pisang baru sebatas pembudidayaan buah dan masih sangat sedikit pemanfaatan bagian lainnya dari pohon pisang ini. Dinegara seperti di Filipina, India, Brazil pisang sudah dibudidayakan secara intensif untuk keperluan tekstil, kertas yang bernilai tinggi, bahkan Mercedes Benz sudah merekayasanya untuk panel interior mobil sedan yang diproduksinya. Penelitian ini berusaha mencari serat pisang yang potensial memiliki kekuatan mekanik yang baik dan merekayasanya menjadi komposit untuk keperluan panel interior otomotif atau bahkan pesawat terbang. Dalam penelitian ini masih dipergunakan matriks epoksi, dan akan diupayakan matriks alam dalam penelitian selanjutnya sehingga dapat diperoleh komposit alam 100%. Dari penelitian tahun pertama ini dari serat-serat yang dipelajari diperoleh serat pisang Abaca paling potensial untuk rekayasa dan manufaktur komposit untuk panel interior otomotif atau pesawat terbang. Kekuatan tarik lamina [0] dan laminat [0,90] mencapai lebih dari 100 Mpa dengan Modulus Young mencapai 5 Gpa. Sampai saat ini masih sedang dijalankan pengujian kestabilan dimensi, siklus panas dingin, impak suhu dingin dan ketahanan warna.

Abstrak :
Indonesia has the world's largest tropical peatlands of about 14.9 million hectares that have important life support roles. However, fire frequently occurs in peatlands. According to experts and field forest fire fighters, fire hotspots that appear in a sequence of two to three days at the same location has a high potential of becoming a forest fire. This study aimed to determine the sequential patterns of hotspot occurrences, classify satellite image data and identify the fire spots. Fire spot identification was done using hotspot sequence patterns that were overlaid with burned area classification results. Sequential pattern mining using the Prefix Span algorithm was applied to identify sequences of hotspot occurrence. Maximum Likelihood method was applied to classify Landsat 7 satellite images toward identifying burned areas in Pulang Pisau and Palangkaraya in Central Kalimantan and Pontianak in West Kalimantan. Sequence patterns were overlaid with image classification results. The study results show that in Pulang Pisau, 26.19% of sequence patterns are located in burned areas and 72.62% sequence patterns were found in the buffer of burned area within a radius of one kilometer. As for Palangkaraya, there were 62.50% sequence patterns located in burned areas and 87.50% sequence patterns in the buffer of burned area with the radius of one kilometer. In total, Â there were 72.62% and 87.50% fire hotspots recorded in Pisau and Palangkaraya, respectively which are strong indicators of peatland fires.