Analisis Curah Hujan Bulanan Di Kota Ambon  Menggunakan Model Heteroskedastisitas: Sarima-Garch

Sinay, Lexy J.; Lembang, Ferry Kondo; Aulele, Salmon N.; Mustamu, Dominique

doi:10.14710/medstat.13.1.68-79

Cited by 5 publications

(3 citation statements)

References 5 publications

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“…Multiple regression analysis is a type of analysis that involves more than one independent variable. Multiple linear regression analysis makes it easy for users to enter more than one independent variable up to (k), as long as the number of (k) is less than the number of observations (n) (Sinay et al, 2020)…”

Section: Multiple Regression Analysismentioning

confidence: 99%

Perceptions and Learning Motivation of Indonesian Students: Multiple Regression Analysis of The Practice of Organizing Film Festivals in Indonesia

Undiana,

Abdullah,

Agustin

et al. 2024

J. of Law and Sust. Develop.

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Purpose: The purpose of this study is to investigate the forms of events that occur in a film festival where the audience is at the center of the dynamics of the contemporary environment. Theoretical reference: Nowadays, the development of the practice of curation is not only seen in activities at museums and art exhibitions, but also in the practice of other activities, such as film festivals. The selection process, work selection, and archiving are all key steps in the process of fusing ideas with the aesthetic form that will be shown. Thus, this study aims at exploring the events form where the audience is at the center of the dynamics of the contemporary environment in a film festival. Method: This study used a survey method involving 306 students with film concentrations from five state universities in Indonesia. The data were analyzed using Heteroscedasticity Test, Normality Test, One Sample Kolmogorov-Smirnov test, Multiple Regression Analysis, T-Test, and Simultaneous Test (F Test). Result and Conclusion: This study revealed that several factors influence perceptions and learning motivation shown by students in the practice of curating and reviewing films in the organization of film festivals. Implication of research: Based on the results of this study, the influence was considered insignificant; the researchers obtained 7.8% of the simultaneous effect of the variables of perception and learning motivation on the practice of organizing film festivals in Indonesia. Originality/value: In this study, the researchers seek to investigate new cultural forms in film festival programs, especially film festivals in Indonesia, to help them capture social concepts as inspiration for helping audiences understand the point of view at the film festival, as well as appreciation from the audience, stakeholders and filmmakers in exploring the form of events in the field during the film festival.

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Section: Multiple Regression Analysismentioning

confidence: 99%

Perceptions and Learning Motivation of Indonesian Students: Multiple Regression Analysis of The Practice of Organizing Film Festivals in Indonesia

Undiana,

Abdullah,

Agustin

et al. 2024

J. of Law and Sust. Develop.

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“…where 𝑑 is the number of references that make the time series data stationary. The ARIMA modelling procedure is given as follows [23] :…”

Section: 𝜙(𝐵)𝑦 𝑡 = 𝜃(𝐵)𝜀 𝑡mentioning

confidence: 99%

Forecasting The Composite Stock Price Index Using Autoregressive Integrated Moving Average Hybrid Model Artificial Neural Network

Sinay

Jaariyah

Lewaherilla

et al. 2022

Pattimura Int. J. Math.

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A stock index is a statistical measure that reflects the overall price movement of a group of stocks selected based on certain criteria and methodologies and evaluated regularly. JCI is included in the composite index, which is the Headline index. The Headline Index is an index that is used as the main reference to describe the performance of the capital market. The JCI is very important in describing the current condition of the capital market because the JCI measures the price performance of all stocks listed on the Main Board and Development Board of the IDX. This study aims to predict JCI data using the time series method. The hybrid Autoregressive Integrated Moving Average–Artificial Neural Network (ARIMA-ANN) model combines the linear ARIMA model and the non-linear ANN model. The best models are the ARIMA model (2,1,1) and the ANN Backpropagation model with one input layer, one hidden layer with 20 neurons, and one output. The ARIMA-ANN hybrid model accurately predicts JCI data because it produces a MAPE value of less than 1%, with the level of forecasting accuracy from testing results being smaller than the level of accuracy during training. In addition, the forecast for the next five days is very accurate because it produces a very small RMSE and a MAPE below 1%, respectively, namely 56.99 and 0.72%.

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“…Pada tahun 2021 dilakukan penelitian dari Set Sasake, Yopi Andry Lesnussa, dan Abraham Zakaria Wattimena menyatakan bahwa dengan menggunakan data curah hujan harian penelitian menggunakan metode rantai markov, peramalan dilakukan dengan melihat probabilitas sesuai cuaca hari sebelumnya [5]. Pada tahun 2017 dilakukan penelitian dari Zaenab Kafara, F. Y. Rumlawang, dan L. J. Sinay menyatakan bahwa curah hujan di kota Ambon tidak selalu memiliki pola musiman sehingga cukup besar perbandingan data aktual dan data peramalan [6] dan pada tahun 2019 Lexy Janzen Sinay, Ferry Kondo Lembang, Salmon Notje Aulele, dan Dominique Mustamu menyatakan bahwa selain musiman curah hujan di kota Ambon termasuk heteroskedatis sehingga penggunaan time series saja belum cukup [7].…”

Section: Pendahuluanunclassified

Prediksi Curah Hujan di Kota Ambon Menggunakan Metode Backpropagation

Leliak¹

2022

JATISI

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Sistem Jaringan Syaraf Tiruan dengan metode Backpropagation dapat digunakan untuk memprediksi curah hujan periode tahun depan berdasarkan pembelajaran pada data curah hujan periode tiga tahun sebelumnya dengan menggunakan error output untuk melakukan penyesuaian pada bobot sampai mendapat hasil yang diinginkan. Penelitian yang dilakukan adalah menggunakan metode backpropagation untuk prediksi curah hujan di Kota Ambon. Pada data pelatihan menunjukkan bahwa hasil prediksi data pelatihan tahun 2020 dengan menggunakan data 2019 sama dengan data curah hujan pada tahun 2020 karena itu dapat dikatakan data pelatihan memiliki akurasi 100% dengan menggunakan sistem pada data pelatihan dilakukan data pengujian untuk hasil prediksi 2021 dengan menggunakan data tahun 2020 hasil tersebut hampir mendekati data curah hujan 2021 dengan tingkat akurasi 80% dengan nilai MSE = 0.070945. Hasil prediksi curah hujan tahun 2022 dapat dipastikan memiliki akurasi 90% dilihat dari rata–rata akurasi data pelatihan dan data pengujian.

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Analisis Curah Hujan Bulanan Di Kota Ambon Menggunakan Model Heteroskedastisitas: Sarima-Garch

Cited by 5 publications

References 5 publications

Perceptions and Learning Motivation of Indonesian Students: Multiple Regression Analysis of The Practice of Organizing Film Festivals in Indonesia

Perceptions and Learning Motivation of Indonesian Students: Multiple Regression Analysis of The Practice of Organizing Film Festivals in Indonesia

Forecasting The Composite Stock Price Index Using Autoregressive Integrated Moving Average Hybrid Model Artificial Neural Network

Prediksi Curah Hujan di Kota Ambon Menggunakan Metode Backpropagation

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