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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 623 Documents
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An Intelligent Food Recommendation System for Dine-in Customers with Non-Communicable Diseases History Imantho, Harry; Seminar, Kudang Boro; Damayanthi , Evy; Suyatma , Nugraha Edhi; Priandana, Karlisa; Ligar, Bonang Waspadadi; Seminar, Annisa Utami
Jurnal Keteknikan Pertanian Vol. 12 No. 1 (2024): Jurnal Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19028/jtep.012.1.140-152

Abstract

The rising prevalence of diet-related diseases necessitates a focus on individual food selection to enhance nutrition intake and promote overall health. This study introduces a novel food recommender system utilizing artificial intelligence, specifically a genetic algorithm (GA), to intelligently match diverse nutritional needs with available food items. The research incorporates machine learning methodologies, such as collaborative and content-based filtering, to develop a recommendation model. Data from a commercial restaurant, Nutrisurvey, and the Indonesian food composition list inform the nutritional analysis of five menu items. Consumer variability, considering factors like sex, body mass index, medical conditions, and physical activity, are integrated into the GA framework for personalized food pattern matching. The presented results demonstrate the efficacy of the proposed model in offering tailored food recommendations for consumers with non-communicable diseases (NCDs), such as diabetes, hypertension, and heart disease. The multi-objective optimization technique employed in the system ensures a balance between nutritional adequacy and individual preferences. The presented GA-based approach holds promise for promoting healthier food choices tailored to individual needs, contributing to the broader goal of fostering a sustainable and personalized food system.
Sifat Fisiko Kimia Tepung Gembili (Dioscorea esculenta L.) dari Umbi Berdaging Putih dan Berdaging Putih-Keunguan Pamungkas, Wiyan Afriyanto; jamaludin, Jamaludin
Jurnal Keteknikan Pertanian Vol. 12 No. 2 (2024): Jurnal Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19028/jtep.012.2.259-271

Abstract

Mutu tepung berupa sifat fisikokimia dan sensoris merupakan parameter yang sangat penting yang akan mempengaruhi desain, proses, dan hasil dalam pengolahan produk turunan tepung gembili. Penelitian ini bertujuan untuk mengevaluasi sifat fisik dan kimia tepung dari umbi gembili berdaging putih (Yawal Porei) dan tepung gembili berdaging putih-keunguan (Thai) serta mengetahui preferensi konsumen terhadap tepung yang dihasilkan. Sifat fisik tepung gembili dianalisis antara lain rendemen, derajat putih, dan modulus kehalusan (FM). Sedangkan, komposisi kimia tepung yang dianalisis meliputi kadar air, karbohidrat, protein, kadar abu dan serat kasar. Sebanyak 35 orang panelis tidak terlatih digunakan pada uji organoleptik untuk menilai preferensi konsumen. Hasil yang diperoleh menujukkan bahwa kedua jenis umbi gembili menghasilkan tepung dengan sifat fisik dan kimia yang berbeda. Tepung gembili putih mempunyai beberapa keunggulan dari segi sifat fisik dan kimia yakni rendemen (15.62%±0.41), derajat putih (79.55±0.98), karbohidrat (82.86%±0.21) dan serat kasar (5.28% ± 0.61) yang berpotensi sebagai beras analog, mie, bahan campuran cake, filler, maupun cookies. Sedangkan, tepung gembili putih-keunguan tinggi kadar protein (5.40%±0.16) dan kadar abu (6.75%±0.05) yang berpotensi dibuat sebagai produk roti. FM kedua jenis tepung gembili tidak jauh berbeda (1.10 ± 0.13 dan 1.11 ± 0.0) serta memiliki kadar air telah memenuhi Standar Nasional Indonesia (SNI) yaitu di bawah 14,5%. Penilaian sensoris menunjukkan bahwa tepung gembili putih lebih disukai oleh panelis dibandingkan tepung gembili putih-keunguan. Tepung gembili yang diperoleh dari penelitian ini berpotensi untuk dikembangkan sebagai tepung komposit untuk produk pangan.
Determination of Sustainable Factory Locations for the Lemon Agroindustry using AHP, Mapping and Water Management Asdak, Chay; Octoyne, Aisyah; Kendarto, Dwi Rustan; Prawiranegara, Boy Macklin Pareira
Jurnal Keteknikan Pertanian Vol. 12 No. 2 (2024): Jurnal Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19028/jtep.012.2.272-283

Abstract

This research was conducted in Suntenjaya Village, Lembang, West Bandung Regency, focusing on lemon agro-industry development through the Analytical Hierarchy Process (AHP) method approach, area mapping, and water management to determine a sustainable factory location. The main objective is the selection of factory site by integrating lemon production considering sustainable agriculture aspects, product aspects, and water conservation programs. The results of the study provide a strong foundation for sustainable agro-industrial development will support sustainable agriculture, local economy, and environmental protection. The research also combined qualitative and quantitative elements with a mixed approach that included Focus Group Discussion (FGD) and AHP with the results showing that integrated drainage management was the top priority, followed by sanitation, clean water, reforestation, and sustainable agriculture. Mapping of areas based on geographical characteristics such as rainfall, slope, and soil type provided a map of water infiltration rates that became a key guide in planning water conservation programs. This research has positive implications in supporting sustainable agricultural practices and local economic empowerment. The results of the AHP analysis and area mapping form a strong framework for the development of a sustainable lemon agro-industry with positive economic and environmental impacts.
Ergonomic Analysis of Small-Scale Palm Sugar Starch Processing Industry in Rancakalong Village, Sumedang Regency Thoriq, Ahmad; Arum, Marsya Sekar; Nanda, Muhammad Achirul
Jurnal Keteknikan Pertanian Vol. 12 No. 2 (2024): Jurnal Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19028/jtep.012.2.153-171

Abstract

Rancakalong village, Sumedang Regency, has been known for its small-scale palm sugar starch processing industry since 2013. This industry produces starch from palm trees, which is crucial for food and beverages. Generally, the processes involved in processing palm sugar starch include (i) splitting of the palm, (ii) grating, (iii) coarse fiber screening, (iv) fine fiber screening, (v) harvesting, and (vi) drying. Initial evaluations indicated that the workers experienced physical discomfort during their work. Therefore, this study aimed to analyze the ergonomic aspects of processing palm sugar starch, including the working posture, standard time, workload, noise, and vibration. Based on the analysis, the risk level for each work element in processing palm sugar starch fell into the high-risk (score 8-10) and very high-risk (score 11-15) categories. These risks cause discomfort due to inappropriate work posture and duration, necessitating significant changes. The standard time required for each work element was as follows: 212.88±28.43 seconds/kg (palm splitting), 363.45±12.90 seconds/kg (grating), 95.08±9.74 seconds/kg (coarse fiber screening), 192.05±21.27 seconds/kg (fine fiber screening), 35.57±5.78 seconds/kg (harvesting), and 1821.01±41.09 seconds/kg (drying). Regarding workload analysis, processing palm sugar starch activities fell into the moderate category with total energy cost (TEC) values ranging from 92.66±1.50 265.55±3.88 kcal/hour. Regarding noise and vibration analysis, the grating work element was identified as the station with the highest exposure, i.e., 96.00±0.82 dB and 1.6±0.05 m/s2, respectively. The results of this study could be used as a basis for developing more efficient work procedures, maintaining health, and improving safety in the processing of palm sugar starch.
Application of Ice Gel For Edible Flowers Distribution Packaging of Butterfly Pea Darmawati, Emmy; Wulandani, Dyah; Ulya, Kamila Nikmatul
Jurnal Keteknikan Pertanian Vol. 12 No. 2 (2024): Jurnal Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19028/jtep.012.2.172-183

Abstract

Butterfly pea (Clitoria ternatea) is a popular edible flower in Indonesia that is rich in antioxidants. However, they are perishable and sensitive to temperature changes during storage and transportation. The use of ice gel in distribution packaging has been identified as an effective solution to maintain its quality. This study aimed to determine the optimal positioning of ice gel in two types of distribution packaging: a Styrofoam box and an insulated box. The experiment involved cooling 36 g of flowers per distribution package over 2 h of simulation using six pieces of ice gel at two different positions (positions 1 and 2). The results showed that the ice gel placed in position 2 reduced the temperature inside the packaging more rapidly and maintained the lowest temperature for a longer period than the ice gel placed in position 1. Therefore, placing the ice gel in position 2 is the best option for application in the distribution package. Ice gel position 2 can reduce the flower’s temperature from 20°C to 10.7°C in the Styrofoam box and from 20oC to 11°C in the insulated box during simulation.
Feasibility Analysis of Using NIR Spectroscopy to Predict Ripeness Parameters of Red Guava Fruit (Psidium guajava L.) Hartanto, Rezza Naftari; Pertiwi, Setyo
Jurnal Keteknikan Pertanian Vol. 12 No. 2 (2024): Jurnal Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19028/jtep.012.2.230-241

Abstract

Red guava is highly preferred by Indonesians because of its delightful flavor, refreshing taste, and numerous advantages. It is a climacteric fruit, and the age at which red guava is picked affects the quality of the fruit. The estimation of the maturity parameters of red guava is physically destructive (damages the fruit). This study aimed to assess the NIR method to predict the maturity parameters of red guava fruit with wavelengths of 1000-2500 nm. Red guavas of four different picking ages were used in this study. The tested maturity parameters included firmness, moisture content, total soluble solids (TSS), acidity, and sugar-acid ratio at various harvest ages. The partial least squares (PLS) method was used for calibration and validation of NIRS data and reference data. The results of this study show that NIRS can estimate the ripeness of red guava fruit based on firmness, acidity, sugar-acid ratio, and water content. The best-estimated value for firmness parameters was obtained with pretreatment MSC factor PLS 14, resulting in r calibration of 0.94, SEP 7.20, CV 25.91%, and RPD 2.90; acidity without pretreatment factor PLS 13 obtained r calibration of 0.82, SEP 0.17, CV 24.42%, RPD 1.68; sugar acid ratio with pretreatment SNV factor PLS 10 obtained r calibration 0.75, SEP 4.03, CV 30.81%, RPD 1.51; and for moisture content using SNV pretreatment factor PLS 13, r calibration 0.88, SEP 0.95, CV 1.08%, RPD 1.95.
Rice Husk Availability Mapping as Biomass Cofiring Material at Power Plant in Indramayu Swastika, Abdul Baits Dehana Padma; Liyantono, Liyantono; Wulandani, Dyah
Jurnal Keteknikan Pertanian Vol. 12 No. 2 (2024): Jurnal Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19028/jtep.012.2.284-300

Abstract

Indonesia berencana untuk mengurangi emisi gas rumah kaca (GRK) sebesar 29% pada tahun 2030 untuk mengatasi penggunaan energi fosil yang tinggi. Salah satu strateginya adalah PT PLN mengimplementasikan teknologi pembakaran biomassa di 52 pembangkit listrik pada tahun 2025. Namun, keberlanjutan pasokan menjadi tantangan tersendiri, dengan penelitian yang belum memadai dan hanya 33,52% yang tercatat di pabrik penggilingan. Penelitian ini menghitung ketersediaan sekam padi untuk pembakaran biomassa di Kabupaten Indramayu, daerah penghasil beras terbesar di Indonesia. Dengan menggunakan pendekatan spasial, survei, wawancara, dan Quantum GIS (QGIS) versi 3.22.12, peta visual ketersediaan sekam padi dibuat. Data dari 95 penggilingan padi (79 kecil, 12 menengah, 4 besar) menunjukkan potensi sekam harian masing-masing sebesar 0,87, 4,83, dan 10,74 ton. Data produksi nasional memperkirakan ketersediaan sekam padi tahunan sebesar 272.106 ton. Analisis spasial dari survei dan wawancara mengindikasikan 601.669 ton/tahun, sementara distribusi menurut skala penggilingan menunjukkan 588.861 ton/tahun. Persaingan penggunaan sekam padi cukup tinggi untuk industri seperti genteng, batu bata, dan semen, dengan fraksi pemulihan sebesar 13,23%, 17,50%, dan 23,33% pada saat panen, serta 3,90%, 10%, dan 15% pada saat tidak panen. Sekam padi yang tersedia di Indramayu untuk bahan bakar biomassa adalah 77.102,17 ton/tahun. Jumlah ini berkontribusi sebesar 0,78% terhadap kebutuhan biomassa nasional dan 45,56% terhadap kebutuhan PLTU Indramayu. Kebijakan yang mendorong penggunaan dan pengelolaan sekam padi di daerah penghasil padi diperlukan untuk meningkatkan implementasi pembakaran biomassa.
Performance profile of Cold Storage Using R32 as Refrigerant for Traditional Fishing Boat with Photovoltaic as Energi Source Suhengki, Suhengki; Manik, Henry Munandar; Hartulistiyoso, Edy; Sumantri, Willi; Yulianto, Muhamad
Jurnal Keteknikan Pertanian Vol. 12 No. 2 (2024): Jurnal Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19028/jtep.012.2.184-203

Abstract

This paper discusses the performance of cold storage using R32 refrigerant. R32 is one of the recommended refrigerant with the main advantage low ODP and GWP (Global Warming Potential) value of around 0 and 675. However, because of this refrigerant classified as a new refrigerant, the implementation is limited to air conditioning and heat pump. In this paper, R32 will be tested for cold storage applications. The cold storage performance will be studied about the achieved temperature, power consumption, cooling capacity and Coefficient of Performance without load. The testing was carried out in 2 ways, cold storage testing on a lab scale and direct testing on a 5 GT fishing boat. The performance results show that both tests on a lab scale and tests directly on a fishing boat without a load can reach a cold storage room temperature of -18oC. Meanwhile, the compressor power consumption supplied by photovoltaic is 0.653-0.776 kW. Based on the test results, shows that R32 has a positive possibility of being applied to cold storage.
Macro-Nutrient Prediction of Paddy Field Soil Using Artificial Neural Network and NIR Spectroscopy Ahmad, Usman; Budiastra, I Wayan; Subrata, I Dewa Made; Firdaus, Jonni
Jurnal Keteknikan Pertanian Vol. 12 No. 2 (2024): Jurnal Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19028/jtep.012.2.242-258

Abstract

Understanding soil fertility, influenced by macronutrients like nitrogen, phosphorus, and potassium, is essential for adaptive agriculture implementation based on various soil conditions. Near-infrared spectroscopy technology provides non-destructive, rapid soil property measurements without chemicals, applicable both in-field and in-laboratory. However, the wide NIR spectrum range and neural network complexities can hinder Artificial Neural Network (ANN) training and inference, leading to time and resource inefficiency, especially without sophisticated computing devices. This study examines data reduction methods to enhance ANN performance in predicting soil macronutrients using NIR spectra. Multiple Linear Regression (MLR) and Principal Component Analysis (PCA) were applied to select wavelengths from the 1000–2500 nm for ANN input, comparing their performance. About 237 NIR reflectance data from paddy soil were transformed into absorbance data. MLR used forward selection to identify wavelengths with correlations higher than 0.9, while PCA selected wavelengths corresponding to the loading factor peaks for each principal component. These selected wavelengths served as inputs for the ANN model. The ANN’s performance was assessed using correlation and determination coefficients, RMSE, RPD, and model consistency. For nitrogen, the PCA+ANN model with reflectance spectra performed better (RPD 2.4-4.8) than the MLR+ANN model (RPD 2.2-2.6) using fewer wavelengths (5-9 for PCA+ANN vs. 9-12 for MLR+ANN). For phosphorus estimation, the PCA+ANN model also excelled (RPD 2.3-7.0 vs. 2.3-2.4) with fewer wavelengths (4-7 vs. 7). For potassium estimation, the PCA+ANN model showed superior performance (RPD 4.3-9.5 vs. 4.2-4.4), using the same number of wavelengths (4-8 vs. 4-6).
Rapid Prediction of Moisture and Ash Content in Sungkai Leaves Herbal Tea (Peronema canescens Jack.) using NIR Spectroscopy Andasuryani, Andasuryani; Ifmalinda
Jurnal Keteknikan Pertanian Vol. 12 No. 3 (2024): Jurnal Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19028/jtep.012.3.301-313

Abstract

It is imperative to measure the chemical composition of Sungkai leaf herbal tea in order to produce high-quality goods that promote human health. The moisture and ash content of Sungkai leaf herbal tea are critical parameters for assessing the quality of herbal tea. This study aimed to evaluate an NIR spectroscopy method for quickly determining the moisture and ash content of Sungkai leaf herbal tea. Sungkai leaf herbal tea has a moisture content between 3.93% and 7.59%, and an ash content between 3.94% and 5.51%. We developed a calibration model using partial least squares (PLS) with several pretreatment methods. We split the data into calibration and prediction sets and performed an internal random cross-validation. A PLS calibration model with Rp2 = 0.86, a root means square error of prediction (RMSEP) of 0.30 (%), and a residual predictive deviation (RPD) of 2.76, performed exceptionally well at predicting the moisture content when the standard normal variate (SNV) pre-treatment was applied to the NIR spectra. The Savitzky-Golay derivative (a 9-point smoothing window, second-order polynomial, dg2) pre-treatment method also generated the best PLS calibration model for ash content determination, with Rp2 = 0.70, RMSEP = 0.16 (%), and RPD = 1.86. NIR spectroscopy can quickly determine the moisture and ash content of Sungkai leaf herbal tea, as suggested by these findings.

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