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All Journal AKSIOMA: Jurnal Program Studi Pendidikan Matematika Journal of Science and Applicative Technology Variance : Journal of Statistics and Its Applications Vygotsky: Jurnal Pendidikan Matematika dan Matematika Journal of Science and Technology MATHunesa: Jurnal Ilmiah Matematika Journal of Fundamental Mathematics and Applications (JFMA) International Journal of Geotourism Science and Developmen AMMA : Jurnal Pengabdian Masyarakat Indonesian Journal of Applied Mathematics TeknoKreatif: Jurnal Pengabdian kepada Masyarakat
Muliawati
Department of Mathematics
Humanities Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Nursing Physics Social Sciences Other

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Recognition of Voronoi Cell Distribution in Earthquake Epicenter Data in the Sunda Strait Region, Indonesia Muliawati, Triyana; Lestari, Fuji; Harbowo, Danni Gathot; S, Mika Alvionita
JOSTECH Journal of Science and Technology Vol 4, No 2: September 2024
Publisher : UIN Imam Bonjol Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15548/jostech.v4i2.9830

Abstract

The Sunda Strait is currently one of the busiest transportation hubs. However, this area has a significant history of geological disasters caused by the dynamic tectonic activity of the Eurasian and Indo-Australian tectonic plates. These disasters include the supervolcanic eruption of Krakatoa in 1883, the Sunda Strait tsunami in 2018, and decades of frequent earthquakes. To address these challenges, this study analyzes the frequency and distribution of seismic activity in the Sunda Strait region based on epicenter data recorded in the United States Geological Survey (USGS) Earthquake Catalog. We collected 440 multivariate earthquake data points between 1990 and 2023 (over three decades). The results of this study show that a machine learning approach accurately identified four relevant parameters for k-means clustering, followed by a silhouette value analysis to recognize the distribution of Voronoi cells. Based on earthquake data from the Sunda Strait from 1990 to 2023, the two highest silhouette analysis values, 0.40 and 0.39, are located at k=3 and k=5 in k-means clustering. This approach has recognized and identified the cell area of earthquake activity in the Sunda Strait, particularly around Anak Krakatoa. This study provides new insights into the spatiotemporal characteristics and identifies clusters of earthquake-prone areas. The information generated in this study facilitates the evaluation of future earthquake disaster risks, especially those with epicenters in the Sunda Strait region.
Estimasi Jumlah Mismanaged Plactic Waste (MPW) Berdasarkan Kenaikan Populasi: Studi Kasus 30 Negara Tahun 2019-2022: Studi Kasus 30 Negara Tahun 2019-2022 Muliawati, Triyana; Supmawati, Meysi; Rahmawati, Eli; Aula, Naila Tsamrotul
Indonesian Journal of Applied Mathematics Vol. 4 No. 1 (2024): Indonesian Journal of Applied Mathematics Vol. 4 No. 1 April Chapter
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM), Institut Teknologi Sumatera, Lampung Selatan, Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35472/indojam.v4i1.1175

Abstract

Abstract: Humans have produced more than 8 billion tons of plastic, more than half of which is directly dumped into landfills and only about 9% is recycled. This makes the author interested in looking at the relationship between population and the amount of waste generated in the hope of helping the government in reducing the amount of waste generated. This study aims to estimate the amount of Mismanaged Plastic Waste (MPW) based on population increase, focusing on 30 countries from 2019 to 2022. The Rank Spearman correlation test method was used to evaluate the relationship between population size and the amount of MPW, showing a strong relationship with a correlation coefficient of 0.60712. Furthermore, an analysis using the Cox-Stuart test was conducted to determine the trend in population size from 2003 to 2022, which showed that there was no clear trend in the population data or an upward trend in the time span. Based on these findings, a predictive estimate of the number of MPW for the period 2019-2020 was conducted, providing additional insight into the impact of population growth on the amount of unmanaged plastic waste in these countries.
Recognizing the Spatial Distribution and Voronoi Patterns of the Recorded Earthquake Epicenters in Sunda Strait, Indonesia Muliawati, Triyana; Lestari, Fuji; Alvionita, Mika; Satria, Ardika; Harbowo, DG
Journal of Fundamental Mathematics and Applications (JFMA) Vol 7, No 2 (2024)
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jfma.v7i2.21931

Abstract

Currently, Sunda Strait is one of the most active transportation hubs. However, this region also bears a notable history of geohazards associated with the dynamics of tectonic activity of the Eurasian and Indo-Australian tectonic plates, such as the super-eruption of Krakatoa volcano in 1883, the Sunda Strait tsunami in 2018, and decades of frequent earthquakes. To address these challenges, this study conducted a statistical analysis of the frequency and distribution of seismic activities in the Sunda Strait region based on recorded epicenter data in the United States Geological Survey's (USGS) Earthquake catalog. We assembled 440 multivariate earthquake data points between 1990 and 2023 (over three decades). The results of this study indicate that the machine learning approach precisely identifies four relevant parameters for -means clustering, followed by an analysis of silhouette values to recognize Voronoi patterns. These statistical patterns also have significant implications for the number of epicenter clusters and recognizing their spatial distribution. It provides a new understanding of the spatial-temporal characteristics and locates the list of frequent earthquake regions. Having all the necessary information would help to comprehensively evaluate geohazard risks in Sunda Strait region.
Statistical Pattern Recognition of Lithosphere Anomalous Activity Along the Indonesian Ring of Fire S, Mika Alvionita; Satria, Ardika; Muliawati, Triyana; Lestari, Fuji; Harbowo, Danni Gathot
Journal of Science and Applicative Technology Vol. 9 No. 1 (2025): Journal of Science and Applicative Technology June Chapter
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM), Institut Teknologi Sumatera, Lampung Selatan, Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35472/jsat.v9i1.1850

Abstract

The introduction of statistical pattern recognition becomes highly important for assessing disaster threats such as earthquakes. This approach is significantly more comprehensive and suitable for long-term event forecasting. Therefore, in the future, efforts can be promptly made to reduce the risk of disasters resulting from anomalies in lithospheric activity, especially frequent earthquakes in the Sumatra Island region, Indonesia. Statistical pattern analysis of lithospheric activity anomalies can be categorized through classification. Earthquake classification is performed based on magnitude scale and mathematical calculations of earthquake parameter unit conversion. The classification method employed in this research includes machine learning methods like k-nearest neighbor and support vector machine. The evaluation metrics used for machine learning models are model accuracy and confusion matrix tables.
Raw Material Inventory Control Using The Period Order Quantity (POQ) Method to Reduce Stockout and Overstock Risks Nasution, Achmad Suryadi; Simbolon, Okto Bryan; Muliawati, Triyana; Edriani, Tiara Shofi; Noor, Dear Michiko Mutiara; Fauzi, Rifky
Vygotsky: Jurnal Pendidikan Matematika dan Matematika Vol. 7 No. 2 (2025): Vygotsky: Jurnal Pendidikan Matematika dan Matematika
Publisher : Universitas Islam Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30736/voj.v7i2.1163

Abstract

The rapid growth of coffee shops in Lampung has increased demand for Robusta Lampung, Arabica Kerinci, and Arabica Aceh Gayo, causing stockouts and overstocking at a coffee roastery. This study uses the Period Order Quantity (POQ) method to optimize inventory by ordering based on predictable demand periods, reducing order frequency and costs. Using demand data from the last six months of the year, POQ outperforms the manual inventory policy. Assuming a 5% holding cost and 90%–99% service levels (ensuring product availability), POQ reduces costs by 0.119%–0.163%, boosting profitability. Adopting POQ with real-time demand tracking can balance inventory and meet rising demand.
Analisis Rantai Markov dalam Memprediksi Status Pasien COVID-19 di Indonesia Putri, Nabila Nurita; Muliawati, Triyana
Indonesian Journal of Applied Mathematics Vol. 1 No. 2 (2021): Indonesian Journal of Applied Mathematics Vol. 1 No. 2 April Chapter
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM), Institut Teknologi Sumatera, Lampung Selatan, Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35472/indojam.v1i2.352

Abstract

COVID-19 is an infectious disease caused by a new type of corona virus, beta coronavirus. The spread of COVID-19 can occur through human interactions. On March 9, 2020 the WHO (World Health Organization) officially declared COVID-19 a pandemic. This means that COVID-19 has spread widely in the world. Until now, there has not been found a drug to treat COVID-19. So, it is necessary to predict when the COVID-19 pandemic will end. This study discusses the Markov chain method in predicting the status of COVID-19 patients in Indonesia. The prediction of the number of people who are positive for COVID-19, recovered, and die can be one of the government's bases for determining when the large-scale social restrictions (PSBB) will end. The results of the study stated that the COVID-19 pandemic in Indonesia would end at the end of 2020. On December 5, 2020 there were no more people infected with COVID-19 with a cure rate of 29.815% of patients with COVID-19 and a death rate of 3, 5933%.
Raw Material Inventory Control Using The Period Order Quantity (POQ) Method to Reduce Stockout and Overstock Risks Nasution, Achmad Suryadi; Simbolon, Okto Bryan; Muliawati, Triyana; Edriani, Tiara Shofi; Noor, Dear Michiko Mutiara; Fauzi, Rifky
Vygotsky: Jurnal Pendidikan Matematika dan Matematika Vol. 7 No. 2 (2025): Vygotsky: Jurnal Pendidikan Matematika dan Matematika
Publisher : Universitas Islam Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30736/voj.v7i2.1163

Abstract

The rapid growth of coffee shops in Lampung has increased demand for Robusta Lampung, Arabica Kerinci, and Arabica Aceh Gayo, causing stockouts and overstocking at a coffee roastery. This study uses the Period Order Quantity (POQ) method to optimize inventory by ordering based on predictable demand periods, reducing order frequency and costs. Using demand data from the last six months of the year, POQ outperforms the manual inventory policy. Assuming a 5% holding cost and 90%–99% service levels (ensuring product availability), POQ reduces costs by 0.119%–0.163%, boosting profitability. Adopting POQ with real-time demand tracking can balance inventory and meet rising demand.
OPTIMASI PORTOFOLIO MEAN ABSOLUTE DEVIATION MENGGUNAKAN METODE SIMPLEKS DUA FASE PADA JAKARTA ISLAMIC INDEX Mutiara Rahma, Visna; Febrianti, Werry; Muliawati, Triyana
MATHunesa: Jurnal Ilmiah Matematika Vol. 14 No. 1 (2026)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/mathunesa.v14n1.p27-37

Abstract

Investment is the activity of allocating capital to issuers with the aim of generating profits. Investment in the Islamic capital market is becoming increasingly popular, and to manage risk, investors need to construct an optimal portfolio. This study aims to optimize the portfolio of Sharia-compliant stocks listed in the Jakarta Islamic Index (JII) using the Mean Absolute Deviation (MAD) model. The MAD model is formulated as a linear programming problem and is solved using LINGO software version 15.0 as well as the two-phase simplex method manually. Both approaches produced identical results. Portofolio optimization involving 5 stocks, the investment weights are evenly distributed at 20% among MEDC, BRMS, BRIS, ADRO, and MDKA stocks, with a portfolio risk of 0.02241 and a portfolio return of 0.00102. Portofolio optimization involving 10 stocks, each stock receives a 10% allocation, with a portfolio risk of 0.02085 and a portfolio return of 0.00074. Portofolio optimization involving 15 stocks portfolio assigns 6.7% to most stocks and 6.2% to MEDC, with a portfolio risk of 0.02042 and a portfolio return of 0.00052. The best performance, with a Sharpe index of 0.04569, is achieved in the five-stock portfolio. The results demonstrate the effectiveness of the MAD model in optimizing Sharia-compliant stock portfolios.
Teknologi Smart Conservation Untuk Identifikasi Spesies Mangrove Di Kawasan Ekowisata Cuku Nyinyi, Lampung Triyana Muliawati; Fuji Lestari; Mika Alvionita Sitinjak; Eristia Arfi; Devia Gahana Cindi Alfian
AMMA : Jurnal Pengabdian Masyarakat Vol. 4 No. 1 : Februari (2025): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Mangroves are a type of forest ecosystem that grows in coastal areas along tropical and subtropical shores throughout Indonesia, particularly in Lampung Province. This ecosystem is found in regions influenced by tidal seawater. Mangroves consist of various species of trees, shrubs, and other plants that can survive in highly saline and muddy environments. Additionally, mangroves provide numerous benefits for environmental sustainability and human well-being. A healthy mangrove ecosystem contains diverse plant species with specific characteristics that help maintain ecological balance and ensure optimal ecological functions.Lampung Province has a mangrove ecotourism site located in Sidodadi Village, Teluk Pandan District, Pesawaran Regency, known as Cuku Nyinyi. Uniquely, Cuku Nyinyi is often used as a research and learning site for students, researchers, and the general public to study mangroves.One of the challenges faced by the ecotourism management team, the Bina Jaya Lestari Forest Farmers Group (KTH), is the difficulty in identifying and classifying mangrove species planted in the Cuku Nyinyi ecotourism area. Additionally, there is a lack of adequate information about mangroves, such as their age, anatomy, habitat, environmental adaptations, benefits, and other relevant details. To address this issue, researchers are developing an automatic identification system for mangrove species based on leaf morphology using a Convolutional Neural Network (CNN) approach. CNN is one of the most effective methods for pattern recognition in images and mangrove image processing. This technology is expected to be implemented in the form of a camera application that can automatically identify information from an image of mangrove leaf morphology captured in the Cuku Nyinyi ecotourism area.The Mangrove Camera Application provides new insights to KTH and the general public regarding the potential and importance of conserving natural resources.
Co-Authors . Kartono Achmad Suryadi Nasution Adelia Azahra Agustina Alfredo Edward Lazuardi Andre Markus Fernando Lubis Aula, Naila Tsamrotul Danni Gathot Harbowo Dedy Rudianto Della Najunda K.S Devia Gahana Cindi Alfian Edi Cahyono Edriani, Tiara Shofi Eli Rahmawati, Eli Erina Rosalia Irda Eristia Arfi Eristia Arfi Febi Erliyani Febrianti, Werry Fuji Lestari Heru Ruwandar Hutama Irwan, Sri Efrinita Jenika Maulina Anjani Juan Daniel Turnip Lestari Malasan Mika Alvionita Sitinjak Muhammad Ammar Alkautsar Muhammad Said Mustika, Mira Mutiara Rahma, Visna Muztaba Nabila Nurita Putri Natalia Noor, Dear Michiko Mutiara Prastyo Puradimadja Putri, Nabila Nurita R Ikhram Raharto Retno Anggraini Rifky Fauzi Rofi Ilmi Fadhillah Satria, Ardika Sekar Anisa Sely Simbolon, Okto Bryan Suhika, Dewi Supmawati, Meysi Yanti Marito Yusuf