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Principal Component Analysis (PCA) Method for Classification of Beef and Pork Aroma Based on Electronic Nose Imam Tazi; Nur Laila Isnaini; Mutmainnah Mutmainnah; Avin Ainur
Indonesian Journal of Halal Research (IJHAR) Vol 1, No 1 (2019): February
Publisher : UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/ijhar.v1i1.4155

There are several testing processes for consuming meat products. Organoleptic evaluation is an evaluation based on color, texture, smell, and taste. This research aims to find out the response pattern of 10 gas sensor array contained in the electronic nose against the odor pattern of beef and pork base on a smell. The classification method used is using the Principal Component Analysis (PCA) method. This method is expected to simplify the test of differences in beef and pork based on the aroma. The meat used is standard beef and pork consumption that has been sold in supermarkets. Samples of beef and pork are then ground until smooth. After that, it is weighed until it reaches 1 ounce. The meat samples were tested using an electronic nose consisting of 10 gas sensors. The multivariate analysis method was used to classify the aroma of beef and pork. The results of the data processing showed that the aroma classification of beef and pork which was indexed by the electronic nose was perfect. Based on the PCA method, the proportion of PC1 is 93.4%, and PC2 is 4.9%. From the second cumulative number, the value of the first PC was obtained 98.3%. This value indicates that only with 2-dimensional data, can represent ten dimensions of data. The loading plot shows that the MQ-138 and MQ-3 sensors are the most powerful sensors in testing samples of beef and pork.

Detection of Taste Change of Bovine and Goat Milk in Room Ambient Using Electronic Tongue Imam Tazi; Anis Choiriyah; Dwi Siswanta; Kuwat Triyana
Indonesian Journal of Chemistry Vol 17, No 3 (2017)
Publisher : Universitas Gadjah Mada

An electronic tongue (e-tongue) based on an array of lipid/polymer membranes has been successfully developed for measuring the taste evolution of natural milk. The e-tongue consisted of 16 different lipid/polymer membranes combined with or without a pH sensor. The natural milk of bovine and goat were purchased from the local farming store in Malang-Indonesia. The taste measurement was carried out, from fresh (0 h) to stale (12 h), every two hours under room ambient without any treatment. The responses of the e-tongue were evaluated using a Principal Component Analysis (PCA) and a Linear Discriminant Analysis (LDA). From PCA results, the taste of both milk samples tends to change by time although some groups show a partial overlapping. LDA results show the high precision of the e-tongue in clustering taste evolution. The correctly classified groups after the cross-validation procedure were achieved 95.7 and 87.1% for bovine and goat milk, respectively. The improvement of the classification using LDA was obtained by adding data from a pH sensor of each measurement as 100 and 98.6% for bovine and goat milk, respectively. This work indicates that the lab-made e-tongue may be useful to predict the quality of natural milk for the food industry.

Pengembangan Sistem Sensor Rasa Berbasis Membran Selektif Ion untuk Klasifikasi Buah Jeruk (Halaman 9 s.d. 13) Bagas Surya Wibowo; Imam Tazi; Kuwat Triyana
Jurnal Fisika Indonesia Vol 17, No 49 (2013)
Publisher : Department of Physics Universitas Gadjah Mada

Sebuah sistem sensor rasa dengan sifat selektivitas global atau yang lebih dikenal sebagai lidah elektronik (e-tongue) berbasis pada larik sensor ion-selektif membran (ISMS)telah dibuat dan diterapkan untuk menganalisis secara kualitatif tiga macam buah jeruk (jeruk peras, jeruk siam dan jeruk nipis). E-tongue dilengkapi dengan sistem pengenal pola berbasis principle component analysis (PCA). Enam jenis lipid yang digunakan untuk membuat membrane selektif ion terdiri atas: asam oleat (OA), dioktil phosphat (DOP), desil alkohol (DA), dodesilamin (DDC), dan metil amonium klorida trioctyl (Toma). Setiap membran selanjutnya dipasang pada bagian dari tabung teflon yang memiliki lubang pada ujungnya, sehingga bagian dalam silinder terisolasi dari luar. Ujung tabung tersebut disegel dengan stopper yang memegang kawat Ag / AgCl. Sistem akuisisi data dalam e-nose dibangun menggunakan mikrokontroler. Agar dapat digunakan, tabung-tabung tersebut diisi dengan larutan KCl dengan konsentrasi 100 mM. Berdasarkan analisis PCA, e-hidung dapat mengklasifikasikan semua pola respon dari empat rasa dasar, yaitu, kepahitan (MgCl2), asin (NaCl), asam (HCl) dan kelezatan atau umami (MSG), ditunjukkan oleh nilai total komponen utama (PC1 dan PC2) sebesar 95,1%. Selanjutnya, e-tongue juga mampu mengklasifikasi tiga jenis buah jeruk yang ditunjukkan oleh nilai total komponen utama sebesar 88,6%. Dengan demikian, e-nose memiliki peluang sebagai alat untuk kendali mutu pada industri minuman berbahan buah jeruk.

Karakterisasi Sensor MAX30102 Sebagai Alat Ukur Detak Jantung dan Suhu Tubuh Berbasis Photoplethysmograph Muthmainnah Muthmainnah; Deni Bako Tabriawan; Imam Tazi
JURNAL PENDIDIKAN MIPA Vol 12 No 3 (2022): JURNAL PENDIDIKAN MIPA
Publisher : Pusat Publikasi Ilmiah, STKIP Taman Siswa Bima

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37630/jpm.v12i3.655

Karakterisasi sensor MAX30102 sebagai alat ukur detak jantung dan suhu tubuh telah dilakukan. Sensor dihubungkan dengan arduino uno dan LCD untuk menampilkan hasil pengukuran. Naracoba yang diukur ada delapan orang dengan usia yang bervariasi. Pengukuran dilakukan dengan menempelkan ujung jari telunjuk tangan kiri pada sensor. Hasil pengukuran menunjukkan bahwa nilai detak jantung dan suhu tubuh pada masing-masing naracoba berbeda. Rentang nilai detak jantung berkisar antara 76,4 bpm sampai dengan 110,4 bpm. Nilai suhu tubuh berkisar antara 36,320C sampai dengan 36,530C. Rata-rata standar deviasi pada pengukuran detak jantung adalah 1,19. Jika menganggap data dari pulse oximeter adalah valid maka sensor MAX30102 memiliki tingkat akurasi 97%. Rata-rata nilai standar deviasi sensor MAX3012 pada pegukuran suhu adalah 0,07. Rata-rata tingkat akurasi sensor jika dibandingkan dengan termometer adalah 99%.

Klasifikasi Pola Aroma Teh Hijau Menggunakan Hidung Elektronik (E-Nose) Berbasis Linear Diskriminan Analisis (LDA) Kusairi Kusairi; Muthmainnah Muthmainnah; Imam Tazi; Moh. Fajrul Falah
JURNAL PENDIDIKAN MIPA Vol 12 No 3 (2022): JURNAL PENDIDIKAN MIPA
Publisher : Pusat Publikasi Ilmiah, STKIP Taman Siswa Bima

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37630/jpm.v12i3.682

Aroma teh merupakan sesuatu yang sulit diukur karena membutuhkan kejelian dalam indra penciuman sehingga untuk mengukur aroma dalam rangka mempertahankan kualitas teh yaitu menggunakan alat Hidung elektronik/enose yang terdiri dari sensor-sensor yang digunakan untuk mendeteksi aroma atau bau. Hidung elektronik/Enose terbuat dari beberapa larik sensor gas dan memiliki sistem kerja seperti indra penciuman manusia. Melalui e-nose aroma teh hijau dapat diidentifikasi dan diklasifikasi menggunakan metode LDA (linear discriminant analysis). Tujuan penelitian ini untuk mengetahui klasifikasi beberapa merek teh hijau menggunakan hidung elektronik dan analisis hasil data keluaran dari hidung elektronik menggunakan metode linear diskriminan analisis (LDA) berdasarkan aromanya. Hasil pengukuran hidung elektronik (e-nose) yang berupa kurva sensing dan flessing, dicari luasannya dengan menggunakan metode integral trapesium. Data berupa luasan diolah dengan menggunakan metode LDA. Dilakukan pengujian untuk tingkat akurasi dan presisi hidung elektronik (e-nose) dengan uji validitas dan reabilitas hasil pengukuran. Hasil pengukuran berbasis hidung elektronik, menghasilkan empat cluster besar dengan menggunakan pengolahan data metode LDA yaitu kelompok teh hijau merek TT dan TJ, kelompok teh hijau TCB, kelompok teh hijau merek TKD dan teh hijau merek TM. Dari data LDA didapatkan Fungsi diskriminan pertama (FD1) dan Fungsi diskriminan kedua (FD2) yang mempunyai nilai 48,8% dan 37,6% dari total varians. Nilai total dua fungsi diskriminan pertama sebesar 86,4 % sudah mampu untuk mengklasifikasikan secara baik berdasarkan grafik score plot.

Development of Optical Sensor Technology for Non-Invasive Hemoglobin Measurement Muthmainnah; Fabriansyah Zakaria Arabani; Imam Tazi; Ninik Chamidah; Wiwis Sasmitaninghidayah; Mokhamad Tirono
Jurnal Penelitian Pendidikan IPA Vol 9 No 11 (2023): November
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v9i11.5610

This research focuses on the development of hardware and software required to implement optical sensor technology. The optical sensor used is the MAX30102, equipped with infrared (IR) and red-light sources along with a receiver. The signals generated by the sensor are processed by NodeMCU and displayed on the OLED. The calibration results indicate the relationship between hemoglobin obtained using the invasive method and the output of the MAX30102 sensor, which is in the form of wavelength. It has the equation Â with an Â value of 0.9114. This equation is utilized to program the NodeMCU through the Arduino IDE. Validation and clinical trials have been conducted to evaluate its accuracy and applicability in clinical contexts. The results show that the non-invasive device has an average standard deviation of 0.32, indicating consistent measurement values. The non-invasive device demonstrates an average accuracy of 99.24%, signifying high precision and similarity to invasive methods. This suggests that the device holds potential as an innovative solution for Hemoglobin measurement.

Performance evaluation of single-mode fiber optic-based surface plasmon resonance sensor on material and geometrical parameters Tazi, Imam; Riana, Dedi; Syahadi, Mohamad; Muthmainnah, Muthmainnah; Sasmitaninghidayah, Wiwis; Aprilia, Lia; Tresna, Wildan Panji
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i5.pp5072-5082

Surface plasmon resonance (SPR) sensors are proficient at detecting minute changes in refractive index, making them ideal for biomolecule detection. Traditional prism-based SPR sensors encounter miniaturization challenges, encouraging exploration of alternatives like fiber optic-based SPR (FO-SPR) sensors. This study comprehensively investigates the effects of material and geometrical parameters on the performance of single-mode FO-SPR sensors using Maxwell's equation solver software based on the finite-difference time-domain (FDTD) method. The findings highlight the influence of plasmonic thin film materials and thickness on SPR spectrum profiles and sensitivity. Silver (Ag) demonstrates superior performance compared to copper (Cu) and gold (Au) in transmission type, achieving a sensitivity of up to 2×103 nm/RIU, while the sensitivities of Cu and Au are lower. Probe length and core diameter impact spectrum profiles, specifically resonance depth, without affecting sensitivity. Furthermore, variations in core refractive index influence both spectrum profiles and sensitivity. Probe types significantly affect both spectrum profiles and sensitivity, with the reflection type surpassing the transmission type. These results provide suggestions for optimizing FO-SPR sensors in biotechnological applications.

Principal Component Analysis (PCA) Method for Classification of Beef and Pork Aroma Based on Electronic Nose Tazi, Imam; Isnaini, Nur Laila; Mutmainnah, Mutmainnah; Ainur, Avin
Indonesian Journal of Halal Research Vol. 1 No. 1 (2019): February
Publisher : UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/ijhar.v1i1.4155

There are several testing processes for consuming meat products. Organoleptic evaluation is an evaluation based on color, texture, smell, and taste. This research aims to find out the response pattern of 10 gas sensor array contained in the electronic nose against the odor pattern of beef and pork base on a smell. The classification method used is using the Principal Component Analysis (PCA) method. This method is expected to simplify the test of differences in beef and pork based on the aroma. The meat used is standard beef and pork consumption that has been sold in supermarkets. Samples of beef and pork are then ground until smooth. After that, it is weighed until it reaches 1 ounce. The meat samples were tested using an electronic nose consisting of 10 gas sensors. The multivariate analysis method was used to classify the aroma of beef and pork. The results of the data processing showed that the aroma classification of beef and pork which was indexed by the electronic nose was perfect. Based on the PCA method, the proportion of PC1 is 93.4%, and PC2 is 4.9%. From the second cumulative number, the value of the first PC was obtained 98.3%. This value indicates that only with 2-dimensional data, can represent ten dimensions of data. The loading plot shows that the MQ-138 and MQ-3 sensors are the most powerful sensors in testing samples of beef and pork.

Analysis of heavy metal content (Pb, Cu, Cd, and Hg) on refilled drinking water in Malang City based on atomic absorption spectroscopy using the PCA method Tazi, Imam; Margareta, Silvi Nadya; Chamidah, Ninik; Muthmainnah, Muthmainnah; Sasmitaninghidayah, Wiwis; Nadliriyah, Naqiibatin
Gravity : Jurnal Ilmiah Penelitian dan Pembelajaran Fisika Vol 11, No 1 (2025)
Publisher : Universitas Sultan Ageng Tirtayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30870/gravity.v11i1.28618

Refillable drinking water was chosen as an alternative to bottled drinking water because the price is cheaper. Drinking water has benefits for the body, but if the levels of heavy metals contained exceed the Ministry of Health's standards, it will have a negative impact on body health. This research was conducted with the aim of determining the quality of refillable drinking water in terms of heavy metal levels. Atomic absorption spectroscopy was used to test the levels of heavy metals (Pb, Cu, Cd, and Hg) in the samples. Research data shows that refill drinking water samples A1, A2, A3, A4 and A5 contain heavy metals at levels that exceed the Ministry of Health's standards. PC1 and PC2 have the highest eigenvalues, with a proportion of PC1 of 60.86% and PC2 of 22.69%. The two PCs have a cumulative proportion of 83.55% and are considered capable of representing the entire data. PCA method was used to identify patterns and group samples based on heavy metal content, with PC1 and PC2 reflecting 83.55% of the data variability. Pb and Cd are the variables that have the longest resultant lines, which shows that these two variables have a large contribution to the formation of new variables. The three secondary data samples, namely A6, A7, and A8, are control samples because their quality is good. Refill drinking water samples that are almost close to control are samples A1, A4, and A5, while samples A2 and A3 are far from control. The further the sample is from the control, the lower the quality. The results of this study highlight the need for strict supervision of refillable drinking water depots and the implementation of more effective purification methods to reduce heavy metal content exceeding health standards.

Internet of things-based water quality monitoring design to improve freshwater lobster farming management Muthmainnah, Muthmainnah; Khasanah, Iva Khuzaini; Hananto, Farid Samsu; Romadani, Arista; Tazi, Imam; Mulyono, Agus; Tirono, Mokhamad
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 4: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i4.pp3717-3726

The development of lobster farming requires careful water quality monitoring to ensure optimal growth and health. This study introduces a novel internet of things (IoT)-based water quality monitoring system designed specifically for lobster farming applications, operating on the Antares IoT platform. The system incorporates pH, temperature, and turbidity sensors to measure critical water quality parameters. The sensors were calibrated and validated using standard methods, yielding high accuracy, with average values of 98.74% for pH, 98.78% for temperature, and 98.56% for turbidity. The study also involved direct monitoring over five days, with pH values ranging between 8-10, temperatures between 23-27°C, and stable turbidity at 90-99 NTU. The novelty of this system lies in its ability to provide real-time, reliable data and predictive analysis to support effective water quality management in lobster farming. Unlike traditional water quality monitoring systems that lack real-time data analysis or predictive capabilities, this system integrates both monitoring and forecasting features, allowing for more proactive management. Additionally, it offers higher accuracy and lower sensor drift compared to older, manual water quality monitoring methods. Experimental results indicate that the proposed monitoring system can deliver accurate and reliable data, supporting optimal farming conditions. These findings align with and expand upon existing literature, offering a more integrated and efficient solution for real-time and accurate monitoring in lobster farming.

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