Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering)
Jurnal Teknik Pertanian Lampung or Journal of Agricultural Engineering (JTEP-L) is a peer-reviewed open-access journal. The journal invites scientists and engineers throughout the world to exchange and disseminate theoretical and practice-oriented researches in the whole aspect of Agricultural Enginering including but not limited to Agricultural Mechanization, Irrigation, Soil and Water Engineering, Postharvest Technology, Renewable Energy, Farm Structure, and related fields. The first issue was published in October 2012 by Department of Agricultural Engineering, Faculty of Agriculture, University of Lampung. Jurnal Teknik Pertanian Lampung has ISSN number 2302 - 559X for print edition on October 10, 2012 then 2549 - 0818 for online edition on January 10, 2017. Jurnal Teknik Pertanian Lampung is issued periodically four times a year in March, June, September, and December. Jurnal Teknik Pertanian Lampung has been indexed by Google Scholar, Crossref, Directory Open Access Journals (DOAJ), and CABI. Since Volume 5 Issue 1 (2016) Jurnal Teknik Pertanian Lampung has been accredited as SINTA 3 by Directorate General of Higher Education (DIKTI). Starting Volume 10 Issue 3 (2021) the journal received accreditation SINTA 2.
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<![CDATA[Physical and Mechanical Characteristics of Natural Adhesives in the Preparation of Composite Boards from Coconut Fiber as an Effort to Address Environmental Issues ]]>
<![CDATA[Mikhael Farly Gahung]]>;
<![CDATA[Dedie Tooy]]>;
<![CDATA[Ireine Adriana Longdong]]>
<![CDATA[ Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol 13, No 2 (2024): June 2024 ]]>
Publisher : <![CDATA[The University of Lampung ]]>
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DOI: 10.23960/jtep-l.v13i2.319-328
<![CDATA[This research aimed to develop coconut fiber boards using a mixture of cassava starch adhesive with a focus on examining the physical characteristics (density, moisture content, and thickness development) and mechanical properties (modulus of elasticity and modulus of rupture) of the composite boards made from coconut fiber using cassava starch adhesive with the addition of 25% citric acid. Additionally, the research evaluated the physical and mechanical characteristics of the fiberboards, following the guidelines of SNI 01-4449-2006 using an experimental method. The results showed that the fiberboards produced from coconut fiber and modified cassava starch adhesive (25% citric acid) exhibited specific physical characteristics. The density, moisture content, and thickness development ranged from 0.46 to 0.57 g/cm³, 13.18% to 14.39%, and 8.39% to 10.60% after two hours of soaking as well as 19.05% to 32.06% after 24 hours. Furthermore, the mechanical properties of the boards indicated a modulus of elasticity (MOE) and a modulus of rupture (MOR) ranging from 19247.33 to 42740.38 kg/cm² and 116.36 to 178.07 kg/cm², respectively. These findings are expected to provide valuable information for further research to obtain environmentally friendly adhesive materials. Keywords: Agriculture, Coconut fiberboard, Environmental friendly, Natural adhesive, Wood.]]>
<![CDATA[Optimization of Red Ginger (Zingiber officinale var. Rubrum) Extraction Using Microwave Assisted Hydrodistillation Method ]]>
<![CDATA[Sarifah Nurjanah]]>;
<![CDATA[Sari Rosalinda]]>;
<![CDATA[Dwita Putri Andina]]>
<![CDATA[ Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol 13, No 2 (2024): June 2024 ]]>
Publisher : <![CDATA[The University of Lampung ]]>
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DOI: 10.23960/jtep-l.v13i2.369-380
<![CDATA[Red ginger is a spice plant that has high economic and social value. One of the uses of red ginger is to process it into a product, namely essential oil. This study aims to determine the optimization of the extraction process conditions on solvent volume, time, and extraction power that can produce optimum yield and residual content of red ginger essential oil solvent. The extraction was carried out with the help of microwaves. The research method is experimental design and optimization process with Response Surface Methodology (RSM) type Box-Behnken Design (BBD). The results showed that the optimum yield was at 700 mL solvent volume, 1 min extraction time, and 10% power (69.9 watts) with the equation Y = 0.2076 + 0.0262A – 0.0300B – 0.0013C and the concentration conditions the optimum remaining solvent with the equation Y = 4.98 – 1.0000A + 4.56B + 5.44C. The optimal yield of red ginger essential oil was 0.205%, with a residual solvent content of 3.8%, specific gravity 0.885, acid number 1.399, refractive index 1.485. The results of the optimum residual solvent content of -6.023%. Based on the results obtained, the yield value with the help of microwaves is higher than that without the help of microwaves. Keywords: Essential oil, Microwave, Residual solvent content, Response surface methodology (RSM), Yield.]]>
<![CDATA[Enhancing Mini Greenhouse Design: A CFD Analysis of Temperature, Humidity, and Wind Flow Distribution ]]>
<![CDATA[Irriwad Putri]]>;
<![CDATA[Rahmah Tasya Aldi]]>;
<![CDATA[Ashadi Hasan]]>
<![CDATA[ Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol 13, No 2 (2024): June 2024 ]]>
Publisher : <![CDATA[The University of Lampung ]]>
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DOI: 10.23960/jtep-l.v13i2.381-393
<![CDATA[Research has been carried out on simulating the distribution of temperature, humidity and wind direction in a mini greenhouse using CFD ansys with several fan speed variations. This study aims to simulate the microclimate in a mini greenhouse, namely in the form of temperature, humidity and wind direction with variations in fan speed, namely with speeds of 1.7 m/s, 2.0 m/s and 2.2 m/s. Field measurement data regarding temperature, humidity (RH) in the tunnel-type mini greenhouse that has been carried out is used as input or input to the boundary conditions in the CFD mini greenhouse simulation. The results of the mini greenhouse CFD simulation using Ansys FLUENT are shown in the form of contour images of each condition. Temperature distribution contour, the humidity distribution contour (RH) and the airflow velocity distribution contour indicated by the vector will be used as the focus of this research. The numerical simulation shows quite good results when compared with the results of measurements in the field with the maximum error value obtained, which is 4.04%. Keywords: Computational Fluid Dynamics, Humidity, Simulation, Temperature, Wind direction.]]>
<![CDATA[Effect of Preprocessing and Augmentation Process in Development of a Deep Learning Model for Fusarium Detection in Shallots ]]>
<![CDATA[Yuvicko Gerhaen Purwansya]]>;
<![CDATA[Mohamad Solahudin]]>;
<![CDATA[Supriyanto Supriyanto]]>
<![CDATA[ Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol 13, No 2 (2024): June 2024 ]]>
Publisher : <![CDATA[The University of Lampung ]]>
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DOI: 10.23960/jtep-l.v13i2.350-360
<![CDATA[As the demand for shallot increases, wide-scale cultivation area must be managed efficiently. However, shallot productivity decreases every year because of plant diseases. Fusarium disease has an intensity up to 60% and can affect yield losses up to 50%. This study was conducted to develop the fusarium disease detection system for shallot using deep learning model and analyze the effect of preprocessing and augmentation adjustment. This study used YOLOv5 deep learning algorithm consisting of the following stages: (1) dataset acquisition, (2) dataset annotation, (3) dataset preprocessing and augmentation, (4) dataset training and validation, and (5) model testing and evaluation. A total 9,664 annotated dataset was trained to YOLOv5m pre-trained weights. Based on testing and evaluation results, precision, recall, and mean average precision (mAP) metrics of the model without preprocessing and augmentation were 55.5%; 54%; and 48.3% respectively. Metric values of the model were increased to 57.6%; 58.4%; and 54.1% respectively with adjustment of preprocessing and augmentation combination process. Percentage increase in metrics when compared to the control model for each value of precision, recall, and mAP were 2.1%; 4.4%; and 5.8%. This shows a significant impact on the addition of preprocessing and augmentation processes that match the characteristics of the dataset to increase the value of model performance. Keywords: Augmentation, Deep learning, Fusarium, Shallot.]]>
<![CDATA[Cover Vol 13 No 2, June 2024 ]]>
<![CDATA[Agus Haryanto]]>
<![CDATA[ Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol 13, No 2 (2024): June 2024 ]]>
Publisher : <![CDATA[The University of Lampung ]]>
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DOI: 10.23960/jtep-l.v13i2.%p
<![CDATA[Redesign and Performance Test of Liquid Fertilizer Based on Variable Rate Application on Chili Cultivation ]]>
<![CDATA[Andi Muh. Saldan]]>;
<![CDATA[Radi Radi]]>;
<![CDATA[Bambang Purwantana]]>;
<![CDATA[Lilik Sutiarso]]>
<![CDATA[ Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol 13, No 2 (2024): June 2024 ]]>
Publisher : <![CDATA[The University of Lampung ]]>
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DOI: 10.23960/jtep-l.v13i2.339-349
<![CDATA[Liquid fertilizer applicator based on Variable Rate Application (VRA) is a technology that is used to fertilize in a controlled and precise manner. This study aims to improve the effectiveness and efficiency of the fertilization process of chili plants. The development carried out is esp32 cam which serves to detect chili plants that lack elements. The method used is input of the nutritional needs of chili plants, spray doses of each plant, and a microcontroller to control applicator components such as sprayer pumps, selenoid valve, and esp32 cam. In this liquid fertilizer applicator there are 2 pipes, each pipe has 4 nozzles. The results of laboratory tests show that the discharge of liquid fertilizer sprayed follows the input results of the nutritional needs of chili plants. The discharge released on the PWM sprayer motor varies from 40 to 100% resulting in very different discharge variations in each PWM spray. The efficiency of this VRA-based liquid fertilizer applicator reaches 87% or an increase of about 14.7% from the applicator before development. Regression analysis of dimmer level to spraying discharge showed a function y = 6.3016x + 18.937 with an R 2 of 0.9921. While the regression analysis of the dimmer level of the applicator speed obtained the function y = 94.075x + 20.203 with an R2 of 0.9936. Keywords: Chili plants, Liquid, Fertilizer, Applicator, VRA.]]>
<![CDATA[Development of Microalgae Growth Monitoring System Using TSD-10 Sensor and ThingSpeak Platform ]]>
<![CDATA[I Dewa Made Subrata]]>;
<![CDATA[Mulki Azmi Novrizal]]>
<![CDATA[ Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol 13, No 2 (2024): June 2024 ]]>
Publisher : <![CDATA[The University of Lampung ]]>
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DOI: 10.23960/jtep-l.v13i2.394-404
<![CDATA[Microalgae chlorella sp. is one of the low-level plants that has many benefits and need to be harvested when they have reached optimum density. This study aims to develop a microalgae density monitoring system using the TSD-10 sensor and the ThingSpeak platform. The output voltage from the TSD-10 sensor was calibrated into microalgae density using hemocytometer and then sent wirelessly to the ThingSpeak cloud server using the ESP8266 module. A linear equation of y = –1.633 x +1421.3 was obtained from the calibration process where y is microalgae density (cell/ml) and x is analog to digital conversion (ADC) value of the TSD-10 sensor. The determination coefficient of the calibration and validation process is 0.9921 and 0.938 respectively. The measurement stability was quite good with a standard deviation ranging from 1.15×104 cell/ml to 2×104 cells/ml of culture medium. The measurement accuracy of the validation process using the RMSE (Root Mean Square Error) formula is 3.25. The time response of the sensor after power on is 5.85 s and the time it takes to display data on the ThingSpeak cloud is 16.03 s. Thus the measuring instrument developed can be said to have a fairly good performance. Keywords: Density monitoring, Microalgae, ThingSpeak platform, Tsd-10 sensor.]]>
<![CDATA[Physical Quality of Tomato Powder (Lycopersicum Esculentum Mill.) Produced by Foam-Mat Drying Method Using Convection Oven ]]>
<![CDATA[Dian Purbasari]]>;
<![CDATA[Gerry Ardhyansyah]]>
<![CDATA[ Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol 13, No 2 (2024): June 2024 ]]>
Publisher : <![CDATA[The University of Lampung ]]>
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DOI: 10.23960/jtep-l.v13i2.329-338
<![CDATA[Tomatoes (Lycopersicum esculentumMill.) have a fairly low shelf life, therefore further processing is needed to increase the shelf life and economic value of tomatoes, one of which is by processing it into tomato powder. The purpose of this study was to determine the physical quality of tomato powder produced from foam drying in a convection oven at different temperature variations and concentrations of Tween 80. This research method used a completely randomized design with two treatment variables, namely temperature and concentration of foaming agent Tween 80. The temperatures used were 60, 70, and 80°C while the concentration of Tween 80 used was 0.4; 0.7; and 1.0%. Data analysis used a two-way ANOVA test followed by the Duncan test and correlation test. The physical quality parameters of tomato powder showed values of the fineness modulus ranging from 1.19 – 1.77; the grain size value ranges from 0.0094 – 0.0141 mm; powder moisture content values range from 5.36 – 6.48%bb; L values range from 76.20 – 79.01; a value ranges from 12.51 – 14.81; b values range from 18.21 – 21.73; bulk density values range from 0.56 – 0.63 g/cm3; oil absorption value ranges from 0.85 – 0.89 ml/g; angle of repose values range from 33.65 – 36.09°. The temperature difference affects the fineness modulus, grain size, and moisture content. While the difference in the concentration of Tween 80 affects the color parameters (L, a, b), bulk density, and angle of repose. Keywords: Drying, Foaming agent, Physical Quality, Temperature, Tomatoes.]]>
<![CDATA[Improving the Taste of Robusta Coffee by Fermentation with Yeast Inoculum and Its Effect on Caffeine Content ]]>
<![CDATA[Hani Fildzah Nadya]]>;
<![CDATA[Usman Ahmad]]>;
<![CDATA[Samsudin Samsudin]]>
<![CDATA[ Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol 13, No 2 (2024): June 2024 ]]>
Publisher : <![CDATA[The University of Lampung ]]>
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DOI: 10.23960/jtep-l.v13i2.298-308
<![CDATA[Harvesting coffee process by farmers generally executed entirety, resulting rainbow harvest. Coffee fermentation with yeast starter cultures Saccharomyces cerevisiae Y612, Candida parapsilosis Y207 and Torulospora delbrueckii Y594 was executed separately to determine the role of starter cultures on caffeine and robusta coffee taste at different maturity levels. The study was conducted at the Indonesian Industrial and Beverage Crops Research Institute in Sukabumi,, from June to November 2022. The experiment used a factorial complete randomized design. The first factor was the maturity level of the coffee and starter culture as the second factor. Fermentation was implemented for 48 hours inoculated with 108 cells/mL starter culture. The results showed that the temperature fluctuated, the pH value always decreased to 4.50 and T. delbrueckii was the starter culture with the highest activity during fermentation. Inoculum-fermented robusta coffee caffeine content was higher than non-inoculum. The lowest caffeine content was found in spontaneously fermented red fruit of 1.39%, while the highest caffeine content was produced by red fruit samples inoculated with C. parapsilosis of 2.7%. Robusta coffee with S. cerevisiae inoculation brought the best taste of robusta coffee with 82.10%, there was no significant difference between the red harvest coffee fruit and the fermented rainbow color with a starter culture. Keywords: Caffeine, Harvest, Inoculation, Maturity level, Starter cultures]]>
<![CDATA[The Influence of Extremely Low Frequency (ELF) Waves for Pasteurization of Cow Milk ]]>
<![CDATA[Anang Supriadi Saleh]]>;
<![CDATA[Yossi Wibisono]]>
<![CDATA[ Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol 13, No 2 (2024): June 2024 ]]>
Publisher : <![CDATA[The University of Lampung ]]>
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DOI: 10.23960/jtep-l.v13i2.361-368
<![CDATA[The extremely low frequency (ELF) magnetic field exposure technology for food processing and preservation is a future technology that produces better food quality. This research aims to examine the exposure of extremely low frequency (ELF) magnetic field waves to pasteurized cow milk and its effect on pH, chemical content, total microbial count, and sensory tests. This research was carried out by exposing ELF waves of 834.8 micro Tesla (μT) for 90 minutes to fresh milk and pasteurized milk. Samples were stored at room temperature then observed at 0, 2, 6, and 21 hours. Each treatment was repeated three times. The results showed that exposure to ELF waves had no effect on chemical content (P<0.05). The pH measurement shows that exposure to ELF waves could maintain the pH value. The total microbial count showed that exposure to ELF waves had an effect on reducing the total microbial count. The organoleptic test showed that pasteurized milk exposed to ELF waves had a smaller level of change. Based on observations, exposure to ELF waves has the potential to be developed in pasteurization, storage of cow milk, and retain its nutritional content. Keywords: Cow milk, Exposure, Extremely low frequency, Influence, Pasteurization.]]>
