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All Journal JURNAL DERIVAT: JURNAL MATEMATIKA DAN PENDIDIKAN MATEMATIKA Jurnal Pembelajaran Berpikir Matematika Enthalpy : Jurnal Ilmiah Mahasiswa Teknik Mesin Teorema: Teori dan Riset Matematika
Pimpi, La
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Education Mathematics Mechanical Engineering

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Perbandingan Uji Likelihood Ratio Dan Uji F Asymtotik Pada Regresi Linier Hermanto, Hermanto; Somayasa, Wayan; Pimpi, La
Jurnal Pembelajaran Berpikir Matematika (Journal of Mathematics Thinking Learning) Vol 5, No 2 (2020)
Publisher : Universitas Halu Oleo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33772/jpbm.v5i2.15032

Abstract

Abstrak: Analisis regresi adalah studi mengenai ketergantungan satu variabel terikat dengan satu atau lebih variabel bebas, dengan tujuan mengestimasi dan memprediksi rata-rata populasi atau nilai rata-rata variabel terikat berdasarkan nilai variabel bebas yang diketahui. Terdapat berbagai uji hipotesis yang dapat digunakan untuk menentukan model yang cocok untuk untuk mengetahui hubungan antar variabel tidak bebas dengan satu atau lebih variabel bebas, di antarannya adalah uji likelihood ratio dan uji F asimtotik. Uji hipotesis menggunakan uji likelihood ratio, dimana merupakan salah satu uji yang berhubungan langsung dengan penduga maksimum likelihood, yang model distribusi dari populasinya mengikuti model distribusi dengan pdf tertentu dimana diasumsikan normal dibandingkan dengan uji hipotesis menggunakan uji F asymtotik, yang merupakan uji di mana perosedur inferensi secara asimtotik tidak membutuhkan asumsi distribusi dari observasinya. uji hipotesis baik uji likelihood ratio dan uji F asymtotik pada analisis regresi menghasilkan bentuk model yang sama.Kata Kunci: Analisis Regresi, Uji Likelihood ratio, Uji F AsymtotikAbstract: Regression analysis is a study of the dependence of one dependent variable with one or more independent variables, with the aim of estimating and predicting the population mean or average value of the dependent variable based on the known value of the independent variable. There are various hypothesis tests that can be used to determine a suitable model to determine the relationship between dependent variables and one or more independent variables, including the likelihood ratio test and the asymptotic F test. Hypothesis testing uses the likelihood ratio test, which is one of the tests that is directly related to the maximum likelihood estimator, where the distribution model of the population follows a distribution model with a particular pdf which is assumed to be normal compared to the hypothesis test using the asymptotic F test, which is a test in which the inference procedure asymptotically it does not require assuming the distribution of the observations. Hypothesis test both likelihood ratio test and asymptotic F test in regression analysis produces the same model.Key words: Regression Analysis, likelihood ratio test, asymptotic F test.
Peramalan Harga Saham PT. Bank Central Asia, Tbk dengan Menggunakan Metode ARIMA Gubu, La; Bakti Sadewa, Muhammad Alfian; Pimpi, La
Jurnal Derivat: Jurnal Matematika dan Pendidikan Matematika Vol. 11 No. 1 (2024): Jurnal Derivat (April 2024)
Publisher : Pendidikan Matematika Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31316/jderivat.v11i1.5329

Abstract

The purpose of this research is to analyze the fluctuations and quantity of daily stock closing data of PT. Bank Central Asia Tbk (BCA) during the period from January 3, 2022, to December 30, 2022, and forecast the closing stock price in January 2023 using the ARIMA model. The research procedure was conducted step by step, including data collection, descriptive analysis, testing data stationarity, determining ARIMA model parameters, writing ARIMA equation models, conducting diagnostic tests on the best ARIMA model, and making predictions or forecasts. The analysis shows that the stock closing prices in 2022 fluctuated with an average range of Rp 7,214.29 - Rp 8,851.14 per share. The highest closing price occurred in November 2022, while the lowest occurred in July 2022. The forecast for the daily closing stock price of BCA from January 2 to January 31, 2023, using the ARIMA Model (1,1,0), ranges from Rp 8,550.00 to Rp 8,550.86. The MAPE value obtained from the forecasting result is 1.07%, indicating that the ARIMA model is highly effective in forecasting the closing stock price of BCA in January 2023. This research provides valuable insights into stock price fluctuations for stakeholders in the stock market. Keywords: fluctuations, ARIMA, stock closing prices, forecast.
Penerapan Trilaterasi dan Underdetermined Linear System dalam Penentuan Posisi Objek di Bumi Melalui Global Positioning System (GPS) Jufra, Jufra; Pimpi, La; Jufra, Arlita Aristianingsih; Alfian, Alfian; Arifin, Samsul; Murnaka, Nerru Pranuta
Teorema: Teori dan Riset Matematika Vol 9, No 2 (2024): September
Publisher : Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/teorema.v9i2.14112

Abstract

Materi yang digunakan dalam penelitian ini adalah konsep matriks dan aljabar vektor yang dapat membantu dalam menyelesaikan sistem persamaan linear yang terbentuk dari perhitungan jarak antara satelit dan receiver di bumi. Jarak ini adalah panjang vektor. Penyelesaian sistem persamaan linier ini berupa titik yang menunjukkan letak benda di muka bumi. Materi selanjutnya adalah tentang cara kerja Global Positioning System (GPS). Alat yang digunakan dalam penelitian ini adalah fasilitas yang dimiliki oleh Departemen Laboratorium Komputasi Matematika Universitas Halu Oleo berupa fasilitas komputer dan perangkat lunak. Berdasarkan hasil pembahasan dapat disimpulkan bahwa. Matriks aljabar dan vektor berperan penting dalam menentukan posisi suatu benda di bumi, khususnya pada GPS. Konsep yang digunakan adalah dengan menerapkan matriks dan vektor dari sistem persamaan linier yang diperoleh berdasarkan perhitungan jarak satelit ke benda bumi yang diterima penerima. Kata kunci: GPS; Matriks; Vektor; Aljabar.
Analisis Ketepatan Metode Exponential Smoothing dan Metode Trend dalam Mengestimasi dan Meramalkan Volume Curah Hujan di Kota Kendari Aswani, Aswani; Pimpi, La; Dwiyanto, M. Riski Imam
Enthalpy : Jurnal Ilmiah Mahasiswa Teknik Mesin Vol 9, No 2 (2024): Enthalpy: Jurnal Ilmiah Mahasiswa Teknik Mesin
Publisher : Teknik Mesin Universitas Halu Oleo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55679/enthalpy.v9i2.49002

Abstract

The importance of information about the weather, especially information about rainfall that is more precise is needed so that research is needed to estimate and predict the occurrence of rain. There have been many studies reporting how to identify rainfall forecasts, but they still have limitations, especially in identifying rainfall in detail in each province in Indonesia. In this study, forecasting rainfall in Kendari City was carried out using two different time series methods, namely the trend method and the exponential smoothing method. The use of these two different methods was carried out with the aim of comparing the accuracy of the two models in predicting time series data, especially rainfall data in Kendari City. This research was conducted from January 2023 to June 2023, using rainfall data from Kendari City. In this study, the following conclusions were obtained: 1) the volume of monthly rainfall in Kendari City fluctuated, which spread in the range of 0 – 578.60 mm with an average of 228.26 mm per month, where on average the highest rainfall occurred in June and the lowest rainfall occurred in October; 2) the Trend method, whether it's Linear Trend, Quadratic Trend or Exponential Growth Trend, is not appropriate for estimating and forecasting Kendari City's monthly rainfall because the resulting estimate has quite high residuals with a relatively low level of accuracy; 3) the Winter's Exponential Smoothing method is quite good for estimating and forecasting Kendari City's monthly rainfall because the resulting estimate has quite low residuals, with a relatively high degree of accuracy; and 4) based on the RMSE, MAE and BIC criteria, it shows that the Winter's Exponential Smoothing model with an alpha (level) parameter value of 0.85, a gamma (trend) of 0.05 and a delta (seasonal) of 0.001 provides a better level of estimation and forecasting accuracy when compared to the Trend model, both Linear Trend and Quadratic Trend. Keywords: Rainfall, exponential smoothing, trend method, time series
Co-Authors Alfian Alfian Aswani, Aswani Bakti Sadewa, Muhammad Alfian Dwiyanto, M. Riski Imam Gubu, La Hermanto Hermanto Jufra, Arlita Aristianingsih Jufra, Jufra Nerru Pranuta Murnaka, Nerru Pranuta Samsul Arifin Wayan Somayasa