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JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI

jmsk
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Published by Universitas Hasanuddin

ISSN : 18581382 EISSN : 26148811 DOI : -

Core Subject : Education,

Mathematics

Jurnal ini mempublikasikan paper-paper original hasil-hasil penelitian dibidang Matematika, Statistika dan Komputasi Matematika.

Arjuna Subject : -

Articles 496 Documents

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Analysis of User Sentiment of Twitter to Draft KUHP Nawang Indah Cahyaningrum; Danty Welmin Yoshida Fatima; Wisnu Adi Kusuma; Sekar Ayu Ramadhani; Muhammad Rizqi Destanto; Rani Nooraeni
Jurnal Matematika, Statistika dan Komputasi Vol. 16 No. 3 (2020): JMSK, MAY, 2020
Publisher : Department of Mathematics, Hasanuddin University

Twitter is one of social media where its user can share many responses for a phenomenon through a tweet. This research used 5000 tweets from Twitter users in Bahasa Indonesia with keyword “RUU KUHP(Draft Law of KUHP)” from 16th of September until 22nd of September 2019. That tweets were processed using Rstudio software with sentiment analysis that is one of Text Mining methods. This research aims to classify Twitter users’ responses to RUU KUHP to be negative sentiment, poisitive negative, and neutral. Also, this research also aims to know about topics’ frequencies that were related to RUU KUHP through visualization with bar plot and also wordcloud. This research also aims to know words that are associated with the most frequent words. Form this research, can be known that Twitter users’ responses to RUU KUHP tend to have neutral sentiment that means they did not take side between agreeing or disagreeing. From this research, also can be known about 10 most frequent words, there are kpk, tunda, dpr, pasal, kesal, jokowi, presiden, masuk, ya, and sahkan. Beside that, can be known the other words that are associated with them and also their probability.

Bayesian inference for Pareto distribution with prior conjugate and prior non conjugate Ferra YANUAR; Cici Saputri
Jurnal Matematika, Statistika dan Komputasi Vol. 16 No. 3 (2020): JMSK, MAY, 2020
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/jmsk.v16i3.8019

The purpose of this study is to determine the best estimator for estimating the shape parameters of the Pareto distribution with the known scale parameter. Estimation of these parameters is done by using the Gamma distribution as the prior distribution of the conjugate and the Uniform distribution as the non-conjugate prior distribution. A comparison of the two prior distributions is done through simulation studies with various sample sizes. The best estimator net is a method that produces the smallest posterior variance, absolute bias, and Bayes confidence interval. This study proves that the Bayes estimator by using the prior conjugate distribution produces all indicators of the goodness of the model with a smaller value than the non-conjugate prior distribution. Thus it can be concluded that the estimator with prior conjugate will produce a better predictive value than prior non-conjugate.

A Union Operation of Non-Dominated K-Coterie in Distributed System NURHIDAYAH NURHIDAYAH; Armin Lawi; Amir Kamal Amir
Jurnal Matematika, Statistika dan Komputasi Vol. 16 No. 3 (2020): JMSK, MAY, 2020
Publisher : Department of Mathematics, Hasanuddin University

Coterie is a set of quorums which has non-empty intersections and are not part of other quorum. The natural development of the coterie system is k-coterie. The k-coterie consists of 2 types, that are non-dominated k-coterie and dominated k-coterie. The non-dominated k-coterie is more resilient to failure than the dominated k-coterie. Combining two non-dominated k-coterie by applying union operation can result the dominated k-coterie. This study aims to define a combination of the non-dominated k-coterie with non-dominated k-coterie using the expanded union operation. The merger of non-dominated k-coterie with the non-dominated k-coterie produces a non-dominated k-coterie.

Precision Analysis of Poisson Control Chart Based on Sample Size Elsa Resa Sari
Jurnal Matematika, Statistika dan Komputasi Vol. 16 No. 3 (2020): JMSK, MAY, 2020
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/jmsk.v16i3.6944

One technique used in performing statistical quality control is by poisson control chart. Poisson control chart used in data that have the same mean and varians for monitoring the number of defects in the study. In some cases, the different sample sizes influence the control chart performance. The control chart performance can be measured using average run length (ARL). The smaller ARL’s value, the better type of control chart. In this study, we used different sample sizes that is and mean . The result show the best performance of control chart is when and m = 200, because its has a smaller ARL’s value.

An application of the finite difference method for solving the mass spring system equation Gabariela Purnama Ningsi; Fransiskus Nendi; Lana Sugiarti
Jurnal Matematika, Statistika dan Komputasi Vol. 16 No. 3 (2020): JMSK, MAY, 2020
Publisher : Department of Mathematics, Hasanuddin University

The numerical method is one method that can be used to solve differential equations, both differential equations that are easy or difficult to solve analytically. The solution obtained from the calculation results is an approximate solution or a solution that approaches an analytic solution, not an analytic solution. That is, in solving differential equations numerically, there is always an error. In this paper, an analytical solution is described and described and the application of different methods in solving a damped mass spring system with a known limit value. The error between the analytic and numerical solutions obtained is very small.

Service Waiting Time Behavior of Express Maintenance (EM) Program of PT. Dunia Barusa Banda Aceh Samsul Anwar; Tri Wahyudi; Mutia Andriani; Dinda Maulina; Juraida Fitri; Raihan Nora; Zulfazli Zulfazli
Jurnal Matematika, Statistika dan Komputasi Vol. 16 No. 3 (2020): JMSK, MAY, 2020
Publisher : Department of Mathematics, Hasanuddin University

Survival analysis is a statistical method that can be used to analyze duration time data of an event occurrence. This research uses secondary data from PT. Dunia Barusa branch Banda Aceh that collected from January to March 2017 which amounted to 107 data. The data is service waiting time (in minutes) of Express Maintenance (EM) program on sub section receptionist, service, final inspection, confirmation, technical complete, invoicing, customer notification and delivery. There are 4 functions analyzed, namely density probability function (PDF), cumulative distribution function (CDF), survival and hazard function. The study shows that the probability of a customer being in the waiting process of service tends to become smaller as the service waiting time become longer on each sub section of the EM program, as well as the probability to remain in the waiting process after the customer has been there within a certain period of time indicated by the survival function. The hazard function shows that the rate of a customer will be served instantaneously in the sub section receptionist, service, invoicing, customer notification and delivery changing over the time, while in the sub section of final inspection, technical complete and confirmation, the rates are constant over the time as high as 0.757, 0.794, and 3.336 respectively.

Modeling of Quantile Regression to Know the Factors Affecting the High Spread Api Malaria in Indonesia yahya matdoan
Jurnal Matematika, Statistika dan Komputasi Vol. 16 No. 3 (2020): JMSK, MAY, 2020
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/jmsk.v16i3.8970

The OLS method estimation is based on a normal distribution, so it is not appropriate to analyze a number of data that are not symmetrical or contain outliers. Therefore, quantile regression was developed which was not affected by outliers. This study compares quantile regression with OLS in the case of factors affecting malaria in Indonesia. The results show that the value of the Quantil Regression model is 0,832 and the MSE value is 0,182. In addition, the OLS model obtained a value of 0,681 and an MSE value of 0,231. So we get the conclusion that the best model is a quantile regression model. Further results were obtained that the main factors causing the spread of malaria in Indonesia were the factor of livable houses, poor population factors and physician factors.

Analysis Relationship of Imported Rice with Rice Production, Imported and Domestic Rice Prices with VECM Abyan Rai; Sasmito Hadi Wibowo
Jurnal Matematika, Statistika dan Komputasi Vol. 16 No. 3 (2020): JMSK, MAY, 2020
Publisher : Department of Mathematics, Hasanuddin University

Rice is the main food for most Indonesians. With much natural resources, Indonesia can naturally fulfill its own rice consumption needs. However, Indonesia actually relies on imports to meet consumption needs. Even Indonesia continues to import while rice production is volatility surplus to maintain domestic rice prices. Based on these problems, this study aims to analyze the relationship of volume of imported rice with rice production, domestic rice prices, and prices of imported rice. The method used is descriptive analysis and Vector Error Correction Model (VECM). In the long-term, rice production and domestic rice prices have significant effect on Indonesia's rice import volume. In short-term, rice production and domestic rice prices have significant effect on Indonesian rice import volume. The results of the causality test show that there is a two-way relationship between Indonesian rice import volume and Indonesian production rice. Meanwhile, a one-way relationship occurs when imported rice volumes influenced by prices of domestic rice.

Support vector regression (SVR) model for forecasting number of passengers on domestic flights at Sultan Hasanudin airport Makassar Drajat Indra Purnama; Siti Setianingsih
Jurnal Matematika, Statistika dan Komputasi Vol. 16 No. 3 (2020): JMSK, MAY, 2020
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/jmsk.v16i3.9176

Sultan Hasanudin Airport is one of the largest airports in Indonesia, located in Makassar City. Its strategic location is the entrance of eastern Indonesia because it is a transit airport to other eastern regions of Indonesia. The number of airplane passengers at Sultan Hasanudin Airport has increased and decreased each time depending on certain moments. The increase in the number of passengers is closely related to the moments of religious holidays or year-end holidays. Whereas the decrease in the number of passengers was greatly influenced by the policy of rising plane ticket prices some time ago. Estimated number of passengers every month is needed in planning and making appropriate decisions from the government relating to fluctuations in the number of domestic flight passengers at Sultan Hasanudin Airport. Therefore, accurate forecasting techniques are needed to predict the number of passengers in the future. Because the data pattern of domestic flight passengers at Sultan Hasanudin Airport is not stationary, the ARIMA model can be used. However, the data on the number of passengers has a nonlinear data pattern, so we need a method that can overcome these problems. In this study the SVR model is used to overcome nonlinear patterns in the data. Compared to the ARIMA model, SVR has the advantage because it does not require stationary data assumptions as in ARIMA. The results of forecasting data on the number of domestic flight passengers at Sultan Hasanudin Airport using SVR show better accuracy or accuracy compared to the ARIMA model because it has a smaller MAPE value.

Riemann Integral Construction Of A Sequence Of Functions In A Normed Space (l^p,‖∙‖_p ) Aswad Hariri Mangalaeng; Naimah Aris; Jusmawati Massalesse
Jurnal Matematika, Statistika dan Komputasi Vol. 16 No. 3 (2020): JMSK, MAY, 2020
Publisher : Department of Mathematics, Hasanuddin University

We construct Riemann Integral for a sequence in a normed space (l^p,‖∙‖_p ). To do construction, we used some theories of real analysis and functional analysis, include some real sequences theories, some Riemann integral theory for functions in R, and some norm theories in a normed space (l^p,‖∙‖_p ). In this paper, we otained that a sequence of functions f=(f_k ):[a,b]⊂R→l^p qualify that the sequence is Riemann integrable on [a,b]⊂R.

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