PERBANDINGAN METODE DOUBLE MOVING AVERAGE, WEIGHTED MOVING AVERAGE, DAN DOUBLE EXPONENTIAL SMOOTHING PADA PERAMALAN RATA-RATA KEHADIRAN PEKERJA WFH DAN WFO (Studi Kasus PT. Pertamina (Persero))

NABILA AMANDA, . (2023) PERBANDINGAN METODE DOUBLE MOVING AVERAGE, WEIGHTED MOVING AVERAGE, DAN DOUBLE EXPONENTIAL SMOOTHING PADA PERAMALAN RATA-RATA KEHADIRAN PEKERJA WFH DAN WFO (Studi Kasus PT. Pertamina (Persero)). Sarjana thesis, UNIVERSITAS NEGERI JAKARTA.

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Abstract

Kasus pneumonia misterius ditemukan di Wuhan, China pada Desember 2019. Setelah diteliti oleh WHO, penyakit ini disebut penyakit Coronavirus Disease (Covid-19). Pandemi Covid-19 yang menyerang dunia mengakibatkan perubahan kebiasaan pada setiap kegiatan yang dilakukan masyarakat. Salah satu upaya dan kebijakan pemerintah dalam menurunkan angka positif Covid-19 adalah menerapkan WFH. Hal tersebut membuat cara dan ritme kerja menjadi berubah dan dinilai memberikan banyak keuntungan bagi para pekerja dan perusahaan. Oleh karena itu, dilakukan peramalan jumlah pekerja WFH dan WFO untuk membantu perusahaan dalam mengambil keputusan untuk menerapkan agile working. Metode yang dapat digunakan adalah Double Moving Average,Weighted Moving Average, dan Double Exponential Smoothing. Penelitian ini bertujuan untuk mencari model terbaik yang dibentuk dari data rata-rata pekerja WFH dan WFO periode September 2021 sampai November 2022 dan memprediksi untuk 5 periode ke depan. Jenis penelitian ini adalah studi pustaka. Data yang digunakan adalah rata-rata pekerja WFH dan WFO PT Pertamina (Persero). Teknik perhitungan hasil penelitian ini menggunakan bantuan software Microsoft Excel. Setelah dilakukan peramalan menggunakan metode Double Moving Average, Weighted Moving Average, dan Double Expo�nential Smoothing, dapat disimpulkan bahwa model terbaik untuk rata- rata jumlah pekerja WFH menggunakan metode Double Moving Average (3×3) dengan nilai MAPE 4,46% dan rata-rata jumlah pekerja WFO menggunakan metode Double Exponential Smoothing alpha 0,9 dengan nilai MAPE 5,90%. Berdasarkan hasil peramalan untuk 5 periode berikutnya didapatkan untuk rata-rata jumlah pekerja WFH terjadi kenaikan sedangkan rata-rata jumlah pekerja WFO terjadi penurunan A mysterious case of pneumonia was discovered in Wuhan, China in December 2019. After being researched by WHO, this disease is called Coronavirus Disease (Covid-19). The Covid-19 pandemic that has attacked the world has resulted in changes in habits in every activity carried out by the community. One of the government’s efforts and policies in the positive cases of Covid-19 is to implement a WFH. This makes the way and rhythm of work change and is considered to provide many benefits for workers and companies. Therefore, forecasting the average attandance of WFH and WFO workers is carried out to assist companies in making decisions to implement agile working. The methods that can be used are Double Moving Average, Weighted Moving Average, and Double Exponential Smoothing. This study aims to find the best model formed from data on the average attandance of WFH and WFO workers for the period of September 2021 to November 2022 and predict for the next 5 periods. This type of research is a literature study. The data used is the average attandance of WFH and WFO workers of PT Pertamina (Persero). The calculation technique of the results of this study uses the help of Microsoft Excel software. After forecasting using the Double Moving Average, Weighted Moving Average, and Double Exponential Smoothing methods, it can be concluded that the best model for the number of WFH workers uses the Double Moving Average (3×3) method with a MAPE value of 4.46% and the average attandance of WFO workers uses the Double Exponential Smoothing alpha method of 0.9 with a MAPE value of 5.90%. Based on the forecasting results for the next 5 periods, the average attandance of WFH workers has increased while the number of WFO workers has decreased.

Item Type:	Thesis (Sarjana)
Additional Information:	1). Dr. Yudi Mahatma, M.Si. ; 2). Ibnu Hadi, M.Si.
Subjects:	Sains > Matematika
Divisions:	FMIPA > S1 Matematika
Depositing User:	Users 17679 not found.
Date Deposited:	07 Mar 2023 05:39
Last Modified:	07 Mar 2023 05:39
URI:	http://repository.unj.ac.id/id/eprint/37960

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