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All Journal Teknotan: Jurnal Industri Teknologi Pertanian Jurnal Agricultural Biosystem Engineering
Oktafri Oktafri, Oktafri
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Agriculture, Biological Sciences & Forestry Automotive Engineering Civil Engineering, Building, Construction & Architecture Engineering Environmental Science Materials Science & Nanotechnology Other

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Unjuk Kerja Mesin Perajang Biomassa Tipe Slicer untuk Perajangan Pelepah Kelapa Sawit Hafizh, Galang Dzakwan; Asmara, Sandi; Oktafri, Oktafri; Suharyatun, Siti
Jurnal Agricultural Biosystem Engineering Vol. 5 No. 1 (2026): March 2026
Publisher : abe.fp.unila.ac.id

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jabe.v5i1.12376

Abstract

This study aimed to evaluate the performance of a slicer-type biomass chopper in processing oil palm fronds at different engine speeds (2000, 2350, and 2700 rpm). The observed parameters included working capacity, fuel consumption, material losses, and ergonomic aspects. The results showed that variations in engine speed significantly affected machine performance. The highest working capacity was achieved at 2700 rpm, reaching 465.96 kg/h, while the lowest was at 2000 rpm with 185.04 kg/h. Fuel consumption ranged from 1.29 to 1.70 L/h, with the lowest value at 2000 rpm and the highest at 2700 rpm. The lowest material loss was recorded at 2000 rpm (0.95%), whereas the highest occurred at 2700 rpm (2.44%). Ergonomic analysis indicated that the Cardiovascular Load (CVL) ranged from 31% to 36%, categorized as moderate workload and still tolerable for operators. Overall, the best performance was obtained at 2700 rpm due to its highest working capacity with relatively acceptable losses.
Uji Kinerja Mesin Chopper Serbaguna untuk Memperkecil Ukuran Pucuk Tebu Fadhil, Naufalda M.; Asmara, Sandi; Oktafri, Oktafri; Suharyatun, Siti
Jurnal Agricultural Biosystem Engineering Vol. 5 No. 1 (2026): March 2026
Publisher : abe.fp.unila.ac.id

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jabe.v5i1.12868

Abstract

This study aimed to evaluate the performance of a multipurpose chopper machine in reducing the size of sugarcane tops as a means of utilizing agricultural biomass waste. The research was conducted at the Laboratory of Power and Agricultural Machinery, Faculty of Agriculture, University of Lampung, using a factorial Completely Randomized Design (CRD) with two factors: engine rotation speed (1500, 1700, and 2000 rpm) and feed input (3, 4, and 5 stalks of sugarcane tops). The parameters observed were work capacity, material losses, fuel consumption, and chopping uniformity. The results revealed that both engine speed and feed input had a highly significant effect on all performance parameters. Increasing engine speed enhanced work capacity up to 172.2 kg/hour, reduced material losses to 8.58%, and maintained efficient fuel consumption at 966 ml/hour under the 2000 rpm and 4-stalk combination. The multipurpose chopper machine proved to be effective and efficient in reducing the size of sugarcane tops, making it suitable for use as biomass fuel or alternative livestock feed.
Design of Portable Soil Moisture Detector Based on Artificial Intelligence Telaumbanua, Mareli; Safitri, Nur Rahma; Haryanto, Agus; Oktafri, Oktafri; Wisnu, Febryan Kusuma; Rahmawati, Winda
Teknotan: Jurnal Industri Teknologi Pertanian Vol 20, No 2 (2026): TEKNOTAN, Agustus 2026
Publisher : Fakultas Teknologi Industri Pertanian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/jt.vol20n2.9

Abstract

Soil moisture plays a crucial role in plant growth as it affects nutrient transport, photosynthesis, transpiration, and cell turgor. Soil moisture is commonly measured using direct gravimetric methods or more practical electrical conductivity-based sensors. However, these sensors have drawbacks, as measurement results can be affected by salinity, temperature, and soil type, requiring calibration at each site. To address these limitations, this study employed an Artificial Neural Network (ANN) model integrated into a microcontroller to automate the measurement process, adapt it for specific tasks, and eliminate manual calibration. The objectives of this study were to design a soil moisture sensor without manual calibration, develop an ANN-based moisture estimation model, and test its accuracy and effectiveness in supporting precision agriculture. The results showed that the soil moisture meter portable performed according to the design criteria. The ANN model produced an RMSE of 1.0366 and an R² of 0.995 in the training phase, and an RMSE of 1.0366 and an R² of 0.9923 in the testing phase. The best activation function is logsig-logsig-logsig, with actual validation showing an R² of 0.8607 and an RMSE of 7.617. This system has the potential to improve the accuracy of soil moisture measurements and irrigation efficiency in supporting sustainable precision agriculture.
Co-Authors Agus Haryanto Ahmad Tusi Alwi, Ivo Ali Saifullah Anhar, Satria Radly Aprilliandi, Reza Berdikari, Rendi Amanda Budianto Lanya Fadhil, Naufalda M. Febryan Kusuma Wisnu Hafizh, Galang Dzakwan Hidayatullah, Martin Sulung Jati, Galih Kuncoro Kuncoro, Sapto Mareli Telaumbanua Muhammad Amin Nugraha, Danang Rezki Putri, Mustika Ridwan, Ridwan Safitri, Nur Rahma Sandi Asmara Sari, Selvi Yunita Siti Suharyatun Tamrin Tamrin W, Nazova Falhbian Warji Warji Winda Rahmawati