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SIMULASI PERGERAKAN TUMPAHAN MINYAK DI LAUT DENGAN PENGARUH ANGIN Millah, Nashrul; Anggriani, Indira; Nugraheni, Kartika
SPECTA Journal of Technology Vol 3 No 3 (2019): SPECTA Journal of Technology
Publisher : LPPM ITK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35718/specta.v3i2.67

Abstract

As a petroleum-producing country, Indonesia has a very important role in supplying national and international petroleum needs. The distribution of oil by sea raises the risk of spills and harms the marine environment, especially for marine life. Most oil spills in the marine environment can form a thin layer on the surface due to the movement of wind, waves, and currents. In this study, the oil spill movement model used the Shallow Water Equation (SWE) model and the equation for the movement of oil spills. The SWE model consists of the equation of mass and momentum derived from the law of conservation of mass which is derived into the equation of continuity and the law of conservation of momentum which is derived into the equation of conservation of momentum. In this model, ocean currents are affected by several disturbances in the form of wind gusts and friction with the bottom. The model is solved numerically through simulation using the finite volume method. Discretization is done by using a staggered grid approach, where the mass and momentum variables are discretized in different cells. From the simulation results, it appears that the movement of oil spills is influenced by wind direction and current. The simulation results also found that the speed of the movement of oil spills has increased in the early times, but then gradually.  
ANALYSIS OF THE EFFECT OF STUART NUMBER AND RADIATION ON VISCOUS FLUID FLOW Anggriani, Indira; Norasia, Yolanda; Tafrikan, Mohamad; Ghani, Mohammad; Widodo, Basuki
Journal of Fundamental Mathematics and Applications (JFMA) Vol 7, No 1 (2024)
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jfma.v7i1.22481

Abstract

Computational fluid dynamics (CFD) is a numerical solution of fluid flow problems built from applied mathematical modeling. The problem of the flow of a viscous fluid which is influenced by a magnetic field gives rise to a boundary layer, from this boundary layer a dimensional building equation is formed. The governing equation is obtained from the continuity equation, momentum equation, and energy equation, then transformed into a non-dimensional equation by substituting non-dimensional variables and transformed into a similarity equation. The numerical solution to this problem uses the Keller Box method. The numerical simulation results show that the Stuart Number increases the velocity profile, while the temperature profile decreases. The effect of radiation parameters on the velocity profile did not change significantly, but the temperature profile decreased.
OPTIMAL CONTROL OF MATHEMATICAL MODELS IN BIOENERGY SYSTEMS AS EMPOWERMENT OF SUSTAINABLE ENERGY SOURCES Nugraheni, Kartika; Soemarsono, Annisa Rahmita; Millah, Nashrul; Anggriani, Indira; Usrotus Wakhidah, Ummi Saydatul
Journal of Fundamental Mathematics and Applications (JFMA) Vol 7, No 1 (2024)
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jfma.v7i1.22482

Abstract

Energy has a very important role in everyday life. Dependence on non-renewable energy increases its vulnerability to supply instability, making it important to seek alternative energy sources to overcome this dependence. Bioenergy is an alternative energy produced from organic materials such as biomass. Control of renewable energy is needed to increase production and empowerment. In this research, a mathematical model of biogas production growth in the form of differential equations formed with optimal control modifications is proposed. Completion of the model is carried out by forming an objective function, as well as determining the Hamilton function and Lagrange function. Numerical simulations in the model show that providing control can increase biogas production as a sustainable energy source.
Implementation of Discrete Time Markov Chain Method to Estimate The Transition of Smartphone Brands Usage in Balikpapan Asyrofi, Anang; Anggriani, Indira; Soemarsono, Annisa Rahmita
Jurnal ILMU DASAR Vol 24 No 2 (2023)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/jid.v24i2.34872

Abstract

The increasingly rapid competition in the industrial world today encourages all companies to be able to compete by prioritizing the products they offer, one of which is smartphones. Indonesia is one of the countries with the largest smartphone market share in Asia, with the number of active smartphone users in Indonesia reaching 177 million people in 2021 according to data released by the Statista research institute in March 2022. With these conditions, many smartphone companies always follow the direction of development of sophisticated communication technology media and offer a variety of complete and attractive facilities to encourage people to buy these products. One method that can be used to model this uncertainty is Discrete Time Markov chain which can be implemented as a tool for decision making and predicting future events. Therefore, this study was conducted to know the shifting pattern of smartphone use by consumers and predict the shift in smartphone market share for the coming period. The results of the study found that the steady state or equilibrium condition was achieved in the 10th period or in 2032 with the steady state percentage of each brand, namely Samsung = 22.49%, Oppo = 20.82 %, Xiaomi = 17.01%, Realme = 11.54%, Vivo = 11.41%, Apple = 10.27%, and other brands = 6.46%. The increase in market share is predicted to occur in the Oppo, Realme, and Vivo brands, while the decrease in market share will occur in the Apple, Samsung, Xiaomi and other brands.
Peningkatan Pengetahuan Keselamatan dan Keamanan Konstruksi Rumah Tinggal di Kelurahan Karang Joang, Kota Balikpapan Anggriani, Indira; Sukmara, Riyan Benny; Ariyaningsih, Ariyaningsih
Abdimas Universal Vol. 7 No. 1 (2025): April
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Balikpapan (LPPM UNIBA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36277/abdimasuniversal.v7i1.521

Abstract

In the context of residential development, safety and security in construction are essential components of the lifestyle of individuals. The geographical condition of Balikpapan, which is susceptible to natural disasters such as landslides, floods, and fires, presents additional obstacles to the provision of safe and secure housing infrastructure. An example of this is the landslide disaster that happened in Karang Joang Village in 2021, which was caused by a lack of awareness regarding the safety and security of residential construction. The resulting damage to numerous houses in the village was significant. This paper tries to examine the practical implementation of construction safety standards in residential homes, including the use of safe building techniques and appropriate materials, through community service activities. This program provided the community with a more comprehensive understanding of disaster risk management and enhanced their ability to take proactive and reactive measures in the event of an emergency. The results of the questionnaire distribution shows that there was a significant difference in the level of community knowledge. In terms of construction design knowledge, more than 50% (from 3 people to 13 people) of residents answered that they already knew the safe construction design after listening to the community service presentation. The same result also occurred in the knowledge of methods, more than 50% (from 3 people to 11 people) of respondents have known the right construction method for their area after attending this community service presentation.
COMPARISON IN PREDICTING THE SHORT-TERM USING THE SARIMA, DSARIMA AND TSARIMA METHODS Giovani, Muhammad; Anggriani, Indira; Simatupang, Syalam Ali Wira Dinata
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 4 (2022): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (529.483 KB) | DOI: 10.30598/barekengvol16iss4pp1487-1496

Abstract

The flow of data and information is growing rapidly and rapidly in various sizes and means which is called Big Data. In the face of a change for the better in the future, a careful analysis and design of a data processing system is needed, in which a predictive framework can formulate the right policy to be one of the efforts to make a good decision. This is one of the appropriate Big Data processing efforts, which can be realized through one of the methods, namely prediction or forecasting is an effort to predict future values or trends as a reference for analyzing conditions in the past. One example of Big Data in the City of Balikpapan, namely the temperature within 2 meters obtained from the NASA satellite published on the website power.larc.nasa.gov. One of the methods used in this research is the ARIMA method and it is developed according to the data used. Based on the data to be used, namely temperature data within a distance of 2 meters in the city of Balikpapan, the development of data processing is carried out to pay attention to three seasonal patterns or the so-called Triple Seasonal ARIMA model. In this study, it can be seen how to build the Triple Seasonal ARIMA model and comparison with alternative models, namely Seasonal ARIMA and Double Seasonal ARIMA, and can see how the results of the Triple Seasonal ARIMA model accuracy when compared with alternative models. The method used in this study is the Seasonal ARIMA, Double Seasonal ARIMA and Triple Seasonal ARIMA methods. The results obtained in this study obtained a comparison of methods in making predictions with a specified time span, the results obtained from the Seasonal ARIMA model that it was very good at predicting a time span of 2 weeks, Double Seasonal ARIMA for a period of 1 month, Double Seasonal ARIMA for a period of 3 months, and Triple Seasonal ARIMA for a period of 6 months.
STUDY TIME CLASSIFICATION OF MATHEMATICS AND INFORMATION TECHNOLOGY DEPARTMENT OF KALIMANTAN INSTITUTE OF TECHNOLOGY USING NAÏVE BAYES ALGORITHM Sucipto, Fatrysia Wikarya; Paninggalih, Ramadhan; Anggriani, Indira
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 3 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss3pp1419-1428

Abstract

Institut Teknologi Kalimantan (ITK) is one of the state universities in Indonesia which has 5 majors, one of them is the Department of Mathematics and Information Technology (JMTI). JMTI has six study programs, and only three study programs have graduates, namely Mathematics, Information Systems, and Informatics. Every year the number of new students continues to grow, but this is not proportional to the number of graduates, because some students study for more than 8 semesters. Because of this, the quality of study programs being poor. In this research, a model was built that could classify student study timeliness, using the naïve Bayes algorithm. The data used is data from JMTI student graduates from the 2013 to 2019 batch. The 2013 to 2018 batch data will be training data and validation data, while the 2019 batch data will be testing data. This research compare accuracy and F1-score naïve Bayes algorithm without correlation and with correlation. The best model obtained from training data is a model with variables that have gone through a correlation test, namely 70:30, 80:20, and 90:10. The attributes selected after the correlation test, namely, IP Tahap Bersama, GPA, Final GPA, Length of Study (Semester), dan Graduation GPA (Category), yield results for accuracy and an F1-score of 1.
APPLICATION OF K-MEANS AND FUZZY C-MEANS ALGORITHMS TO DETERMINE FLOOD VULNERABILITY CLUSTERS (CASE STUDY: KUTAI KARTANEGARA REGENCY) Nurjanah, Desi; Anggriani, Indira; Hasanah, Primadina
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 2 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss2pp0821-0836

Abstract

Flooding show situation where areas that are not usually inundated, such as farmland and settlements, and city district areas, become inundated due to water. Floods can to occur when the flow of water on rivers or waste channels overrun its normal measurements. This study describes the K-Means and Fuzzy C-Means Algorithm methods for clustered flood-prone areas built on Districts in Kutai Kartanegara Regency. This research begins with data collection in the character of rainfall, land elevation, the number of victims affected, the quantity of damaged houses, the quantity of damage to facilities and the quantity of flood events. Before the data is processed using these two methods, data normalization will be carried out in a dataset which aims to shape the data into positional values from the same range. K-Means and Fuzzy C-Means are accustomed to identifying groups in each sub-district in Kutai Kartanegara Regency that have a level of vulnerability to floods. At this stage, 3 initial clusters were carried out, namely high, medium, and low vulnerability clusters. The validity test produces a Silhouette Index value of 0.574283589 and a Partition Coefficient Index of 0.78905. The outcome of the K-Means method with the standard deviation within and between clusters are 0.5131 and the Fuzzy C-Means method for the standard deviations within and between clusters is 0.3489. based uppon value of the silhouette index, partition coefficient index and standard deviation within and between clusters it results that Fuzzy C-Means is the best method of this study.