Judul: Analisis Perbandingan Kandungan Serat Pangan Daun Kolesom (Talinum triangulare (Jacq.) Willd) dengan Pemupukan Organik dan Anorganik pada Perbedaan Musim
Abstrak: Waterleaf (Talinum triangulare (Jacq.) Willd) is one of tropical plant and has long been used as herbs and vegetable in daily menu. Its leaves are fleshy and sticky, presumably due to the high pectin content. Pectin is soluble dietary fiber component that performs ability to reduce cholesterol and LDL level in blood. The aim of this research was to study the effect of organic and inorganic fertilization as well as the cultivating season to the level of TDF, IDF, SDF and pectic substance in waterleaf. The research was conducted in five steps, i.e. cultivation, sample preparation, chemical analysis, data analysis, and meta analysis. The samples were ten waterleaf cultivated in dry season with organic and inorganic fertilizations, each in five different concentration of fertilizers. The TDF, IDF, SDF, and pectic substance in waterleaf cultivated with organic fertilizer were 40.52 2.72; 27.12 1.54; 13.40 1.68; and 6.58 0.74 g/100 dry basis respectively, while in waterleaf with inorganic fertilizer were 42.57 1.84; 27.12 0.75; 15.41 1.85; and 6.01 0.35 g/100 g dry basis respectively. All parameters, except IDF, were significantly different (p < 0.05). The meta analysis showed that the dry season waterleaf contain less TDF and IDF, and more SDF and pectic substance than the wet season waterleaf do (p < 0.01). The SDF and pectic substance content of the dry season waterleaf are relatively higher compared to other vegetables. It indicates that waterleaf is potential to be developed as functional food for lowering cholesterol and LDL level in blood.
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Judul: Kandungan Serat Pangan Daun Kolesom (Talinum Triangulare (Jacq.) Willd) pada Budidaya dengan Pemupukan Organik dan Anorganik
Abstrak: Water leaf (Talinum triangulare (Jacq.) Willd is one of tropical vegetables which widely grown in Indonesia and has long been used as traditional medicinal plant. Water leaves are sticky presumably due to its pectin content. Pectin is soluble dietary fiber component that performs ability to reduce LDL level in blood. The aim of this research is to study the effect of organic and inorganic fertilization to the level of TDF, IDF, SDF, and pectic substances in water leaf vegetable. This research was conducted in four phases: sample cultivation, sample preparation, chemical analysis, and data analysis. This research used five samples cultivated with organic fertilizers and five samples cultivated with inorganic fertilizers. Samples were dried using drying oven for 17 hours at 60 C. The result shows that TDF, IDF, and SDF level of organic and inorganic water leaf vegetables are significantly different with each p-value of 0,026; 0,022; and 0,215 respectively. Meanwhile, the level of pectic substance is not significantly different for both treatments with p-value of 0,718. Overall result shows that inorganically cultivated samples contain higher dietary fiber and pectic substance than organically fertilized samples. IDF content in water leaf vegetable is higher than its SDF content. It means that dietary fiber in water leaf can help the intestinal health. However, pectic substance contents, which is also part of SDF, are relatively similar in all samples and did not affected by the cultivation treatment. It indicates that water leaf vegetable has the potential to be developed as functional food.
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Judul: Estimating Parameter and the Convergence of Parameter Estimator of Poisson Hidden Markov Model
Abstrak: Model hidden Markov terdiri dari sepasang proses stokastik yaitu proses observasi dan proses yang memengaruhi observasi. Proses stokastik yang memengaruhi observasi ini diasumsikan membentuk rantai Markov dan tidak diamati. Model Poisson hidden Markov (MPHM) adalah salah satu model hidden Markov diskret dan proses observasinya jika diketahui proses yang memengaruhinya diasumsikan menyebar Poisson., A hidden Markov model (HMM) consists of a pair of stochastic processes, that is the observation process and process that affected observation. The stochastic process which causes this observation is assumed to form a Markov chain and is not observed. Poisson hidden Markov models (PHMM) is one of the discrete HMM and the observation process given the cause is assumed having a Poisson distribution.
Keyword: Poisson hidden Markov model, Forward-Backward algorithm, Expectation Maximization algorithm