Claim Missing Document
Check
Articles

Found 4 Documents
Search
Journal : Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering)

Non-Destructive Measurement of Rice Amylose Content Based on Image Processing and Artificial Neural Networks (ANN) Model Tri Wahyu Saputra; Yagus Wijayanto; Suci Ristiyana; Ika Purnamasari; Wildan Muhlison
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol 11, No 2 (2022): June
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v11i2.231-241

Abstract

The purpose of this study was to develop a method of measuring the amylose content of rice using image processing techniques and an Artificial Neural Network (ANN) model. The rice samples came from six varieties, namely Way Apo Buru, Mapan P05, IR-64, Cibogo, Inpari IR Nutri Zinc, and Inpari 33. The amylose content was measured by laboratory tests and the color intensity was measured based on the RGB (Red, Green, Blue). The ANN model will correlate the RGB color intensity as input with the amylose content as the output. The ANN model used is backpropagation type with 3 input layer nodes and 2 hidden layers with 3-5-5-1 architecture. Variations in the training model used are 27 variations of the activation function. The amount of data used for model training of 30 data while for validation of 12 data. The best ANN model is determined from the high value of accuracy (100%-MAPE) and the value of coefficient of determination (R2). The results showed the best network architecture on the activation function purelin-logsig-tansig. The R2 value on the best training and validation results of 0.98 and 0.66 while the accuracy values for the best training and validation results of 98.15 and 66.82. The validation results show that the developed non-destructive method can be used to quickly and accurately measure the amylose value of rice based on RGB color value. The test results show that the non-destructive method developed cannot be used to measure the amylose content of rice quickly and accurately based on the RGB color intensity, so it needs further development. Keywords:   Amylose, Artificial neural networks, Image processing, Rice
The Effect of Nutritioning Interval on Automatic Drip Hydroponic System on Growth and Production of Three Varieties of Lettuce (Lactuca sativa L.) Ristiyana, Suci; Fanata, Wahyu Indra Duwi; Saputra, Tri Wahyu; Purnamasari, Ika; Dewanti, Parawita; Taufik, Rahadian Falqi
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol 14, No 1 (2025): February 2025
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v14i1.146-154

Abstract

Lettuce (Lactuca sativa L.) is a leaf vegetable that has a high level of consumer demand and commercial value and can be cultivated using a combination of hydroponic substrate and drip irrigation methods. This research aims to determine the effect of the time interval for providing nutrients on the growth and harvest results of three lettuce plant varieties. Plants were cultivated on cocopeat and husk charcoal media (ratio 1:3) and arranged using a Randomized Block Design (RAK) consisting of two treatments. The first treatment is the nutritional interval which consists of an interval of 2 hours with a discharge of 17 ml (I1), 3 hours with a discharge of 25 ml (I2), and 4 hours using a discharge of 34 ml (I3). The second treatment is the plant variety which consists of the Grand Rapids variety (V1), the Green Coral variety (V2), and the Red Coral variety (V3). The data is analyzed using analysis of variance and if the results obtained are significantly different then a DMRT test will be carried out. The research results showed that the Green Coral lettuce variety was better than the Grand Rapids and Red Coral varieties. This is shown by the results with the highest and best values for the observation variables of number of leaves, plant fresh weight, and chlorophyll content. The nutritional interval which consists of an interval of 2, 4, and 6 hours gave results that were inversely proportional to the variety treatment, that is, they were not significantly different in all observed variables. Keywords: lettuce plants, plant varieties, nutritional interval, substrate hydroponics
Development of Irrigation Networks Based on Priorities Using the Multiple Attribute Decision Making Method Ristiyana, Suci; Saputra, Tri Wahyu; Purnamasari, Ika; Wijayanto, Yagus; Alfatah, Naufal Akbar; Al-Ghofiqi, M. Faris; Destria Putri, Romadhona; Prasojo, Sri Irawan Laras
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 14 No. 4 (2025): August 2025
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtepl.v14i4.1359-1368

Abstract

Development of irrigation networks is a crucial element in increasing the efficiency and effectiveness of water distribution for agriculture. This research aims to determine priorities for developing irrigation networks in the Bedadung Irrigation Area, Jember Regency, using the Multiple Attribute Decision Making (MADM) method. This method consider various criteria influencing decision-making, such as physical condition of the channel, land area, water requirements, and level of infrastructure damage. This research involved collecting primary and secondary data through field surveys, interviews with interpreters, as well as reviewing technical and administrative documents related to irrigation networks. Data was analyzed using several MADM techniques, such as Simple Additive Weighting (SAW), Weighted Product (WP), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to obtain the weight of each criterion and determine development priorities. The results show that the main priority for developing irrigation networks in the Bedadung Irrigation Area is repairing primary, secondary, and tertiary canals that are badly damaged, followed by increasing canal capacity to meet water needs in the dry season. Implementation of the results of this research is expected to increase the efficiency of irrigation water distribution, reduce water losses, and increase agricultural productivity.
The Effect of Nutritioning Interval on Automatic Drip Hydroponic System on Growth and Production of Three Varieties of Lettuce (Lactuca sativa L.) Ristiyana, Suci; Fanata, Wahyu Indra Duwi; Saputra, Tri Wahyu; Purnamasari, Ika; Dewanti, Parawita; Taufik, Rahadian Falqi
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 14 No. 1 (2025): February 2025
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v14i1.146-154

Abstract

Lettuce (Lactuca sativa L.) is a leaf vegetable that has a high level of consumer demand and commercial value and can be cultivated using a combination of hydroponic substrate and drip irrigation methods. This research aims to determine the effect of the time interval for providing nutrients on the growth and harvest results of three lettuce plant varieties. Plants were cultivated on cocopeat and husk charcoal media (ratio 1:3) and arranged using a Randomized Block Design (RAK) consisting of two treatments. The first treatment is the nutritional interval which consists of an interval of 2 hours with a discharge of 17 ml (I1), 3 hours with a discharge of 25 ml (I2), and 4 hours using a discharge of 34 ml (I3). The second treatment is the plant variety which consists of the Grand Rapids variety (V1), the Green Coral variety (V2), and the Red Coral variety (V3). The data is analyzed using analysis of variance and if the results obtained are significantly different then a DMRT test will be carried out. The research results showed that the Green Coral lettuce variety was better than the Grand Rapids and Red Coral varieties. This is shown by the results with the highest and best values for the observation variables of number of leaves, plant fresh weight, and chlorophyll content. The nutritional interval which consists of an interval of 2, 4, and 6 hours gave results that were inversely proportional to the variety treatment, that is, they were not significantly different in all observed variables. Keywords: lettuce plants, plant varieties, nutritional interval, substrate hydroponics