KESTABILAN MODEL PETRI NET DARI SISTEM PEMBAYARAN TAGIHAN LISTRIK PT. PLN (Persero) RAYON AMBON TIMUR

This research develops the previous one of the electricity bill payment system in PT. PLN (Persero) Rayon East Ambon modelled by Petri Net. The previous researcher had built the Petri Net model of this payment system. In this research, we determine whether the system modelled before is stable or not. This stability will be analysed using the Lyapunov stability theory related to the Petri Net. The result shows that the electricity bill payment system modelled by Petri Net before is not stable but can be stabilized. This can be caused there is a transition which is ‘always enable’ in the modelled which is built. This research also performs a stable model of Petri Net that represents the electricity bill payment system with deleting the ‘always enable’ transition

PENDUGAAN PARAMETER MODEl DISTRIBUTED LAG POLA POLINOMIAL MENGGUNAKAN METODE ALMON

The distributed lag model is a regression model that describes the relationship between the dependent variable of a given period and the independent variables of a certain or previous periods. The model can be used to determine the impact of the independent variable to dependent variables over time and forecast time series data for the next periods. There are two forms of distributed lag model that have been widely proposed in the estimation of distributed lag regression model. The first form is proposed by Koyck and the second form by Almon. This paper aims to apply the Almon model to examine the effect of the ratio of BOPO (Operating Cost and Operating Income) to the ROA (Return on Asset) of a government bank based on quarterly data, to estimate its parameters, to examine the feasibility of the model, and to predict the next quarter. Results shows that distributed lag model is = 10.110 - 0.078 + 0.015 + 0.026 – 0.045 with Yt is ROA, and Xt is the ratio BOPO on the 1st quarter until the previous 3 quarters. The model is quite good according to the determination coefficient that is 0.75, no autocorrelation in the model, t test and F test are also significant. Based on the model, the value of ROA ratio next quarter predicted 4.63%. The decrease in profitability ROA ratio is due to an increase in interest expense while interest income can not compensate

DESAIN KONTROL PENGOBATAN PADA MODEL SIRD UNTUK PENYEBARAN VIRUS COVID-19 MENGGUNAKAN BACKSTEPPING

In this article, we present a control design on a SIRD model with treatment in infected individuals. The SIRD model with treatment is obtained from literature study and the parameter model is obtained from covid-19 daily case in the Riau province using the Particle Swarm Optimization method. The control design is carried out based on the backstepping method combined with feedback linearization based on input and output (IOFL). The SIRD model which is a nonlinear system will be transformed into a normal form using IOFL. Each variable is then stabilized Lyapunov using virtual control which at the same time generates a new state variable. This stage will be carried out iteratively until the last state variable is stabilized using a real control function. This control function is then applied to the SIRD model using the inverse of IOFL transformation. The simulation results compared with the Pontryagin Minimum Principle (PMP) method show that by selecting the appropriate control parameters, backstepping obtains better control performance which is a smaller number of infected populations.

MASALAH EIGEN DAN EIGENMODE MATRIKS ATAS ALJABAR MIN-PLUS

Eigen problems and eigenmode are important components related to square matrices. In max-plus algebra, a square matrix can be represented in the form of a graph called a communication graph. The communication graph can be strongly connected graph and a not strongly connected graph. The representation matrix of a strongly connected graph is called an irreducible matrix, while the representation matrix of a graph that is not strongly connected is called a reduced matrix. The purpose of this research is set the steps to determine the eigenvalues and eigenvectors of the irreducible matrix over min-plus algebra and also eigenmode of the regular reduced matrix over min-plus algebra. Min-plus algebra has an ispmorphic structure with max-plus algebra. Therefore, eigen problems and eigenmode matrices over min-plus algebra can be determined based on the theory of eigenvalues, eigenvectors and eigenmode matrices over max-plus algebra. The results of this research obtained steps to determine the eigenvalues and eigenvectors of the irreducible matrix over min-plus algebra and eigenmode algorithm of the regular reduced matrix over min-plus algebra

DETEKSI PENYALAHGUNAAN NARKOBA DENGAN METODE TWIN BOUNDED SVM

Twin Bounded SVM (TB-SVM) is an improvement of the Twin SVM method and has advantages in classification problems compared to standard SVM. In this research, linear TB-SVM and nonlinear TB-SVM methods will be applied to detect drug use based on 23 symptoms experienced. The training and testing data is divided into three partition data schemes (60/40 scheme, 70/30 scheme and 80/20 scheme) in order to determine the best level of accuracy that can be obtained. The test results show that the nonlinear TB-SVM with the RBF kernel has a better accuracy rate than the linear TB-SVM, that is 80% at 60/40 scheme, 90% at 70/30 scheme, and 95% at 80/20 scheme.

ANALISIS CREDIT SCORING TERHADAP STATUS PEMBAYARAN BARANG ELEKTRONIK DAN FURNITURE MENGGUNAKAN BOOTSTRAP AGGREGATING K-NEAREST NEIGHBOR

Classification is the process of grouping objects that have the same characteristics into several categories. This study applies a combination of classification algorithms, namely Bootstrap Aggregating K-Nearest Neighbor in credit scoring analysis. The aim is to classify the credit payment status of electronic goods and furniture at PT KB Finansia Multi Finance in 2020 and determine the level of accuracy produced. Credit payment status is grouped into 2 categories, namely smoothly and not smoothly. There are 7 independent variables that are used to describe the characteristics of the debtor, namely age, number of dependents, length of stay, years of service, income, amount of payment, and payment period. The application of the classification algorithm at the credit scoring analysis is expected to assist creditors in making decisions to accept or reject credit applications from prospective debtors. The results showed that the accuracy obtained from the Bootstrap Aggregating K-Nearest Neighbor algorithm with a proportion of 90:10, m=80%, C=73, and K=5 was the best, which was 92.308%.

PERMODELAN POLA PERENCANAAN KEUANGAN BERDASARKAN STATUS PERNIKAHAN

A Marital status at community can make an impact on financial management. The purpose of this study was to analyze financial planning based on marital status with the variables of financial attitude, financial behavior, and financial literacy towards people who live in Sumbawa. The data were analyzed using Structural Equation Modeling Partial Least Square (SEM-PLS) through smartPLS version 3.0 software. The results of the analysis in this study indicate that (1) financial attitude has a significant effect on financial behavior both based on married and unmarried status, (2) financial attitude has a significant effect on financial literacy both based on married and unmarried status, (3) financial attitude has an effect significant on financial planning based on both married and unmarried status, (4) financial behavior has no significant effect on financial literacy both based on married and unmarried status, (5) financial behavior has no significant effect on financial planning both based on married and unmarried status, (6) financial literacy has no significant effect on financial planning based on both married and unmarried status, and (7) There is no difference in financial planning based on marital status

MODEL SUSCEPTIBLE VACCINATED INFECTED TREATMENT RECOVERED DENGAN KASUS KAMBUH DAN PENERAPANNYA (KASUS TUBERKULOSIS DI INDONESIA)

Tuberculosis (TB) is caused by Mycobacterium tuberculosis. BCG vaccination is prevention the spread of TB in Indonesia. Individuals who are vaccinated (vaccinated) are healthy individuals and susceptible to infection. If a person is infected with TB then curative efforts through DOTS treatment must be carried out in order to recover. In the case of TB, recovered individuals may relapse. The susceptible vaccinated infected treatment recovered ( ) model with relapse cases is able to represent the spread of TB. This study aims to build the model with relapse, apply it to TB in Indonesia using data from 2004-2019, and interpret the results of implementing the TB-free target in Indonesia in 2050. The model is nonlinear first-order differential equations. The graph of the pattern of TB spread shows that all groups of individuals are experiencing an uptrend and it is predicted that the TB-free target has not been achieved. However, if the coverage of BCG vaccination and DOTS treatment is increased, contacts with TB sufferers are reduced, and relapse cases are reduced, it is predicted that the TB-free target will be achieved.

PERBANDINGAN PRINCIPAL AXIS FACTORING DAN MAXIMUM LIKELIHOOD DALAM MENENTUKAN FAKTOR DOMINAN YANG MEMPENGARUHI PEMBELAJARAN NAHWU SHOROF (STUDI KASUS PONDOK PESANTREN ROUDLOTUL MUTA’ALLIMIN PUTRI)

This study discusses the dominant factors that influence the success of learning nahwu shorof at the Roudlotul Mutaalimin Islamic Boarding School for the daughter of Minggirsari Village. Determining the dominant factor is done to maximize the quality of education in the boarding school, so that the interest of prospective students is increasing. In this study, two extraction methods were compared, namely the Principal Axis Factoring and Maximum Likelihood methods. There are 13 variables that affect the success of nahwu shorof learning, namely the natural environment (P1), social environment (P23), curriculum (P49), madrasa program (P1012), facilities and facilities (P1315), teaching staff (P1619), condition of physiological (P2021), condition of the five senses (P22), interest in learning (P2325), intelligence of students (P26), student talent (P27), motivation of students (P28), cognitive ability (P2930). The purpose of this study, namely to determine the most appropriate extraction method used in the analysis. The result of this study is the Maximum Likelihood method which is more appropriate than the Principal Axis Factoring method, because it has a smaller RMSE (Root Mean Squared Error) value.