Perbandingan Metode-metode Peramalan Statistika untuk Data Indeks Harga Pangan

Gunaryati, Aris; Fauziah, Fauziah; Andryana, Septi

doi:10.30998/string.v2i3.2200

Cited by 5 publications

(5 citation statements)

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“…Note the following Table 3. Based on the results of the study, the architecture of Artificial Neural Networks with hyperbolic tangent activation functions is more suitable and accurate [13]. These two studies are only different in terms of using the activation function namely LOGSIG by this present study.…”

Section: Methods Comparisonmentioning

confidence: 82%

Comparison of Accuracy and Predictive Results of ES-Holt Method and ANN-Back Propagation Method: Case Study of Number of Tourists

Syaharuddin¹,

Sihombing²,

Agustina³

et al. 2021

Proceedings of the 2nd International Seminar of Science and Applied Technology (ISSAT 2021)

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The COVID-19 pandemic has weakened many sectors, one of which is tourism. Almost all priority tourism locations of the government experience a significant decrease in the number of foreign and domestic visitors. This also impacts the level of welfare of the community around the tourism area. This study is conducted to compare the Exponential Smoothing (ES) Holt and Artificial Neural Network (ANN) Back Propagation methods. That aims to see how the effectiveness and accuracy of both methods to be applied to the predictive process of the number of tourist visits in North Maluku Province using the G-MFS-based MATLAB application. The data on the number of tourists were taken from the Central Statistics Agency of North Maluku Province in 2008-2019. The accuracy parameter indicates that the error for the Holt method has a MAPE value of 9.2976. As for the Back Propagation method, the error is smaller, with a MAPE value of 1.2585. From the results, in 2020 the number of tourists visiting North Maluku should have been around 13,868 people per month. This result can at least be compared to the number of real visitors in 2020 during the COVID-19 outbreak. There is a very high difference between what was predicted and what happened in the field. From the results of this research, it is expected that tourism-related parties or institutions can conduct further research and studies so that they can know the policies to be taken in order to increase the number of tourists visiting North Maluku Province.

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Section: Methods Comparisonmentioning

confidence: 82%

Comparison of Accuracy and Predictive Results of ES-Holt Method and ANN-Back Propagation Method: Case Study of Number of Tourists

Syaharuddin¹,

Sihombing²,

Agustina³

et al. 2021

Proceedings of the 2nd International Seminar of Science and Applied Technology (ISSAT 2021)

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“…When using the multiplicative method, it is assumed that the seasonal pattern increases as the data value increases. On the other hand, the additive method assumes that data values are centered around a constant width of trends (Gunaryati & Suhendra, 2015).…”

Section: Multiplicative Decomposition Methodsmentioning

confidence: 99%

Enhancing Demand Forecasting Accuracy for Electronic Components: A Case Study of PT Omron Indonesia

Rizqi Az Zahran,

Prayudha Hidayat

2024

JASTH

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In the dynamic realm of manufacturing, precise demand forecasting is crucial for optimizing supply chains and production processes. This study addresses PT Omron Indonesia's challenge of inaccurate demand forecasts leading to production disruptions. Utilizing the Plan-Do-Study-Act (PDSA) cycle, alongside Multiplicative Decomposition methods, the research aims to improve forecasting accuracy. Results indicate that the Multiplicative Decomposition - Centered Moving Average method yields a lower Mean Absolute Percentage Error (MAPE), though refinement is needed to meet set standards. The estimated demand for the next period is 1308 units, with a MAPE of 140%. The study concludes that iterative refinement of the selected method is essential for achieving higher forecasting accuracy. This research contributes to enhancing production efficiency and mitigating the impact of part shortages in the electronics industry.

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“…Data time series (runtun waktu) adalah data yang ditampilkan berdasarkan waktu, seperti data bulanan, data harian, data mingguan, data tahunan, atau jenis waktu adalah adanya rentang waktu tertentu dan bukannya data pada satu waktu tertentu [7]. Analisis time series adalah analisis yang mempertimbangkan pengaruh waktu secara beruntun.…”

Section: B Data Time Seriesunclassified

Prediksi Data Indeks Harga Konsumen Provinsi Riau Berbasis Time Series Dengan Metode Double Exponential Smoothing

Septiawati

Gusti

Syafria

et al. 2022

jipi. jurnal. ilmiah. penelitian. dan. pembelajaran. informatik

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5)ABSTRAK Indeks Harga Konsumen merupakan indeks yang menghitung rata-rata perubahan harga barang dan jasa. Penelitian ini menggunakan data Indeks Harga Konsumen Provinsi Riau bulan Januari tahun 1999 sampai dengan bulan Desember tahun 2021 yang bersumber dari website resmi Badan Pusat Statistik Provinsi Riau. Penelitian ini bertujuan untuk memberikan gambaran tentang perkembangan indeks harga konsumen apakah mengalami kenaikan atau penurunan sehingga dapat dijadikan sebagai bahan evaluasi kebijakan yang akan diambil oleh pihak pemerintah, swasta, maupun pemegang otoritas moneter. Tahapan untuk prediksi dengan menggunakan metode double exponential smoothing yaitu menghitung nilai pemulusan tunggal (single smoothing), menghitung pemulusan ganda (double smoothing), menghitung nilai konstanta pemulusan, menghitung nilai kofisien trend, dan melalukan prediksi. Untuk melakukan pengujian prediksi maka dilakukan dengan cara perhitungan mean absolute percentage error. Berdasarkan perhitungan yang telah dilakukan, diperoleh hasil prediksi nilai indeks harga konsumen sebesar 105,17 dengan alpha 0,6 bernilai 3,132646%. Dapat disimpulkan bahwa metode double exponential smoothing mempunyai kemampuan yang baik dalam prediksi nilai indeks harga konsumen.

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Perbandingan Metode-metode Peramalan Statistika untuk Data Indeks Harga Pangan

Cited by 5 publications

References 0 publications

Comparison of Accuracy and Predictive Results of ES-Holt Method and ANN-Back Propagation Method: Case Study of Number of Tourists

Comparison of Accuracy and Predictive Results of ES-Holt Method and ANN-Back Propagation Method: Case Study of Number of Tourists

Enhancing Demand Forecasting Accuracy for Electronic Components: A Case Study of PT Omron Indonesia

Prediksi Data Indeks Harga Konsumen Provinsi Riau Berbasis Time Series Dengan Metode Double Exponential Smoothing

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