Ontology reasoning using SPARQL query: A case study of e-learning usage

The involvement of learning pedagogy towards implementation of e-learning contribute to the additional values, and it is assign as a benchmark when the investigation and evaluation will carry out. The results obtained later believed would be fit to the domain problem.The results might provide instructional theories including recommendation after reasoning that can be used to improve the quality of teaching and learning in the virtual classroom. Ontology as formal conceptualization has been chosen as research methodology. Ontology conceptualization helps to illustrate the e-learning usage including activities and actions, likewise learning pedagogy in the form of concepts, class, relationships and instances. The ontology constructed in this paper is used in conjunction with the SPARQL rules, which are designed to test the reasoning ability of ontology. Reasoning results should be able to describe the knowledge contained in ontology, as well the facts on it. The SPARQL rules contains triplets to verify if the students are actively engaged in a meaningful way towards e-learning usage. The backward engine is optimized to store the facts obtained from queries. Development of ontology knowledge based and reasoning rules with SPARQL queries allow to contribute a sustainable competitive advantages regarding the e-learning utilization. Eventually, this research produced a learning ontology with reasoning capability to get meaningful information

Identifikasi Potensi Akuifer Berdasarkan Metode Geolistrik Tahanan Jenis pada Daerah Krisis Air Bersih di Kota Semarang

Semarang city has a unique geological rock formations constituent layers in each region. The uniqueness of the identification of the presence of roundwater show that is different. Groundwater reserves in fulfilling the water requipments decreasing due to population growth, industrial growth and infrastructure development. This study aims to identify potential of aquifer to know the type of lithology layers, thickness and depth. The method used in this research is a geoelectric resistivity Schlumberger configurations with measurement points are Cangkiran, Cepoko, Ngadirgo, Gunungpati, Pakintelan, Pesantren, Tandang and Rowosari. The results suggest the potential for aquifer interpretations are based on the value of resistivity 19,6 Ωm – 92,5 Ωm with lithology as a sandstone. The aquifer grouped into the deep aquifer and the shallow aquifer. Deep aquifer has range of depth between 50-100 meters on point CA-3, CA-4, CE-1, CE-2, NG-2 and TA-1. Shallow aquifer has range of depth between 10-4 meters on point of GP, NG1, PA, PE and RO

Penerapan Metode Klasifikasi Support Vector Machine (Svm) Pada Data Akreditasi Sekolah Dasar (SD) Di Kabupaten Magelang

Accreditation is the recognition of an educational institution given by a competent authority, that is Badan Akreditasi Nasional Sekolah/Madrasah (BAN - S/M) after it is assessed that the institution has met the eight components of the accreditation assessment. An elementary school, as one of the compulsory basic education, should have the status of accreditation to ensure the quality of education. This study aimed to apply the classification method Support Vector Machine (SVM) on the data accreditation SD in Magelang. Support Vector Machine (SVM) is a method that can be used as a predictive classification by using the concept of searching hyperplane (separator functions) that can separate the data according to the class. SVM using the kernel trick for non-linear problems which can transform data into a high dimensional space using a kernel function, so that the data can be classified linearly. The results of this study indicate that the prediction accuracy of SVM classification using Gaussian kernel function RBF is 93.902%. It is calculated from 77 of 82 elementary schools that are classified correctly with the original classes

Uji Aktivitas Imunomodulator Fermentasi Teh Rosela Jamur Kombucha Terhadap Proliferasi Sel Limfosit Mencit Galur Balb/c Secara in Vitro

Recently, some research showed that there is an immunomodulator effect in the fermentation of Rosella kombucha mushroom tea and it can be caused by flavonoid and organic acid. The purpose of this research was to show the activity of immunomodulator Rosella kombucha mushroom tea to against the proliferation of lymphocyte cells of Balb/C mice in vitro and to show the dose and length of fermentation that induces highest immunomodulator activity. Kombucha mushroom was fermented for 5 days, 10 days and also 15 days with boiled Rosella tea, water and sugar. The yield of fermentation in the concentration of 6,25; 12,5; 25; 50 and 100 µg/mL were tested on lymphocyte cells proliferation by the MTT Assay. The OD (Optical Density) data obtained was statistically analyzed by nonparametric Friedman test and continuoused by Mann-Whitney test. The result of this research showed that the fermentation of Rosella kombucha mushroom tea has an immunostimulatory activity on lymphocyte cells proliferation with the concentration 6,25; 12,5 and 25 µg/mL in the 10 days and the highest immunostimulatory activity showed by the concentration 25 µg/mL and 10 days of fermentation time

Puskesmas Stelsel Berdinding Botol: Solusi Inovatif Meningkatkan Akses Pelayanan Kesehatan di Daerah Endemik Malaria

Some areas of Indonesia are malaria endemic areas with the National Annual Parasite Incidence (API) is 2.4%. Inequality in the number of puskesmas is one of the causes of high rates of malaria transmission. Solution of this problem is to build new puskesmas in that areas. The costs of this construction can be reduced by utilizing waste plastic bottles to replace a brick as the wall of puskesmas. Next, the bottle walled puskesmas will be built in stelsel system in order to improve access to health services in malaria endemic areas. Thus, the rate of malaria transmission can be suppressed

Applied clustering analysis for grouping behaviour of e-learning usage based on meaningful learning characteristics

One of the critical success factors of e-learning is positive interest of students towards e-learning. The majority of activities of current e-learning usage are viewing and downloading. These activities are not meaningful with regard to enhancing learning quality. Due to that, the aim of this paper is to analyze students’ usage based on meaningful learning characteristics by clustering students’ activities and actions during online learning. We first define meaningful learning characteristics (as those which are active, authentic, cooperative, collaborative, and intentional) and associate these with e-learning activities and actions. Then, we analyze the students’ e-learning usage and define the cluster of student’s meaningful characteristics by using the K-Means cluster method. A case study has been conducted based on the e-learning log files of 37 students on Computational Intelligence Course at the Software Engineering Department, Universiti Teknologi Malaysia. The result of this clustering enables us to determine the students with high ratings on these meaningful activities and actions during online learning. We found out that students with high hits on add, update, and edit are included in the high cluster group. On the contrary, students with high hits on the view actions for all e-learning activities are included in the low cluster group. This result may assist instructors while preparing the strategy of computer usage for education, in terms of providing a greater variety of learning activities, which is applicable for any courses

Modeling the Size Distribution and Chemical Composition of Secondary Organic Aerosols during the Reactive Uptake of Isoprene-Derived Epoxydiols under Low-Humidity Condition

Reactive uptake of isoprene epoxydiols (IEPOX), which are isoprene oxidation products, onto acidic sulfate aerosols is recognized to be an important mechanism for the formation of isoprene-derived secondary organic aerosol (SOA). While a mechanistic understanding of IEPOX-SOA formation exists, several processes affecting their formation remain uncertain. Evaluating mechanistic IEPOX-SOA models with controlled laboratory experiments under longer atmospherically relevant time scales is critical. Here, we implement our latest understanding of IEPOX-SOA formation within a box model to simulate the measured reactive uptake of IEPOX on polydisperse ammonium bisulfate seed aerosols within an environmental Teflon chamber. The model is evaluated with single-particle measurements of size distribution, volume, density, and composition of aerosols due to IEPOX-SOA formation at time scales of hours. We find that the model can simulate the growth of particles due to IEPOX multiphase chemistry, as reflected in increases of the mean particle size and volume concentrations, and a shift of the number size distribution to larger sizes. The model also predicts the observed evolution of particle number mean diameter and total volume concentrations at the end of the experiment. We show that in addition to the self-limiting effects of IEPOX-SOA coatings, the mass accommodation coefficient of IEPOX and accounting for the molar balance between inorganic and organic sulfate are important parameters governing the modeling of the IEPOX-SOA formation. Thus, models which do not account for the molar sulfate balance and/or diffusion limitations within IEPOX-SOA coatings are likely to predict IEPOX-SOA formation too high