Sistem Klasifikasi Rasa Kopi Berbasis Electronic Tongue Menggunakan Madaline Neural Network
| Dublin Core | PKP Metadata Items | Metadata for this Document | |
| 1. | Title | Title of document | Sistem Klasifikasi Rasa Kopi Berbasis Electronic Tongue Menggunakan Madaline Neural Network |
| 2. | Creator | Author's name, affiliation, country | Yudi Anom Priambudi; Indonesia |
| 2. | Creator | Author's name, affiliation, country | Sri Hartati; urusan Ilmu Komputer dan Elektronika, FMIPA UGM, Yogyakarta; Indonesia |
| 2. | Creator | Author's name, affiliation, country | Danang Lelono; Jurusan Ilmu Komputer dan Elektronika, FMIPA UGM, Yogyakarta; Indonesia |
| 3. | Subject | Discipline(s) | |
| 3. | Subject | Keyword(s) | madaline neural network, membrane, taste sensor, interface, coffee |
| 4. | Description | Abstract | Abstrak Penelitian ini dilatar belakangi karena minimnya pengembangan dari sensor rasa yang ada selama ini dan bertujuan untuk mengimpelentasikan delapan buah sensor rasa berbasis komputer dengan menggunakan membran Decyl Alcohol (DA), Oleic Acid (OA), Dioctyl Phosphate (DOP), Trioctylmethyl ammonium chloride (TOMA), Dodevylamine (DDC), DA:OA 5:5, DA:DOP 5:5, dan DDC:TOMA 5:5 dilengkapi dengan semi auto sampler dan mampu menampilkan hasil pengukuran dan menyimpan data dari delapan sensor sekaligus. Sistem diimplementasikan pada beberapa merek kopi instan, serta dapat mempola karakter beberapa merek kopi dengan perbandingan pendeteksian secara fisis. Pengujian karakterisasi membran dilakukan setiap hari dengan menggunakan sampel beberapa merek kopi instan yang ada di pasaran yang kemudian dideteksi pola karateristiknya. Alat yang digunakan sebagai ADC adalah PhidgetInterFaceKit 8/8/8 yang merupakan elektrometer pada penelitian ini. Dan digunakan program yang menggunakan Microsoft Visual Basic 2010 sebagai antarmuka sehingga dapat berinteraksi dengan alat. Serta digunakan toolbox dari program Matlab R2009a untuk pemanfaatan program madaline neural network.
Hasil penelitian menunjukkan pola yang dikarakterisasi menggunakan sistem ini dapat diidentifikasi jenisnya menggunakan madaline neural network. Data hasil dari sistem ini dapat disimpan dalam bentuk excel.
Kata kunci— madaline neural network, membran, sensor rasa, antarmuka, kopi
Abstract This research is motivated by the lack of the nowadays taste sensor development and this study aims ti implement eight computer-based taste sensor with Decyl Alcohol (DA), Oleic Acid (OA), Dioctyl Phosphate (DOP), Trioctylmethyl ammonium chloride (TOMA), Dodecylamine(DDC), DA:OA 5:5, DA:DOP 5:5, and DDC:TOMA 5:5 membranes with semi auto sampler and it could show the measuring result and store the data from eight sensors as one. System implemented on few instant coffees, and patterned characterization on the coffees with physical detection comparation. The membrane character testing was did everyday with some instant coffee samples and then the pattern characterization be done. Tool that used as ADC was PhidgetInterFaceKit 8/8/8 that was an electrometer for this research. And uses program based on Microsoft Visual Basic 2010 as the interface so it can be interacted with the tool. And used the toolbox of Matlab R2009a program for madaline neural network utilization.
The results showed a pattern characterized using this system can be identified using the madaline neural network. Data results from this system can be stored in the form of excel.
Keywords— madaline neural network, membrane, taste sensor, interface, coffee |
| 5. | Publisher | Organizing agency, location | IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. |
| 6. | Contributor | Sponsor(s) | IndoCEISS |
| 7. | Date | (YYYY-MM-DD) | 2014-10-31 |
| 8. | Type | Status & genre | Peer-reviewed Article |
| 8. | Type | Type | |
| 9. | Format | File format | |
| 10. | Identifier | Uniform Resource Identifier | https://jurnal.ugm.ac.id/ijeis/article/view/7124 |
| 10. | Identifier | Digital Object Identifier (DOI) | https://doi.org/10.22146/ijeis.7124 |
| 11. | Source | Title; vol., no. (year) | IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 4, No 2 (2014): October |
| 12. | Language | English=en | |
| 14. | Coverage | Geo-spatial location, chronological period, research sample (gender, age, etc.) | |
| 15. | Rights | Copyright and permissions |
Copyright (c) 2014 IJEIS - Indonesian Journal of Electronics and Instrumentation Systems This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. |