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IPTEK The Journal for Technology and Science
Published by Institut Teknologi Sepuluh Nopember Surabaya
ISSN : 08534098     EISSN : 20882033     DOI : -
Core Subject : Science,
Computer Science & IT
IPTEK The Journal for Technology and Science (eISSN: 2088-2033; Print ISSN:0853-4098), is an academic journal on the issued related to natural science and technology. The journal initially published four issues every year, i.e. February, May, August, and November. From 2014, IPTEK the Journal for Technology and Science publish three times a year, they are in April, August and December in online version.
Arjuna Subject : -
Articles 6 Documents
 1 
Search results for , issue "Vol 32, No 1 (2021)" : 6 Documents clear
The Efficacy of Choosing Strategy with General Regression Neural Network on Evolutionary Markov Games Shirin Kordnoori; Hamidreza Mostafaei; Mohammadmohsen Ostadrahimi; Saeed Agha Banihashemi
IPTEK The Journal for Technology and Science Vol 32, No 1 (2021)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v32i1.7074

Abstract

Nowadays, Evolutionary Game Theory which studies the learning model of players,has attracted more attention than before. These Games can simulate the real situationand dynamic during processing time. This paper creates the Evolutionary MarkovGames, which maps players’ strategy-choosing to a Markov Decision Processes(MDPs) with payoffs. Boltzmann distribution is used for transition probability andthe General Regression Neural Network (GRNN) simulating the strategy-choosing inEvolutionary Markov Games. Prisoner’s dilemma is a problem that uses the methodand output results showing the overlapping the human strategy-choosing line andGRNN strategy-choosing line after 48 iterations, and they choose the same strate-gies. Also, the error rate of the GRNN training by Tit for Tat (TFT) strategy is lowerthan similar work and shows a better res
High-Stability Foam of Silica Nanofluid to Overcome Liquid Loading in Enhancing Natural Gas Production Ajiz, Hendrix Abdul; Mawarani, Lizda Johar; Widiyastuti, Widiyastuti; Setyawan, Heru
IPTEK The Journal for Technology and Science Vol 32, No 1 (2021)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v32i1.7092

Abstract

One of the promising solutions to overcome the liquid loading problem in natural gas production is using a foaming agent. The extreme condition in the gas well causes the foam used tends to break up. Therefore, it is required to enhance the foam stability by adding a stabilizer agent. This research aims to investigate the effect of silica nanoparticles as a surfactant stabilizer to obtain a high-stability foam using silica nanofluid. Silica nanofluid was synthesized from sodium silicate solution by the solgel method. Then, the colloidal silica was added to the surfactant solution without a coupling agent. The effects of aging time and silica concentration were investigated. The results show that the surface tension tends to increase with the increase of aging time and silica concentration but decrease in foam stability which is indicated by a decrease in the foam half-life time. The best foam stability is obtained in silica nanofluids with an aging time of 6 hours and a silica concentration of 30 ppm, which shows a foam half-life of 42 hours and can improve foam stability with several parameters representing the conditions of the gas well
Controllable Core Size of Au@TiO2 through Al(NO3)3 Addition and Its Effects on DSSC Performance Utama, Sangsaka Wira; Fadhilah, Nur; Haekal, Muhammad Husain; Zakaria, Rozalina; Hidayat, Rachmat; Risanti, Doty Dewi
IPTEK The Journal for Technology and Science Vol 32, No 1 (2021)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v32i1.7003

Abstract

It is known that plasmonic nanoparticles in dye-sensitized solar cells (DSSC) could enhance efficiency through improvement in light absorbance and electron dynamics. Herein we investigated various sizes of AuNP through spontaneous Al(NO3 )3 addition. Core-Shell Au@TiO2 was prepared with various Al(NO3 )3 concentrations of 0.25 mM, 0.5 mM, 0.75 mM and 1 mM. The Au@TiO2 volume fraction of 1% was further added to TiO2 photoanode. Based on the particle size analyzer (PSA) characteristics, the synthesized AuNP’s size was within a range of 34.62 nm – 139.5 nm. The highest efficiency of DSSC was obtained for the sample with the largest AuNP ’s diameter, i.e., 0.0313%, which is about three times higher than pristine DSSC. The increase in efficiency was in accord with Metallic Nanoparticle Boundary Element Method (MNPBEM) simulation, UV-vis spectroscopy, and Incident Photon to Current Conversion Efficiency (IPCE) analysis largest Au core diameter contributes to the strong absorbance and hence the short circuit current
Predict The Spread of COVID-19 in Iran with A SEIR Model Shirin Kordnoori; Mahboobe Sadat Kobari; Hamidreza Mostafaei
IPTEK The Journal for Technology and Science Vol 32, No 1 (2021)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v32i1.7227

Abstract

The current coronavirus disease 2019 (COVID-19) outbreak has recently been declared a pandemic and spread over 200 countries and territories. Forecasting the long-term trend of the COVID-19 epidemic can help health authorities determine the transmission characteristics of the virus and take appropriate prevention and control strategies beforehand. Previous studies that solely applied traditional epidemic models or machine learning models were subject to underfitting or overfitting problems. This paper designed a predictive model based on the mathematical model Susceptible-Exposed-Infective-Recovered (SEIR). SEIR is represented by a set of differential-algebraic equations incorporated with machine learning techniques to fit the data reported to estimate the spread of the COVID-19 epidemic in long-term in the Islamic Republic of Iran up to the end of July 0f 2020. This paper reduced R0 after a certain amount of days to account for containment measures and used delays to allow for lagging official data. Two evaluation criteria, R2 and RMSE, had used in this research which estimates the model on officially reported confirmed cases from different regions in Iran. The results proved the model’s effectiveness in simulating and predicting the trend of the COVID-19 outbreak. Results showed the integrated approach of epidemic and machine learning models could accurately forecast the long-term trend of the COVID-19 outbreak.
Effect Of The Application Of Different Cooking Periods On The Physicochemical Properties And Microbial Safety Of Hot Pepper Sauce Ebenezer Narteh Nartey; Emmanuel Tei-Mensah; Stephen Adusei; Doreen Asante; Charity Abaati
IPTEK The Journal for Technology and Science Vol 32, No 1 (2021)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v32i1.8678

Abstract

Hot pepper sauce is a frequently used product in most Ghanaian homes, schools, and restaurants, which occasionally serves as condiments. The cooking period during the production process of hot pepper sauce results in physicochemical changes, which affect the quality and safety of the sauce. The study seeks to determine the effect of the application of different cooking times on the physicochemical properties and microbial safety of hot pepper sauce. The cooking periods were 10 minutes, 20 minutes, 30 minutes, and 1 hour for samples A, B, C, and D. Standard physicochemical and microbiological techniques were employed in the various analysis. Sample D (1 hour cooked) recorded the least moisture and ash content, insoluble acid ash, and a statistically significant acid value (P
Mooring Lines Reliability Analysis Case Study: Fso Abherka Garry Raditya Putra; Daniel Mohammad Rosyid; Rudi Walujo Prastianto
IPTEK The Journal for Technology and Science Vol 32, No 1 (2021)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v32i1.8628

Abstract

Floating Storage and Offloading (FSO) demands good designs. One of the design is FSO’s mooring lines. The mooring lines of the FSO would face various environmental conditions, so that they are required to have good reliability. FSO Abherka, installed in the Madura stratit, has dimensions of LOA 242.90 m, LPP 232 m, Breadth 41.6 m, Height 19.7 m, Draft 12,894 m, and a deadweight of 85829 tons. The strait has a water depth of 100 m with contour variations of ± 2 m. Each four cluster of mooring lines of FSO Abherka has three mooring ropes. This study analyzed the strength of mooring lines in intact and damaged conditions using DNV software Genie and DNV HydroD. This study models a hydrodynamic FSO. This study also measured the reliability of the mooring lines from 2 cases: 1 intact and one damage from the most dangerous conditions. This study used the mean Value First Order Second Moment method to find the reliability of these mooring lines. Based on the reliability calculation set by DNV according to DNV-OS E301, the mooring lines design meet the established reliability criteria

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