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IPTEK Journal of Science

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Published by Institut Teknologi Sepuluh Nopember Surabaya

ISSN : - EISSN : 23378530 DOI : -

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IPTEK Jounal of Science (E-ISSN: 2337-8530) is an academic journal on the issued related to natural science, mathematics, and statistics. Published actually in March, June, September, and December. It is open to all scientist, researchers, education practitioners, and other scholar. Therefore this journal welcomes to various topics that have recieved by Proffesors and Doctors specifying on related studies, and they come from reputable universities all over Indonesia and universities abroad.

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Articles 12 Documents

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Application of Confidence Intervals for Parameters of Nonparametric Spline Truncated Regression on Index Development Gender in East Java Rifani Nur Sindy Setiawan; I Nyoman Budiantara; Vita Ratnasari
IPTEK Journal of Science Vol 2, No 3 (2017)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat

The Gender Development Index (GDI) is an index that measures the achievement of human basic capability development for the health, education and economic sectors within a region by considering equality between men and women. In this research GDI with the factors that are suspected to affect it will be modeled using nonparametric spline truncated regression, because the results of scatterplot pattern of GDI with some predictor variables not to follow a certain pattern. Determination of predictor variables that significantly influence GDI by using confidence interval obtained high school enrollment rate of female population, morbidity of female population, percentage of last aid of birth by medical, and female labor-force participation rate have significantly influenced to GDI in East Java.

3D Tomographic Imaging of P Wave Velocity Structure Beneath Java Island using Fast Marching Tomography Method Uswatun Chasanah; Bagus Jaya Santosa
IPTEK Journal of Science Vol 2, No 1 (2017)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat

Java Island one of the best locations for geophysics research, as it’s located near the edge of the junction of continental Eurasia Plate and the Indo-Australia Plate with the movement of the plates 6 cm/year. Its needed the accurate imaging of subsurface structure to understanding complex tectonic setting. The first arrival time from local earthquake of Java (6,360-9,150 S and 105,890-115,540 E) with magnitude greater than 4,5 Mw occurred from 2011 until 2013 recorded by local network seismograph has been inverted for three dimensional variation of the depth to the P wave velocity in the Java island. At the same time, earthquake hypocenter location has been corrected simultaneous. This research apply a new tomographic inversion scheme FMTOMO that has been developed by Rawlinson (2004). The results of inversion show that there are three layer in 100 km from the surface at continental plate side (Eurasia). The continental upper crust has P wave velocity variation about 4-5,5 km/s in the depth until 30 km from the surface. There are low velocity anomaly inclined towards the slab which probably have associated with shallow earthquake along the slab

Modified Convolutional Neural Network Architecture for Batik Motif Image Classification Ardian Yusuf Wicaksono; Nanik Suciati; Chastine Fatichah; Keiichi Uchimura; Gou Koutaki
IPTEK Journal of Science Vol 2, No 2 (2017)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat

Batik is one of the cultural heritages of Indonesia that have many different motifs in each region as well as in its usage. However, the Indonesians sometimes not knowing the batik motif that they’re wearing every day, and sometimes they have a batik image without knowing batik information contained in their batik image. With the growing number of images of batik and batik motifs, a classification method that can classify various motifs of batik is required to automatically detect the motif from the batik image. Image processing using the Deep Learning especially for image classification is widely used recently because it has good results. The most popular method in deep learning is Convolutional Neural Network (CNN) which has been proved robust in natural images. This study offers a batik motif image classification system using CNN method with new network architecture developed by combining GoogLeNet and Residual Networks named IncRes. IncRes merges the Inception Module with Residual Network structure. With the 70.84% accuracy, the system can be used to classify the batik image motif accurately.

Calibrating Weather Forecast using Bayesian Model Averaging and Geostatistical Output Perturbation Muhammad Luthfi; Sutikno Sutikno; Purhadi Purhadi
IPTEK Journal of Science Vol 3, No 1 (2018)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat

Numerical Weather Prediction (NWP) has not yet been able to produce the weather forecast accurately. In order to overcome that, one approach could be taken is ensemble postprocessing. Ensemble is a combination of several methods to improve its accuracy and precision yet still possesses underdispersive nature. Bayesian Model Averaging (BMA) is intended to calibrate the ensemble prediction and create more reliable interval, though, does not consider spatial correlation. Unlike BMA, Geostatistical Output Perturbation (GOP) reckons spatial correlation among many locations altogether. Analysis applied to calibrate the temperature forecast at eight meteorological sites within Jakarta, Bogor, Tangerang and Bekasi (Jabotabek) are BMA and GOP. The ensemble members of BMA are the prediction of PLS, PCR, and Ridge. For training period over 30 days and based on some assessment indicators, BMA is better than GOP in terms of accuracy, precision, and calibration

Parameter Estimation of Smith Model Max-Stable Process Spatial Extreme Value (Case-Study: Extreme Rainfall Modelling in Ngawi Regency) Siti Azizah; Sutikno Sutikno; Purhadi Purhadi
IPTEK Journal of Science Vol 2, No 1 (2017)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat

The unpredictable extreme rainfall can affect flood. Prediction of extreme rainfall is needed to do, so that the efforts to preventing the flood can be effective. One of the methods that can predict the extreme rainfall is the Spatial Extreme Value (SEV) with the Max-Stable Process (MSP) approach. The important purpose of SEV is calculated of return level (the extreme value prediction). The calculation of return level depends on parameter estimation in that method. This research discusses about parameter estimation of the Spatial Extreme Value Max-Stable Process especially Smith model. Parameter estimation was performed using Maximum Composite Likelihood Estimation (MCLE) method and Maximum Pairwise Likelihood Estimation (MPLE) method. The result of estimation using this method is not closed form, it must be continued by using numerical iteration method. The iteration method used in this research is Broyden-Fletcher Goldfarb-Shanno (BFGS) Quasi Newton, which is faster than other methods to achieve convergence. The result of parameter estimation applied to the rainfall data of Ngawi Regency which is the Regency with the largest rice production in East Java Province (the province with the largest rice farm in Indonesia). Based on the results of data analysis obtained trend surface model (s) = 2,794 + 0,242 v(s); (s) = 1,8196 + 0,1106 v(s); (s) = 1,012 with goodness criterion model Takeuchi Information Criterion (TIC) 26237,62. Root Mean Square Error (RMSE) based on 20 testing data is 32,078 and Mean Absolute Percentage Error (MAPE) is 27,165%

Data Reconciliation on PLTGU Gresik Using Particle Swarm Optimization (PSO) Wahyu T Pratiwi; Totok R. Biyanto
IPTEK Journal of Science Vol 2, No 3 (2017)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat

The innaccurate on process data in PLTGU Gresik does not satisfy the mass and energy balance. Data reconciliation techniques can effectively improve precision and reduce measurement error on process variable estimation of data plant through modeling and optimization techniques. In this paper, we propose PSO (Particle Swarm Optimization) algorithm to solve the data reconciliation problem for precise improvement and error minimization. As a result, the standard deviation of data measurement and reconciliation is different on each variable heat exchanger component, so that indicates random errors on measurement. Based on the result, PSO algorithm is capable generate reliable data and minimizing error with sum square error is equal to 1.153. It means PSO algorithm is compatible with the instrument system on PLTGU Gresik. Moreover, data reconciliation is applied then followed with detection gross error using statistical test that is Global Test. As the result, there is not gross error on the measurement.

Tax Complaints Classification on Twitter Using Text Mining Prita Dellia; Aris Tjahyanto
IPTEK Journal of Science Vol 2, No 1 (2017)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat

Twitter growth and utilization encourage the emergence of limitless textual information so that people can express their complaints easily This leads the Directorate General of Taxation uses twitter to deal with tax complaints faced by the community. However, the messages on twitter can contain any information, either the tax complaint or not. This will cause difficulties in handling complaints process. It is important to automatically identify so tax complaint handling can be done effectively and efficiently. Given these problems, it is necessary to do the twitter tax complaint classification with the support of text mining. There are several methods of classification such as Naïve Bayes classifiers, Support Vector Machine (SVM) and Decision Tree. This research aims to classify the tax complaint on twitter automatically by using text mining. The experimental results show the value of f-measure of SVM, Naïve Bayes and Decision Tree, respectively, are 89.3%, 85.6% and 76.9%

Effect of Intrinsic Layer Energy Gap and Thicknesses Optimization on the Efficiency of p-i-n Amorphous Silicon Solar Cell Ignatio Benigno; Darminto Darminto
IPTEK Journal of Science Vol 2, No 3 (2017)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat

morphous silicon solar cells with single p-i-n layer were grown on 10 cm2 ITO coated glass substrates. Fabrication process done by using 13.56 MHz RF-Plasma Enhanced Chemical Vapor Deposition (PECVD). Hydrogen flow on the deposition process is widely known to enable the passivation of the dangling bond on Silicon bonds. The passivation of dangling bond affects the band gap of each layer and cell performance in the absorption of photon. In the deposition process of intrinsic layer, SiH4 gas flow is set constant at 2.5 sccm, while variation is done in hydrogen gas flow at 0 sccm – 90 sccm. Energy gaps obtained for p-layer and n-layer are 2.0 eV and 2.2 eV at thickness 64 nm and 36 nm respectively. Optimizations have been done for intrinsic layer which band gaps are 1.4 eV, 1.6 eV and 1.9 eV at thickness 400 nm. The solar cell efficiency was increased from 4.8% to 5.64% based on the band gaps variety. In addition, i-layer thicknesses were also varied from 400 nm, 500 nm and 600 nm. Thicknesses variation shows an increase of 5.78% in the solar cell efficiency.

System Dynamics Development Model for Operations Strategy in Power Generation System through Integrated Transmission and Distribution System Lilia Trisyathia Quentara; Erma Suryani
IPTEK Journal of Science Vol 2, No 1 (2017)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat

Electrification Ratio in East Java (Indonesia) has reached 86.67% at the end of 2015 due to in Madura island only 60.55% who have received electricity supply from PLN. The topography of Madura which far-flung distances per village, as well as the small number of households in the village are being constraint in build up the electricity infrastructure investment. The main problem in electrical operating system is how to meet the demand and supply of electric power by maintaining the continuity of effective and efficient services to PLN customers. These problems would take a long-term solution in electrical system which is able to increase the role of renewable energy, improve the reliability, safety and efficiency, reduce energy costs, and can recover quickly from interruptions. Effective and efficient electrical operational systems in real time is expected to improve the sustainability of supply electric power. The Dynamic System method is used to analyze the electrical operating system by developing a scenario model to identify the factors and variables that affect the system, to be use-full as consideration in taking strategic policy in operational PLN

Small Area Estimation Of Expenditure Per-capita in Banyuwangi with Hierarchical Bayesian and Empirical Bayes Methods Wirajaya Kusuma; Nur Iriawan; Irhamah Irhamah
IPTEK Journal of Science Vol 2, No 3 (2017)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat

One of the economic indicators that are widely used to measure the level of prosperity and welfare is per capita income. However, an accurate income data is difficult to be obtained. In Susenas this data is approached by using data on expenditures per capita. This study employ Hierarchical Bayes (HB) and Empirical Bayes (EB) methods to be applied to Small Area Estimation (SAE) to estimate the expenditure per-capita in Banyuwangi. The results showed indirect estimation using hierarchical Bayes and Empirical Bayes produce RMSE values smaller than the direct estimation. The HB method, on the other hand, produces smaller RMSE value than the EB method. Finally, this research suggests to use HB method to estimate the expenditure per-capita in Banyuwangi rather than direct estimation which is used nowadays.

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