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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Journal of Environmental Engineering and Sustainable Technology INDONESIAN JOURNAL OF ESSENTIAL OIL
Candra Dewi
Brawijaya University
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Energy Environmental Science Mechanical Engineering

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Identifying Citronella Plants From UAV Imagery Using Support Vector Machine Candra Dewi; Achmad Basuki
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 4: August 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i4.7450

Abstract

High-resolution imagery taken from Unmanned Aerial Vehicle (UAV) is now often used as an alternative in monitoring the agronomic plants compared to satellite imagery. This paper presents a method to identify Citronella among other plants based on UAV imagery. The method utilizes Support Vector Machine (SVM) to classify Citronella among other plants according to the extraction of texture feature. The implementation of the method was evaluated using two group of datasets: 1) consists of Citronella, Kaffir Lime, other green plants, vacant soil, and buildings, and 2) consists of Citronella and paddy rice plants. The evaluation results show that the proposed method can identify Citronella on the first group of datasets with an accuracy 94.23% and Kappa value 88.48%, whereas on the second group of datasets with an accuracy 100% and Kappa value 100%.
Design Of Web Based Monitoring System For Essential Plantation Candra Dewi; Gusti Ngurah Wisnu Paramartha; Rakhmadina Noviyanti; Enny Trisnawati
INDONESIAN JOURNAL OF ESSENTIAL OIL Vol 2, No 1 (2017)
Publisher : Institut Atsiri Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (635.653 KB) | DOI: 10.21776/ub.ijeo.2017.002.01.06

Abstract

The world needs of essential oil that is high and the limitations of plant cultivation in Indonesia, requires management planning of essential products. To increase the production of agroforestry especially essential both in terms of quantity, quality and continuity of provision, the necessary supply of raw materials, one of which comes from essential plant. The availability of actual and accurately data and information about the essential plants in a certain scale and are available on a regular basis is necessary. Therefore, the planning can be implemented effectively and efficiently. It is very necessary to develop a system that can be used to manage and monitor the availability of essential plant information. This paper presents the design of a system to monitor essential plant in East Java in particular and Indonesia in general. The system is developed as a web-based system with a database that can be used to store data and information about plant essential. Design includes identification of information needs to be stored in the system, database design, process design and interface design. With the existence of this database, essential data such as the distribution of plant species, planting location, owner, size, and so forth will be stored and can be accessed by various parties easily and quickly.
IDENTIFICATION OF PATCHOULI LEAVES QUALITY USING SELF ORGANIZING MAPS (SOM) ARTIFICIAL NEURAL NETWORK Kartika Purwandari; Candra Dewi; Imam Cholissodin
Journal of Environmental Engineering and Sustainable Technology Vol 3, No 1 (2016)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (671.627 KB) | DOI: 10.21776/ub.jeest.2016.003.01.6

Abstract

One of the essential oil export commodities from Indonesia is patchouli oil. However, the price of patchouli todays is unstable caused by the low quality of the oils, which has high levels of acid and lower alcohol content. One part of patchouli that is widely used to obtain essential oils is the leaf. The better quality of leaves will produce oil with grade quality. The quality of the leaves can be identified by its physical characteristics. Leaves that have a good quality are small leaves, thick and slightly yellowish red color. This identification process can be done visually, but, it will be easier if it can be done automatically using computer applications. Therefore, this paper performs automatic identification of leaves utilizing image of patchouli leaves and artificial neural network algorithm Self Organizing Maps (SOM). Identification was done to distinguish the leaves with good quality and poor. From the test results using the initial learning rate 0.1, 0.3 deduction learning rate, the minimum rate learning 0.0001, 40 training data and testing the data 60 obtained an average accuracy of 82.82%.
Co-Authors Achmad Basuki Enny Trisnawati Gusti Ngurah Wisnu Paramartha Imam Cholissodin Kartika Purwandari Rakhmadina Noviyanti