PEMBINAAN PESERTA DIDIK DALAM IMPLEMENTASI KEBIJAKAN SISTEM ZONASI DI SMAN 1 SRENGAT

New Student Admission, hereinafter abbreviated as PPDB, is stated in the Regulation of the Minister of Education and Culture of the Republic of Indonesia Number 51 of 2018, carried out based on the principles of non-discrimination, objective, transparent, accountable and fair. One of them is implemented with the PPDB zoning system policy. The New Student Admission (PPDB) zoning system raises a number of impacts. In practice, SMAN 1 Srengat has encountered several effects that have arisen since the implementation of the PPDB zoning system. Among them are the random input of students and the low enthusiasm for learning in students who are accepted through the zoning route without any selection with qualifications based on the acquisition of learning outcomes at the previous level. This research tries to review overcoming the problems of the teaching and learning process after the implementation of the zoning system PPDB policy at SMAN 1 Srengat. So that it can be seen that, in response to the implementation of the PPDB policy of the zoning system which generates random input and raises problems in the spirit of learning, SMAN 1 Srengat implements innovation and development of transformative and comprehensive student coaching.

A stochastic matching model on hypergraphs

Motivated by applications to a wide range of areas, including assemble-to-order systems, operations scheduling, healthcare systems, and the collaborative economy, we study a stochastic matching model on hypergraphs, extending the model of Mairesse and Moyal (J. Appl. Prob.53, 2016) to the case of hypergraphical (rather than graphical) matching structures. We address a discrete-event system under a random input of single items, simply using the system as an interface to be matched in groups of two or more. We primarily study the stability of this model, for various hypergraph geometries.

Random Integer Lattice Generation via the Hermite Normal Form

Lattices used in cryptography are integer lattices. Defining and generating a “random integer lattice” are interesting topics. A generation algorithm for a random integer lattice can be used to serve as a random input of all the lattice algorithms. In this paper, we recall the definition of the random integer lattice given by G. Hu et al. and present an improved generation algorithm for it via the Hermite normal form. It can be proven that with probability ≥0.99, this algorithm outputs an n-dim random integer lattice within O(n2) operations.

Poisson limit of bumping routes in the Robinson–Schensted correspondence

We consider the Robinson–Schensted–Knuth algorithm applied to a random input and investigate the shape of the bumping route (in the vicinity of the y-axis) when a specified number is inserted into a large Plancherel-distributed random tableau. We show that after a projective change of the coordinate system the bumping route converges in distribution to the Poisson process.

Improved MSHA-1 algorithm with mixing method

Abstract—Recently, a Modified SHA-1 (MSHA-1) has been proposed and claimed to have better security performance over SHA-1. However, the study showed that MSHA-1 hashing time performance was slower. In this research, an improved version of MSHA-1 was analyzed using avalanche effect and hashing time as performance measure applying 160-bit output and the mixing method to improve the diffusion rate. The diffusion results showed the improvement in the avalanche effect of the improved MSHA-1 algorithm by 51.88%, which is higher than the 50% standard to be considered secured. MSHA-1 attained 50.53% avalanche effect while SHA1 achieved only 47.03% thereby showing that the improved MSHA-1 performed better security performance by having an improvement of 9.00% over the original SHA-1 and 3.00% over MSHA-1. The improvement was also tested using 500 random string for ten trials. The improved MSHA-1 has better hashing time performance as indicated by 31.03% improvement. Hash test program has been used to test the effectiveness of the algorithm by producing 1000 hashes from random input strings and showed zero (0) duplicate hashes.

Comparison of quadrature and regression based generalized polynomial chaos expansions for structural acoustics

This work performs a direct comparison between generalized polynomial chaos (GPC) expansion techniques applied to structural acoustic problems. Broadly, the GPC techniques are grouped in two categories: , where the stochastic sampling is predetermined according to a quadrature rule; and , where an arbitrary selection of points is used as long as they are a representative sample of the random input. As a baseline comparison, Monte Carlo type simulations are also performed although they take many more sampling points. The test problems considered include both canonical and more applied cases that exemplify the features and types of calculations commonly arising in vibrations and acoustics. A range of different numbers of random input variables are considered. The primary point of comparison between the methods is the number of sampling points they require to generate an accurate GPC expansion. This is due to the general consideration that the most expensive part of a GPC analysis is evaluating the deterministic problem of interest; thus the method with the fewest sampling points will often be the fastest. Accuracy of each GPC expansion is judged using several metrics including basic statistical moments as well as features of the actual reconstructed probability density function.

Inference of genetic networks using random forests: performance improvement using a new variable importance measure

Background: Among the various methods so far proposed for genetic network inference, this study focuses on the random-forest-based methods. Confidence values are assigned to all of the candidate regulations when taking the random-forest-based approach. To our knowledge, all of the random-forest-based methods make the assignments using the standard variable importance measure defined in tree-based machine learning techniques. We think however that this measure has drawbacks in the inference of genetic networks. Results: In this study we therefore propose an alternative measure, what we call ``the random-input variable importance measure,'' and design a new inference method that uses the proposed measure in place of the standard measure in the existing random-forest-based inference method. We show, through numerical experiments, that the use of the random-input variable importance measure improves the performance of the existing random-forest-based inference method by as much as 45.5% with respect to the area under the recall-precision curve (AURPC). Conclusion: This study proposed the random-input variable importance measure for the inference of genetic networks. The use of our measure improved the performance of the random-forest-based inference method. In this study, we checked the performance of the proposed measure only on several genetic network inference problems. However, the experimental results suggest that the proposed measure will work well in other applications of random forests.

Directed Data-Processing Inequalities for Systems with Feedback

We present novel data-processing inequalities relating the mutual information and the directed information in systems with feedback. The internal deterministic blocks within such systems are restricted only to be causal mappings, but are allowed to be non-linear and time varying, and randomized by their own external random input, can yield any stochastic mapping. These randomized blocks can for example represent source encoders, decoders, or even communication channels. Moreover, the involved signals can be arbitrarily distributed. Our first main result relates mutual and directed information and can be interpreted as a law of conservation of information flow. Our second main result is a pair of data-processing inequalities (one the conditional version of the other) between nested pairs of random sequences entirely within the closed loop. Our third main result introduces and characterizes the notion of in-the-loop (ITL) transmission rate for channel coding scenarios in which the messages are internal to the loop. Interestingly, in this case the conventional notions of transmission rate associated with the entropy of the messages and of channel capacity based on maximizing the mutual information between the messages and the output turn out to be inadequate. Instead, as we show, the ITL transmission rate is the unique notion of rate for which a channel code attains zero error probability if and only if such an ITL rate does not exceed the corresponding directed information rate from messages to decoded messages. We apply our data-processing inequalities to show that the supremum of achievable (in the usual channel coding sense) ITL transmission rates is upper bounded by the supremum of the directed information rate across the communication channel. Moreover, we present an example in which this upper bound is attained. Finally, we further illustrate the applicability of our results by discussing how they make possible the generalization of two fundamental inequalities known in networked control literature.

Design and Comparison of Strategies for Level Control in a Nonlinear Tank

In this work, a study of the water level control of an inverted conical tank system is presented. This type of tank has highly nonlinear mathematical and dynamic characteristics. Four control strategies are designed, applied, and compared, namely classical Proportional–Integral–Derivative (PID), Gain Scheduling (GS), Internal Model Control (IMC), and Fuzzy Logic (FL). To determine which of the designed control strategies are the most suitable for an inverted conical tank, a comparative study of the behavior of the system is carried out. With this purpose, and considering situations much closer to reality, a variety of scenarios, such as step responses, random input disturbances, and momentary load disturbances, are conducted. Additionally, performance indexes (error- and statistics-based) are calculated to assess the system’s response.