Prediksi Jumlah Pelanggaran Hukum Di Laut Indonesia Menggunakan Metode Double Exponential Smoothing

Lumaksono, Heru; Hozairi, Hozairi; Buhari, Buhari; Tukan, Markus

doi:10.36040/mnemonic.v3i1.2525

Cited by 4 publications

(4 citation statements)

References 2 publications

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“…Menurut Sbrana & Silvestrini (2020) [7] peramalan yang diperoleh dengan metode Double Exponential Smoothing Holt menghasilkan tren yang tidak terbatas. Dengan hasil prediksi melebihi dari data aktual, terutama selama periode peramalan jangka panjang seperti pada penelitian Lumaksono et.al (2020) yang menghasilkan kesalahan yang besar [8].Gardner dan Mackenzie memperkenalkan parameter untuk meredam tren menuju ke garis datar pada tahap berikutnya [9]. Metode Damped Trend dibangun dengan menambahkan parameter (phi).…”

Section: Pendahuluanunclassified

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Maulidiyah

2023

jik

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Stocks are one of the capital market transactions that are the choice of investors and traders. Investors and traders need strategies to profit from stocks to reduce losses. One of the predictions of future stock price movements is by using the time series method approach. DES Holt method is a stock price prediction method from time series data. However, Holt's DES method has the problem of overcasting, which needs to be mitigated by using Damped Trend. This study uses DES Holt and Damped Trend to determine the effect of Damped Trend in reducing trend forecasting. DES Holt's application uses two parameters, namely alpha and beta. Damped Trend uses three parameters, namely alpha, beta, and phi, which are performed on four stock data. The results of the study using the DES Holt method on the TLKM dataset achieved an accuracy value of 91.1693%, the MDKA dataset achieved an accuracy of 84.9775%, the HMSP dataset had an accuracy value of 92.2785%, the KLBF dataset achieved an accuracy of 92.5582%. The results of the study using Damped Trend on the TLKM dataset achieved an accuracy of 96.3035%, the MDKA dataset had an accuracy of 94.4714%, the HMSP dataset had an accuracy of 92.4587%, and the KLBF dataset had an accuracy of 98.0674%. The results of the comparison show that the Damped Trend method is able to increase the accuracy of the four datasets. The increase in the accuracy of the four datasets for TLKM data was 5.1342%, MDKA 9.4938%, and HMSP 0.1802% and the increase in KLBF accuracy was 5.5092%.

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Section: Pendahuluanunclassified

Untitled

Maulidiyah

2023

jik

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“…Metode ini juga digunakan untuk melakukan peramalan dengan cara menentukan besarnya α (alpha) yang paling optimal. Parameter yang digunakan pada metode ini yaitu α (alpha yang memiliki nilai antara 0 dan 1) [8].…”

Section: Metode Double Exponential Smoothingunclassified

Sistem Peramalan Penjualan Pakaian Wanita Menggunakan Metode Double Exponential Smoothing

Adrian Rahma Chiesa,

Achmadi,

Dedy Irawan

2023

jati

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IME Female Fashion merupakan salah satu toko fashion wanita di Indonesia. Sistem peramalan penjualan pada produk pakaian wanita di IME Female Fashion menggunakan metode Double Exponential Smoothing. Peran dari metode ini akan dijangkau secara mendetail yang mencakup rancangan sistem peramalan penjualan pakaian wanita menggunakan metode Double Exponential Smoothing berbasis Website. Proses penerapan metode Double Exponential Smoothing dalam peramalan penjualan pakaian wanita di IME Female Fashion juga akan diperhatikan secara lebih terperinci. Data Aktual yang digunakan untuk peramalan penjualan ini diambil selama 1 Tahun. Proses peramalan penjualan produknya dilengkapi efektifitasnya oleh metode Double Exponential dan pengujian black box di akhir analisis peramalan penjualan produknya. Pada akhirnya, peran metode Double Exponential Smoothing secara lebih lanjut akan dijabarkan dalam keberhasilannya meramalkan penjualan pakaian wanita di IME Female Fashion untuk 5 hari kedepan

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“…There are various forecasting methods that have been used to predict the number of law violations, including Double Exponential Smoothing (ES) [3], Triple Exponential Smoothing [4], Fuzzy Logic [5], Exponential Smoothing [6]. In addition, the use of forecasting methods to predict the number of law violations has been practiced in various places such as the Indonesian seas [3], Probolinggo Regency, and Batam City.…”

Section: Introductionmentioning

confidence: 99%

Maintaining Religious Harmony through Predicting the Level of Lawlessness using Linear Regression

Wardana,

Aldamawan,

Lillah

et al. 2023

Khazanah Journal of Religion and Technology

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Crimes are basically committed due to low human faith and ultimately disrupt harmony, including inter-religious harmony. Therefore, the purpose of this study is to predict and determine the number of law violations that occurred in Yogyakarta Province in 2022 as a case study using a linear regression algorithm based on data ranging from 2012 to some of the data on law violations in 2022. The method used is the forecasting method in which the stages of data collection, data preprocessing, data modeling, and prediction processes are carried out. The accuracy of the linear regression model is 90%. However, there is a difference in accuracy between the training data and the test data. The training data gets an accuracy of 99% while the accuracy achieved by the test data is at 94% which is 5% lower than the training data. The prediction results using the linear regression model shows the number of the data on law violation that will occur in 2022 with correlation between crimes.

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Prediksi Jumlah Pelanggaran Hukum Di Laut Indonesia Menggunakan Metode Double Exponential Smoothing

Cited by 4 publications

References 2 publications

Untitled

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Sistem Peramalan Penjualan Pakaian Wanita Menggunakan Metode Double Exponential Smoothing

Maintaining Religious Harmony through Predicting the Level of Lawlessness using Linear Regression

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