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All Journal Perfecting a Video Game with Game Metrics Proceeding of the Electrical Engineering Computer Science and Informatics Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE)
Muchnuria Rachmawati
Universitas Brawijaya
Agriculture, Biological Sciences & Forestry Computer Science & IT Electrical & Electronics Engineering Engineering Immunology & microbiology Industrial & Manufacturing Engineering Mechanical Engineering

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Image Analysis using Color Co-occurrence Matrix Textural Features for Predicting Nitrogen Content in Spinach Yusuf Hendrawan; Indah Mustika Sakti; Yusuf Wibisono; Muchnuria Rachmawati; Sandra Malin Sutan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 6: December 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i6.10326

Abstract

This study aimed to determine the nitrogen content of spinach leaves by using computer imaging technology. The application of Color Co-occurrence Matrix (CCM) texture analysis was used to recognize the pattern of nitrogen content in spinach leaves. The texture analysis consisted of 40 CCM textural features constructed from RGB and grey colors. From the 40 textural features, the best features-subset was selected by using features selection method. Features selection method can increase the accuracy of image analysis using ANN model to predict nitrogen content of spinach leaves. The combination of ANN with Ant Colony Optimization resulted in the most optimal modelling with mean square error validation value of 0.0000083 and the R2 testing-set data = 0.99 by using 10 CCM textural features as the input of ANN. The computer vision method using ANN model which has been developed can be used as non-invasive sensing device to predict nitrogen content of spinach and for guiding farmers in the accurate application of their nitrogen fertilization strategies using low cost computer imaging technology.
Development of Discrete-Cockroach Algorithm (DCA) for Feature Selection Optimization Yusuf Hendrawan; Muchnuria Rachmawati; Muchammad Fauzy
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (890.446 KB) | DOI: 10.11591/eecsi.v5.1639

Abstract

One of the recently proposed algorithms in the field of bio-inspired algorithm is the Hungry Roach Infestation Optimization (HRIO) algorithm. Haven has developed optimization algorithms HRIO that is inspired by recent discoveries in the social behaviour of cockroaches. Result showed that HRIO was effective at finding the global optima of a suite of test functions. However, there is no researcher who has observed HRIO for solving discrete problems. Therefore, we try to develop a discrete-cockroach algorithm (DCA) as the modification of HRIO for solving discrete optimization problem. We test the algorithm to solve bio-computation problem using single and multi-objectives optimization. The results showed DCA has better performance compared to the existed bio-inspired optimization algorithms such as genetic algorithms (GA) and discrete-particle swarm optimization (discrete-PSO).
Application of microwave assisted extraction in extracting Torbangun leaves (Coleus ambonicus, L.) and its effects on polyphenol and flavonoids content Yusuf Hendrawan; Niken Dieni Pramesi; Muchnuria Rachmawati; Bambang Susilo; Yusuf Wibisono; Shinta Rosalia Dewi; Ni'matul Izza
Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE) Vol 1, No 2 (2018)
Publisher : Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (953.802 KB) | DOI: 10.21776/ub.afssaae.2018.001.02.2

Abstract

Torbangun leaves (Coleus ambonicus, L.) contain polyphenol compounds, flavonoids and antioxidant compounds that can be obtained by extraction methods. However, with the conventional extraction method it has the disadvantage of long extraction time and requires a lot of solvents. Therefore, this study discusses the use of microwave assisted extraction (MAE) method to extract the leaves of Torbangun. This study uses two treatment factors on MAE i.e. power variations (100, 180 and 300 Watts) and extraction time (1, 2 and 3 minutes). This study aims to analyze the effect of MAE on the content of polyphenol compounds and flavonoids in the extraction process of Torbangun leaf. The results showed that the highest total phenol (4196.59 mg GAE/g extract) was found in the treatment of 300 watt of power with extraction time of 3-minutes with IC50 value of 9.89 mg/ml. The highest total flavonoid value was 300 watt of power with 1-minute extraction time which was 4.54 mg QE/g DW.
Co-Authors Bambang Susilo Indah Mustika Sakti Izza, Sylvia Ni’matul Muchammad Fauzy Niken Dieni Pramesi Sandra Sandra Shinta Rosalia Dewi Yusuf Hendrawan Yusuf Wibisono