International Journal on Advanced Science, Engineering and Information Technology
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Rhizopora apiculata (Blume) Density, NDVI, and Utilization by Fishermen Community in Muara Angke Wildlife Reserve, Penjaringan District, Jakarta, Indonesia
Get PDFRhizopora apiculata is a common mangrove species found in tropical Asia, and it is also widely used by communities living near mangrove forests, including in Indonesia, due to its wood durability. This study aims to assess the status and utilization of R. apiculata, primarily by the fishermen community living near Muara Angke Wildlife Reserve in Jakarta Bay, Indonesia. The density of R. apiculata was determined by placing 100-meter-long transects from west to East in Muara Angke. While the normalized difference vegetation index (NDVI) of R. apiculata was studied using Landsat 8 satellite images with specific near-infrared and red wavelengths. The utilization of R. apiculata was assessed through interviews with 108 fishermen. The results showed that the west parts of Muara Angke had higher density, NDVI values, and canopy covers, with the R. apiculata density, NDVI, and canopy cover ranges being 3339.5-2856.3 Ha-1 trees, 0.79-0.99 percent, and 90-100 percent. There was a positive relationship between R. apiculata density, NDVI, and cover and the distance to the fishermen's village, decreasing NDVI trends toward villages. NDVI values in R. apiculata populations located far (> 1 km) from villages were higher, while NDVI values in R. apiculata populations located close (1 km) to villages were lower. Low density and NDVI values near the village were linked to fishermen's understanding and use of R. apiculata. This research can help to conserve and sustainably use the remaining mangrove community, primarily in Jakarta Bay
Application of Machine Learning to Determine the Factors Affecting Deterioration in Patients with Chronic Kidney Disease
Get PDFHospital databases generally contain large amounts of data and various, but it has not been used optimally. It needs a technique that can utilize mountains of data into strategically valuable information. This paper will investigate ways to use hospital data to help determine the factors that influence the deterioration in patients with chronic kidney disease. The criteria for the selected patients were patients with a diagnosis of chronic kidney disease and chemotherapy treatment at least once. Three hundred seventy-six patients met these criteria. Subsequently, observation the patient's treatment course for three years. Ninety patients died in the hospital during that period. All the results of patients' blood tests were collected for further analysis. In forming the classification model, there are three stages carried out. The first stage deals with diverse, incomplete, and inconsistent data. Then through the process of changing continuous data into categorical data, each variable is classified into several categories. The next stage is to create a predictive model to determine the factors that influence the deterioration in patients with kidney failure using the Random Forest, Logistic Regression, and Decision Tree algorithms. Information of the classification model, 12 variables were selected, namely age, sex, and the results of clinical pathology laboratory examinations-Ureum, Thrombocyte, Natrium, Creatinine, Chloride, Kalium, Hemoglobin, Hematocrit, and Leukocytes. The three algorithms can classify training data with an accuracy of 98% (Random Forest), 83% (Logistic Regression), 98% (ID3)
Sensory and Physicochemical Characteristics of Two Common Roast Defects in Robusta Coffee
Get PDFRoasting is an important coffee processing step to generate coffee aroma and flavor. Because roasting is time-temperature dependent, the variation of time and temperature applied may influence the structural properties, visual appearance, and chemistry of coffee. Improper roasting creates roast defects that reduce coffee quality and acceptance. Despite this importance, studies on coffee roast defects, particularly in Robusta coffee is limited. This study aims to characterize two common roast defects, i.e., underdeveloped and overdeveloped, compared with medium roast in Robusta coffee. Sensory evaluation by trained panelists and physicochemical evaluation reveal that the two common roast defect in Robusta coffee can be distinguished clearly through differences in sensory (aroma defect) characteristics as well as physicochemical properties. The overdeveloped roast defect produced darker coffee with the highest pH and total dissolve solids (TDS), and can be characterized by pyridine, furan, phenol and pyrrole derivatives. The carbony and ashy notes of the overdeveloped coffee were potentially contributed by phenol and polyphenol derivatives. In contrast to the overdeveloped coffee, the underdeveloped coffee is markedly characterized by higher concentration of aliphatic acids and higher concentration of pyrazines that contributes to raw nut-like notes. The combination of time and temperature during roasting influences the breakdown of chemical compounds through complex mechanisms involving proteins, carbohydrates and polyphenols degradation. Thus, roasting process variations that determine coffee cup quality and in turn drive consumer acceptance should be controlled
Antituberculosis Activity and Iron Chelation Ability of Brazilin Isolated from Caesalpinia Sappan L.
Get PDFThe present study was conducted to evaluate the anti-tubercular activity of Brazilin and to know the role of iron chelation on the anti-tuberculosis activity of Brazilin. Anti-tuberculosis activity in vitro was tested through MIC values and a reduction in the number of Mtb bacterial cells. The MIC and MBC tests utilized extent technique comprising four treatment groups; the positive control (Lowenstein-Jensen medium inoculated with Mtb), the negative control (LJ medium), the anti-tuberculosis drugs (rifampicin, isoniazid, ethambutol, and streptomycin), and Brazilin at concentration 1, 2, 4, 8, 16, 32, 64, 128, 256, 512, and 1024 ppm that were watched for about eight weeks. The iron chelation capability was assessed using atomic absorption spectrophotometer. The results indicated that the MIC from Brazilin is 128 ppm and MBC of 256 ppm. Brazilin at 128 ppm showed iron chelation of 32.96% capacity and can reduce up to 72% Mtb cells in 10-3 inoculum dilution. Iron levels at Brazilin 128 ppm (MIC) are higher than iron levels at concentrations of 256 ppm (MBC), indicating that Brazilin binds to iron. The binding of iron by Brazilin results in the unavailability of iron for Mtb, and causes suppression of Mtb growth, further resulting in Mtb cell death. These results exhibit that Brazilin can be used as an iron-chelating agent that might be advantageous in treating and controlling mycobacteria infection
The Modified Structural Quasi Score Estimator for Poisson Regression Parameters with Covariate Measurement Error
Get PDFThis article proposed the Modified Structural Quasi Score (MSQS) estimators for Poisson regression parameters when a covariate is subject to measurement error. We study the situation when the true covariate in the Poisson regression model is unobserved, and the surrogate for this covariate is related to the true covariate by the additive measurement error model. We assumed that true covariate as a random variable with unknown density function distribution and its observable values as surrogates, which also has Poisson distribution. We applied the Empirical Bayes Deconvolution (EBD) method for estimating the true covariate density with a finite discrete support set. To estimate Poisson regression parameters, we construct an MSQS estimating equation based on proper functions for the mean and variance of the Poisson distributed surrogate. The MSQS estimator for the Poisson regression parameter is the root of the quasi-score function based on the quasi-likelihood method. We did some simulation scenarios for assessing the MSQS estimator by assuming the true covariate comes from Gamma distribution as a conjugate before Poison distribution. We compute the standard error of the mean, standard deviation, and bias of the MSQS estimator for various sample sizes to examine the estimator's appropriateness. The simulation showed that a combination of the finite discrete support set of surrogates based on the range values and smaller-scale parameter of Gamma distribution yields smaller values of bias estimator and the estimated standard deviation
Soft Set Parametric-based Data Clustering for Building Data Set
Get PDFIdentifying buildings for safety purposes is critical to anticipate unforeseen scenarios during a disaster. Rapid Visual Screening (RVS) is one of the procedures that can be used to determine a building's hazardous structure. The growing number of buildings necessitates grouping to provide recommendations for improving the analysis or conducting a more extensive review of the same building group. This article investigates the application of fuzzy clustering to the RVS dataset. Numerous strategies are compared, including fuzzy centroid clustering, fuzzy K-partition clustering, and multi-soft set clustering. The technique is applied to the RVS data set from Kulon Progo, Yogyakarta, which has 144 cases for grouping construction. Four clusters are formed from four distinct variables with fewer conditions: Plan Drawing, Floor Plan, Connection, and Stance. The experiment is based on the rank index, the Dunn index, and response time. The results indicate that multi-soft set-based clustering outperforms other baseline approaches. The investigator or government can utilize this information to suggest treating each cluster's "less" variable
Analysis of The Pipelines Headrace of Micro-Hydropower Plant
Get PDFThe area around Andalas University has the potential for renewable water sources that have not been utilized optimally. This can be used to meet the electricity needs of Andalas University. University requires electricity costs of 720 million per month. With the Micro Hydro Power Plant, the campus can save electricity costs for this purpose. This research aims to study the most optimum headraces and the generated power capacity. A hydrology analysis is needed to obtain a reliable discharge as a reference for potential river flow in determining the electric power capacity; the dependable discharge is used with a percentage of events throughout the year of 85%. The dependable discharge analysis is carried out by the F.J Mock method and the NRECA model, where the calculation results of these two methods are almost close to 1.1 m3/s. This study uses EPANET 2.0 software in modeling the water distribution network to the MHP turbine. The rainfall data used is for 11 years (2008-2018), where the data is taken from Batu Busuk station, Ladang Padi station, Simpang Alai station and Gunung Nago station. The climatological data needed is the climatological data for the city of Padang. In this study, several alternative channel traces were used to make it easier to determine the most optimum channel trace. Based on the EPANET simulation results, an alternative D is obtained as the best trace with a carrier channel along 1692.82 m using HDPE pipe Ø720. The discharge that can be passed is 1,098 m3/s, and the power generated is 0.6 MW. Alternative D trace is superior to others because it does not pass-through steep slopes, so it is safe and easy to install
Mangroves and the Sustainability of Longtail Shad Fish (Tenualosa macroura) in Riau Province Water, Indonesia
Get PDFMangroves are crucial to fisheries as nurseries; they can be used as spawning and feeding grounds for fish, including Longtail Shad fish (Tenualosa macroura). The objective of the study was to analyze the mangrove vegetation used as Longtail Shad fish spawning ground. It was carried out from January to May 2021, using a checkered line method with six sampling stations. Each station was placed in three transects with three plots for each transect. Density, relative density, frequency, relative frequency, dominance, relative dominance, and importance value index were included in the vegetation analysis. There were 13 true mangrove types and 1 mangrove associate type at the study locations. The highest mangrove density was found at Station 3 with 3300.48 Ind/Ha, categorized as good. The highest mangrove coverage was found at Station 2, with an exceptionally dense category (76.34%). The regression analysis revealed a substantial relationship between density and mangrove and the water salinity at a 0.002 significance value
Morphological in situ Characterization of Mortiño (Vaccinium floribundum Kunth) in the Andes of Ecuador
Get PDFVaccinium is one of the largest in the Ericaceae family, distributed worldwide. Mortiño (Vaccinium floribundum Kunth) is an Andean fruit threatened by agriculture, livestock, and forestry activities, causing genetic erosion. The importance of the mortiño fruit is also because of its nutritional composition due to its high content of functional compounds in comparison to other Andean fruits. The characterization of a species allows scientists to estimate the population’s genome variability. The morphological characterization reveals important distinctive morphological features, some of which will promote the species’ commercial value. This study aims to apply morphological and agronomic descriptors to mortiño in situ in the paramos of Ecuador. Three locations in three different provinces of the Ecuadorian highlands were selected: San Pablo in Imbabura, Atacazo in Pichincha, and Quilotoa in Cotopaxi, all located between 3200 and 4050 masl. Forty-two descriptors were registered in 15 mortiño populations, of which 16 were quantitative and 26 qualitative. The results demonstrated the existence of two morphological groups of mortiño, the first formed by populations in Imbabura and the second by those in Pichincha and Cotopaxi. The discriminating descriptors of the mortiño plants in the three locations were: the altitude of the site, total soluble solids, and acidity of the fruit, plant height, growth habit, and flower characteristics. The floral formula of the mortiño is K (5); C (5); A (7); G (3). To the best of our knowledge, this study is the first comprehensive morphological description of Andean Vacccinium floribundum
Karangkemiri Village Landslide Potential Risk Mapping Based on Integrating Litho-structure and Morphology
Get PDFThe Karangkemiri Village, Jeruklegi District, Cilacap Regency, Central Java Province, has a high risk of rock-mass movement. This is proven by the occurrence of a landslide in March 2020. The susceptibility of landslides is influenced by eight factors: slope, lithology, land cover, elevation, loading, rainfall, distance from rivers, and roads. Therefore, a landslide potential risk map is needed as a disaster mitigation effort. The integration between litho-structure and morphology was applied to understand the distribution of landslides vulnerability in Karangkemiri Village. The Analytical Hierarchy Process (AHP) method was adopted to find the dominant factor that causes a landslide. The result of this study was the geology of a research area consisting of 3 geomorphological units, namely the Structural Curve Slab Hills Unit (S3), Structural Waveed Hills Unit (S2), and Intrusion Unit to Basalt (S11). Stratigraphy of research areas is composed of sandstone (Tmph) and andesite lava (Tmpk) units. Special study methods use the AHP, assessment, and weighting against the landslide movement's causative factors, such calculations combined with primary and secondary data. The data and calculations were inserted into the parameter map then combined to obtain a map of the rock-mass movement susceptibility zone. Analyzing results show research areas divided into two levels of rock-mass movement vulnerability, medium, and high vulnerability levels. Medium levels of vulnerability cover 60% of Karangkemiri Village. Meanwhile, a high level of vulnerability encompasses 40% of Karangkemiri Village