International Journal on Advanced Science, Engineering and Information Technology
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GIS Analysis for Flood Problem in the Big City: A Case Study in Pekanbaru City, Riau Province, Indonesia
Get PDFPekanbaru City, Riau Province, Indonesia located at 0°25'29.20"- 0°39'15.22" N and 101°20'43.39"- 101°34'25.60" E. This research aims to study the common causes of flooding in Pekanbaru city with a good geological condition. Research in the flood area of the city of Pekanbaru using primary and secondary data; geological, geomorphological, rainfall, and land use data. Information about this earth system combined with geographic information system (GIS) analysis using a small unmanned aerial vehicle (UAV) / drones including Geographic Positioning Systems (GPS) combined with online coordinate systems that can help spatial analysis to determine the level of vulnerability of flood disasters by producing a visual mapping model. The study shows that 4 locations were found vulnerable to being affected by flooding when it rained. The flood impact in those areas happened because those locations are in a geomorphological system with a low topographic area, the natural river system that controls the water to the main river, and a poor water escape-system / drainage. The geomorphological analysis showed two geomorphological units, i.e., lowland denudational and lowland structural with river flow-pattern that is dendritic, sub-dendritic, and parallel. Rainfall is quite high in 2018 with 2621.5 mm and caused flood-prone areas, which are divided into three categories: Non-vulnerable area (64.575%), Medium Vulnerable area (23,386%), and Vulnerable area (12,039%) from the entire of the research area
Investigate the Thermal Behavior of the Portable Weather Monitoring System Based on Arduino Nano
Get PDFThis work aims to achieve a functional system in terms of software and hardware to measure humidity with temperature and raining fall. Also, this system allows monitoring the date and time. We used Arduino Nano with the interfacing of the DHT22 sensor and a raindrop sensor placed in the local environment to measure the mentioned data. After designing the system that depends on the microcontroller Embedded on the Arduino board, we will display the data on a screen of the PC by the Arduino window (serial monitor) and display it on the LCD screen. This paper describes a simple portable design for humidity, temperature, and rain or no rain. The portable design can be made with a low cost of electronic components. It is efficiently and locally available so that it can be used to monitor weather conditions at any place. The test results showed that this system's component is small and can be packaged in a small plastic box. Besides, through the programming, we recorded the data on the Excel program, and at the same time. The data were recorded in a memory added to the manufactured system. The data obtained every five seconds are the (date, time, temperature, humidity, weather if rainy or not rainy). The system consists of two parts; the first part is inside the indoor, and it can be placed outdoor as needed and the second part is a rain sensor that can be placed outdoor. In case of rain, the buzzer and LED can be turned on to indicate the condition of rain
Fuzzy-Based Application Model and Profile Matching for Recommendation Suitability of Type 2 Diabetic
Get PDFDiabetes Mellitus (DM) is a metabolic disease characterized by hyperglycemia due to insulin secretion abnormalities and a global health threat. DM has several types, namely type 1, 2, gestational, and other types. Type 2 diabetes patients have the largest number in the world. DM therapy can be done in 2 (two) ways: improving lifestyle and administering drugs. The problems and risks in recommending drugs are essential in the patient's healing process because they are likely to take medicine for life. Approximately 260,000 patients with type 2 diabetes experienced medication errors in 2017. The doctor's mistake in recommending drugs causes a long healing process and costs more. Recommending drugs requires pharmacological knowledge, and not all hospitals have pharmacologists. Several researchers have researched recommendations for antidiabetic drugs, but no studies have yet been found that discuss recommendations for combination antidiabetic drugs for type two to determine dosage and frequency. The number of medications used is 6 to 7, with many parameters 5 to 8. The latest endocrinology guidelines for 2020 state that in recommending antidiabetic drugs, not only 6 to 7 participants, but still need to maintain other aspects. Therefore, this study aims to build an expert system model with a new approach in recommending antidiabetic drugs with more complete parameters and recommend dosage and frequency. The model developed uses the Fuzzy Profile Matching method. Fuzzy is used to calculate the suitability between the patient's condition and the type of antidiabetic drug. Profile Matching is used to calculate the core factor and secondary factor to obtain each drug's total value. The dose was calculated using the FIS Tsukamoto for inputting low dosage, and high dosage calculated the weighted average value. Determination of frequency using the IF-Then function. Model evaluation is done by comparing recommendation data from doctors. The results of the evaluation of the model obtained an accuracy of 90%. This system will reduce medical personnel errors in recommending antidiabetic drugs that can positively impact patients' time, the healing process, and costs. This study provides knowledge that antidiabetes drugs' determination requires many parameters, while other studies used only 4 to 8. This study also provides an overview of the dosages of drugs that drug companies can produce. Usually, the company only makes low and high dosage. This study shows that creating multiple drug dosage is more efficient for patients
Rice Growth Stages Mapping with Normalized Difference Vegetation Index (NDVI) Algorithm Using Sentinel-2 Time Series Satellite Imagery
Get PDFRice as one of the staple food commodities consumed by most of Indonesia's population. In terms of the rice consumption level, the trend always follows national population growth every year. In 2016, Bojonegoro Regency reached 1,050,000 tons of rice; hence, it obtained a surplus of 750,000 tons of rice from the production target. Considering this potency, it is necessary to monitor the stability of agricultural production regularly. This study monitored the rice growth stages by utilizing remote sensing data of Sentinel-2 optical satellite imagery. Analyzing the growth stages of rice plants can be done through the vegetation index algorithm. The algorithm used in this study is the Normalized Difference Vegetation Index (NDVI) in time series. From the analysis of NDVI time-series graphs, the correlation between NDVI values of Sentinel-2 images and the rice growth stages is 0.896 with a coefficient of determination of 0.803 or 80.34%. The seedling phase has an NDVI value <0.224. The vegetative phase has a range of values of NDVI 0.224 - 0.894. The generative phase has NDVI value range of 0.894 - 0.270. The fallow phase has a range of NDVI values <0.270. The results of the Sentinel-2 image classification obtained classification accuracy-test values for images on January 9, 2019 with a Kappa coefficient of 0.7824 and overall accuracy of 83.87%
A Survey of Query Expansion Methods to Improve Relevant Search Engine Results
Get PDFDue to large volumes of documents available for retrieval in a search database, an intelligent method is required to retrieve relevant search results. Query expansion is one of such methods widely used in retrieving pertinent results of various search domains. The increased amount of information stored in a search engine database requires the use of query expansion. A query expansion deals with expanding the query by adding additional information to the query for effective retrieving relevant results. Recently, many query expansion techniques have been proposed to addresses the vocabulary mismatch problem that may arise in the information retrieval system. However, these techniques still have low precision results. This paper presents a systematic review of query expansion research from 1999 to 2018. The paper reviewed and discussed 573 research papers on query expansion methods and their application areas. It focuses only on the query expansion in text retrieval of search engines. This review's primary goal is to provide a broad overview of query expansion research and view how research approaches changed. The research paper analyzed and presented the contributions of each query expansion study. It also identifies major application areas of query expansions and their future opportunities. The finding of this study indicates a trend towards using semantic-ontology and pseudo-relevant feedbacks methods. This work will be beneficial to query expansion researchers in extending future work on query expansion research
Vertical Market Integration for Beef Prices Using Vector Error Correction Model (VECM) In Indonesia
Get PDFNormatively, price changes that occur in the consumer market will be passed on to the producer’s market. The price change is not necessarily enjoyed by beef cattle farmers in Indonesia. The purpose of this research was to examine whether there is a vertical market integration of beef among consumer and producer market in Indonesia. The examination of this issue was done through the Vector Error Correction Model (VECM). The data used in this study were secondary. This study used monthly price data of beef (Rp/kg) in Indonesia, consisting of 96 observations from January 2011 to December 2018. This study reveals that there is a long-term relationship among the consumer market and producer market in Indonesia. The short-run was also found that vertical beef market integration in Indonesia is only one direction, from consumers to producers. This finding represents that the beef market is vertically integrated, but the integration is not perfect. Imperfect integration of beef marketing in Indonesia signifies that the beef market in Indonesia is inefficient both in the short and long term. This study recommends the government formulate policies that provide infrastructure to avoid market exploitation and asymmetry information from the consumer market to the producer market. Besides, the government needs a price brand policy, where the government sets a reasonable price disparity between prices at the farm level and prices at the consumer level
Assessment of Spatial Water Quality Observation of Citarum River Bandung Regency Using Multivariate Statistical Methods
Get PDFCitarum River is one of the most important rivers in Indonesia. Around 16 million people interrelate with this river, covers 12,000 Km2 of the watershed, supplies water for irrigation of 420,000 hectares of rice fields, provides 80% of water need for the city of Jakarta- the capital of Indonesia. Unfortunately, Citarum was also known as one of the most polluted rivers in the world. Although there is much attention to this river nowadays, there is still no analysis to determine the latent contributing factors of water quality cluster distribution. This study aims to provide spatial water quality on the Citarum River Bandung Regency. This study can help the government decide on how to manage the water quality of Citarum and all socio-cultural factors involved in polluting the river. Open Data can also use the data and result for further research. Assessment of Citarum water quality is done through the application of multivariate statistical approaches. The data set comprises one-month observation data from 75 stations positioned in Citarum Bandung Regency and its tributaries. Factor Analysis with PCA as the extraction method gives two factors while CA showed three clusters suggesting the different physicochemical characteristics and pollution levels of the Citarum water systems. BOD, COD and DO, together with total P and Fecal Coliform are identified as two underlying factors on water quality in Citarum and its tributaries in Bandung Regency. Descriptive Statistic values confirm the quality of Citarum Bandung Regency low water quality
High-Resolution Landslide Susceptibility Map Generation using Machine Learning (Case Study in Pacitan, Indonesia)
Get PDFLandslide, one of the most disastrous natural hazards, causes damage to infrastructure worldwide and local communities. Pacitan, Indonesia is one city with high susceptibility to landslides occurrence. The conditions of landslide occurrence are assumed to be the same in the future. This study’s objective is to produce a landslide susceptibility map by using machine learning methods based on topographical factors including elevation, slope, aspect, profile curvature, plan curvature, Topographic Wetness Index (TWI), distance to the river, and geological map as independent variables, whereas the landslide inventory map derived from Sentinel-2A and Landsat 7 were used as the dependent variables in the model construction. This study's datasets were constructed in three different compositions where each composition was treated as input in Random Forest, Decision Tree, and Logistic regression model. The first dataset was composed of a 70:30 ratio for training and testing sample points, the second dataset with a 60:40 ratio, and the third with a 50:50 ratio. The performance of each model using each dataset composition was analyzed using various accuracy assessments. This study also considered each topographical factor's effect on model performance by excluding several factors in model construction. From the results, random forest with the first dataset appeared to give the best performance for mapping landslide susceptibility area, shown by the highest Area Under Curve (AUC) value, Coefficient Correlation (CC), and Cohen’s Kappa of 0.96, 0.92 (92%) and 0.84, respectively. Elevation and geological maps were considered as essential variables shown by significant drops in model accuracy assessment when these two factors were separately excluded, while profile curvature was the least essential variable based on the insignificant drop in the model accuracy assessment result
The Linear Model of Saccharomyces cerevisiae Turbidity in Liquid Media
Get PDFThe study aims to investigate the relationship between the turbidity and density or the total suspended inorganic particles have been obtained many models. The live cells as the homogeneous particle are presumed to cause turbid in liquid media, and that has a linear relationship that can be utilized on the cell counting. The method for the term of clouded liquid form is the measurement based on the reflection and scattered of light, i.e., the turbidimetry. Knowledge attainment of microbial cell counting should be answered how many Nephelometric Turbidity Unit of the one cell. We work to obtain a turbidity model of cells in water-based media for the estimation of cell numbers. This paper aims to construct the computational structure on the turbidity modeling of Saccharomyces cerevisiae in pure water and to test a consistent model in liquid nutrients medium. The modeling was performed in systematized stages of the diagnostic-analysis-test; the regression assurances, the simulation of the lowest error, and the coefficient value itself of turbidity factors. We constructed an optimal analysis and diagnosis to create a computational structure of cell turbidity modeling. The measurement and stopping bivariate elimination of the simulation is a subsystem of the algorithm of obtaining and testing models. The first mathematics model is a standard curve on turbidimetry, and the second, turbidity mathematics model of cell growth in liquid nutrients medium. Both models have an equal coefficient of cell turbidity. The turbidity coefficient of cell growth time interval in the carbonyl diamide - potato dextrose broth is significant
Genetic Variation Based on RAPD Profiling and Production Loss of Cayenne Pepper due to Periodic Flooding
Get PDFCayenne pepper is known as a sensitive plant to water stress, either drought or flooding. However, not many studies on the plant's response to the naturally occurring periodic flooding have been reported to date. This study aimed to determine the agronomic and genetic response of cayenne pepper against periodic flooding and find whether RAPD profile reflects periodic flooding endurance. Three cultivars of cayenne pepper: Cakra Hijau (CH); Mhanu XR (M); and Sret (S) were used. Plants were treated with periodic flooding P0 (one day of flooding followed by two days of drainage), P1 (2 x P0), and P2 (3 x P0), and C as control. A completely randomized design was used for the experiment, and the data obtained were analyzed statistically. Plant height and the number of fruits between the control and every flooding treated plant were significantly different, indicating that periodic flooding caused the delay of stem growth and decreased fruit number of all cultivars. The number of branches was influenced significantly by periodic flooding. In contrast, the plant survival rate showed no significant difference among all treatments. The higher the periodic flooding, the higher the risk of plant death and increased risk of production loss. Jaccard’s clustering on RAPD profiling indicated that the group was developed based on cultivar more than periodic flooding. It was concluded that CH differed from others and had better endurance against periodic flooding, made it a right candidate for a breeding program