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INDONESIA
Jurnal Keteknikan Pertanian
Published by Institut Pertanian Bogor
ISSN : 24070475     EISSN : 23388439     DOI : -
Core Subject : Agriculture,
Agriculture, Biological Sciences & Forestry
Jurnal Keteknikan Pertanian dengan No. ISSN 2338-8439, pada awalnya bernama Buletin Keteknikan Pertanian, merupakan publikasi resmi Perhimpunan Teknik Pertanian Indonesia (PERTETA) bekerjasama dengan Departemen Teknik Mesin dan Biosistem (TMB) IPB yang terbit pertama kali pada tahun 1984, berkiprah dalam pengembangan ilmu keteknikan untuk pertanian tropika dan lingkungan hayati. Jurnal ini diterbitkan dua kali setahun. Penulis makalah tidak dibatasi pada anggota PERTETA tetapi terbuka bagi masyarakat umum. Lingkup makalah, antara lain: teknik sumberdaya lahan dan air, alat dan mesin budidaya, lingkungan dan bangunan, energi alternatif dan elektrifikasi, ergonomika dan elektronika, teknik pengolahan pangan dan hasil pertanian, manajemen dan sistem informasi. Makalah dikelompokkan dalam invited paper yang menyajikan isu aktual nasional dan internasional, review perkembangan penelitian, atau penerpan ilmu dan teknologi, technical paper hasil penelitian, penerapan, atau diseminasi, serta research methodology berkaitan pengembangan modul, metode, prosedur, program aplikasi, dan lain sebagainya.
Arjuna Subject : -
Articles 638 Documents
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Prototype of AI-Integrated Chatbot for Shallot Price Forecasting and Advisory Support to Assist Farmer Decision Making Muhammad Naufal Rauf Ibrahim; Risnandar; Alvin Fatikhunnada
Jurnal Keteknikan Pertanian Vol. 14 No. 1 (2026): Jurnal Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19028/jtep.014.1.17-31

Abstract

Forecasting agricultural commodity prices is a fundamental tool for sustainable development in the agricultural economy and broader economic stability. With rapid and simple access to information on future prices, farmers can plan their planting schedules to optimize profits. This study presents a prototype AI chatbot that integrates price forecasting and advisory functions to assist farmers in decision-making and interact as an extension agent. Price forecasting employed Random Forest regression, achieving MAPE of 8.34% training, 13.98% validation, and 15.62% testing. The chatbot was developed to access price forecasting information for the next four months. This system also integrates an LLM-AI model for consultations on planting schedules and other topics using a trusted knowledge base. During the testing phase, the chatbot successfully made predictions, provided recommendations, and interacted as an extension agent. Although demonstrating promising results, this study is limited to shallot price forecasting in Yogyakarta, highlighting the need for broader commodity and regional coverage in future studies. Unlike previous studies that focused only on forecasting or advisory, this study integrates predictive analytics with conversational AI in a farmer friendly chatbot.
Effect of Soy Protein Isolate (SPI) Concentration on Anthocyanin-Based Smart Indicator Labels from Purple Sweet Potato Waste Rijanti Rahaju Maulani; Indrawan Cahyo Adilaksono; Angela Valentina Saputra; Rika Alfianny; Laras Putri Wigati; Aep Supriyadi; Nita Yuniati
Jurnal Keteknikan Pertanian Vol. 14 No. 1 (2026): Jurnal Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19028/jtep.014.1.1-16

Abstract

Indonesia has a high level of food waste, with up to 30% of the country’s total fruit production contributing to it. Smart packaging, such as that with anthocyanin based freshness indicator labels and Soy Protein Isolate (SPI), can help reduce waste by providing visual information about the product’s condition within the packaging. This research aims to determine the effect of SPI concentrations on the characteristics of anthocyanin-based smart packaging indicator labels extracted from purple sweet potato waste (Ipomoea batatas (L.) Lam). The indicator label was made using cornstarch (2.5%) as the matrix, glycerol as the plasticizer,  and SPI as the crosslinking agent. The researchers employed a simple Completely Randomized Design with SPI concentration variations of 0%, 1%, 2%, 3%,  and 4%. The researchers tested several parameters on the indicator labels, including pH sensitivity, color stability against storage temperature (4°C and 25°C), water absorption capacity, color reversibility, and biodegradability. The results indicate that adding SPI affects label characteristics, with 1% SPI concentration yielding the best performance. The 1% SPI concentration obtained the lowest color stability value at cold temperatures (∆E*ab = 5.15), the highest biodegradation rate (97.33% on day 4),  the most varied color response to pH, and good physical durability of the label. Therefore, a 1% SPI concentration is recommended as the most effective formulation for an anthocyanin-based freshness indicator label.
Evaluation of Catechin Content in Gambir Leaf Herbal Tea Using NIR Spectroscopy with PLS and MLR Andasuryani Andasuryani; Santos Santos; Ifmalinda Ifmalinda
Jurnal Keteknikan Pertanian Vol. 14 No. 1 (2026): Jurnal Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19028/jtep.014.1.64-80

Abstract

Several factors, including drying duration, leaf maturity level, and drying temperature, can influence the catechin content of gambir herbal tea. Therefore, evaluating the quality of gambir herbal tea is essential. The commonly used method involves laboratory chemical analysis, which is destructive, generates chemical waste, and requires considerable time. The objective of this study was to develop an NIR model capable of rapidly, nondestructively, and environmentally friendly predicting the catechin content of gambir herbal tea. The reflectance of herbal tea samples was measured using a Büchi NIRFlex N500 spectrophotometer over 1000–2500 nm. The catechin content was determined through chemical analysis using ethanol as the solvent. Spectral data were calibrated against the actual catechin values using Partial Least Squares (PLS) and Multiple Linear Regression (MLR) in The Unscrambler X software. The pretreatments applied included Standard Normal Variate (SNV), Multiplicative Scatter Correction (MSC), and Baseline correction. The best model was obtained using the MLR method combined with MSC pretreatment, yielding Rc² = 0.91, Rp² = 0.92, RMSEC = 1.78, RMSEP = 1.79, SEC = 1.69, SEP = 1.77, RPD = 3.44, and RER = 10.77. The PLS model with Baseline pretreatment also produced reliable predictions with Rc² = 0.93, Rp² = 0.89, RMSEC = 1.50, RMSEP = 2.09, SEC = 1.52, SEP = 2.08, RPD = 3.00, and RER = 9.56. This study successfully developed an NIR model capable of predicting catechin content in gambir leaves herbal tea with strong predictive performance
Optimization of Foaming and Filling Agents in Foam-Mat Drying Method for Kombucha Powder Production Farah Fadhilah Widiaputri; Sutrisno S Mardjan; Siti Mariana Widayanti
Jurnal Keteknikan Pertanian Vol. 14 No. 1 (2026): Jurnal Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19028/jtep.014.1.49-63

Abstract

Kombucha is a functional beverage produced by fermenting tea with a symbiotic culture of bacteria and yeast (SCOBY).  It is known for its various health benefits but is limited by its short shelf-life. To improve its stability, kombucha can be converted into powder using the foam-mat drying method, the effectiveness of which depends strongly on the formulation of foaming and filling agents. This study aimed to determine the optimal formulation of foaming and filling agents in kombucha. This study evaluated four formulations combining maltodextrin (15% and 20%), Tween-80 (0.25–1%), egg albumen (0–5%), and carboxymethyl cellulose (CMC; 0.3%). The formulation of 500 g kombucha with 15% maltodextrin, 0.3% CMC, 0.5% Tween-80,  and 5% egg albumen produced the best results, yielding 14.38% powder with 5.78% moisture, a hue value of 1.32, chroma of 14.80,  and whiteness index of 81.84. These findings indicate that the selected formulation is effective in producing kombucha powder with desirable physical properties.
Impact of Storage Conditions on Moisture Content and Colour Characteristics of Roasted Arabica Coffee Using Imaging Techniques Hasanah Johari; Mahirah Jahari; Siti Khairunniza Bejo; Nur Azuan Husin; Noor Zafira Noor Hasnan; Nur Hamizah Abdul Ghani@Hashim; Danial Fatchurrahman
Jurnal Keteknikan Pertanian Vol. 14 No. 1 (2026): Jurnal Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19028/jtep.014.1.81-107

Abstract

Coffee, specifically Coffea arabica, is highly valued for its quality, aroma, and flavor. Understanding the factors affecting coffee quality is essential for farmers, industry players, and consumers. One key factor is the storage conditions, including air exposure, light, moisture, and temperature. Moisture content (MC) and color are commonly used indicators of coffee quality. This study analysed MC and colour trends of dark and medium roasted Arabica ground coffee stored under various conditions (cold vs. room temperature, airtight vs. non-airtight, and opaque vs. transparent) over a 10-week period. The results showed that the MC increased under all conditions. For dark roast, the lowest MC was observed in cold, airtight, transparent storage, whereas the highest was observed in room-temperature, non-airtight, opaque storage. For medium roast, the lowest MC occurred in cold, airtight, opaque storage, and the highest occurred in room-temperature, non-airtight, transparent storage. Color analysis using RGB imaging provided reliable grayscale values consistent with visual observations, although the trends fluctuated and were not strictly increasing or decreasing. Nevertheless, the method effectively distinguished roast levels, with dark roast showing lower grayscale values than the medium roast. A relationship between MC and color was also observed, where a higher MC corresponded to higher grayscale values (slightly brighter appearance). Overall, this study highlights the impact of storage conditions on MC and color, offering insights for improving coffee storage practices to maintain quality and freshness.
Characteristics of Lahat Robusta Coffee Cupping Scores Based on Natural Post-Harvest Processing Ricky Rikardo; Dias Indrasti; Dian Herawati
Jurnal Keteknikan Pertanian Vol. 14 No. 2 (2026): Jurnal Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19028/r3q3s096

Abstract

Robusta coffee from Lahat Regency, South Sumatra, is one of the leading commodities with quality potential that needs to be supported by proper post-harvest processing to achieve specialty (fine Robusta) quality standards. Natural post-harvest processing is known to form unique sensory characteristics through natural fermentation during drying. This study aimed to evaluate the cupping score characteristics of Lahat Robusta coffee based on natural post-harvest processing. Coffee bean samples were processed using the natural method to a moisture content of 10–11%, roasted, and evaluated using a cupping test by certified R-graders in accordance with Fine Robusta Standards and Protocols for the attributes of aroma/fragrance, flavor, aftertaste, salt or acid, bitter or sweet, mouthfeel, uniform cup, balance, clean cup, overall, taints-faults, and total scores. The results showed that Lahat Robusta coffee with natural post-harvest processing produced superior characteristics, with a final cupping score of 83.88, placing it in the specialty coffee category. The resulting sensory profile was dominated by the attributes of brown sugar, honey, dark chocolate, hazelnut, fresh fruity, acidic, nutty, cereally, and spicy. Natural post-harvest processing has proven to be effective in enriching flavor precursor compounds. Lahat Robusta coffee has the potential for regional authenticity and high quality. These findings can support the development of quality and strengthen the identity of Lahat Robusta coffee at the national scale.
Optimasi Pola Tanam Berbasis Analisis Keseimbangan Air Tanah dan Distribusi Spasialnya di Kabupaten Rambipuji, Jember Vivi Fitriani; Retno Purnamasari; Cahyoadi Bowo; Marga Mandala; La Gandri; Herlan Hidayat
Jurnal Keteknikan Pertanian Vol. 14 No. 2 (2026): Jurnal Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19028/7vwg7w49

Abstract

Optimasi pola tanam di bawah iklim muson memerlukan informasi yang akurat tentang ketersediaan air tanah dan variabilitas spasialnya. Studi ini bertujuan untuk mengoptimalkan pola tanam dan menentukan waktu tanam optimal berdasarkan analisis keseimbangan air tanah dan distribusi spasialnya di Kabupaten Rambipuji, Kabupaten Jember, Indonesia. Keseimbangan air tanah bulanan dianalisis menggunakan metode Thornthwaite–Mather berdasarkan data klimatologi sepuluh tahun (2015–2024), termasuk curah hujan dan evapotranspirasi referensi, dikombinasikan dengan pengukuran kapasitas lapangan tanah pada kedalaman 0–20 cm di lima unit pemetaan lahan (LUM) yang dibedakan berdasarkan kemiringan, kelompok tanah, dan penggunaan lahan. Waktu tanam ditentukan menggunakan kriteria ilmiah di mana kelembaban tanah mencapai kapasitas lapang dan rasio curah hujan efektif terhadap evapotranspirasi tanaman (Peff/ETc) ≥ 0,75. Hasil menunjukkan pola muson yang jelas, dengan surplus air terjadi dari November hingga April dan defisit yang signifikan dari Mei hingga Oktober. Tekstur tanah secara signifikan mempengaruhi kapasitas penahanan air, menyebabkan variasi dalam durasi dan intensitas defisit air di antara LUM. Berdasarkan kondisi ini, LUM 1, 2, dan 5 direkomendasikan untuk penanaman pada Desember, sementara LUM 3 dan 4 lebih cocok untuk Januari. Pola tanam optimal terdiri dari budidaya padi pada musim tanam pertama diikuti oleh tanaman sekunder pada musim kedua dan ketiga, mencerminkan strategi penggunaan air yang adaptif di bawah kondisi curah hujan yang menurun. Temuan ini menunjukkan bahwa integrasi analisis keseimbangan tanah-air dengan karakteristik spasial tanah memberikan dasar yang andal untuk perencanaan kalender tanam yang presisi, mendukung pengelolaan pertanian berkelanjutan dan sistem pendukung keputusan di bidang pertanian dan rekayasa biosistem.
Kalman Filter Stabilization of Multi-Sensor Water Quality Measurements under Turbulent Flow in Eel Aquaculture Ahmad Zambarkah Sarwo Surono; Herry Suhardiyanto; I Dewa Made Subrata; Yonvitner
Jurnal Keteknikan Pertanian Vol. 14 No. 2 (2026): Jurnal Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19028/pzce9v17

Abstract

While Kalman Filters are widely used for water quality sensors, most studies focus on static environments, ignoring hydrodynamic noise in continuous-flow systems such as eel aquaculture, where turbulence-induced sensor instability may directly affect automated control decisions. This study evaluated the performance of the Kalman Filter in mitigating multi-sensor reading noise caused by unsteady flow from a wavemaker in a closed aquarium. Experiments simulated an eel environment (salinity 5-7 ppt, flow velocity 0.27 m/s) to measure pH, electrical conductivity (EC), dissolved oxygen (DO), and water temperature in situ. The performance of the Kalman Filter was compared directly with the that of Simple Moving Average (SMA), Exponentially Weighted Moving Average (EWMA), and Butterworth filters. The performance of these filters was assessed using the Standard Deviation, Root Mean Square Error (RMSE), Noise Reduction Ratio (NRR), Signal-to-Noise Ratio (SNR), and Smoothness Index. The results demonstrate that the Kalman Filter not only reduces signal fluctuations but also improves measurement accuracy, as validated by lower RMSE values relative to ground truth references under static conditions. It outperformed the other algorithms by reducing the average standard deviation by 87.65%, lowering the mean RMSE by 28.22%, decreasing the average noise by 13.56%, and increasing the mean SNR by 4.44 dB. This study demonstrates the superiority of the Kalman Filter in stabilizing sensor data against complex hydrodynamic turbulence.

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