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All Journal Jurnal Penelitian Saintek Proceedings of Annual International Conference Syiah Kuala University - Life Sciences & Engineering Chapter Jurnal Teknologi Pertanian agriTECH Indonesian Journal of Chemistry SINTECH (Science and Information Technology) Journal Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Jurnal Serambi Engineering Agroteknika Agro Bali: Agricultural Journal Jurnal Kedokteran Hewan Jurnal Ilmiah Mahasiswa Pertanian Rona Teknik Pertanian
Agus Arip Munawar
Department Of Agricultural Engineering, Syiah Kuala University, Aceh
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Energy Engineering Environmental Science Immunology & microbiology Mechanical Engineering Medicine & Pharmacology Veterinary Other

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Non-destructive method for maturity assessment of Indonesian’s mangoes by NIRS spectroscopy Muhammad Ikhsan Sulaiman; Agus Arip Munawar; . Ichwana
Proceedings of The Annual International Conference, Syiah Kuala University - Life Sciences & Engineering Chapter Vol 2, No 1 (2012): Life Sciences
Publisher : Syiah Kuala University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (334.222 KB)

Abstract

Rapid and non-destructive method to determine maturity quality of mangoes accurately has played an increasing role in the fruits supply chain involving automation. Diffuse reflectance spectra (R) and absorbance spectra (Log 1/R) in the spectral range from 900 to 1400 nm were measured using NIRS spectroscopy at three different points of 257 Indonesians mangoes cultivar arumanis, manalagi, gadong, gincu and golek of different ripeness indices. Through principle component analysis (PCA) and cluster analysis (CA) of the absorbance and reflectance spectra, cultivars can be differed with an accuracy of 99.8%. Multiple linear regression was applied to develop calibration models from mangoes with soluble solid content ranged between 5.5 and 13.5 % Brix and firmness ranged between 0.25 and 4.50 kgf. Log 1 /R calibration model could assess the soluble solid content and firmness of the mangoes with higher accuracy than R model with the coefficient of determination of 0.96 and 0.93, respectively. Results showed that NIRS spectroscopy has the feasibility to be employed in the maturity measures of Indonesian’s mangoes.
Near Infrared Reflectance Spectroscopy: Prediksi Cepat dan Simultan Kadar Unsur Hara Makro pada Tanah Pertanian Devianti Devianti; Sufardi Sufardi; Zulfahrizal Zulfahrizal; Agus Arip Munawar
agriTECH Vol 39, No 1 (2019)
Publisher : Faculty of Agricultural Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (413.135 KB) | DOI: 10.22146/agritech.42430

Abstract

Plants need an ideal and healthy soil condition for their growth and a sufficient amount of soil macronutrients. To determine soil nutrients, several methods have been widely employed. Yet, most of them are based on solvent extraction, which is normally time-consuming, requires complicated sample preparation, and sometimes involves chemical materials. Thus, a novel, fast and simultaneous method is required as an alternative method used to predict soil macronutrients in a short period and without involving chemical materials. Near infrared spectroscopy (NIRS) can be considered for this need, since this method is fast, environmentally friendly, and non-destructive. Therefore, the main objective of this study is to apply an NIRS method to predict soil macronutrients (N, P, and K). The diffuse reflectance spectrum was acquired for soil samples in a wavelength range from 1000–2500 nm. Spectra data were corrected using a smoothing method whilst prediction models were developed using principal component regression (PCR) and partial least square regression (PLSR). Prediction accuracy and robustness were evaluated using these following statistical indicators: correlation coefficient (r), root mean square error (RMSEC) and residual predictive deviation (RPD). The results showed that NIRS was able to predict soil macronutrients simultaneously with a maximum correlation coefficient r = 0.97 for N prediction, r = 0.99 for P prediction, and r = 0.95 for K prediction. Thus, it may be concluded that an NIRS method is feasible to be applied as a novel, reliable and fast method to predict soil macronutrients (N, P, and K) simultaneously.
PREDIKSI TOTAL PADATAN TERLARUT BUAH MELON GOLDEN MENGGUNAKAN VIS-SWNIRS DAN ANALISIS MULTIVARIAT Yuda Hadiwijaya; Kusumiyati Kusumiyati; Agus Arip Munawar
Jurnal Penelitian Saintek Vol 25, No 2 (2020)
Publisher : Institute of Research and Community Services, Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jps.v25i2.34487

Abstract

Penelitian ini bertujuan untuk memprediksi total padatan terlarut buah melon golden (Cucumis melo L.) menggunakan Vis-SWNIRS dan analisis multivariat. Terdapat 82 sampel buah melon golden dipilih untuk dianalisis di Laboratorium Hortikultura, Fakultas Pertanian, Universitas Padjadjaran. Nirvana AG410 spectrometer dengan rentang panjang gelombang 300 sampai 1050 nm digunakan untuk pengambilan data spektra pada sampel buah melon utuh. Metode koreksi spektra yang digunakan yaitu Standard Normal Variate (SNV), Multiplicative Scatter Correction (MSC), dan Orthogonal Signal Correction (OSC). Pemodelan kalibrasi dilakukan menggunakan Partial Least Squares Regression (PLSR). Hasil penelitian menunjukkan bahwa penggunaan metode koreksi spektra OSC menampikan model kalibrasi terbaik dibandingkan spektra original dan 2 spektra lainnya yang telah dikoreksi. Koefisien determinasi pada spektra OSC memperlihatkan nilai R2 tertinggi yaitu 0,99. Di samping itu, nilai ratio performance to deviation (RPD) yang diperoleh sebesar 3,40. Hal ini membuktikan total padatan terlarut buah melon golden dapat diprediksi dengan akurasi yang tinggi menggunakan Vis-SWNIRS dan analisis multivariat.PREDICTION OF TOTAL SOLUBLE SOLIDS OF GOLDEN MELON USING Vis-SWNIRS AND MULTIVARIATE ANALYSISThis study was aimed at predicting the total dissolved solids of golden melon (Cucumis melo L.) using Vis-SWNIRS and multivariate analysis. There were 82 golden melon fruit samples selected for analysis at the Horticulture Laboratory, Faculty of Agriculture, Padjadjaran University. Nirvana AG410 spectrometer with a wavelength range of 300 to 1050 nm was used to collect spectral data on intact melon fruit samples. The spectra correction methods used were Standard Normal Variate (SNV), Multiplicative Scatter Correction (MSC), and Orthogonal Signal Correction (OSC). Calibration modeling was carried out using Partial Least Squares Regression (PLSR). The results show that the use of the OSC spectra correction method presents the best calibration model compared to the original spectra and 2 other corrected spectra. The coefficient of determination on the OSC spectra shows the highest R2 value, namely 0.99, besides that the ratio performance to deviation (RPD) value obtained is 3.40. This proves that the total dissolved solids of golden melon can be predicted with high accuracy using Vis-SWNIRS and multivariate analysis.
PENERAPAN ALGORITMA DISKRIMINASI MENGGUNAKAN METODE PRINCIPAL COMPONENT ANALYSIS (PCA) DAN Vis-SWNIR SPECTROSCOPY PADA BUAH CABAI RAWIT DOMBA BERBAGAI TINGKAT KEMATANGAN Ine Elisa Putri; Kusumiyati Kusumiyati; Agus Arip Munawar
SINTECH (Science and Information Technology) Journal Vol. 4 No. 1 (2021): SINTECH Journal Edition April 2021
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v4i1.680

Abstract

Cayenne pepper fruit can be used for health because it is a source of antioxidants. Detection of quality fruit can use non-destructive methods as an alternative method. Visible short wavelength near infrared (Vis-SWNIR) spectroscopy is non-destructive measurement. This method can be used to discriminate fruit by using the principal component analysis (PCA). This research aimed to discriminate between Cayenne pepper with various maturity by using Vis-SWNIR spectroscopy with a wavelength of 300-1065 nm and principal component analysis (PCA). Cayenne pepper fruit was devided into three groups, namely green, orange and red. The spectrum used the absorbance spectrum data (original). The research was carried out from March to June 2020. The result showed that the use of Vis-SWNIR and PCA were able to discriminate various maturity of cayenne pepper with a 100% success rate.
Simulasi Penurunan Kadar Asam Askorbat Buah Jambu Biji (Psidium Guajava L.) Selama Penyimpanan Menggunakan Visual Basic 6.0 Annisa Azzahra; Ratna Ratna; Agus Arip Munawar
Jurnal Serambi Engineering Vol 6, No 2: April 2021
Publisher : Fakultas Teknik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jse.v6i2.2956

Abstract

Technological advances continue to develop rapidly and people need technology that is more efficient and faster in their work, including in the field of agriculture. Therefore, simulation is a suitable way to be implemented in the scope of modern society. This study aims to reduce the number of research and experimental trials in the laboratory because it takes a lot of time and money. This research refers to a simulation of decreasing levels of ascorbic acid in guava fruit during the storage period which is carried out by presenting data obtained from various sources, programming and simulation design using Visual Basic 6.0 and program testing. Guava fruit (Psidium guajava L) has  vitamin C content about 183.5 mg / 100 grams of material. The test results of this program, within 10 days of storage at room temperature (25oC) the levels of Ascorbic Acid in Guava fruit decreased by 56.1% and decreased levels of Ascorbic Acid by 92.26%, from 183.5 mg / 100 gr to around 12, 84 mg / 100 gr guava fruit for 720 hours. Therefore, the results of this simulation program succeeded in approaching the real number of decreases in ascorbic acid levels tested in original observations.
Pengembangan Produk Minyak Nilam Dalam Upaya Memenuhi Standar Quality Patchouli Alcohol Menggunakan Chemometric Zikrul Khalid; Hesti Meilina; Syaubari Syaubari; Agus Arip Munawar
Jurnal Serambi Engineering Vol 1, No 2 (2017)
Publisher : Fakultas Teknik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jse.v1i2.502

Abstract

Minyak nilam merupakan salah satu komoditas ekspor paling besar di Indonesia, akan tetapi saat ini kualitias dari minyak nilam masih sangat rendah hal ini ditandai dengan rendahnya kandungan patchouli alkohol sebagai kompenen utama. Tujuan dari penelitian ini yaitu untuk menganalisis komponen  utama minyak nilam (patchoulialkohol) secara cepat tanpa merusak sampel. Rancangan penelitian ini menggunakan model kalibrasi dan validasi pada patchouli alkohol dengan menggunakan Partial Least Square (PLS) sebagai bagian dari analisis Chemometrics. Hasil penelitian menunjukkan bahwa peningkatan performa kinerja PLS pada pretreatment multiplicative scatter correction dengan nilai RPD yang paling besar yaitu 302,5. Sehingga dapat tergolong ke dalam good model performance dengan nilai koefisien korelasi (r) yang tinggi 0,99, nilai koefisien determinasi (R2) yang bagus 83%, dan nilai error (RMSECV) yang paling kecil yaitu 0,02.
Penerapan Teknologi Visible-Near Infrared Spectroscopy untuk Prediksi Cepat dan Simultan Kadar Air Buah Melon (Cucumis melo L.) Golden Yuda Hadiwijaya; Kusumiyati Kusumiyati; Agus Arip Munawar
Agroteknika Vol 3 No 2 (2020): Desember 2020
Publisher : Green Engineering Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32530/agroteknika.v3i2.83

Abstract

Kadar air merupakan salah satu atribut kualitas yang penting pada komoditas hortikultura. Penetapan kadar air buah melon dengan metode konvensional memakan waktu yang lama dan perlu merusak sampel buah. Penelitian ini bertujuan untuk memprediksi kadar air buah melon golden menggunakan teknologi visible-near infrared spectroscopy (Vis-NIRS). Metode koreksi spektra orthogonal signal correction (OSC) diterapkan pada spektra original untuk meningkatkan kehandalan model kalibrasi. Partial least squares regression (PLSR) digunakan sebagai metode pendekatan regresi untuk mengekstraksi data spektra Vis-NIRS. Hasil penelitian membuktikan bahwa Vis-NIRS dapat diandalkan untuk memprediksi kadar air buah melon golden. Metode koreksi spektra OSC mampu memperkecil jumlah principal component (PC) pada spektra original. Linieritas pada model kalibrasi menggunakan spektra OSC tercatat memperoleh nilai tertinggi sebesar 0,92. Ratio of performance to deviation (RPD) pada spektra OSC menampilkan nilai tertinggi pula yaitu 3,63. Model kalibrasi yang diperoleh pada penelitian ini dapat ditransfer ke dalam spektrometer Vis-NIRS untuk prediksi kadar air melon golden secara cepat dan simultan.
Model Prediksi Kadar Air Buah Cabai Rawit Domba (Capsicum frutescens L.) Menggunakan Spektroskopi Ultraviolet Visible Near Infrared Kusumiyati Kusumiyati; Ine Elisa Putri; Agus Arip Munawar
Agro Bali : Agricultural Journal Vol 4, No 1 (2021)
Publisher : Universitas Panji Sakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (733.641 KB) | DOI: 10.37637/ab.v0i0.615

Abstract

Penelitian ini bertujuan untuk menduga kadar air buah cabai rawit domba (Capsicum frutescens L.) menggunakan spektroskopi UV-Vis-NIR. Total sampel yang digunakan yaitu 45 buah. Analisis dilakukan di Laboratorium Hortikultura, Fakultas Pertanian, Universitas Padjadjaran. Akuisisi data spektra dengan rentang panjang gelombang 300 – 1050 nm (Nirvana AG410). Spektra diperbaiki dengan metode multiplicative scatter correction (MSC), standard normal variate transformation (SNV), orthogonal signal correction (OSC), first derivative (dg1) dan second derivative (dg2). Analisis data dilakukan dengan menggunakan partial least squares regression (PLSR). Berdasarkan penelitian ini menunjukkan bahwa metode koreksi OSC menghasilkan model kalibrasi tertinggi dengan Rkal, RMSEC, Rval, RMSECV, RPD dan faktornya masing-masing yaitu 0.99, 0.31, 0.98, 0.68, 6.62 dan 4. Hal ini menunjukkan bahwa spektroskopi UV-Vis-NIR dapat digunakan untuk memprediksi kadar air pada buah cabai rawit domba.
Extraction, Isolation, and Characterization of Nanocrystalline Cellulose from Barangan Banana (Musa acuminata L.) Peduncles Waste Ratna Ratna; Nasrul Arahman; Agus Arip Munawar; Sri Aprilia
Indonesian Journal of Chemistry Vol 23, No 1 (2023)
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijc.74718

Abstract

Microwave-assisted acid hydrolysis has an impact on the characteristics of nanocrystalline cellulose (NCCs). In this study, NCCs was prepared from banana peduncles through hydrolysis of sulfuric acid (concentrations of 1, 2, and 3 M) and hydrolysis time (0.5 and 1.5 h) assisted by microwave and ultrasonic energy to obtain the best NCCs. The characterization of NCCs properties, namely, yield, morphology, functional groups, crystallinity, heat resistance, particle size, and color. The results showed that the yield of NCCs decreased as sulfuric acid concentration and the time length of hydrolysis increased. The FTIR spectra of NCCs showed the most relevant molecular bands, namely O–H, C–H, and C–O, at the wavenumbers range of 3200–4000, 2500–3200, and 500–1500 cm−1, respectively. The TGA test showed that the decomposition of NCCs occurred at a temperature of 275.35–409.40 °C, with a weight loss ranging from 84.00% to 94.09%. Crystallinity index and crystal sizes range from 53.99% to 57.33% and 22.35 to 36.28 nm, respectively. The brightest color of NCCs powder was generated with 1 M sulfuric acid and a hydrolysis time of 0.5 h. In conclusion, barangan banana peduncles waste can be used as raw material for producing NCCs.
PREDIKSI CEPAT KUALITAS AIR MENGGUNAKAN LPAS (LASER PHOTO-ACOUSTIC SPECTROSCOPY) DENGAN MENERAPKAN METODE KOREKSI CUTTING EDGE FILTERING Ichwana Ramli; Agus arip Munawar; Khairul Abdi Ruslana
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.v10i2.220-227

Abstract

A tool that can predict water quality by capturing sound vibrations generated by collisions between water samples and light is LPAS (Laser Photo-Acoustic Spectroscopy). To process the data acquired by LPAS, spectrum correction is needed to eliminate data errors when making acquisitions on water samples. The correction method used in this research is the cutting edge filtering correction method. The regression model that can be used is the PLSR (Partial Least Square Regression) regression model. This research was conducted in the Instrumentation and Energy Laboratory, Agricultural Engineering Study Program, Faculty of Agriculture, Syiah Kuala University. Water sample analysis was carried out at the Laboratory of the Industrial Research and Standardization Center (BARISTAND) Banda Aceh. This study used 4 monitoring wells within the TPA (Final Disposal Site) and 4 samples were taken from community wells outside the scope of TPA Gampong Jawa, Banda Aceh City. The results of this study indicate the parameters (temperature, turbidity, Ph, TSS, DO, BOD and Nitrate) are predicted to be in the frequency range 4000 - 10,000 cm-1. Raw spectrum data for pH and Nitrate (NO3-) parameters produce better data than the spectrum data for cutting edge filtering correction methods while cutting edge filtering spectrum data for temperature, turbidity, TSS, DO and BOD-5 parameters are better than spectrum raw data. This study also shows that the cutting edge filtering correction method is able to cut boundaries and compress the spectrum so that it can provide data limits on the spectrum so that the PLSR method can be applied to predict water quality. Keywords: water quality; Laser Photo-Acoustic Spectroscopy, correction method, regression method
Co-Authors . Ichwana Abuijal Muhammad Rifaldi Agussabti Agussabti Annisa Azzahra Aulia Ifnu Akbar Br Padang, Sheila Saharani Cut Dahlia Iskandar Darwin Darwin Desi Nanda Sari Devianti Devianti Devianti Devianti Devianti Devianti Devianti Devianti Dewi Sri Jayanti Dian Sri Bintang Hasiholan Manihuruk Diding Suhandy Diswandi Nurba, Diswandi Dwi Anindea Putri Endamin Endamin Fachruddin Fachruddin Fitria Nisak Fredinan Yulianda Giar Pramanda Putra Hairatun Hairatun Hayati Zahra Hesti Meilina Ichwana Ichwana Ichwana Ramli Ichwana Ramli Indera Sakti Nasution Ine Elisa Putri Ine Elisa Putri Intan Ratna Juwita Irfan Maibriadi Khairul Abdi Ruslana Khairul Abdi Ruslana Kiman Siregar Kusumiyati Masdar Masdar Mohd Nazar Isza Putra Muaida Alfia Mubarak Hulda Muhammad Ikhram Muhammad Ikhsan Sulaiman Muhammad Zikri Pratama Munanda Irawan Murtahar Murtahar Muslem Muslem Mustaqimah Mustaqimah Najla Mumtazmi Nasrul Arahman Nur Alfah Puji Meihani Qurratul Zulmi Raida Agustina Raida Agustina Ramayanty Bulan Ratna Ratna Ratna Ratna Ratna Ratna Ridwan Ridwan Rina Aulia Barus Riska Nurul Saputri Rita Khathir Rita Zahara Salman Rivaldi Solly Aryza Sri Aprilia Sri Purnama Sari Sufardi Sufardi Suswita Sari Syahrul Ramadhan Syaubari syaubari Teuku Hafidh Tyas Al Khalis Yesi Ardiani Yovita Amanda Yuda Hadiwijaya Yusmanizar Yusmanizar Yusril Agus Putra Yuswar Yunus Z Zainuddin Zikrul Khalid Zulfahrizal Zulfahrizal zulfahrizal zulfahrizal Zulfahrizal Zulfahrizal Zulfahrizal Zulfahrizal Zulfahrizal Zulfahrizal Zulkifli Nasution