The Existence of Affine Structures on the Borel Subalgebra of Dimension 6

The notion of affine structures arises in many fields of mathematics, including convex homogeneous cones, vertex algebras, and affine manifolds. On the other hand, it is well known that Frobenius Lie algebras correspond to the research of homogeneous domains. Moreover, there are 16 isomorphism classes of 6-dimensional Frobenius Lie algebras over an algebraically closed field. The research studied the affine structures for the 6-dimensional Borel subalgebra of a simple Lie algebra. The Borel subalgebra was isomorphic to the first class of Csikós and Verhóczki’s classification of the Frobenius Lie algebras of dimension 6 over an algebraically closed field. The main purpose was to prove that the Borel subalgebra of dimension 6 was equipped with incomplete affine structures. To achieve the purpose, the axiomatic method was considered by studying some important notions corresponding to affine structures and their completeness, Borel subalgebras, and Frobenius Lie algebras. A chosen Frobenius functional of the Borel subalgebra helped to determine the affine structure formulas well. The result shows that the Borel subalgebra of dimension 6 has affine structures which are not complete. Furthermore, the research also gives explicit formulas of affine structures. For future research, another isomorphism class of 6-dimensional Frobenius Lie algebra still needs to be investigated whether it has complete affine structures or not.

Enterprise Resource Planning Modification: A Literature Review

The current low success level of Enterprise Resource Planning (ERP) implementation stimulates the rise of research to find the critical success factor of it. One of the challenges of ERP implementation is to find a ‘fit’ between business and system requirements. It is claimed that standardizing business processes to follow the ERP system will positively impact organizations to follow the best practice process. However, there is another challenge that organization should not reengineer their business process to fit the ERP system, but rather modify or customize the ERP system to match their business process. This belief argues that standardizing business processes is not the right solution that applies to every organization since it can degrade an organization’s competitive advantages. Based on the background, the research aimed to construct a comprehensive review to succeed in implementing an ERP system, particularly on ERP modification, using a systematic literature review method. It was done by collecting and analyzing scientific publications related to ERP critical success factors with special attention to system modification. The literature review results in a comprehensive explanation of ERP modification. It includes elaborating on different types of misfit and customization to cultivate the understanding of ERP modification, a flowchart to analyze misfit to help the organization to evaluate modification requests, and critical success factors of modified ERP implementation.

Overall Equipment Effectiveness to Increase Productivity of Injection Molding Machine: A Case Study in Plastic Manufacturing Industry

In line with the unstable market conditions in Indonesia, especially the plastic manufacturing industry, the companies need to be well prepared to survive. There were two research goals. First, it was to find out why the Overall Equipment Effectiveness (OEE) rate at the company did not meet the expected standard. Second, it was to determine what improvement should be made to increase the OEE for the machine. The research applied a case study in one of the plastic manufacturing industries located in Tangerang, Indonesia. It focused on the performance of Toshiba injection molding machine number 42/IS 450 GSW. The analysis was performed by applying Failure Mode and Effect Analysis (FMEA) with support from other tools such as Pareto chart, Cause and Effect Diagram (CED), and six big losses. By following the whole framework of the research, it finds causes of why the OEE does not meet the target. Then, from the results, it can be concluded that the implementation of the methods has a positive impact on the company. The OEE rate increases from an average of 26,43% to 78,87%. It means the OEE rate has achieved the company target of 75%.

Improving Ballastless Track Quality Using Project Quality Management and SmartPLS

Transportation is still a significant problem in Indonesia. Indonesians prefer to use private vehicles for daily mobility purposes because public transportation lacks safety and comfort and has a longer trip duration. This issue causes congestion and air pollution problems. Hence, sustainable railbased public transportation is recommended. Light Rail Transit (LRT) tends to be congestion-free and has a relatively shorter travel time with a large passenger capacity. Most LRT track constructions use the ballastless track. However, this track construction is still new in Indonesia. The research aimed to determine the most important factors in improving ballastless track construction performance on LRT. The research referred to the existing LRT construction in Indonesia using Lean Construction (LC) and Project Quality Management (PQM) approaches. Statistical science approach with SmartPLS software was also used in data processing and modeling the relationship between variables. The research was conducted by distributing questionnaires to determine the most important factors in improving the quality of ballastless tracks with variables and indicators extracted from LC and PQM methods. From five tested hypotheses, only one hypothesis is accepted. Quality control has a positive effect on track quality. It is also found that quality control becomes the most important variable in improving ballastless track quality.

Pricing of Medical Instrument Products for Domestic Production through Investment Feasibility Analysis

Pricing products is an important factor to penetrate the Indonesian market successfully. Since Indonesia’s medical device products market has more than 90% import, local production companies must be competitive in price. The current pricing approach relies on the cost of sold goods, profit margin, and cost. Hence, a new pricing model is needed. The price from the new model must be better than the current price from the conventional pricing approach. The research aimed to formulate a pricing model for local medical device products that the market could accept and provide a framework model in local production pricing using investment feasibility analysis. The research used mathematical models, engineering economics, and pricing frameworks to optimize product prices from a local company (PT Enesser Mitra Berkah). The studied object was the domestic production of Anesthesia A8500. The research has several findings. First, the Break-Even Point (BEP) (X2) is an alternative standpoint to determine the price in a local production investment for medical device products. Second, the production company can consider the market price (X3). The research develops a simple mathematical model of X3 > Y2 = X2 + Ct > X1 (Y2 = new price, X1= cost of sold goods, Ct = profit and cost). The result provides the pricing framework model as a new approach for developing a medical device product price when the company initiates new local production.

Mathematical Modeling on the Control of Hunting Problems

Modeling a natural phenomenon or the action mechanism of a tool is often done in science and technology. Observations through computer simulations cost less relatively. In the research, a bullet control model moving towards the target was explored. The research aimed to try to simulate the trajectory of the bullet that could be controlled in hunting. To model a controlled bullet, the Dubins model was used. Then, the used approach was control theory. The optimal trajectory and control for bullets were designed using the Pontryagin Maximum Principle. The results show that with this principle and the dynamic system of the bullet, a system of differential equations and adjoining is obtained. The fundamental problem arises because the bullet dynamics model in the form of a differential equation system has initial and final requirements. However, the adjoint matching system has no conditions at all. This problem is solved by using numerical methods. In addition, the research proves the convergence of the calculation results with the required results. The track simulation results are also reported at the end of the research to ensure a successful control design. From the simulation results, the presented method with its convergence has successfully solved the problem of bullet control.

Volatility Fitting Performance of QGARCH(1,1) Model with Student-t, GED, and SGED Distributions

The research had two objectives. First, it compared the performance of the Generalized Autoregressive Conditional Heteroscedasticity (1,1) (GARCH) and Quadratic GARCH (1,1) (QGARCH)) models based on the fitting to real data sets. The model assumed that return error follows four different distributions: Normal (Gaussian), Student-t, General Error Distribution (GED), and Skew GED (SGED). Maximum likelihood estimation was usually employed in estimating the GARCH model, but it might not be easily applied to more complicated ones. Second, it provided two ways to evaluate the considered models. The models were estimated using the Generalized Reduced Gradient (GRG) Non-Linear method in Excel’s Solver and the Adaptive Random Walk Metropolis (ARWM) in the Scilab program. The real data in the empirical study were Financial Times Stock Exchange Milano Italia Borsa (FTSEMIB) and Stoxx Europe 600 indices over the daily period from January 2000 to December 2017 to test the conditional variance process and see whether the estimation methods could adapt to the complicated models. The analysis shows that GRG Non-Linear in Excel’s Solver and ARWM methods have close results. It indicates a good estimation ability. Based on the Akaike Information Criterion (AIC), the QGARCH(1,1) model provides a better fitting than the GARCH(1,1) model on each distribution specification. Overall, the QGARCH(1,1) with SGED distribution best fits both data.

Forecasting and Mapping Coffee Borer Beetle Attacks Using GSTAR-SUR Kriging and GSTARX-SUR Kriging Models

The research aimed to use Generalized Space Time Autoregressive (GSTAR) and GSTARX modeling with the Seemingly Unrelated Regression (SUR) approach and combine them with the Kriging interpolation technique in an unobserved location. The case study was coffee borer beetle forecasting in Probolinggo Regency, East Java, Indonesia, with Watupanjang Village as the unobserved location. The results show that GSTAR-SUR Kriging and GSTARX-SUR Kriging models can predict coffee borer beetle attacks in unobserved areas with high accuracy. It is indicated by the Mean Absolute Percentage Error (MAPE) values of less than 10%. The addition of exogenous variables (rainfall) into the model is proven to improve the accuracy of the model. The Root-Mean-Square Error (RMSE) value of the GSTARX-SUR Kriging model is smaller than the GSTAR-SUR Kriging model. The structure of the model produced from the research, GSTARX-SUR (1,[1,12])(10,0,0), can be used as a reference in modeling coffee borer beetle attacks in other regencies. Map of forecasting coffee borer beetle attack shows that the spread of coffee borer beetle attack is spatial clustering with the attack center located in the eastern region of Probolinggo Regency.

Finding Biomarkers from a High-Dimensional Imbalanced Dataset Using the Hybrid Method of Random Undersampling and Lasso

The research conducted undersampling and gene selection as a starting point for cancer classification in gene expression datasets with a high-dimensional and imbalanced class. It investigated whether implementing undersampling before gene selection gave better results than without implementing undersampling. The used undersampling method was Random Undersampling (RUS), and for gene selection, it was Lasso. Then, the selected genes based on theory were validated. To explore the effectiveness of applying RUS before gene selection, the researchers used two gene expression datasets. Both of the datasets consisted of two classes, 1.545 observations and 10.935 genes, but had a different imbalance ratio. The results show that the proposed gene selection methods, namely Lasso and RUS + Lasso, can produce several important biomarkers, and the obtained model has high accuracy. However, the model is complicated since it involves too many genes. It also finds that undersampling is not affected when it is implemented in a less imbalanced class. Meanwhile, when the dataset is highly imbalanced, undersampling can remove a lot of information from the majority class. Nevertheless, the effectiveness of undersampling remains unclear. Simulation studies can be carried out in the next research to investigate when undersampling should be implemented.

The Effect Analysis of Braden Scale on Pressure Ulcer in Community-Dwelling Older Adults

The research aimed to analyze the Braden Scale on the incidence of compressive wounds in elderly people who lived in homes, whether they were or not under the supervision of health workers. The research was analytic with a cross-sectional study. With the purposive sampling technique, the data collection was carried out from several areas in Bandung from October to November 2017. Moreover, the analysis used was multiple regression to see the effect of the Braden Scale on pressure ulcers. The multiple linear regression model was also tested. The results show that 48,22% of pressure ulcer factors can be influenced by sensory perception, humidity, activity, mobility, nutrition, and friction. Sensory perception, activity and friction have significant influence on incidence of pressure ulcers. Meanwhile, the humidity, mobility, and nutrition do not significantly influence it.