scholarly journals Pengembangan Metode Klasifikasi Biji Kopi Beras Arabika Gayo dan Robusta Gayo dengan Metode PCA (Principal Component Analysis) Berdasarkan Pengolahannya

2020 ◽  
Vol 4 (4) ◽  
pp. 472-481
Author(s):  
Ilka Agusti Febriyansyah ◽  
Rahmat Fadhil ◽  
Zulfahrizal Zulfahrizal
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Coffee Bean ◽  
Wet Process ◽  
Robusta Coffee ◽  
Coffee Beans ◽  
Ft Ir ◽  
The Difference ◽  
Spectrum Data

Abstrak. Kopi merupakan salah satu tanaman yang telah banyak dibudidayakan karena memiliki manfaat dan memiliki nilai jual yang cukup tinggi. Pengolahan kopi secara basah dapat dilakukan dengan dua cara yaitu dengan cara basah (full wash)  dan semi basah (semi wash). Secara visual sulit mengidentifikasi perbedaan dari biji kopi beras robusta proses basah (full wash) dengan kopi semi basah (semi wash). Tujuan yang ingin dicapai dalam  penelitian  ini adalah untuk membangun metode klasifikasi kopi Arabika Gayo dan Robusta Gayo dalam bentuk biji kopi beras menggunakan pengolahan basah (full wash) dan pengolahan semi basah (semi wash). Bahan yang digunakan dalam penelitian ini biji kopi beras Arabika dan Robusta dari tanah Gayo. Penelitian ini menggunakan Principal Component Analysis (PCA) sebagai metode pengolah data spektrum. Pengukuran spektrum kopi menggunakan Self developed FT-IR IPTEK T-1516. Panjang gelombang yang digunakan pada penelitian ini antara 1000-2500 nm dengan interval 0.4 nm. Data spektrum diolah menggunakan unscrambler software® X version 10.1. Hasil penelitian menunjukkan bahwa NIRS dengan metode PCA juga mampu mengklasifikasikan biji kopi beras full wash dengan semi wash pada biji kopi Arabika dan Robusta dimana zat dominan pembeda adalah asam amino dan lemak.Development of Gayo Arabica and Robusta Gayo Arabica Coffee Bean Classification Methods with PCA( Principal Component Analysis) Method Based on ProcessingAbstract. Coffee is a plant that has been widely cultivated because it has benefits and has a high selling value. Wet coffee processing can be done in two ways, namely by means of wet (full wash) and semi-wet (semi wash). It is visually difficult to identify the difference between the wet process robusta coffee beans (full wash) and semi-wash coffee. The aim of this research is to develop a method of classifying Arabica Gayo and Robusta Gayo coffee in the form of rice coffee beans using wet wash (full wash) and semi wash. The material used in this study was Arabica and Robusta rice coffee beans from Gayo soil. This study uses Principal Component Analysis (PCA) as a method for processing spectrum data. The measurement of coffee spectrum uses Self-developed FT-IR IPTEK T-1516. Wavelengths used in this study are between 1000-2500 nm with 0.4 nm intervals. Spectrum data are processed using unscrambler software® X version 10.1. The results showed that NIRS with PCA method was also able to classify full wash coffee beans with semi wash in Arabica and Robusta coffee beans where the dominant differentiating substances were amino acids and fats.

scholarly journals Pengembangan Metode Klasifikasi Biji Kopi Sangrai Arabika Gayo dan Robusta Gayo dengan Metode PCA (Principal Component Analysis) Berdasarkan Pengolahannya

2020 ◽  
Vol 4 (4) ◽  
pp. 562-571
Author(s):  
Cut Faradilla Zha Zha Maura ◽  
Rahmat Fadhil ◽  
Zulfahrizal Zulfahrizal
Keyword(s):  
Principal Component Analysis ◽  
Near Infrared ◽  
Principal Component ◽  
Component Analysis ◽  
Roasted Coffee ◽  
Near Infrared Reflectance ◽  
Coffee Beans ◽  
Medium Level ◽  
Pca Method ◽  
Ft Ir

Abstrak. Tanaman kopi merupakan suatu tanaman yang dapat meningkatkan sumber devisa negara lewat ekspor biji mentah maupun olahan dari biji kopi. Pengolahan kopi yang berbeda maka akan menghasilkan mutu kopi yang berbeda juga, semakin bagus prosesnya maka akan semakin tinggi mutu dan harga dari kopi. Pendeteksian perbedaan proses pengolahannya yang cepat dan efisien dapat diwujudkan dengan teknologi Near Infrared Reflectance Spectroscopy (NIRS). Tujuan yang ingin dicapai dalam penelitian ini adalah untuk membangun metode klasifikasi kopi arabika dan robusta Gayo menggunakan pengolahan full wash dan semi wash dalam bentuk biji kopi yang telah disangrai. Kopi disangrai pada tingkat medium (200-205ºC) dalam waktu 16 menit. Akuisisi spektrum kopi menggunakan Self developed FT-IR IPTEK T-1516. Selanjutnya data spektrum diolah menggunakan unscrambler software® X version 10.1 dengan metode PCA (Principal Component Analysis). Hasil penelitian menunjukkan bahwa NIRS dengan metode PCA mampu mengklasifikasikan biji kopi sangrai berdasarkan pengolahannya yaitu Semi wash dan Full wash. Melalui studi ini ditemukan juga selang panjang gelombang yang dapat mengidentifikasikan kualitas kopi sehingga dapat digunakan untuk penelitian selanjutnya dalam pengembangan model identifikasi kualitas kopi.Development of Classification Methods for Gayo Roasted Arabica Coffee and Gayo Robusta by PCA Method (Principal Component Analysis)Abstract. Coffee crop is a plant that can increase the country's foreign exchange source through the export of raw beans and processed coffee beans. Different coffee processing will produce different coffee quality as well, the better the process then the quality and price of the coffee is more higher. Therefore, alternative rapid and efficiently method is needed to detect differences in the processing of coffee. Near Infrared Spectroscopy (NIRS) can be considered to be used due to its advantages. The main objective of this study is to build classification method of Gayo Arabica and Robusta coffee using fullwash and semiwash processing in form of roasted. Coffee is roasted at a medium level (200-205ºC) within 16 minutes. Acquisition of the coffee spectrum using Self-developed FT-IR IPTEK T-1516. Furthermore, the spectrum data is processed using unscrambler software ® X version 10.1 with the PCA (Principal Component Analysis) method. The results showed that NIRS with the PCA method was able to classify roasted coffee beans based on its processing, namely Semi wash and Full wash. Through this study, it was also found that wavelength intervals can identify coffee quality so that it can be used for further research in developing coffee quality identification models

Analisis Skrining Fitokimia dan Aktivitas Antioksidan Ekstrakk Biji Sangrai Kopi Robusta (Coffea canephora) dari Tanaman Hasil Pemupukan Organik dan Anorganik

2021 ◽  
Vol 3 (2) ◽  
Author(s):  
Farah Aida Qotrun Nada ◽  
Tintrim Rahayu ◽  
Ari Hayati
Keyword(s):  
Statistical Tests ◽  
Linear Regression Analysis ◽  
Coffea Canephora ◽  
Coffee Bean ◽  
Phytochemical Screening ◽  
Robusta Coffee ◽  
A Value ◽  
Coffee Beans ◽  
Ic50 Value ◽  
The Difference

Ground coffee is coffee beans that have been roasted, ground or ground so that they have a smooth shape. The purpose of this study was to determine the content of compounds in robusta coffee roasted seed extract (Coffea canephora) from plants produced by organic and inorganic fertilization, and to know the difference in compounds between the results of organic and inorganic fertilization. The characteristics of phytochemical screening were carried out qualitatively on alkaloids, flavonoids, tannins, terpenoids and saponins and the antioxidant activity was carried out by the DPPH (1,1-dipenyl-2-picrihidrazil) method. Phytochemical screening characteristic test results show that robusta coffee bean extract extract from the results of organic and inorganic fertilization both contain flavonoids, alkaloids, tannins, and saponins, while the antioxidant test activity of robusta coffee beans extracts shows differences based on the results of statistical tests of linear regression analysis with the IC50 value the highest antioxidant content was inorganic coffee roasted bean extract only 14.0629 ppm compared to the organic roasted extract with a value of 30.6159 ppmKeywords: Robusta Coffee (Coffea canophora), Phytochemical Screening, DPPH MethodABSTRAKKopi bubuk adalah biji kopi yang telah disangrai digiling atau ditumbuk sehingga mempunyai bentuk halus. Tujuan dari penelitian ini adalah untuk mengetahui kandungan senyawa dalam ekstrak biji sangrai kopi robusta (Coffe canephora) dari tanaman hasil pemupukan organik dan anorganik, dan mengetahui perbedaan senyawa antara hasil pemupukan organik dan anorganik. Karakteristik skrining fitokimia dilakukan secara kualitatif yang dilakukan terhadap alkaloid, flavonoid, tanin, terpenoid dan saponin dan aktivitas antioksidan dilakukan dengan metode DPPH (1,1-difenil-2-pikrihidrazil). Hasil uji karakteristik skrining fitokimia menunjukkan bahwa ekstrak biji sangrai kopi robusta dari hasil pemupukan oganik dan anorganik keduanya sama mengandung senyawa flavonoid, alkaloid, tanin, dan saponin,  sedangkan pada aktifitas uji antioksidan ekstrak biji sangrai kopi robusta menunjukan perbedaan berdasarkan hasil uji statistik analisis regresi linear dengan nilai IC50 kadar antioksidan paling tinggi adalah ekstrak biji sangrai kopi anorganik hanya 14,0629 ppm dibandingkan dengan ekstrak sangrai dari organik dengan nilai 30,6159 ppm.Kata kunci : Kopi Robusta (Coffea canophera), Skrining Fitokimia, Metode DPPH

scholarly journals Deteksi Formalin Pada Buah Tomat (Lycopersicum esculentum Mill) Dengan Teknologi Hidung Elektronik (Electronic Nose)

2019 ◽  
Vol 4 (2) ◽  
pp. 359-366
Author(s):  
Irfan Maibriadi ◽  
Ratna Ratna ◽  
Agus Arip Munawar
Keyword(s):  
Principal Component Analysis ◽  
Electronic Nose ◽  
Principal Component ◽  
Component Analysis ◽  
Lycopersicum Esculentum ◽  
Olfactory Ability ◽  
Pca Method ◽  
The Difference ◽  
Electronic Nose Technology

Abstrak,  Tujuan dari penelitian ini adalah mendeteksi kandungan dan kadar formalin pada buah tomat dengan menggunakan instrument berbasis teknologi Electronic nose. Penelitian ini menggunakan buah tomat yang telah direndam dengan formalin dengan kadar 0.5%, 1%, 2%, 3%, 4%, dan buah tomat tanpa perendaman dengan formalin (0%). Jumlah sampel yang digunakan pada penelitian ini adalah sebanyak 18 sampel. Pengukuran spektrum beras menggunakan sensor Piezoelectric Tranducer. Klasifikasi data spektrum buah tomat menggunakan metode Principal Component Analysis (PCA) dengan pretreatment nya adalah Gap Reduction. Hasil penelitian ini diperoleh yaitu: Hidung elektronik mulai merespon aroma formalin pada buah tomat pada detik ke-8.14, dan dapat mengklasifikasikan kandungan dan kadar formalin pada buah tomat pada detik ke 25.77. Hidung elektronik yang dikombinasikan dengan metode principal component analysis (PCA) telah berhasil mendeteksikandungan dan kadar formalin pada buah tomat dengan tingkat keberhasilan sebesar 99% (PC-1 sebesar 93% dan PC-2 sebesar 6%). Perbedaan kadar formalin menjadi faktor utama yang menyebabkan Elektronik nose mampu membedakan sampel buah tomat yang diuji, karena semakin tinggi kadar formalin pada buah tomat maka aroma khas dari buah tomat pun semakin menghilang, sehingga Electronic nose yang berbasis kemampuan penciuman dapat membedakannya.Detect Formaldehyde on Tomato (Lycopersicum esculentum Mill) With Electronic Nose TechnologyAbstract, The purpose of this study is to detect the contents and levels of formalin in tomatoes by using instruments based on Electronic nose technology. This study used tomatoes that have been soaked in formalin with a concentration of 0.5%, 1%, 2%, 3%, 4%, 5% and tomatoes without soaking with formalin (0%). The samples in this study were 18 samples. The measurements of the intensity on tomatoes aroma were using Piezoelectric Transducer sensors. The classification of tomato spectrum data was using the Principal Component Analysis (PCA) method with Gap Reduction pretreatment. The results of this study were obtained: the Electronic nose began to respond the smell of formalin on tomatoes at 8.14 seconds, and it could classify the content and formalin levels in tomatoes at 25.77 seconds. Electronic nose combined with the principal component analysis (PCA) method have successfully detected the content and levels of formalin in tomatoes with a success rate at 99% (PC-1 of 93% and PC-2 of 6%). The difference of grade formalin levels is the main factor that causes Electronic nose to be able to distinguish the tomato samples tested, because the higher of formalin content in tomatoes, the distinctive of tomatoes aroma is increasingly disappearing. Thereby, the Electronic nose based on  the olfactory ability can distinguish them. 

RECOGNITION OF SMILING FACES USING NEURAL NETWORKS AND SPCA

2004 ◽  
Vol 04 (02) ◽  
pp. 153-163 ◽  
Author(s):  
MIYOKO NAKANO ◽  
FUMIKO YASUKATA ◽  
MINORU FUKUMI
Keyword(s):  
Neural Networks ◽  
Principal Component Analysis ◽  
High Speed ◽  
Principal Component ◽  
Component Analysis ◽  
Research Field ◽  
A Value ◽  
Large Matrix ◽  
The Difference ◽  
The Cost

Research on "man-machine interface" has increased in many fields of engineering and its application to facial expressions recognition is expected. The eigenface method by using the principal component analysis (PCA) is popular in this research field. However, it is not easy to compute eigenvectors with a large matrix if the cost of calculation when applying it for time-varying processing is taken into consideration. In this paper, in order to achieve high-speed PCA, the simple principal component analysis (SPCA) is applied to compress the dimensionality of portions that constitute a face. A value of cos θ is calculated using an eigenvector by SPCA as well as a gray-scale image vector of each picture pattern. By using neural networks (NNs), the difference in the value of cos θ between the true and the false (plastic) smiles is clarified and the true smile is discriminated. Finally, in order to show the effectiveness of the proposed face classification method for true or false smiles, computer simulations are done with real images. Furthermore, an experiment using the self-organisation map (SOM) is also conducted as a comparison.

Regional Education Development Research Based on Robust Principal Component Analysis

2014 ◽  
Vol 915-916 ◽  
pp. 1361-1366
Author(s):  
Xian Fen Xie ◽  
Bin Hui Wang
Keyword(s):  
Principal Component Analysis ◽  
Basic Education ◽  
Principal Component ◽  
Component Analysis ◽  
Robust Principal Component Analysis ◽  
Education Development ◽  
Comparison Research ◽  
Regional Population ◽  
The Difference ◽  
Regional Education

Education development is the product of endogenous socio-economic; studying on regional differences of education level plays an important role in social and economic development. This paper constructs regional education development index system based on two aspects of basic educational facilities and educational scale, applies robust principal component analysis method to explore education development level differences of China's 31 provinces, and with the traditional principal component analysis for comparison. Research shows that, results obtained by robust principal component analysis is more in line with China's actual situation; the overall level of education is not high and the difference between regions is large; China's basic education is positively correlated with regional economy, while inversely correlated with regional population.

scholarly journals ANALISIS ADULTERAN PADA KOPI LUWAK DENGAN METODE Fourier Transform Infrared (FTIR)

2021 ◽  
Vol 6 (1) ◽  
pp. 26
Author(s):  
Ivan Andriansyah ◽  
Hilman Nur Mukhlis Wijaya ◽  
Purwaniati Purwaniati
Keyword(s):  
Principal Component Analysis ◽  
Fourier Transform ◽  
Principal Component ◽  
Fourier Transform Infrared ◽  
Component Analysis ◽  
Ft Ir

Kopi merupakan bahan minuman yang sangat terkenal bukan hanya di Indonesia melainkan di seluruh dunia, jenis yang sering dijumpai yaitu arabika dan robusta. Tingginya harga dan permintaan kopi banyak produsen memalsukan atau mencampur kopi dengan bahan lain. Adulterasi adalah upaya menambah atau mengganti bahan makanan dengan tujuan memperoleh, sehingga memberikan dampak buruk pada konsumen. Tujuan dari jurnal ini adalah untuk mengetahui ada atau tidaknya adulteran pada kopi luwak yang beredar dipasaran. Metode analisis FTIR digunakan untuk membuat pola sidik jari dari ekstrak kopi melalui analisis kemometrik dengan metode Principal Component Analysis (PCA). Ekstraksi dilakukan dengan cara maserasi menggunakan pelarut etanol 96%. Pengukuran spektrum inframerah menggunakan alat FT-IR, pada bilangan gelombang 4000-650cm-1 dan resolusi 4 cm-1. Klasifikasi dari kopi yang diadulteran dengan arabika dan kopi luwak menggunakan data PC-1 dan PC-2 dengan nilai berturut-turut 82% dan 14%. Hasil menunjukkan nilai scores menggunakan PC-1 dan PC-2 sampel kopi A berada dekat kuadran kopi luwak, sampel kopi B berada di antara kuadran kopi arabika (adulteran) dan luwak, dan kopi sampel C berada dekat kuadran arabika (adulteran). Metode FTIR dapat mendeteksi dengan batas deteksi 15% (b/b)

scholarly journals Principal Component Analysis of the Running Ground Reaction Forces With Different Speeds

2021 ◽  
Vol 9 ◽  
Author(s):  
Lin Yu ◽  
Qichang Mei ◽  
Liangliang Xiang ◽  
Wei Liu ◽  
Nur Ikhwan Mohamad ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Loading Rate ◽  
Reaction Force ◽  
Principal Component ◽  
Component Analysis ◽  
Heel Strike ◽  
Impact Peak ◽  
Reaction Forces ◽  
The Difference ◽  
Second Peak

Ground reaction force (GRF) is a key metric in biomechanical research, including parameters of loading rate (LR), first impact peak, second impact peak, and transient between first and second impact peaks in heel strike runners. The GRFs vary over time during stance. This study was aimed to investigate the variances of GRFs in rearfoot striking runners across incremental speeds. Thirty female and male runners joined the running tests on the instrumented treadmill with speeds of 2.7, 3.0, 3.3, and 3.7 m/s. The discrete parameters of vertical average loading rate in the current study are consistent with the literature findings. The principal component analysis was modeled to investigate the main variances (95%) in the GRFs over stance. The females varied in the magnitude of braking and propulsive forces (PC1, 84.93%), whereas the male runners varied in the timing of propulsion (PC1, 53.38%). The female runners dominantly varied in the transient between the first and second peaks of vertical GRF (PC1, 36.52%) and LR (PC2, 33.76%), whereas the males variated in the LR and second peak of vertical GRF (PC1, 78.69%). Knowledge reported in the current study suggested the difference of the magnitude and patterns of GRF between male and female runners across different speeds. These findings may have implications for the prevention of sex-specific running-related injuries and could be integrated with wearable signals for the in-field prediction and estimation of impact loadings and GRFs.

scholarly journals Principal Component Analysis applied directly to Sequence Matrix

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Tomokazu Konishi ◽  
Shiori Matsukuma ◽  
Hayami Fuji ◽  
Daiki Nakamura ◽  
Nozomi Satou ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Sequence Data ◽  
Principal Component ◽  
Environmental Dna ◽  
Distance Matrix ◽  
Component Analysis ◽  
Sequence Motifs ◽  
Tree Shape ◽  
Asiatic Lion ◽  
The Difference

AbstractSequence data is now widely used to observe relationships among organisms. However, understanding structure of the qualitative data is challenging. Conventionally, the relationships are analysed using a dendrogram that estimates a tree shape. This approach has difficulty in verifying the appropriateness of the tree shape; rather, horizontal gene transfers and mating can make the shape of the relationship as networks. As a connection-free approach, principal component analysis (PCA) is used to summarize the distance matrix, which records distances between each combination of samples. However, this approach is limited regarding the treatment of information of sequence motifs; distances caused by different motifs are mixed up. This hides clues to figure out how the samples are different. As any bases may change independently, a sequence is multivariate data essentially. Hence, differences among samples and bases that contribute to the difference should be observed coincidentally. To archive this, the sequence matrix is transferred to boolean vector and directly analysed by using PCA. The effects are confirmed in diversity of Asiatic lion and human as well as environmental DNA. Resolution of samples and robustness of calculation is improved. Relationship of a direction of difference and causative nucleotides has become obvious at a glance.

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