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All Journal AKSIOMA: Jurnal Program Studi Pendidikan Matematika Science and Technology Indonesia Jurnal Siger Matematika

Mustofa Usman

Universitas Lampung

Author-ID : 4317915

Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Education Environmental Science Materials Science & Nanotechnology Mathematics Physics

Published : 6 Documents Claim Missing Document

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Articles

Peramalan Data Time Series Seasonal Menggunakan Metode Analisis Spektral Anis Mahfud Al’afi; Widiarti Widiarti; Dian Kurniasari; Mustofa Usman
Jurnal Siger Matematika Vol 1, No 1 (2020): Jurnal Siger Matematika
Publisher : FMIPA Universitas Lampung

Air transportation is now a mode of transportation that is often the first choice. Although the transportation costs are relatively expensive, it can save a lot of time to get to the destination. Therefore, predicting the number of aircraft passengers is an interesting thing to study. In this study forecasting the number of aircraft passengers at Raden Intan II Airport using spectral analysis methods. Spectral analysis is used to obtain more complete information about the time series data characteristics to examine the periodicity. After getting the periodicity the data is modeled using the ARIMA Seasonal Method. Based on the analysis results it is known that the best model for forecasting aircraft passengers at Raden Intan II Airport is Seasonal ARIMA (0,1,1) (0,1,1)3

PERAMALAN JUMLAH KLAIM DI BPJS KESEHATAN CABANG METRO MENGGUNAKAN METODE DOUBLE EXPONENTIAL SMOOTHING Anisa Fitriyani; Mustofa Usman; Muhammad Taufiq Sofrizal; Dian Kurniasari
Jurnal Siger Matematika Vol 3, No 1 (2022): Volume 3 No 1
Publisher : FMIPA Universitas Lampung

Peramalan merupakan suatu proses atau metode dalam meramal suatu peristiwa yang akan terjadi pada masa yang akan datang. Exponensial smoothing adalah suatu metode peramalan rata-rata bergerak yang melakukan pembobotan menurun secara eksponensial terhadap nilai observasi yang lebih lama. Pada penelitian ini membahas tentang metode yang lebih baik dalam peramalan yaitu antara metode double exponential smoothing satu parameter dari Brown dan double exponential smoothing dua parameter dari Holt dalam meramalkan jumlah klaim pasien rawat inap RS Islam Metro yang diajukan ke BPJS Kesehatan cabang Metro. Melalui trial and error dihasilkan untuk double exponential smooting satu parameter dari Brown yaitu α = 0,11dengan nilai MAPE sebesar 19.89. Sedangkan metode double exponential smooting dua parameter dari Holt dengan α = 0,1 dan g= 0.1 menghasilkan nilai MAPE sebesar 19.60, sehingga metode double exponential smooting dua parameter dari Holt menjadi metode terbaik yang digunakan dalam meramalkan jumlah kasus rawat inap RS Islam Metro karena memiliki nilai MAPE yang lebih kecil. Setelah dilakukan peramalan menggunakan metode double exponential smooting dua parameter dari Holtmenghasilkan ramalan jumlah peserta pada bulan Desember 2021 adalah 91 kasus, bulan Januari 2022 adalah 83, bulan Februari 2022 adalah 75, bulan Maret 2022 adalah 68, dan April 2022 adalah 60.Double Exponential Smoothing Dua Parameter dari Holt, Double Exponential Smoothing Satu Parameter dari Brown, MAPE

Analisis Regresi Logistik Biner Terhadap Data Indeks Kedalaman Kemiskinan Di Indonesia Tahun 2020 Regita Elza Fitri; Eri Setiawan; Mustofa Usman; Dorrah Aziz
Jurnal Siger Matematika Vol 3, No 2 (2022): Jurnal Siger Matematika
Publisher : FMIPA Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jsm.v3i2.3117

Poverty is a serious problem that occurs in many countries, both developing and developed countries. This issue needs to be addressed by the government, especially in countries with large and dense populations such as Indonesia. Poverty inequality as measured by the poverty depth index shows a number that tends to be stable from year to year. Therefore, it’s necessary know the causal factors that affect the depth of poverty in Indonesia. This study discusses the factors that affect the poverty depth index in Indonesia in 2020 using binary logistic regression analysis to determine the best binary logistic regression model and find out the magnitude of the classification accuracy of what factors affect the poverty depth index in 34 provinces in Indonesia in 2020. This problem can be overcome by using binary logistic regression because the response variable only consists of two categories, namely high and low poverty depth. Based on the analysis, it can be concluded that the open unemployment rate variable and the average expenditure per capita for one month for food have a significant effect on the classification of the poverty depth index in Indonesia 2020.

Enumerating the Number of Connected Vertices Labeled Graph of Order Six with Maximum Ten Loops and Containing No Parallel Edges Wamiliana Wamiliana; Amanto Amanto; Mustofa Usman; Muslim Ansori; Fadila Cahya Puri
Science and Technology Indonesia Vol. 5 No. 4 (2020): October
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

A Graph G (V, E) is said to be a connected graph if for every two vertices on the graph there exist at least a path connecting them, otherwise, the graph is disconnected. Two edges or more that connect the same pair of vertices are called parallel edges, and an edge that starts and ends at the same vertex is called a loop. A graph is called simple if it containing no loops nor parallel edges. Given n vertices and m edges, m ≥ 1, there are many graphs that can be formed, either connected or disconnected. In this research, we will discuss how to calculate the number of connected vertices labeled graphs of order six (isomorphism graphs are counted as one), with a maximum loop of ten without parallel edges.

IMPLEMENTATION OF DECISION TREE AND SUPPORT VECTOR MACHINE ON RAISIN SEED CLASSIFICATION Wardhani Utami Dewi; Khoirin Nisa; Mustofa Usman
AKSIOMA: Jurnal Program Studi Pendidikan Matematika Vol 12, No 1 (2023)
Publisher : UNIVERSITAS MUHAMMADIYAH METRO

In everyday life there are many complex and global problems, especially in terms of decision making. Machine learning (ML) which is built from the concepts of computer science statistics and mathematics can automatically solve problems without guidance from ordinary users. Decision tree (DT) and support vector machine (SVM) are two supervised learning methods among several classification algorithms in ML. Both algorithms are the most popular classification techniques due to their ability to change a complex decision-making process into a simple process. In this study, the accuracy of the DT and SVM algorithms is studied on classifying raisin seeds into the Besni class and the Kecimen class based on existing features. The raisin data are divided into training and testing data, and the evaluation of the two methods is done using the testing data. The results of the evaluation are compared based on the accuracy, sensitivity, specificity, and kappa levels of the DT and SVM algorithms. The results on classifying raisin seeds data show that the SVM algorithm is superior to DT, therefor the number of positive observations is more precise in the prediction.

Pemodelan Dinamis Distributed Lag Dengan Menggunakan Metode Koyck Dan Metode Almon Dora Panny Nurcahaya Sitorus; Widiarti Widiarti; Agus Sutrisno; Mustofa Usman
Jurnal Siger Matematika Vol 4, No 1 (2023): Jurnal Siger Matematika
Publisher : FMIPA Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jsm.v4i1.9210

The distributed lag Model is a dynamic model due to the effect of a one-unit change in the value of the distributed independent variable (X) over a period of time. Distributed lag Model there are 2 types, namely: infinite lag model and finite lag model. Infinite lag modeling using koyck method and finite lag modeling using Almon method. This distributed lag Model is used to visualize the impact caused by the independent variable on the dependent variable. This study aims to apply a dynamic model of distributed lag by using the koyck transformation method and Almon transformation method to assess the effect of the rupiah exchange rate on the value of garment exports PT. Shinwon went abroad and determined the best model in Dynamic Modeling of distributed lag using the koyck transformation method and the Almon transformation method. The results showed that dynamic modeling of distributed lag with Almon transformation method is better than koyck transformation.

Co-Authors . Wamiliana Agus Sutrisno Amanto Amanto Anis Mahfud Al’afi Anisa Fitriyani Dian Kurniasari Dora Panny Nurcahaya Sitorus Dorrah Azis Eri Setiawan Fadila Cahya Puri Khoirin Nisa Muhammad Taufiq Sofrizal Muslim Ansori Regita Elza Fitri Wardhani Utami Dewi Widiarti Widiarti

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