Akurasi Model Hybrid ARIMA-Artificial Neural Network dengan Model Non Hybrid pada Peramalan Peredaran Uang Elektronik di Indonesia

Susila, Muktar Redy; Santoso, Bambang Hadi

doi:10.34312/jjom.v5i1.14889

Cited by 3 publications

(4 citation statements)

References 12 publications

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“…Kriteria penilaian uji beda adalah apabila nilai Sig. atas hasil pengujian adalah kurang dari 0,05, maka dapat dinyatakan terdapat perbedaan antara efisiensi kedua bank (Susila, 2023;Susila et al, 2023). Langkah awal analisis data yaitu menghitung nilai statistik deskriptif untuk variabel input dan output dari bank umum konvensional milik pemerintah dan milik swasta untuk tahun 2018 hingga 2022.…”

Section: Metode Penelitianunclassified

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Komparasi Efisiensi Bank Umum Konvensional Pemerintah dan Bank Umum Konvensional Swasta dengan Pendekatan Data Envelopment Analysis

Susila,

Nugroho,

Arini

2024

JSEB

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The research aim is to compare the level of efficiency between government-owned conventional commercial banks and privately owned conventional commercial banks. The samples are government-owned and privately owned conventional commercial banks registered in the period 2018 to 2022. The input variables used are deposits, labor costs and fixed assets; while output variables include total credit and operating income. Efficiency scores were analyzed using the data envelopment analysis method, and for the difference test the Mann-Whitney method was used. The results show that there is no significant difference in efficiency scores between government-owned conventional commercial banks and privately owned conventional commercial banks.

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Section: Metode Penelitianunclassified

“…Kriteria penilaian uji beda yaitu apabila nilai Sig. adalah kurang dari 0,05, maka dinyatakan terdapat perbedaan antara efisiensi kedua bank (Susila et al, 2023).…”

Section: Metode Penelitianunclassified

Komparasi Efisiensi Bank Umum Konvensional Pemerintah dan Bank Umum Konvensional Swasta dengan Pendekatan Data Envelopment Analysis

Susila,

Nugroho,

Arini

2024

JSEB

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“…Model tersebut menggunakan input lag dan error dari data dan model. Keunggulan dari model ARIMA yaitu dalam penentuan input lag dan error dapat menggunakan uji secara statistik [10].…”

Section: Pendahuluanunclassified

Implementasi Model Autoregressive Integrated Moving Average pada Proyeksi Komoditas Ekspor Timah

Dalimunthe,

Aldila

2023

Jambura J. Math

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The Bangka Belitung Archipelago is a potential area in the mining sector because many soils contain tin minerals and minerals that are spread evenly. Based on this phenomenon, this study uses the ARIMA model to analyze the prediction of the number of tin export commodities in the Bangka Belitung Islands Province. The time series data used in this study begins in January 2020 and ends in September 2022, with projected results ending in June 2023. Based on the analysis results, it is found that the ARIMA model (1,1,0) is the best model that can be used to project the value of tin export commodities in the Bangka Belitung Islands Province. This model was selected through the results of the correlogram test, which shows that the data is cut off at the second lag for the Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) plots. This projection analysis was carried out after passing the stationarity test first through the Augmented Dicky Fuller (ADF) test. Through this test, it is found that the data is stationary at the first difference, and the prob value is 0.0003 with the projected result that there will be an increase in the number of exports of tin commodities with a total increase of 0.03%. The results of this analysis can certainly be part of preventive actions for the government to be able to assist the country in increasing the country’s foreign exchange through increasing export commodities.

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“…To get the results of river water level prediction, input that describes rainfall conditions is needed. One method that has high accuracy to predict a future event is the hybrid model (Susila, 2021). The way the hybrid method works is to combine several forecasting methods or models into one output of forecast results.…”

Section: Introductionmentioning

confidence: 99%

Smart Disaster Mitigation: The Role of IoT and Machine Learning

Nur Laily,

Juwita Sari,

Muktar Redy Susila

2023

int.jour.sci.res.mana

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This prototype output research has the aim of creating a dashboard that is used to monitor river water levels. The dashboard created will display data in real-time and prediction results. The use of the dashboard is to minimize the risk in the event of flooding caused by river overflow. The way this prototype works is to take data from sensors that have been installed at several points. The recorded data will be stored in a database using the working principles of the Internet of Things. For predictions, machine learning is used to produce future river water level figures. The machine learning used is using time series regression with rainfall input and river water level output. Long-term output data is needed, therefore to forecast future rainfall the Hybrid method is used. Data generated from sensors as well as from prediction results are stored in one database. From the database, data visualization is displayed along with important figures used for river overflow intelligence. Therefore, the dashboard is very useful for people living around the river flow.

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Akurasi Model Hybrid ARIMA-Artificial Neural Network dengan Model Non Hybrid pada Peramalan Peredaran Uang Elektronik di Indonesia

Cited by 3 publications

References 12 publications

Komparasi Efisiensi Bank Umum Konvensional Pemerintah dan Bank Umum Konvensional Swasta dengan Pendekatan Data Envelopment Analysis

Komparasi Efisiensi Bank Umum Konvensional Pemerintah dan Bank Umum Konvensional Swasta dengan Pendekatan Data Envelopment Analysis

Implementasi Model Autoregressive Integrated Moving Average pada Proyeksi Komoditas Ekspor Timah

Smart Disaster Mitigation: The Role of IoT and Machine Learning

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