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All Journal Indonesian Journal of Geography Berkala Ilmiah Pertanian Jurnal Online Mahasiswa (JOM) Bidang Perikanan dan Ilmu Kelautan JTSL (Jurnal Tanah dan Sumberdaya Lahan) Techno: Jurnal Penelitian Pelita Perkebunan Journal of Degraded and Mining Lands Management Jurnal Teknik Pengairan: Journal of Water Resources Engineering AGRIVITA, Journal of Agricultural Science Jurnal Agro Indonesian Journal of Science and Technology Jurnal Ilmiah Rekayasa Pertanian dan Biosistem Agriprima : Journal of Applied Agricultural Sciences Dinamisia: Jurnal Pengabdian Kepada Masyarakat Jurnal Agrotek UMMat SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Jurnal Agrotek Tropika Jurnal Pengabdian Magister Pendidikan IPA Jurnal Teknologi Pertanian Andalas Jurnal Ilmiah Inovasi JUSTIN (Jurnal Sistem dan Teknologi Informasi) Media Pertanian Asian Journal of Management, Entrepreneurship and Social Science
Tri Wahyu Saputra
Program Studi Agroteknologi, Fakultas Pertanian, Universitas Jember
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Journal : Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering)

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SISTEM FERTIGASI RAIN PIPE OTOMATIS PADA MAIN NURSERY KELAPA SAWIT (Elaeis guineensis Jacq) BERBASIS MIKROKONTROLER ARDUINO UNO Anri Kurniawan; Tri Wahyu Saputra; Anugerah Ramadan
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol 9, No 3 (2020): September 2020
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v9i3.184-190

Abstract

This research conducted to designed, implemented, and tested an automatic rain pipe fertigation system using temperature and soil moisture sensors. The system applied to three irrigation treatments, namely manual fertilization, semi-manual fertilization, and automatic fertigation. The automatic fertigation actuator setting point is at temperature of  ≥ 31 ° C and humidity of ≤ 60% to turn on the water pump and nutrient pump then the water pump will shut down when the temperature value of 25 °C and humidity of  ≥ 80%. The results showed a significant difference in the use of irrigation water based on variance test results with an error value of 5%. The use of water from automatic fertigation is 12.770 ml or 65.9% more efficient than manual irrigation with the same growth in plant height. The height of oil palm plants in the main nursery with automatic fertigation is higher on days 7 to 12. Automatic fertilization requires a fertilizer of 1.8 tons per ha, less than manual fertilization which reaches 3 tons per ha. Keywords: fertigation, microcontroller, oil palm, sensors, soil moisture
PENENTUAN NILAI PARAMETER KINETIKA ORDE SATU PADA SINTESIS BIODIESEL DARI MINYAK JELANTAH Amieria Citra Gita; Agus Haryanto; Tri Wahyu Saputra; Mareli Telaumbanua
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol 7, No 2 (2018): Agustus
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1013.894 KB) | DOI: 10.23960/jtep-l.v7i2.72-79

Abstract

Biodiesel merupakan alternatif pengganti bahan bakar solar yang dapat dibuat dari minyak jelantah.  Pembuatan biodiesel dapat dilakukan dengan metode transesterifikasi yaitu mereaksikan antara minyak jelantah dan metanol sehingga menghasilkan metil ester dan gliserol dengan bantuan katalis basa. Penelitian ini bertujuan mengetahui pengaruh suhu dan waktu reaksi dalam pembuatan biodiesel dan menentukan nilai parameter kinetika orde satu pada sintesis biodiesel dari minyak jelantah untuk memprediksi hasil reaksi.  Penelitian ini menggunakan  rasio molar 1:6 dengan waktu reaksi sebesar 0.25, 0.5, 1, 2, 3, 6 dan 10 menit dan suhu reaksi sebesar 30, 35, 40, 45, 50, dan 55 °C.  Bahan yang digunakan meliputi minyak jelantah, metanol dan NaOH dengan parameter penelitian meliputi rendemen, massa jenis dan viskositas.  Kinetika reaksi merupakan reaksi orde satu dari fungsi suhu dan konsentrasi non biodiesel untuk memperoleh konstanta laju reaksi dan energi aktivasi. Hasil penelitian menunjukkan rendemen biodiesel tertinggi terdapat pada suhu 55 °C dan waktu reaksi 10 menit. Biodiesel yang dihasilkan memiliki massa jenis antara 0,863-0,885 gram/ml (sesuai SNI), dan viskositas 2,825-5,277 cSt (sesuai SNI). Nilai konstanta laju reaksi (k) pada suhu suhu 30, 35, 40, 45, 50 dan 55 °C sebesar 9,8×10-4 s-1, 10,8×10-4 s-1, 11,67×10-4 s-1, 14×10-4 s-1, 14,83×10-4 s-1,  dan 21,67×10-4 s-1. Nilai energi aktivasi (Ea) reaksi yang dihasilkan sebesar 23,83 kJ/mol. Kata Kunci:   Biodiesel; Minyak Jelantah; Transesterifikasi Basa; Kinetika Reaksi
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
Mathematical Model of Drying Edamame (Glycine max (L.) Merill) Using Food Dehydrator Technology Based on Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) Rizza Wijaya; Silvia Oktavianur Yudiastuti; Anna Mardhiana Handayani; Elok Kurnia Novita Sari; Tri Wahyu Saputra; Febryan Kusuma Wisnu; Aulia Brilliantina
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol 11, No 4 (2022): Desember 2022
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v11i4.589-600

Abstract

Edamame is included in perishable products or products that have a fairly short shelf life if post-harvest processing is not carried out. One of the post-harvest processing methods commonly used by the community is drying. The purpose of this study was to analyze the drying process of edamame related to the MLRL and ANN models. This study used a completely randomized design (CRD) with three variations of air velocity, namely 1 m/s, 3 m/s, and 5 m/s. Data collection was repeated three times every 30 minutes until 330 minutes.  Multiple linear regression (MLR) model training and validation produce accuracy values of 88.03 and 82.23, and the value of R2 of 0.93 and 0.90. While the training and validation of the artificial neural network (ANN) model resulted in accuracy values of 88.34 and 82.15, and R2 values of 0.93 and 0.90. Keywords:    ANN, Drying, Edamame, Food  dehydrator
MEMPELAJARI KARAKTERISTIK FISIK BIJI KAKAO (Theobrema cacao L.) PADA SUHU PENGERINGAN YANG BERBEDA Sri Waluyo; Tri Wahyu Saputra; Nikita Permatahati
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol 10, No 2 (2021): Juni
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v10i2.200-208

Abstract

Drying is a common process step for agricultural grain products for ease of handling and to achieve the desired quality levels. One of the commodities that have high economic value produced by farmers in Lampung Province is cocoa beans. The drying process may change the physical properties of the cocoa beans and affect the processing of cocoa beans at a later stage. This study aims to determine the effect of drying temperature on changes in the physical properties of cocoa beans such as dimension, volume, weight, surface area, true density, bulk density, porosity, sphericity, and angle of repose. This research was applied to fresh non-fermented cocoa beans in testing. The cocoa beans were dried at temperatures of 40, 50 or 60oC. The research data were then statistically tested using paired sample T-Test at the 95% level to determine whether there is any effect of drying temperature on changes in its physical properties. The results showed a significant effect of drying temperature on weight, volume, geometric mean diameter (Dg), surface area, bulk density, porosity, and angle of repose of cocoa beans. Meanwhile, the sphericity and true density parameters did not significantly change. Keywords: cocoa beans, drying, physical properties
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
Classification of Banana Types Based on The Geometrical Attributes using Artificial Neural Network Method Sri Waluyo; Retama Agung Pangestu; Warji Warji; Tri Wahyu Saputra
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol 13, No 1 (2024): March 2024
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v13i1.223-231

Abstract

Banana (Musa paradisiaca) is one of the important horticultural commodities. This study aims to measure the physical and geometrical parameters of three different bananas (Muli, Ambon, and Kepok) and to develop prediction equations using an Artificial Neural Network (ANN) model. In this study the backpropagation ANN model with supervised learning method was used. The ANN model had one output node, two hidden layers, and network architecture of 8 inputs, namely fruit weight and volume, projected area and roundness of the fruit, cross section, peel color, and geometric mean fruit cross section diameter. The data for building the model and testing the model were respectively 70% and 30% of the 150 data number in total. The results showed that the best ANN model structure for estimating Muli, Ambon and Kepok bananas was purelin-logsig-logsig with an RMSE value of 0.0077 and an R2 of 0.9999. This shows that the ANN model is highly robust to predict the banana types. Using the built model, the accuracy of the prediction results is 100%.  Keywords:  Artificial Neural Network,  Banana fruits,  Geometry attribute. 
Morpho-Physiological Responses of Purbalingga and Purowkerto Local Black Rices to Drought Stress Sholikhah, Ummi; Khamidah, Khusna; Handoyo, Tri; Tanzil, Ahmad Ilham; Fanata, Wahyu Indra Duwi; Ratnasari, Tri; Saputra, Tri Wahyu
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.v14i4.1148-1155

Abstract

Black rice (Oryza sativa L. indica) is a pigmented rice plant that has high antioxidant content. Drought is an abiotic stress that can inhibit the growth and productivity of rice plants. Planting of local black rice with several drought treatments using PEG 6000 was observed in this study. The aim of this research is to determine the morphological and physiological response of local black rice plants in Purbalingga and Purwokerto at various levels of drought stress. This research used a Completely Randomized Design (CRD) with 2 factors. The first factor is 2 local black rice plants, namely Purbalingga and Purwokerto. The second factor was drought stress treatment via PEG 6000 with 4 treatments, namely 0% PEG (control), 5%, 10%, and 15%. The results showed that when applying 15% PEG, local black rice in Purbalingga and Purwokerto experienced a decrease in plant height and number of leaves but increased root length. Based on the physiological response, when addition 15% PEG there was a decrease in the amount of chlorophyll and an increase in the content of H2O2 and anthocyanins in both Purbalingga and Purwokerto local black rice.   Keywords: Black Rice, Drought Stress, Morphological Response, Physiological Response.
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.
Mathematical Model of Drying Edamame (Glycine max (L.) Merill) Using Food Dehydrator Technology Based on Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) Wijaya, Rizza; Yudiastuti, Silvia Oktavianur; Handayani, Anna Mardhiana; Sari, Elok Kurnia Novita; Saputra, Tri Wahyu; Wisnu, Febryan Kusuma; Brilliantina, Aulia
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 11 No. 4 (2022): Desember 2022
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v11i4.589-600

Abstract

Edamame is included in perishable products or products that have a fairly short shelf life if post-harvest processing is not carried out. One of the post-harvest processing methods commonly used by the community is drying. The purpose of this study was to analyze the drying process of edamame related to the MLRL and ANN models. This study used a completely randomized design (CRD) with three variations of air velocity, namely 1 m/s, 3 m/s, and 5 m/s. Data collection was repeated three times every 30 minutes until 330 minutes.  Multiple linear regression (MLR) model training and validation produce accuracy values of 88.03 and 82.23, and the value of R2 of 0.93 and 0.90. While the training and validation of the artificial neural network (ANN) model resulted in accuracy values of 88.34 and 82.15, and R2 values of 0.93 and 0.90. Keywords:    ANN, Drying, Edamame, Food  dehydrator
Co-Authors Abdillah, Moc. Reza Wahyu Agus Haryanto Ahmad Ilham Tanzil Ahmad Ilham Tanzil Al-Ghofiqi, M. Faris Alfarisy, Fariz Kustiawan Alfatah, Naufal Akbar Amelia Tri Arsita Amieria Citra Gita Anantoro, Tri Andhika Setiawan Andrie Septiawan Anna Mardiana Handayani Anugerah Ramadan Arthur Frans Cesar Regar Arthur Frans Cesar Regar Arum, Ayu Puspita Basuki , Brilliantina, Aulia Budi Hariono Budiman, Subhan Arif Cindy Febrian, Berlian Clarissa Myra Ananta Destria Putri, Romadhona Edison Edison Elok Kurnia Novita Sari Elok Kurnia Novita Sari Else Emilia Rumekso Ersya Kamelia Rosana Evita Soliha Hani Evita Soliha Hani Fahrudin, Danil Eka Fanata, Wahyu Indra Duwi Fandri, Ferdi Zul Fariz Kustiawan Alfarisy Febryan Kusuma Wisnu Gatot Subroto Gita, Amiera Citra Hadi, Yusnan Handayani, Anna Mardhiana HARI PURNOMO Ika Purnamasari Ika Purnamasari Irwanto Sucipto Kacung Hariyono Khamidah, Khusna Kharisma Adi Bagaskara Khotijah Khotijah Kurniawan, Anri Kurniawan, Bintang Lailatus Sufiaah, Annisa Laily Ilman Widuri Laily Ilman Widuri, Laily Ilman Laily Mutmainnah Leona, Agis Listya Purnamasari Maghfirah, Intan Hadiatun Mandala, Marga Mareli Telaumbanua Mirna Ilza Moch. Reza Wahyu Abdilah Mohammad Ubaidilah Nanda Khoirun Nisa Ahmad Nikita Permatahati Oria Alit Farisi Pambudi , Satrio Lintang Pangestu, Retama Agung Parawita Dewanti Prasojo, Sri Irawan Laras Puji Rahayu Pusparani, Syafina Putri, Romadhona Destria Rachmandhika, Yusuf Ratnasari, Tri Regar, Arthur FC Retama Agung Pangestu Rina Kumalasari Riska Annisyafira Ristiyana, Suci Rizky Harikurniawan Rizza Wijaya Rizza Wijaya Rona Al Kanza Roni Bahtiar Roni Yulianto Rosyady, Muhammad Gufron Safitri, Mahardika Saydi, Royhan Setiawati, Tri Candra Setiyono Setiyono Sigit Soeparjono Sigit Soeparjono Silvia Oktavia Nur Yudiastuti Sri Hartatik Sri Waluyo Sri Waluyo Subhan Arif Budiman Subroto, Gatot Suci Ristiyana Suci Ristiyana Sultan Ghozi Imaduddin Syafina Pusparani Syahputra, Wahyu Nurkholis Hadi Taufik, Rahadian Falqi TRI HANDOYO Tri Ratnasari Tursina Tursina Ummi Sholikah Ummi Sholikhah Vega Kartika Sari Warji Warji Warji Warji Wildan Muhlison Wildan Muhlison, Wildan Yagus Wijayanto Yeremia Rivieri Yoandita Velina Aprilia Yudiastuti, Silvia Oktavianur Yulianti Yulianti Yulianto, Roni Yusuf Rachmandhika Zaky Firmansyah Maulana