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ANALISIS PERENCANAAN PRODUKSI MENGGUNAKAN METODE
FORECASTING
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Alviyanur
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Abstrak
Kegiatan produksi memerlukan peramalan yang tepat dan perencanaan keseluruhan untuk
mengatasi masalah peramalan permintaan bahwa penjualan dapat menurun atau meningkat dari
waktu ke waktu di masa depan. Penelitian ini bertujuan untuk memaksimumkan tingkat
pelayanan pelanggan, meminimumkan investasi inventori dan efisiensi operasi.Penelitan ini
menggunakan metode peramalan menggunakan data masa lalu dengan menggunakan 2 metode
perhitungan, yaitu menggunakan metode Moving Average dan Exponential Smoothing untuk
meramalkan produksi kayu gergajian yang di produksi oleh CV. Diki Putra di Kec. Sebulu Kutai
Kartanegara. Unit usaha ini telah berdiri dari tahun 2008 hingga sekarang, dalam perencanaan
produksi yang selama ini digunakan menggunakan metode perhitungan musim yaitu, musim
kemarau dan musim penghujan sehingga terjadi kelangkaan bahan baku disaat musim tertentu
padahal jumlah stok kayu di Kalimantan timur masih memadai untuk produksi kayu olahan, maka
dari itu dilakukan peramalan dengan metode perhitungan Moving Average 6 bulanan dan
Exponential Smoothing α = 0.9 dengan 3 alat ukur ketepatan data yaitu Mean Absolute Deviation,
Mean Square Error, dan Mean Absolute Percentage Error. Setelah dianalisis diperoleh hasil
bahwa Exponential Smoothing lebih tepat digunakan karena mendekati nilai riil jumlah produksi
selama ini dengan hasil Exponential Smoothing dengan total 114.176M^3setiap bulannya dengan
nilai MAD 1.480, MSE 3.232.175, dan nilai MAPE 1,35%.
Kata kunci: Metode Musiman; Peramalan; Moving Average; Exponential Smoothing
Abstract
Production activities require precise forecasting and overall planning to address the problem of
forecasting demand that sales may decline or increase over time in the future. This study aims to
maximize the level of customer service, minimize inventory investment and operating efficiency.
This research uses a forecasting method using past data using 2 calculation methods, namely using
the Moving Average and Exponential Smoothing methods to forecast the production of sawn timber
produced by CV. Diki Putra in Kec. Sebulu Kutai Kartanegara. This business unit has been
established since 2008 until now, in production planning which has been using the seasonal
calculation method, namely, the dry season and the rainy season so that there is a shortage of raw
materials during certain seasons even though the amount of wood stock in East Kalimantan is still
adequate for the production of processed wood. Therefore, forecasting is carried out using the 6-
month Moving Average and Exponential Smoothing = 0.9 with 3 data accuracy measurement tools,
namely Mean Absolute Deviation, Mean Square Error, and Mean Absolute Percentage Error.
After analyzing the results, it was found that Exponential Smoothing is more appropriate because
it is close to the real value of the amount of production so far with Exponential Smoothing results
with a total of 114.176M^3 per month with a MAD value of 1.480, MSE 3.232.175, and a MAPE
value of 1.35%.
Keywords: Seasonal Method; Forecasting; Moving Averages; Exponential Smoothing
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Data Produksi 2018-2020
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Perbandingan untuk Hasil Prediksi yang Tepat
B.(4.C)O&0!G.C-,.!6.')G)*)(!)C)&!O)/0*!6'.,03/0!I)(4!6)*0(4!C.6)C!,.(4)(!K)')!
G.GN)(,0(43)(!)(C)'!G.C-,.!I)0C&!
!
2)N.*!"@!M.'N)(,0(4)(!M.')G)*)(!
Metode
Akurasi Peramalan
MAD
MSE
MAPE
Moving Average
11.51
8
209.304.48
9
10,87%
Exponential
Smoothing
1.480
3.232.175
1,35%
1&GN.'!5!,)C)!,0-*)OA!#<##@!
!
Dapat dilihat dari tabel perbandingan diatas bahwa metode exponential smoothing
D " /B1
memiliki nilai akurasi peramalan (forecast error) yang sangat baik dibandingkan
dengan metode moving average dengan nilai MAD 1.480, MSE sebesar 3.232.175, dan
MAPE 1,35% atau memiliki nilai terkecil dibandingkan metode moving average 6
bulanan. Maka dalam penelitian ini metode exponential smoothing
D " /B1
akan
digunakan untuk memperediksi perencanaan produksi kayu penggergajian CV. Diki Putra
untuk tahun 2021-2023. Jadi hasil peramalan perencanaan produksi kayu penggergajian
siap pakai CV. Diki Putra untuk tahun 2021-2023 setiap bulannya adalah 114.176
!
!
.
!
Analisis Metode Musiman dan Metode Forecasting
L*E0I)(&'!
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3./)*)O)((I)!,)'0!G.C-,.!moving averageA!-*.O!3)'.()!0C&!G.C-,.!exponential smoothing!
,04&()3)(!&(C&3!G.')G)*3)(!6.'.(K)())(!6'-,&3/0!3)I&!4.'4)S0)(@!!
!
Kesimpulan
M.'.(K)())(!6'-,&3/0! I)(4! /.*)G)!0(0! ,04&()3)(! ),)*)O!/0/C.G! G&/0G)(!I)0C&A!!
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N&*)C! I)(4! ,0,)C)(43)(! ,)'0! O&*&! /&(4)0! G)O)3)G! G.(4)*)G0! 3.(,)*)! 3.! C.G6)C!
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3.6&C&/)(@!Q.',)/)'3)(!G.C-,.!forecasting S&G*)O!6.G)3)0)(!N)O)(!N)3&!N0/)!,0&3&'!
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average!,)(!exponential smoothing!,06.'-*.O!O)/0*!N)OF)!G.C-,.!6.')G)*)(!I)(4!6)*0(4!
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L()*0/0/!M.'.(K)())(!M'-,&3/0!B.(44&()3)(!B.C-,.!Forecasting!
":$ Jurnal Indonesia Sosial TeknologiA!?-*@!:A!8-@!:A!B)'.C!#<##!
),)*)O!G.C-,.!exponential smoothing!,.(4)(!C-C)*!WW"@W9$Ba:!/.C0)6!N&*)((I)!,.(4)(!
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Y030!M&C')!C.*)O!G.(K)6)0!C)'4.C!6'-,&3/0!I)(4!,0'.(K)()3)(@!
Bibliografi
!
L'03&(C-A! 1&O)'/0G0@! #<<#@! \B.C-,-*-40! M.(.*0C0)(! 1&)C&! M.(,.3)C)(! M'-6-/)*@]!
Jakarta: PT. Rineka Cipta@!
Q0.4.*A!%-O(A!H@!#<<<@!\M.(4.(,)*0)(!M'-,&3/0!5!1&)C&!M.(,.3)C)(!R&)*0C)C0P@]!Jakarta:
Akademika Pressindo@!
H,,IA!V.'S)(C-@!#<<b@!Manajemen Operasi (Edisi 3)@!o')/0(,-@!
[')(3*0(A! 1C.6O.(! o@A! )(,! o.-'4.! d@! 2.''I@! #<<<@! Principios de Administración@!
f-G6)0)@!
[-4)'CIA!Y-()*,!^@A!.C!)*@!W==W@!Production & Inventory Management@!1-&CO;^./C.'(!
M&N*0/O0(4!f-@@!
o)/6.'/eA! ?0(K.(C@! W==b@! \M'-,&KC0-(! M*)((0(4! )(,! +(E.(C-'I! f-(C'-*! Q.',)/)'3)(!
M.(,.3)C)(! 10/C.G! 2.'0(C.4')/0! BdM! ++! Y)(! %+2! B.(&S&! B)(&P)3C&'0(4! #W@]!
Jakarta: Gramedia Pustaka Utama@!
!V.0e.'A! %)IA! .C! )*@! #<W>@! Dirección de La Producción y de Operaciones: Decisiones
Estratégicas@!M.)'/-(!.,&K)K0p(@!
+(,)OA!Y.F0!d-/)A!)(,!HE0!d)OG),)(0@!#<Wb@!\10/C.G![-'.K)/C0(4!M.'.(K)())(!M'-,&3/0!
Y.(4)(!B.C-,.!10(4*.!H3/6-(.(/0)*!1G--CO0(4!M),)!R.'0603!10(43-(4!1'03)(,0!
Y0!R-C)!U)(4/)@]!Jurnal Penelitian Ekonomi Akutansi (JENSI)A!E-*@!#A!(-@!WA!66@!W<7
Wb@!
+')F)(A!V.'0!2'0A!.C!)*@!#<#<@!qM.(44&())(!Moving Average!,)(!Exponential Smoothing!
&(C&3! B.G6'.,03/0! R.N&C&O)(! Q.')/! d)/30(! ,0! R-C)! Q)(,)! LK.O@q! Jurnal
Optimalisasi,E-*@!$!A!(-@!#@!
U..A! fO.(4;[.FA! .C! )*@! #<W$@! Essentials of Excel, Excel VBA, SAS and Minitab for
Statistical and Financial Analyses@!16'0(4.'@!
c3C)'0I)(C-A!Q.((I@!#<#<@]M.'*&!M.',)!M.'.,)')(!R)I&]@!Y0)3/./!6),)!##!8-E.GN.'!
#<#<@!FFF@(-G-'/)C&3)*C0G@K-G!
M)(4./C03)A! ^0C,I)@! #<W=@! \B.(4.()*! B.C-,.! Forecasting! &(C&3! R.6.(C0(4)(! Q0/(0/!
L(,)]@!Y0)3/./!6),)!<#!c3C-N.'!#<#<@!FFF@S&'()*@0,!
M-'C)*! B.,0)! M.(4.C)O&)(! c(*0(.A! 1.6&C)'! M.(4.C)O&)(@! \! M.(4.'C0)(! M.')G)*)(!
XForecastingZA!2&S&)(A![&(4/0A!B)(P))CA!B.C-,.!r!%.(0/(I)]@!Y0)3/./!6),)!C)(44)*!
W:!1.6C.GN.'!#<#<@!FFF@/.6&C)'6.(4.C)O&)(@K-@0,!
M')/.CI)F)(A! k&,O)A! )(,! L'G)(! V)30G! 8)/&C0-(@! #<<b@! Perencanaan Dan
Pengendalian Produksi@!k-4I)3)'C)5!o')O)!+*G&@!
1.3)')(A!DG)A!)(,!d-4.'!Q-&40.@!#<W9@!B.C-,.!M.(.*0C0)(!D(C&3!Q0/(0/!M.(,.3)C)(@!
Pengembangan-Keahlian. Jakarta. Salemba Empat@!
2)'/0C-A!1&40I-(-@!#<W"@!\B.C-,.!M.(.*0C0)(!R&)(C0C)C0PA!R&)*0C)C0P!Y)(!drY@]!Alfabeta.
Bandung@!
2'&N&/A!d.,)3/0@!#<W=!\8.4.'0!Q.'4.*0G)(4!R)I&]@!%)3)'C)!5!2'&N&/!1F),)I)@!
2)&6)/)'@K-G@!#<W=@!\!%.(0/;%.(0/!B.C-,.!M.')G)*)(!XForecastingZ!,)*)G!H3-(-G0A!
L*E0I)(&'!
Jurnal Indonesia Sosial TeknologiA!?-*@!:A!8-@!:A!B)'.C!#<##! !!!!!!! ! !!!":9!
Q0/(0/! B)&6&(! Salesmanship]@! B-,&*! B)C.'0! 2.-'0! H3-(-G03)! D(0E.'/0C)/!
B.'K&N&)();1-O0N&*!B&(0'@!Y0)3/./!6),)!#$!1.6C.GN.'!#<#<@!FFF@C)&6)/)'@K-G!
^)OI&(0A!^0,OIA!)(,!LKOG),!1I)0KO&@!#<W>@!\M.(.')6)(!B.C-,.!M.')G)*)(!1.N)4)0!
L*)C! Q)(C&! D(C&3! B.(.(C&3)(! M.'.(K)())(! M'-,&3/0! Y0! MC@! 133@]! Spektrum
IndustriA!E-*@!W:A!(-@!#A!6@!W::A!,-05W<@W#=#bT/0@EW:0#@#$=W@!
^0,0I)'0(0A!^0,0I)'0(0@!#<W>@!\M.'.(K)())(!M'-,&3/0!B.(44&()3)(!B.C-,.!M.')G)*)(!
D(C&3!B.(.(C&3)(!2-C)*!M.'G0(C))(!M'-,&3!R)I&!L*N)/0)!Q)'.!f-'.@]!Seminar
Nasional Cendekiawan, 2'0/)3C0!D(0E.'/0CI@!
^0S)I)A!L(,IA!.C!)*@!#<#<@!Manajemen Operasi Produksi@!k)I)/)(!R0C)!B.(&*0/@!
!
!
