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DESTILASI AIR LAUT MENGGUNAKAN PEMANAS MATAHARI DENGAN REFLEKTOR CERMIN CEKUNG Fanrico Sanjaya Tambunan; Muhammad Edisar; Juandi M
Jurnal Online Mahasiswa (JOM) Bidang Matematika dan Ilmu Pengetahuan Alam Vol 2, No 1 (2015): Wisuda Februari 2015
Publisher : Jurnal Online Mahasiswa (JOM) Bidang Matematika dan Ilmu Pengetahuan Alam

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Abstract

A research has been done in distilling seawater using solar heater with and without concave mirror reflector. The concave reflector mirror has been made with its diameter of 2.2 meters, height of 0.3 meters and focus of 1 meter. The reflector was placed on the ground and was directly illuminated by the sunlight. The collector which contained seawater was exactly placed on the focus of the reflektor. During the heating, thetemperature was measured every hour from 08.00 to 16.00 WIB. The observation was done for seven days. The results showed that maximum temperature of seawater using the reflector was about 100o C and 140oC at the focus and the best daily destilling volumewas 688 ml. The results distilling without reflector showed maximum temperature of seawater was about 64oC and the best daily destilling volume was 180 ml. The laboratory testing of the samples before and after distilling showed that there was significantly improvement of water quality, especially in salinity which decreased to be zero after distilling.
ANALISA KOEFISIEN ABSORPSI BUNYI MATERIAL SERAT BATANG KELAPA SAWIT DENGAN GYPSUM MENGGUNAKAN SONIC WAVE ANALYZER Qory Gunanda; Riad Syech; Muhammad Edisar
Jurnal Online Mahasiswa (JOM) Bidang Matematika dan Ilmu Pengetahuan Alam Vol 1, No 2 (2014): Wisuda Oktober 2014
Publisher : Jurnal Online Mahasiswa (JOM) Bidang Matematika dan Ilmu Pengetahuan Alam

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A research has  been done  in  analyzing  a coefficient absorption of composite material of oil palm trunk fiber and gypsum using a sonic wave analyzer (SOWAN) and carried out using sound  wave of 150 Hz frequency.  Sample  was formed  as  a  cylinder made from gypsum  with  3:5  ratio  of water and gypsum,  formed  a  pipe with  7,5 cm  outer  diameter and heights  of 2 cm, 3 cm, 4 cm, 5 cm, and 6 cm (sample    thickness). The  pipe with the outer  diameter  of  6 cm  was used  for  making  a  cavity  in  the  samples  and  then the composed of oil palm trunk fiber of ± 1 cm length with the variation percentage of fiber of 12,24%, 24,48%, 36,73%, and 48,97% filled in to each sample. Ao (initial amplitude) and A (final  amplitude)  then  were  measured by  Sonic Wave  Analyzer (SOWAN) with the intensity  of  65 dB, 70 dB, 75 dB, dan 80 dB.  Results  of the measurements  showed that the bigger  percentation  of fiber,  the higher  coefficient of sound  absorption andthicker sample  produced  bigger the coefficient of sound absorption.  The biggest absorption  coefficient  was  0,4957,  due to the  sample with 6  cm thickness when the intensity  was  80 dB and the smallest  absorption  coefficient was  0,3088,  of the  sample with 2 cm thickness  when the intensity  was  65 dB. The maximum  absorptioncoefficients of the sample thickness of 2 cm, 3 cm, 4 cm, and 5 cm were 0,3557, 0,3779,0,4155,  and  0,4863,  respectively.  This  showed that  preparing the sample by method  ofarranging the oil palm stem's fiber inside the sample  was  more effective to  absorb  the sound for low frequencies (150Hz) if viewed from the standard of absorption coefficientof  gypsum  was  0.29  for  frequency  of  150  Hz.  Based on  the  results of  this study  the absorption  coefficients  exceed  the  minimum  limit  0.15  as suggested  ISO 11654 as a silencer.
ESTIMASI PERMEABILITAS RESERVOIR DARI DATA LOG MENGGUNAKAN JARINGAN SYARAF TIRUAN PADA FORMASI MENGGALA PT CHEVRON PACIFIC INDONESIA Liana Zamri; Juandi M; Muhammad Edisar
Jurnal Online Mahasiswa (JOM) Bidang Matematika dan Ilmu Pengetahuan Alam Vol 2, No 1 (2015): Wisuda Februari 2015
Publisher : Jurnal Online Mahasiswa (JOM) Bidang Matematika dan Ilmu Pengetahuan Alam

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A research has been conducted to apply artificial neural network in order to predict permeability of reservoir. Method of this research was analytical description. Backpropagation neural network used input layer of 4 neurons, hidden layer of 6 neurons, and output layer of 1 neuron, which was optimal architecture in this research. Result of this research showed that the biggest correlation was 0,9999 for BL#33 well and the lowest correlation was 0,9977 for BL#19 well. The rmse value of BL#19 well was 1,02%, BL#33 well was 0,21%, and was 2,42% for BL#34 well. When rmse decreased, prediction disposed approximated true value. This results indicated the solution based on backpropagation model was reasonable and feasible.
ANALISIS ELASTISITAS BATU BATA YANG DIBUAT DENGAN TEKNIK PEMANAS TENAGA SURYA MENGGUNAKAN REFLEKTOR CERMIN CEKUNG Anda Yani; Muhammad Edisar; Antonius Surbakti
Jurnal Online Mahasiswa (JOM) Bidang Matematika dan Ilmu Pengetahuan Alam Vol 2, No 1 (2015): Wisuda Februari 2015
Publisher : Jurnal Online Mahasiswa (JOM) Bidang Matematika dan Ilmu Pengetahuan Alam

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Abstract

The research has been conducted to investigate the quality of some bricks. The quality of the bricks was tested after heating by solar energy using concave mirror reflector on their elastic properties. The quality of the bricks after being heated was compared with the bricks that were prepared by conventional way (by heating using fire). The elasticity properties were calculated from the time propagation of the seismic wave in the bricks. The results of the research showed that the elasticity of the bricks heated using solar energy for 80 hours was 50.623 (N/m²), and the lowest elasticity heated for 10 hours was 16.530 (N/m). While the elasticity of bricks heated using fire with the distance of 0.7 meters was 72.199 (N/m²) and the lowest elasticity of bricks with the distance from fire of 0.76 meter was 32.555 (N / m²). The results also showed that the quality of the bricks was better through direct burning using fire compared to the one prepared by solar energy.