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All Journal Journal of Applied Agricultural Science and Technology Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Eksakta : Berkala Ilmiah Bidang MIPA Jurnal Teknologi Pertanian Andalas Warta Pengabdian Andalas: Jurnal Ilmiah Pengembangan Dan Penerapan Ipteks Andalasian International Journal of Agricultural and Natural Sciences Journal of Applied Agricultural Science and Technology Jurnal Al Karim : Jurnal Pendidikan, Psikologi dan Studi Islam Andalasian International Journal of Social and Entrepreneurial Development Rona Teknik Pertanian
Muhammad Makky
Universitas Andalas
Religion Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Education Energy Engineering Environmental Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Social Sciences Other

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

 1 
Prediction of Caffeine and Protein of Arabica Coffee Beans Using Near Infrared Spectroscopy (NIRS) Fitri Yuwita; Ifmalinda Ifmalinda; Muhammad Makky
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol 12, No 4 (2023): December 2023
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v12i4.852-862

Abstract

Testing the chemical components of coffee beans has so far been carried out conventionally with laboratory analysis which requires a long time and is expensive. Technological advances allow testing of chemical components to be carried out quickly and accurately using the NIRS (Near Infra Red Spectroscopy) method. This research aims to develop a prediction model for caffeine and protein in Solok Radjo coffee beans using the NIRS method. Solok Radjo coffee is a type of Arabica with specialty grade because of its very strong character, aroma and taste. A total of 30 samples with a weight of 6 g per sample were used in this study. This research uses NIRS Type FT-IR IPTEK T-1516 with a wavelength of 1000 - 2500 nm. The partial least squares (PLS) method was used to process the data with several SNV, MN, and MSC pretreatments to improve the model. The research results show that caffeine is found at wavelengths of 1456 - 1475 nm, 1937 - 1974 nm. Proteins 1455 - 1475 nm, and 1935 - 1974 nm. MSC pretreatment is able to improve PLS performance results. Caffeine calibration values are R2 = 0.996 and SEC = 0.002%, validation values R2 = 0.989, SEP = 0.002%, and RPD 11.869 while protein calibration R2 = 0.999 and SEC = 0.004%, Validation values R2 = 0.999, SEP = 0.010%, and RPD 19,943. NIRS can be used to predict the chemical components of Solok Radjo coffee non-destructively using the PLS method. Key work: Caffeine, NIRS, PLS, predict, protein 
Non-destructive Evaluation of Oil Content and Carotene in Oil Palm Fresh Fruit Bunches Based on Optical Properties Using Partial Least Square (PLS) Suaidah Rahmi; Dinah Cherie; Ifmalinda Ifmalinda; Muhammad Makky
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol 13, No 3 (2024): September 2024
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v13i3.720-729

Abstract

Crude palm oil (CPO) is a raw material for making cooking oil that comes from palm oil, which is greatly influenced by the quality of oil palm fresh fruit bunches (FFB). Oil and carotene content in the FFB influence the quality of palm oil. The oil content is usually determined using a chemical method (Soxhlet extraction) which is time consuming and destructive. This research aimed to predict the oil and carotene content contained in oil palm FFB using partial least square (PLS). In this research, the sample used was the Tenera variety with a maturity of 140-160 day after anthesis (DAA) and 200-220 DAA. The nondestructive method involves recording images using an optical camera, which produces RGB and L*a*b* values. Results showed that PLS predicts the relationship between optical properties and oil and carotene content in palm oil. Non-destructive prediction results using PLS provided consistently correlation of L*a*b* values with estimated oil and carotene content in the FFB. Keywords: Non-destructive, Optical properties, Fresh fruit bunch, Oil palm.
Mini Cutting Force Sensor: A Novel Approach for Predicting Cutting Forces of Agricultural Products Putri, Irriwad; Putri, Renny Eka; Makky, Muhammad; Santosa, Santosa
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol 14, No 2 (2025): April 2025
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v14i2.645-656

Abstract

Innovation in agricultural mechanization is crucial for the sustainable development of agricultural machinery in Indonesia. This study aims to design and develop a cutting force measurement device for agricultural products. The device consists of a mechanical system utilizing a linear actuator (5.88 mm/s) as a blade pusher and a control system employing a load cell as a force sensor. Testing was conducted using three blade types with cutting angles of 10°, 15°, and 20° on taro, chayote, and papaya. Measurement data were displayed as graphs on an LCD and stored as XLS files on an SD card. The tested materials had moisture content ranging from 85% to 95%. Results showed that taro required the highest cutting force (74.3 N), followed by chayote (39.77 N) and papaya (31.1 N), corresponding to their hardness and moisture content. In contrast, the highest cutting speed was observed in chayote (6.1 mm/s), followed by papaya (5.8 mm/s) and taro (3.5 mm/s) using a 20° blade. These findings confirm that harder materials with lower moisture content require greater cutting force than softer materials with higher moisture content. Keywords: Controller, Cutting force, Load cell, Mechanization, Small-scale.
Non-Destructive Evaluation of Oil and Free Fatty Acid Content of Oil Palm Fresh Fruit Bunch Based on Thermal Properties Using Partial Least Square (PLS) Monica Guspa; Muhammad Makky; Santosa Santosa; Dinah Cherie
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol 13, No 3 (2024): September 2024
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v13i3.772-781

Abstract

Indonesia is the largest producer of palm oil in the world, contributing 59 % of global production in 2022. The palm oil industry is a pillar of the economy and a source of foreign exchange through agricultural exports. To increase productivity and global competitiveness, strategies are needed, including improving cultivation technology and determining optimum harvest times through the application of appropriate cultivation technology. This research aims to increase oil palm productivity by focusing on the harvest time of Fresh Fruit Bunches (FFB). The sample used was Tenera variety palm FFB with two levels of ripeness, namely 140-160 DAP and 200-220 HSP. Non-destructive technology can accurately measure the optimum ripeness level of FFB. This approach uses thermal camera technology for nondestructive evaluation, recording the intensity of infrared radiation from TBS. All measurement parameters resulting from thermal image processing (RGB, L*a*b and temperature) will be used as input variable data to be modeled with oil content free fatty acid data in the laboratory. The model design will be built using the Principal Component Analysis (PCA) and Partial Least Square (PLS) methods. The results showed that the coefficient of determination (R2) for oil content was 0.8681 and free fatty acid content was 0.786. Keywords: FFB, Nondestructive, Oil content, PLS, Thermal properties
Non-destructive Evaluation of Oil Content and Carotene in Oil Palm Fresh Fruit Bunches Based on Optical Properties Using Partial Least Square (PLS) Rahmi, Suaidah; Cherie, Dinah; Ifmalinda, Ifmalinda; Makky, Muhammad
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 13 No. 3 (2024): September 2024
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v13i3.720-729

Abstract

Crude palm oil (CPO) is a raw material for making cooking oil that comes from palm oil, which is greatly influenced by the quality of oil palm fresh fruit bunches (FFB). Oil and carotene content in the FFB influence the quality of palm oil. The oil content is usually determined using a chemical method (Soxhlet extraction) which is time consuming and destructive. This research aimed to predict the oil and carotene content contained in oil palm FFB using partial least square (PLS). In this research, the sample used was the Tenera variety with a maturity of 140-160 day after anthesis (DAA) and 200-220 DAA. The nondestructive method involves recording images using an optical camera, which produces RGB and L*a*b* values. Results showed that PLS predicts the relationship between optical properties and oil and carotene content in palm oil. Non-destructive prediction results using PLS provided consistently correlation of L*a*b* values with estimated oil and carotene content in the FFB. Keywords: Non-destructive, Optical properties, Fresh fruit bunch, Oil palm.
Non-Destructive Evaluation of Oil and Free Fatty Acid Content of Oil Palm Fresh Fruit Bunch Based on Thermal Properties Using Partial Least Square (PLS) Guspa, Monica; Makky, Muhammad; Santosa, Santosa; Cherie, Dinah
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 13 No. 3 (2024): September 2024
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v13i3.772-781

Abstract

Indonesia is the largest producer of palm oil in the world, contributing 59 % of global production in 2022. The palm oil industry is a pillar of the economy and a source of foreign exchange through agricultural exports. To increase productivity and global competitiveness, strategies are needed, including improving cultivation technology and determining optimum harvest times through the application of appropriate cultivation technology. This research aims to increase oil palm productivity by focusing on the harvest time of Fresh Fruit Bunches (FFB). The sample used was Tenera variety palm FFB with two levels of ripeness, namely 140-160 DAP and 200-220 HSP. Non-destructive technology can accurately measure the optimum ripeness level of FFB. This approach uses thermal camera technology for nondestructive evaluation, recording the intensity of infrared radiation from TBS. All measurement parameters resulting from thermal image processing (RGB, L*a*b and temperature) will be used as input variable data to be modeled with oil content free fatty acid data in the laboratory. The model design will be built using the Principal Component Analysis (PCA) and Partial Least Square (PLS) methods. The results showed that the coefficient of determination (R2) for oil content was 0.8681 and free fatty acid content was 0.786. Keywords: FFB, Nondestructive, Oil content, PLS, Thermal properties
Mini Cutting Force Sensor: A Novel Approach for Predicting Cutting Forces of Agricultural Products Putri, Irriwad; Turnando, Ardi; Lubis, Mei Mardhiani; Makky, Muhammad; Putri, Renny Eka; Santosa, Santosa
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 14 No. 2 (2025): April 2025
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v14i2.645-656

Abstract

Innovation in agricultural mechanization is crucial for the sustainable development of agricultural machinery in Indonesia. This study aims to design and develop a cutting force measurement device for agricultural products. The device consists of a mechanical system utilizing a linear actuator (5.88 mm/s) as a blade pusher and a control system employing a load cell as a force sensor. Testing was conducted using three blade types with cutting angles of 10°, 15°, and 20° on taro, chayote, and papaya. Measurement data were displayed as graphs on an LCD and stored as XLS files on an SD card. The tested materials had moisture content ranging from 85% to 95%. Results showed that taro required the highest cutting force (74.3 N), followed by chayote (39.77 N) and papaya (31.1 N), corresponding to their hardness and moisture content. In contrast, the highest cutting speed was observed in chayote (6.1 mm/s), followed by papaya (5.8 mm/s) and taro (3.5 mm/s) using a 20° blade. These findings confirm that harder materials with lower moisture content require greater cutting force than softer materials with higher moisture content. Keywords: Controller, Cutting force, Load cell, Mechanization, Small-scale.
Co-Authors - Andasuryani Alfian Zein Ardi Ardi Astri Harnov Putri Azrifirwan, Azrifirwan Berri Brilliant Albar Cherie Dinah, Cherie Daimon Syukri Dina, Mivtahul Eka Candra Lina Fithra Herdian Fitri Yuwita Guspa, Monica Halwa, Haniyatul Haniyatul Halwa Hendra Hendra Heri, Deden Ifmalinda Indra Dwipa Jamaluddin Jamaluddin Khandra Fahmi Khandra Fahmy Leo Saputra Napitu Lubis, Mei Mardhiani Mivtahul Dina Mohamad Erihadiana, Mohamad Monica Guspa NOVRI NELLY PERDANA PUTERA Prima Fithri Putri, Irriwad Rahmi, Suaidah Renny Eka Putri, Renny Eka Rini Rini Rini Rini RINI RINI Rusnam Rusnam Santosa Santosa Santosa Santosa Sinambela, Juli Arifiansyah Sirtin, Ardillah Anggraini Sri Aulia Novita Suaidah Rahmi Surya, Ridho Adi Turnando, Ardi Vonny Indah Mutiara Yulianti Zakiah, Qiqi