Search

An apples water content and rind colour affect Indonesia's people in choosing and buying this fruit. Near- infrared (NIR) spectroscopy was applied to predict precisely the best "before date" of fruits in industries by predicting the changes of water content and rind colour. Thirty apples of Red Delicious Washington species bought from supermarket served as research materials. Water content data were obtained by six times weighing within two months and simultaneously measured their L*, a*, and b* coordinates (CIE) for rind colour in two places using ColorReader CR-10 Plus and NIR spectrometer. 288 data changes of water content and rind colour were combined with their NIR spectra for analysis using CV-PLSR (cross- validation partial least squares regression) as chemometrics to produce the prediction. The water content changes in the samples were 0.8%, while the rind colour changes were 5.9 (ΔE*) within two months of research. The application ofNIR to predict changes of water content and rind colour in apple resulted 0.72 and 0.42 of R2CV, respectively, as the best prediction result from their original NIR spectra data. NIR spectroscopy could predict sufficiently the changes in water content and rind colour of apple fruit in room temperature during storage. NIR spectroscopy showed more precision to predict water than the colour of organic materials. [ABSTRACT FROM AUTHOR]

Indonesia is a country that is flanked by three tectonic plates, called the Indo-Australian Plate, the Eurasian Plate, and the Pacific plate. The three tectonic plates are still active today, increasing the risk of the potential for tectonic earthquakes to occur in Indonesia. On May 27, 2006, the city of Yogyakarta experienced a natural disaster, a tectonic earthquake which was quite strong at the 6.3 Richter Scale according to USGR calculations (United States Geological Survey). This earthquake caused a lot of losses, one of which many buildings collapsed or were damaged, making these buildings uninhabitable. According to BNPB data for 2020 (National Disaster Management Agency), more than 1000 units of worship facilities and offices were damaged, and as many as 376 units of health facilities also had structural damage. For this reason, research was taken on earthquake forces on building structures using the response spectrum method based on SNI 1726:2019, which BSN only released in the last few years. Response Spectrum is a method that analyzes earthquake forces based on the structure's curve between periods and acceleration according to the earthquake map in Indonesia. This method analyzed the structural response in the 16-floor Student Dormitory UMY using ETABS software. It was concluded in this study that the story drift exceeds the permitted limit for floors 1 to 10 in the X-direction and the Y-direction for the 1st and 4th floors to the rooftop. There is no P-Delta effect in either the X or Y directions. The horizontal structural irregularity analysis has a re-entrant corner irregularity (type 2). For the analysis of vertical irregularities, there were soft-story irregularities type 1a and 1b and vertical geometric irregularities (vertical irregularity type 3). [ABSTRACT FROM AUTHOR]

The Meteorology, Climatology and Geophysics Agency (BMKG) since 2006 until now has installed a lot of accelerograph equipment as many as 669 station locations, to determine the quality and characteristics of the seismic noise, in this study an evaluation of the accelerograph data was carried out. The evaluation report is carried out on weekly data so that in this study, seismic noise recording data was used for 7 days from September 27 to October 3, 2021. Evaluation such as analyzing the noise level using the Probabilistic Power Spectral Density (PPSD) method. The PPSD method describes the quality of the accelerograph data compared with the signal spectral of Power Spectral Density (PSD) for 7 days with the standard accelerometer noise model, namely the Accelerometer Low-Noise Model (ALNM) and the Accelerometer High-Noise Model (AHNM) subjectively. The results of data quality analysis were evaluated by weighting the results of the PPSD analysis by 50% with other parameters by 50% in the form of Root Mean Square (RMS), amplitude ratio, percentage of data availability, number of gaps, and amount of overlap. Furthermore, based on the results of PSD signal analysis and accelerograph data, 193 locations with high cultural noise were found, 27 locations had the digitizer or sensor damages, 12 locations experienced dataless equipment response errors, and 37 locations frequently experienced data gaps. Based on the results of spectrum analysis and supporting parameters, the evaluation form of accelerograph data quality are grouped into good condition, fair condition, bad, and off condition. As a result, 669 accelerograph locations, 217 locations were good condition, 177 fair conditions, 96 bad conditions, and 179 were off condition. Finally, recommendations for locations that have fair condition and bad condition were maintenance, sensor replacement. Meanwhile, it has been suggested that location changes can be adopted if the environmental noise has extremely high. [ABSTRACT FROM AUTHOR]

The Singular Spectrum Analysis (SSA) forecasting method has been used widely recently. SSA has characteristics and advantages in decomposing data into trends, oscillations, and noise, which are for forecasting. Forecasting withSSA can be done by several ways e.g. Linear Recurrent Formula (LRF), Vector, and Simultaneous. The Bootstrapping process is implemented in those forecasting methods to increase the accuracy and builds the interval forecast. This study focuses on testing the sensitivity and accuracy of the combination of the Bootstrap-LRF and Bootstrap-Vector methods. The tests are applied to data that contains structural breaks, namely Indonesia's trade monthly data (exports and imports) from 1993 to 2019. The test results show that Bootstrap-Vector has a smaller forecasting range and is more accurate than Bootstrap-LRF in long-horizon forecast. Moreover, the Bootstrap-Vector is more stable in the presence of structural break in the data, meaning that this method is less sensitive to structural changes. Meanwhile, Bootstrap-LRF is more accurate in short horizon forecast. [ABSTRACT FROM AUTHOR]

Palm oil is one of the plantation subsectors playing an important role in Indonesia. Palm oil is one of the largest exports and contributes to Indonesia's GDP. One of the palm oil producing areas is East Kalimantan, where production is increasing year by year. Time series analysis can be used to forecast palm oil production in East Kalimantan. This study would compare singular spectrum analysis (SSA) and autoregressive integrated moving averages (ARIMA) based on mean absolute percentage error (MAPE) to predict palm oil production in East Kalimantan. Based on data analysis, the SSA method hasd a MAPE of 2.3476 percent and the ARIMA model had a MAPE of 7.1214 percent. These results showed that the SSA method is superior to ARIMA in predicting palm oil production in East Kalimantan. [ABSTRACT FROM AUTHOR]

Bengawan Solo is a watershed in Indonesia with an area of ±16,100 km2. The Gondang Reservoir Lamongan Post is one of the posts passed by the Bengawan Solo River Basin. Gondang Reservoir has benefits such as supplying field reservoirs and irrigation, providing water, controlling the flood or drought, and tourism objects. However, the flow of the Gondang Reservoir river has a negative side that has the potential to damage, so that it can cause disasters in the form of floods, drought, or broken embankments. Therefore it is necessary to have a control system to reduce the risk of disasters in the future. One of the important components in the watershed is rainfall data. Rainfall is very useful in determining the beginning of the season and evaluating a model. Rainfall forecasting is very important for workers in various sectors to determine the direction of a policy to be drawn up and be able to control the flows of the river in conditions that are not destructive. Forecasting techniques is one of the statistical methods that can be used to predict rainfall data because it provides significant results in predicting time series data in the long term. In this research, the Singular Spectrum Analysis (SSA) method was applied for rainfall forecasting in the Gondang Reservoir. The SSA method consists of two stages, decomposition, and reconstruction. Each stage consists of several parts. The decomposition stage consists of embedding and singular value decomposition. Meanwhile, the reconstruction stage consists of grouping and diagonal averaging. Forecasting was conducted on Gondang Reservoir rainfall data from January 2010 to December 2020. From this analysis, it can be concluded that the SSA method could predict well enough rainfall data in the Gondang Reservoir Lamongan post using L = 32 and 5 groups with an MSE value of 43.87 and MAPE value of 21.28%. [ABSTRACT FROM AUTHOR]

Synchrotron radiation-based X-ray fluorescence is a powerful spectroscopy technique that uses synchrotron radiation to induce X-ray fluorescence in samples and provides valuable information on the micron and submicron scale. The characteristics of synchrotron radiation permit implementing multi elemental nondestructive spectrochemical analysis with spatial resolution on the micrometer scale, high efficiency for trace element determination, minimal sample preparation, and reasonable time of analysis. At the IAEA beamline end-station at the Elettra Sincrotrone Trieste, the measurement of airborne particulate PM2.5 samples collected in industrial sites in Indonesia were carried out. The typical reflection 45/45 irradiation geometry was employed for both the micro-XRF and Xray Absorption Near Edge Structure (XANES) measurements. The micro-XRF scanning analyses were performed at different incident beam energies and a total area of about 4 mm×4 mm was analyzed by performing 9×9 measurements with a step size of 0.5 mm with 10 s acquisition time per step. Selected elemental analysis of airborne particulate PM2.5 samples using SR micro XRF were carried out at selected beam energies of 13.5, 12.5 and 7 keV for highly sensitive elemental compositional analysis. Several selected elements such as Na, Mg, Al, Si, S, Cl, K, Ca, Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Br and Pb were determined. For the determination of the chemical state of certain trace elements, XANES measurements was also performed using the fluorescence mode of analysis at the respective spots identified with the more abundant trace element concentration. XANES spectroscopy was used to determine the oxidation state of arsenic and chromium in APM samples. [ABSTRACT FROM AUTHOR]

This study aimed to determine the accuracy of forecasting methods for trend and seasonal Indonesia visitor arrival. Three single methods, Seasonal Autoregressive Moving Average (SARIMA), Singular Spectrum Analysis (SSA), and Fuzzy Time Series (FTS) were used to model and predict the monthly arrival. We have also compared the three single methods with two hybrid approaches, SARIMA-FTS, and SSA-FTS. Results show that SARIMA-FTS is the most appropriate model to capture the trend and seasonal pattern of the series in term of Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). [ABSTRACT FROM AUTHOR]

Jumoyo Bridge is one of bridges connecting the main highways of Magelang-Yogyakarta, Indonesia. The bridge durability test was conducted to determine self-frequency and motion direction of the bridge's particles. Measurements were performed in two circumstances, namely when the location was crowded and deserted to be passed by vehicles. Measurements points consisted of six points along Jumoyo Bridge, and one point above the ground level near the bridge. Obtaining the movement of particles and HVSR spectrum, the data analysis was conducted by using Geopsy software. The self-frequency values of the bridge were calculated based on HVSR spectrum. The process of selecting signal (windowing) was performed manually on the ambient signals. The self-frequency values of the bridge obtained were in the range of 2.74 to 2.95 Hz, with the amplitude were 0.48 to 1.63 mm. The bridge's particle motion in vertical direction have trending N-S, while in horizontal direction tends to SW-NE. The ground's frequency value around the bridge was 0.79 Hz. Based on these results, it can be said that Jumoyo Bridge has resistance towards the resonance danger of the ground. For the next measurement, it needs to measure the stresses that occur to obtain more complete analysis. [ABSTRACT FROM AUTHOR]