Judul: Allelopathic Effects between Chili (Capsicum annuum L.) and Potato (Solanum tuberosum L.) Plants on Vegetative Growth: An ex vitro Assay
Abstrak: Budidaya tanaman cabai (Capsicum annuum L.) dan kentang (Solanum tuberosum L.) di Indonesia banyak dilakukan dengan teknik tumpang sari karena dinilai lebih mampu meningkatkan produktivitas lahan. Salah satu syarat tanaman yang akan ditumpangsarikan adalah tidak mendapatkan pengaruh buruk alelopati dari tanaman lain di sekitarnya. Penelitian ini bertujuan menganalisis efek alelopati antara tanaman cabai dan tanaman kentang terhadap pertumbuhan kedua tanaman tersebut, serta menguji alelokimia yang terkandung dalam media tumbuhnya secara kualitatif. Metode penelitian ini menggunakan rancangan acak lengkap (RAL) dengan tiga perlakuan. Perlakuan pertama (P1), bibit cabai dan kentang ditanam pada media bekas tanaman lain dari spesies yang sama setelah dua minggu penumbuhan, lalu pertumbuhannya diamati selama satu minggu; perlakuan kedua (P2), bibit cabai dan kentang ditanam pada media bekas tanaman lain dari spesies yang berbeda setelah dua minggu penumbuhan, lalu pertumbuhannya diamati selama satu minggu; dan perlakuan ketiga (P3), bibit cabai dan kentang ditanam berdampingan pada satu media yang sama selama tiga minggu. Kontrol (K) berupa bibit cabai dan kentang ditanam secara monokultur selama tiga minggu. Hasil penelitian menunjukkan adanya efek alelopati antara tanaman cabai dan kentang yang bersifat menghambat pertumbuhan cabai, dan perlakuan P3 memberikan hambatan pertumbuhan paling besar dibandingkan perlakuan lainnya. Tanaman cabai juga diduga memiliki efek autotoksisitas yang bersifat menghambat pertumbuhannya. Efek alelopati antara kedua tanaman tersebut tidak dapat diamati pada kentang karena tanaman mati akibat pengaruh lingkungan yang kurang sesuai. Hasil uji kualitatif alelokimia menunjukkan semua media tanam, baik pada cabai maupun kentang tidak mengandung senyawa fenolat, namun semua media perlakuan cabai yang berinteraksi dengan tanaman kentang (perlakuan P2 dan P3) dan semua media tanam kentang positif mengandung alkaloid. Hal ini menunjukkan bahwa hambatan pertumbuhan yang terjadi disebabkan efek alelopati antar kedua jenis tanaman tersebut, antara lain oleh kelompok senyawa alkaloid.
Keyword: alkaloids, allelochemicals, intercropping, plants interactions

Judul: Pengaruh aplikasi bakteri perakaran pemacu pertumbuhan tanaman pada tiga genotipe cabai (Capsicum annum L.) terhadap pertumbuhan tanaman serta kejadian penyakit penting cabai
Abstrak: In Indonesia, chilli was an important vegetable commodity refer to production area as well as it’s value, but production of chilli in Indonesia still very low. The low production was caused by a lack of proper cultivation techniques, seed quality, and pest and plant disease. Important disease that can decrease the production of chilli includes antrachnose disease, bacterial wilt, mosaic and mottle virus in chilli. The disease controlling effort that were recently developed and relatively safe for the environment, using Plant Growth-promoting Rhizobacteria (PGPR). The objective of this study was to determine the effect of PGPR usage, that were P. fluorescens PG01 isolates, B. polymixa BG25 and a mixture of both isolates (PG01 + BG25) against agronomic characters and incidence of important diseases in the three genotypes of chilli (IPB C5, C10 IPB, and Kopay) on the field. The experiment was performed from February until November, 2009 on farmer land were located on Desa Cibatok I, Kecamatan Cibungbulang, Kabupaten Bogor. The experiment was arranged in split plot design, were randomly treated with bacterial group as main plots and genotypes as subplots. Four levels main plots were PGPR treatments isolates PG01, BG25, PG01 + BG25, and without PGPR treatment as a comparison. The three subplots were C10 IPB, C5 IPB, and Kopay. In the experiment there were 12 treatment combinations, each treatment consisted of three replications, so there are 36 experimental units. Each experimental unit consisted of 20 plants, with a total 720 plants were tested. PGPR treatments significantly influenced the plant height and number of branches, but gave no significant effect on leaves number. The highest growth improvement on vegetative phase was occurred by the mixed bacterial treatment (PG01 + BG25). IPB C10, C5 genotypes and varieties of IPB Kopay have different agronomic characteristics measured on plant height, number of branches and number of leaves. PGPR treatment did not affect significantly to crop production and disease incidence (antraknosa, bacterial wilt, TMV, CMV, and ChiVMV). Antrachnose infections most commonly found in Kopay varieties, while the bacterial wilt infection occurs more frequently in genotypes IPB C5.
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Judul: Signature Recognition using VFI5 Algorithm and Wavelet Preprocess.
Abstrak: Biometric is a science in recognizing the identity of a person based on their physical or behavioral traits. Today, one of the most widely applied biometric object is hand-written signature. In this research, we tried to identify offline handwritten signature using VFI5 (Voting Feature Intervals 5) classification algorithm. The VFI5 classification algorithm has been used previously on non-image objects with promising result. The feature used in the classification is the grayscale value of the image and the signature image dimension used in this research is 40×60 pixels which means originally there are 2400 features that relatively large to compute. Thus, Haar wavelet transform is used to reduce the dimension. This is done by taking only the approximation image of the transformation result, and leave the horizontal, vertical, diagonal details. The wavelet decomposition is applied until the fifth level, creating new low level images with 20×30, 10×15, 5×8, 3×4, 2×2 dimension respectively for the first, second, third, fourth, and fifth decomposition levels. The approximation images then classified using VFI5 algorithm, with 97.5%, 95%, 90%, 65%, and 62.5% accuracy respectively for the first, second, third, fourth, and fifth decomposition levels. It turned out that VFI5 algorithm can be used to identify images with wavelet transform to reduce the image dimension with good result, and the higher decomposition level applied, the more accuracy dropped. Keywords: signature identification, wavelet image dimension reduction, image classification, VFI5 algorithm.
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