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Jurnal Keteknikan Pertanian Tropis dan Biosistem
Published by Universitas Brawijaya
ISSN : -     EISSN : 2656243X     DOI : https://doi.org/10.21776/ub.jkptb
Core Subject : Science, Agriculture, Engineering,
Agriculture, Biological Sciences & Forestry Control & Systems Engineering Electrical & Electronics Engineering Energy Mechanical Engineering
Jurnal Keteknikan Pertanian Tropis dan Biosistem (JKPTB) (ISSN: 2656-243X) has published the state-of-art articles which focus on both fundamental studies and applied engineering including Power and Agricultural Machinery, Mechatronics and Agro-industrial Machinery, Food and Post-Harvest Technology and Soil and Water Engineering. By providing an update issue and current topic in agricultural technology field, JKPTB becomes the reference for many scientist and stakeholders who work on Agricultural Engineering
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 455 Documents
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Effect of a Fuzzy Neo-Based Temperature Control System on the Physicochemical Characteristics of Sweet Corn Yoghurt Yunira, Eka Nur'azmi; Az-zahra, Nilandra Ayu; Pratama, Borneo Satria
Jurnal Keteknikan Pertanian Tropis dan Biosistem Vol. 14 No. 1 (2026): April 2026
Publisher : Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jkptb.2026.014.01.09

Abstract

Milk can be utilized as a raw material in yoghurt production. The fermentation process of yoghurt involves Lactobacillus bulgaricus and Streptococcus thermophilus as lactic acid-producing microorganisms. The fermentation temperature is a crucial factor affecting the quality of yoghurt; therefore, an accurate temperature control system is required, one of which can be achieved through the implementation of the fuzzy control method. The addition of sweet corn extract is also applied to enhance the flavor of the product. This study aims to analyze the effect of implementing a fuzzy Neo-based temperature control system and the variation of sweet corn extract concentration on the physicochemical properties of yoghurt. The fermentation process was carried out at temperatures of 39.97 °C and 44.99 °C with the addition of 30% and 60% sweet corn extract. The results showed that the best treatment was obtained from yoghurt produced with fuzzy-based temperature control at 44.99 °C and 30% sweet corn extract addition (F-30%-44.99 °C), which exhibited a pH value of 4.3, total soluble solids of 11.5°Brix, viscosity of 124 m.Ps, and lactic acid content of 0.7905%.
Optimized ResNet-18 Model for Ripeness Classification of Javanese Long Pepper (Piper retrofractum) Using Reflectance and Fluorescence Imaging Sandra; Damayanti, Retno; Sa'diyah, Mitha; Nainggolan, Rut Juniar
Jurnal Keteknikan Pertanian Tropis dan Biosistem Vol. 14 No. 1 (2026): April 2026
Publisher : Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jkptb.2026.014.01.12

Abstract

Javanese long pepper (Piper retrofractum Vahl.) is a high-valuable horticultural commodity crop whose quality and bioactive composition depend strongly on fruit ripeness. Conventional visual assessment is often subjective and inconsistent, emphasizing the need for an objective and non-destructive alternative. This study aimed to develop an automated classification system for determining ripeness stages (green, orange, and red) using reflectance (visible light) and fluorescence (ultraviolet) imaging analyzed through a fine-tuned ResNet-18 deep learning model. A total of 300 images per modality were captured under controlled studio conditions and processed through standardized background removal, size normalization, and data augmentation. Color feature analysis across RGB, CIELAB, and HSV color spaces revealed that reflectance imaging effectively captured pigment transitions associated with chlorophyll degradation and carotenoid accumulation, with the a* channel serving as the most discriminative single-channel indicator. Fluorescence imaging provided complementary physiological information through chlorophyll emission dynamics, exhibiting greater inter-class overlap particularly between green and orange stages. The ResNet-18 model was evaluated using three optimizers (Adam, SGDM, and RMSprop) based on accuracy, precision, recall, Macro F1-score, and loss. For reflectance imaging, SGDM and RMSprop both achieved perfect test classification (accuracy = 100%, Macro F1 = 1.000), while fluorescence-based models achieved up to 97.78% accuracy. Training curve analysis confirmed stable convergence without overfitting across all combinations. Confusion matrix analysis showed that misclassifications were confined to adjacent ripeness stage boundaries, and Grad-CAM visualization confirmed physiologically consistent spatial attention patterns in the best-performing models. The proposed imaging and modeling pipeline offered a reproducible framework for postharvest quality evaluation and standardization of Piper retrofractum and similar horticultural commodities.
Integration of Regression Analysis and Spatial Interpolation in Multi-Sensor Soil Calibration Optimization Based on RS485 to Support Precision Agriculture Priyonggo, Budi; Hafidz, Muhammad; Azadi, Athoillah; Wirawan, Adi; Nucholis, Jati; Muharfiza, Muharfiza; Jahari, Mahirah
Jurnal Keteknikan Pertanian Tropis dan Biosistem Vol. 14 No. 1 (2026): April 2026
Publisher : Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jkptb.2026.014.01.13

Abstract

Technological developments provide significant opportunities to utilise measurement equipment to enhance the effectiveness and efficiency of agricultural production. Accurate soil content measurement is very important for evaluating soil quality, helping farmers understand soil conditions and take appropriate steps to improve or maintain it. Calibration is required to ensure that the measuring instruments used provide accurate readings. The objective of this research was to calibrate the soil comprehensive sensor type RS485. The parameters tested are WET sensor, pH sensor, and temperature sensor. Data analysis was conducted using spatial interpolation, linear regression, and multiple linear regression. The calibration results obtained the calibration function  (R2 0.9566) for the WET sensor, (R2 0.9845) for the pH sensor, and  (R2 0.9963) for T sensor. The results of the spatial interpolation analysis using the calibration function indicate an improvement in the accuracy between the tested sensor and the calibrator compared to before calibration. The improvement in the accuracy of the parameter values was obtained by performing multiple linear regression analysis involving all sensors. The equations WETe4, pHe4, and Te4 were chosen as the best estimated equations that can improve the accuracy of sensor readings. The results of spatial interpolation analysis of the functions WETe4, pHe4, and Te4 showed a better improvement in accuracy compared to the calibration function. The equations WETe4, pHe4, and Te4 can be used as alternative functions to approximate the correct values in the use of soil comprehensive sensor type RS485. The spatial interpolation analysis conducted can provide an illustration of values based on color distribution to understand of the distribution of those values.
Evaluation of Land Suitability for Oil Palm Based on Geographic Information System in Konawe Selatan District Aldiansyah, Septianto; Saudi, Fitriyani; Ati, Amniar
Jurnal Keteknikan Pertanian Tropis dan Biosistem Vol. 14 No. 2 (2026): August 2026
Publisher : Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jkptb.2026.014.02.01

Abstract

Oil palm is an important commodity in the industrial sector. Konawe Selatan Regency has begun to develop oil palm plantations in various regions, but land suitability analysis with a spatial approach has never been carried out. This study is important to support oil palm cultivation by taking into account environmental characteristics. This study utilizes Geographic Information Systems using parameters of temperature, rainfall, dry month, soil texture, soil depth, soil pH, slope, and erosion. Konawe Selatan Regency has oil palm suitability that is classified as very suitable (S1) 0.04%, quite suitable (S2) 40.41%, marginally suitable (S3) 31.19%, and not suitable (N) 28.36%. The limiting factors in this area are hotter and colder temperatures and steep slopes. Oil palm development must be carried out with primary consideration in conservation areas, considering that Konawe Selatan Regency has agronomic and ecological limitations.
The Effect of Skimmed Milk Level on the Characteristics of Physicochemical and Hedonic Test of Mozzarella Cheese Maharani, Nanda Intan; Rahmat, Iqbal Zulfahmi; Daud, Muhammad Farhan; Ariyanto , Ardi Nur; Setyawardani, Triana; Sumarmono, Juni; Arkan, Naofal Dhia; Fadhlurrohman, Irfan
Jurnal Keteknikan Pertanian Tropis dan Biosistem Vol. 14 No. 2 (2026): August 2026
Publisher : Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/

Abstract

This study aims to examine how the addition of skimmed milk at different levels affects the physical, chemical and hedonic test characteristics. The research was conducted using a Complete Random Design (RAL) consisting of 4 treatments, namely: control (P0); skimmed milk 2.5% (P1); skimmed milk 5% (P2); and skimmed milk 7.5% (P3). The results showed that the addition of skimmed milk had a very pronounced effect on all parameters tested (P<0.01). The pH value increased from 5.48±0.02 (P0) to 5.51±0.04 (P1), 5.73±0.04 (P2), and 5.78±0.06 (P3). Yields increased from 4.9±0.47% (P0) to 8.4±0.34% (P1), 8.7±0.10% (P2), and 9.2±0.23% (P3). The higher the level of skim milk added, the yield and pH of the cheese increases, so that the amount of cheese produced is more and the pH is higher but the distinctive taste of the cheese decreases. However, the increase in skim milk also causes the cheese to become harder, the moisture content decreases, and the level of ductility or ability of the cheese to be drawn is significantly reduced. Based on the hedonic test, mozzarella cheese with the addition of skim milk of up to 7.5% was still acceptable to the panellists, despite a decrease in the ductility aspect. Thus, the addition of skimmed milk can be an alternative to increase the quantity of mozzarella cheese production, but it is necessary to pay attention to the balance between the quantity and texture quality of the cheese to keep it in accordance with the characteristics expected by consumers.
Combustion Characteristics and Mechanical Properties of Sugarcane Bagasse Bio-Briquettes: Effects of Charcoal and Tapioca Binder Formulation Handoko, Tri; Rosalinda, Widya; Agustin, Cherly; Silaban, Rahel Jesika; Marzuqoh, Siti Difa; Kusuma Riandara, Hervianna Indira; Harmiansyah
Jurnal Keteknikan Pertanian Tropis dan Biosistem Vol. 14 No. 2 (2026): August 2026
Publisher : Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/

Abstract

Sugarcane bagasse is an abundant agricultural by-product in Indonesia due to high sugarcane production, particularly in major producing provinces. The limited utilization of bagasse may cause environmental problems, highlighting the need for sustainable waste management strategies. This study aimed to evaluate the potential of sugarcane bagasse as a raw material for biobriquettes and to analyze the effect of different charcoal binder compositions on the physical and mechanical properties of the briquettes. The research was conducted at the Biosystems Engineering Laboratory using carbonized sugarcane bagasse (biochar) molded into briquettes with a pressing pressure of 50 kg/cm². Four composition ratios were applied, namely 45:5, 46:4, 47:3, and 48:2 (g of charcoal : g of tapioca binder). The briquettes were evaluated based on density, dimensional stability, moisture content, mechanical strength using a drop test, and combustion rate. The results showed that briquettes with a composition of 45 g charcoal and 5 g binder exhibited the highest density (approximately 0.59 g/cm³) and the lowest drop test value, indicating strong mechanical integrity. All samples demonstrated low moisture content (0.35–1.94%), which contributes to efficient and stable combustion. Variations in material composition significantly influenced the stability and combustion characteristics of the briquettes. Overall, sugarcane bagasse shows strong potential as a sustainable and environmentally friendly raw material for producing high-quality biobriquettes as an alternative renewable energy source.
Effects of Operational Factors on The Productivity, Efficiency, And Power Consumption of a Fish Meal Pelleting Machine Kosemani, Babajide; Sule, Shakiru Okanlawon; Adewumi, Idowu Olugbenga; Afolabi, Bukola Olanrewaju; Mufutau, Monsuru Olayinka
Jurnal Keteknikan Pertanian Tropis dan Biosistem Vol. 14 No. 2 (2026): August 2026
Publisher : Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/

Abstract

Pelletizing remains one of the most economical and technologically advanced techniques for producing fish feed. The quality characteristics of the resulting pellets are influenced by several operational variables, which, when improperly controlled, can lead to suboptimal feed quality. This research work optimizes some operational parameters including die size, shaft speed and feeding rate of an indigenous fish meal pelletizing machine for productivity, efficiency, power consumption and specific energy consumption. Mixed fish feed materials were pelletized at 29, 31 and 31m/s die speed, loaded onto the pelleting machine at different feeding rates (15, 20, and 25kg/hr) and die hole (3, 4, 5). The RSM was employed to improve the machine performance by analysing the impact of multiple operational variables on the response including productivity, efficiency, power consumption and specific energy consumption. The interaction of the operational parameters and response factors were established through Quadratic models. The impact of the operational parameters on productivity, efficiency, power consumption and specific energy consumption were significant (p ?0.01). The optimal condition of the process for die speed, die hole and feeding rate were 31m/s, 5mm and 20kg/hr, respectively, resulting in machine productivity, efficiency, power consumption and specific energy consumption of 82.02kg/hr, 86.09%, 2.55kW, and 0.029 kWh/kg, respectively. This indicates that the fish meal pelletising machine ran efficiently under optimal conditions, therefore validating the generated models.
Deep Neural Network-Based Estimation of Irrigation Water Requirements for Verticulture and Its Application in Irrigation Management Suhardi; Dafik; Agustin, Ika Hesti; Marhaenanto, Bambang
Jurnal Keteknikan Pertanian Tropis dan Biosistem Vol. 14 No. 2 (2026): August 2026
Publisher : Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/

Abstract

Vertical farming is a crop cultivation system with a tiered planting medium configuration designed to optimize accessibility, maintenance, and harvesting efficiency. The implementation of modern technology based on environmental sensors allows real-time monitoring of microclimate parameters to support precise irrigation management through estimation of evapotranspiration rates (ETo). This study aims to evaluate and estimate ETo values in vertical farming systems using a DNN architecture. Estimation is carried out through Python programming language simulations on the Google Colaboratory platform using a pre-trained DNN model (4 hidden layers) based on input data of average temperature (Tmean) and average relative humidity (RHmean) over a 4-hours duration. The implemented DNN model was validated against actual ETo data in previous studies to ensure the reliability of predictions. The results show that DNN-based evapotranspiration values are significantly influenced by temperature and relative humidity factors. Furthermore, evapotranspiration values, plant growth phases, and planting area are variables needed to calculate irrigation water requirements in the vegetative, generative, and final phases, which require 6.41 liters, 22.85 liters, and 21.73 liters, respectively. Thus, the use of the validated DNN model is proven to be a reliable predictive instrument for precisely determining crop water requirements to achieve more efficient irrigation management.
Control System Design and Implementation of Multi Seed Smart Dryer (MSSD) for Smallholder Farmers Pandunata, Priza; Sujarwo, Mohamad Wawan; Indarto, Indarto; Nurhayati, Diana
Jurnal Keteknikan Pertanian Tropis dan Biosistem Vol. 14 No. 2 (2026): August 2026
Publisher : Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/

Abstract

This study presents the design and implementation of the Multi-Seed Smart Dryer (MSSD) control system. Other research objectives include developing a simple, low-cost, low-energy consumption dryer. The MSSD is designed to be more suitable for seed farmers. The methodology comprises engineering design, fabrication, smart-control development, and implementation. The power supply of 300 W and three (3) fans will generate hot air flow. The dry air flow moves horizontally from the left to right side through 10 rack layers in the drying chamber. Then, racks are arranged vertically to convey the seed. The smart control is designed with two modes and is based on fuzzy logic. The prototype of the dryer was tested using multiple seeds. The results show that MSSD performs well for seed drying. Functional tests using various seeds show that the drying chamber temperature ranges from 32 to 37 °C Meanwhile, relative humidity ranges from 42 to 90%. Furthermore, the germination rate of the dry seed is more than 85%. The system operated stably with an average power consumption of approximately 237 W, below the theoretical demand due to an effective control strategy, indicating energy-efficient and cost-effective drying potential for smallholder farmers under prevailing electricity tariffs (below IDR 2,000/drying cycle). Finally, MSSD can potentially be distributed to farmers for their everyday tasks in seed production.
Comparative Performance of Lightweight and Medium YOLO Models for Conveyor-Based Chili Ripeness Detection Taqiya, Muhammad Abyad Hofid; Khalil, Fakhrul Irfan; Sadimantara, Muhammad Syukri Sadimantara; Arief, Muhammad Akbar Andi; Kurniawan, Hary
Jurnal Keteknikan Pertanian Tropis dan Biosistem Vol. 14 No. 2 (2026): August 2026
Publisher : Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/

Abstract

This study conducts a comparative performance evaluation of lightweight and medium variants of YOLO models, specifically YOLOv8, YOLOv10, and YOLOv12, for real-time chili ripeness detection using digital image analysis. A dataset comprising 1,450 images of Baskara chili peppers at four ripeness stages, namely green, yellow, orange, and red, was collected using a conveyor-based imaging system under controlled lighting conditions. The images were manually annotated with bounding boxes and divided into training, validation, and test sets in proportions of 73.1%, 18.3%, and 8.6%, respectively. All models were trained with identical parameters to ensure a fair comparison and evaluated using precision, recall, F1-score, mean Average Precision, and computational efficiency metrics. The results indicate that YOLOv12s achieved the highest overall performance, with a precision of 0.918, recall of 0.938, mAP@0.5 of 0.960, mAP@0.5:0.95 of 0.865, F1-score of 0.927, 21.2 GFLOPs, and an inference time of 3.1 ms. Evaluation on 125 additional images confirmed robust generalization, with a precision of 0.908, recall of 0.923, mAP@0.5 of 0.931, and mAP@0.5:0.95 of 0.849. Class-wise analysis showed that the green class achieved the highest detection accuracy, while the orange class was the most challenging due to visual similarity with adjacent ripeness stages. Overall, YOLOv12s achieved an optimal balance between detection accuracy and computational efficiency, making it promising for real-time chili sorting in smart agriculture applications.

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