scholarly journals Metode Exponential Smoothing Pada Peramalan Tingkat Kriminalitas Pencurian Sepeda Motor

2021 ◽  
Vol 1 (1) ◽  
pp. 15-20
Author(s):  
Novianti Novianti ◽  
Muhammad Amin ◽  
Wan Mariatul Kifti

Abstract : This study aims to determine thecrime rate in motorbike theft cases using the programmeing langiage PHP and MySQL as a database and the application of the Exponential Smoothing method to determine the crime rate of motorcycle theft that occurs in the city of Tanjung Balai for the next period. The data used in this study is motorcycle theft report data from 2018 to 2019 wich was obtained from the Tanjung Balai Police. The benefits of this research can be used by the Tanjung Balai police to determine the extent of the motorcycle theft crime that will occur in a shorter, easier and more accurate manner so that it can take optimal prevention. With the Exponential Smoothing method the alpha value will be searched randomly to find an alpha value that was a minimum error value calculated using Means Absolute Percetage Error (MAPE). Then the prediction results that have an alphan with a minimum error are the best of recommended as a prediction result for the next period. Based on this research, the prediction results obtained from the prediction of the number of motorcycle theft cases the occurred in the city of Tanjung Balai in 2020 were 12 units with an MAPE error value of 0,153%. Keyword : Exponential Smoothing, Theft, Motorcycle, Forecasting  Abstrak : Penelitian ini bertujuan untuk menentukan tingkat kriminalitas kasus pencurian sepeda motor dengan menggunakan bahasa pemrograman PHP dan MySQL sebagai basis data serta penerapan metode Exponential Smoothing untuk menentukan tingkat kriminalitas pencurian sepeda motor yang terjadi di kota Tanjung Balai untuk periode berikutnya. Data yang digunakan dalam penelitian ini adalah data laporan pencurian sepeda motor dari tahun 2018 sampai dengan tahun 2019 yang diperoleh dari POLRES Tanjung Balai. Manfaat dari penelitian ini dapat digunakan oleh kepolisian Tanjung Balai untuk menentukan seberapa besar tindak kriminalitas pencurian sepeda motor yang akan terjadi secara lebih singkat, mudah dan akurat sehingga dapat melakukan pencegahan yang optimal. Dengan metode Exponential Smoothing  akan dicari nilai alpha secara acak sampai menemukan nilai alpha yang memiliki nilai error yang minimum yang dihitung menggunakan Means Absolute Percetage Error (MAPE). Maka hasil prediksi yang memiliki alpha dengan error minimumlah yang paling baik atau direkomendasikan sebagai hasil prediksi untuk periode selanjutnya. Berdasarkan penelitian ini diperoleh hasil prediksi peramalan jumlah kasus pencurian sepeda motor yang terjadi di kota Tanjung Balai tahun 2020 adalah 12 unit dengan nilai error MAPE sebesar 0,153%. Kata Kunci : Exponential Smoothing, Pencurian, Sepeda Motor, Forecasting

2013 ◽  
Vol 13 (1) ◽  
pp. 68
Author(s):  
Romy Biri ◽  
Yohanes A.R Langi ◽  
Marline S Paendong

PENGGUNAAN METODE SMOOTHING EKSPONENSIAL DALAM MERAMAL PERGERAKAN INFLASI KOTA PALU ABSTRAK Penelitian dilakukan untuk mengetahui pergerakan inflasi dan meramal pergerakan inflasi di Kota Palu. Data pergerakan inflasi ini berjumlah 160 data bulan pengamatan, dari januari 2000 sampai april 2013. Peramalan pergerakan inflasi di Kota Palu sebesar 0,2683 persen, artinya pergerakan inflasi di Kota Palu kembali mengalami penurunan dari periode bulan sebelumnya. Data peramalan pergerakan ini, tidak mengalami perbedaan yang signifikan di bandingkan dengan data yang di keluarkan oleh Badan Pusat Statistika di kota tersebut. Kata kunci : Meramal Pergerakan Inflasi, Smoothing Eksponential tunggal THE USING OF EXPONENTIAL SMOOTHING METHOD TO PREDICT INFLATION MOVEMENT FROM PALU CITY ABSTRACT The Research was conducted to determine the movement of inflation and predicting it in Palu. The data of inflation movement numbered 160 data observation month, from January 2000 until April 2013. Predicting the movement of inflation in Palu of 0,2683 percent, it means the movement of inflation in Palu decreased again from month period previously. The data of these movement, not significant difference in comporison with the data that released by Central Statistical Corporation in the city. Keywords : Predicting the Movement of Inflation, Single Exponential Smoothing


2020 ◽  
Vol 18 (2) ◽  
pp. 277
Author(s):  
Khoirin Azaro ◽  
Nur Indah Riwajanti ◽  
Anik Kusmintarti

This research aims to predict the number of train and airplane passengers in 2020. Forecasting of train and airplane passengers is interest to analyze and estimate consumer demand to help the train or airline company prepare effective and efficient planning. This type of research is descriptive quantitative and uses data taken from the Indonesian Statistic Agency (BPS). Data were analyzed using Exponential smoothing Method. Train and airplane passenger data shows trend and seasonal patterns so that the exponential method used is Triple Exponential smoothing. The results of the study show that train passengers in 2020 are increase. While forecast results related to aircraft passengers in 2020 also tend to increase.


2019 ◽  
Vol 125 ◽  
pp. 23006
Author(s):  
Dyna Marisa Khairina ◽  
Aqib Muaddam ◽  
Septya Maharani ◽  
Heliza Rahmania

Setting the target of groundwater tax revenues for the next year is an important thing for Kutai Kartanegara Regional Office of Revenue to maximize the regional income and accelerate regional development. Process of setting the target of groundwater tax revenue for the next year still using estimation only and not using a mathematical calculation method that can generate target reference value. If the realization of groundwater tax revenue is not approaching the target, the implementation of development in the Government of Kutai Kartanegara can be disrupted. The mathematical method commonly used to predict revenue value is the Single Exponential Smoothing (SES) method, which uses alpha constant value which is randomly selected for the calculation process. Forecasting of groundwater tax revenue for 2018 using groundwater tax revenue data from 2013 to 2017. Single Exponential Smoothing method using alpha constant value consists of 0.1, 0.2, 0.3, 0.4 and 0.5. The forecasting error value of each alpha value is calculated using the Mean Absolute Percentage Error (MAPE) method. The best result is forecasting using alpha value 0.1 with MAPE error value was 45.868 and the best forecasting value of groundwater tax for 2018 is Rp 443.904.600,7192.


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