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All Journal Jurnal Amplifier: Jurnal Ilmiah Bidang Teknik Elektro dan Komputer
Ika Novia Anggraini
Program Studi Teknik Elektro Fakultas Teknik Universitas Bengkulu
Computer Science & IT Electrical & Electronics Engineering Engineering

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Pengujian Sludge Battery Dengan Teknologi Microbial Fuel Cell Sebagai Sumber Energi Listrik Terbarukan Ika Novia Anggraini; Afriyastuti Herawati
JURNAL AMPLIFIER : JURNAL ILMIAH BIDANG TEKNIK ELEKTRO DAN KOMPUTER Vol 8, No 2 (2018): Amplifier November 2018
Publisher : Universitas Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/jamplifier.v8i2.15091

Abstract

ABSTRACTMicrobial Fuel Cells are devices which convert chemical energy into electrical energy through catalytic reactions by microorganisms. In this study, the potential of electricity in MFC will be analyzed by using samples of sea mud, lake mud, land mud, and river mud. While the method used in this study is one series connected vessel, two vessels connected series with mud-water, two mud-mud series vessels, and the stack series method. The highest electrical conductivity produced by river mud reaches 3.63 mS/cm, while the lowest is lake mud with a conductivity value of 0.35 mS/cm. The highest electric power density produced by river mud by the two mud-mud vessel method is 46.766 mW/m2, while the lowest electrical power density in lake mud is 18.040 mW/m2. The highest electrical power is produced by river mud through a single vessel series system with a maximum power of 7.26 mW, while the lowest power is found in marine mud with a system of two mud-water vessels which is equal to 0.30 mW. The pattern of increase in voltage or current produced by the battery sludge is on average until the 7th day, then a decrease occurs until the last day of testing. The greatest potential for electrical energy is obtained by river mud using a single vessel series system with a maximum voltage of 5.38 V and lasting up to 14 days.Keyword : electric power density, microbial fuel cells, sludge battery
Pengenalan Gangguan Ginjal Melalui Iridologi Menggunakan Hidden Markov Model (HMM) Reza Satria Rinaldi; Wagiasih Wagiasih; Ika Novia Anggraini
JURNAL AMPLIFIER : JURNAL ILMIAH BIDANG TEKNIK ELEKTRO DAN KOMPUTER Vol 9, No 2 (2019): Amplifier November 2019 Vol 9 No 2
Publisher : Universitas Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/jamplifier.v9i2.15379

Abstract

ABSTRACTIridology has not been widely applied for the recognition of kidney disorders. identification of kidney disorders through iris image using iridology chart, can make it easier to make diagnosis to find out about kidney disorders. The method used in the process of recognition of kidney disorders through iridology is the Hidden Markov Model (HMM) method, with a HMM parameter determination system using the calculation of the koefisien Singular Value Decomposition (SVD) coefficient. The size of the codebook used is 7, i.e. 16, 32, 64, 128, 256, 512 and 1024. Different sizes of codebooks will result in different recognition times. The time needed will be longer when the size of the codebook is getting bigger. The accuracy of the process of recognition of kidney disorders through iridology using the HMM method in this study is 68.75% for codebook 16, 87.5% for codebook 32, 100% for codebook 128 and 100% for codebook 512. Keywords : iridology, codebook, image processing, singular value decomposition (SVD), Hidden Markov Model (HMM).
Co-Authors Afriyastuti Herawati Reza Satria Rinaldi Wagiasih Wagiasih