ANALISIS PERILAKUKOS AKTVITASErina

COST BEHAVIORPerilaku biaya adalah suatu istilah umum untuk menggambarkan apakah suatu biaya jumlahnya tetap atau berubah dalam kaitannya dengan perubahan tingkat aktivitas.

Dalam praktik, biasanya perilaku biaya dikaitkan dengan time horizon (Cakrawala waktu):Jangka panjang semua biaya adalah variabelJangka pendek paling tidak ada satu jenis biaya yang bersifat tetap.

Jenis Biaya berdasarkan PerilakuCostsFIXED COSTSMIXED COSTSVARIABLE COSTSStep Fixed CostsStep Variabel CostsACTIVITY

Variable Cost0QRpY = $100Q Perunit tetapTotal berubah scr proporsional dengan perubahan aktivitas10100$1.000$10.000

Regresif

Fixed Cost0QRpY = $25.000

Relevan RangePerunit berubah terbalik dgn perubahan volume,Total tidak berubah dalam relevan range ttt.$25.000

Biaya ProduksiBBKL: KAYU, PAKU, Var TKL: TUKANG KAYU VarGaji Mandor Campuran (Var + Fix)Cat VarListrik Campuran (var + Fix)Bahan penolongVarAmplas VarMesin Moulding Depresiasi Mesin Fix

Mixed Cost0QRpY = aY = a + bQAda unsur tetapAda unsur variabel

Step Cost

Step variabelStep Fixed

Biaya CampuranY = a + b x

Tujuan Pemisahan MCUntuk menghitung tarif BOP dan analisis variansiUntuk menyusun fleksibel budget dan analisis variansiUntuk analisis kontribusi margin dan direct costingUntuk analisis B-V-LUntuk analisis Komparatif dan differentialUntuk analisis maksimasi profit dan minimasi biayaUntuk analisi budget modalUntuk analisis profitabilitas segmen baik menurut wilayah, produk, customer dsb

METODE PEMISAHAN BIAYA CAMPURANThe High-Low Method The Scatterplot Method The Method of Least SquaresSimple RegressionMultiple RegressionManagement Judgement

TUJUAN PEMISAHAN BIAYAMenentukan tarif FOHMenyusun budget fleksibel dan analisis varianAnalisis kontribusi margin dan pelaporan segmentasiAnalisis Break Even Point (BEP)Analisis differentialAnalisis minimasi biaya dan maksimasi profit jangka pendekAnalisis budget modalAnalisis profitabilitas segmen

Month Setup Costs Setup HoursJanuary $1,000100February 1,250200March 2,250300April 2,500400May 3,750500

The High-Low MethodStep 1: Solve for variable cost (b)

Month Setup Costs Setup HoursJanuary $1,000100February 1,250200March 2,250300April 2,500400May 3,750500

The High-Low Method

Month Setup Costs Setup Hours

January $1,000100February 1,250200March 2,250300April 2,500400May 3,750500

The High-Low Method

b = $6.875Step 2: Using either the high cost or low cost, solve for the total fixed cost (a).The High-Low Method

Y = a + b (x) $3,750 = a + $6.875(500) $312.50 = aHigh EndY = a + b (x) $1,000 = a + $6.875(100) $312.50 = aLow EndThe cost formula using the high-low method is: Total cost = $312.50 + ($6.875 x Setup hours)The High-Low Method

Sheet1

MonthTCFCVC

Jan1,000312.50687.50

Feb1,250312.50937.50

Mar2,250312.501,937.50

Apr2,500312.502,187.50

May3,750312.503,437.50

0.0

0.0

Sheet2

Sheet3

The Scatterplot Method

Data

Sheet1

MonthBiayaJam

ListrikKerja

Jan64034000

Feb62030000

Mar62034000

April59039000

May50042000

June53032000

July50026000

August50026000

Sept53031000

Oct55035000

Nov58043000

Dec68048000

JUMLAH6,840420,000

RERATA57035,000

Sheet2

Sheet3

ActivityCost0Activity Output*

**

*

*The Scatterplot MethodNonlinear Relationship

*

*

*

*

*

*

*$440

Perhitungan Biaya rata-rata per bulan.......... $570Komponen tetap (grafik)........... $440 -Komponen variabel.................. $ 130Biaya variabel per unit: b = $0.0037 PER DLH

The Method of Least Squares

Sheet1

MonthSetup CostsSetup Hours

Jan1,000$100

Feb1,250$200

Mar2,250$300

Apr2,500$400

May3,750$500

Jumlah10,750$1,500

Rerata2,150$300

Sheet2

Sheet3

The Method of Least SquaresRegression Output for Larson Company

Sheet1

Regression Output:

Constant125

Std. Err of Y Est299.30

R Squared0.94

No. of Observation5

Degrees of Freedom3

X Coefficient(s)6.75

Std. Err of Coef.0.95

Sheet2

Sheet3

The Method of Least SquaresThe results give rise to the following equation:Setup costs = $125 + ($6.75 x Setup hours)R2 = .944, or 94.4 percent of the variation in setup costs is explained by the number of setup hours variable.

TC = a + ( b1X1) + (b2X2) + . . . a = the fixed cost or intercept

b1 = the variable rate for the first independent variable

X1 = the first independent variable

b2 = the variable rate for the second independent variable

X2 = the second independent variable

Multiple Regression

Multiple RegressionData for Phoenix Factory Utilities Cost Regression

Sheet1

MonthMhrsSummerUtilities Cost

Jan1,3400$1,688

Feb1,29801,636

Mar1,37601,734

April1,40501,770

May1,50012,390

June1,43212,304

July1,32212,166

August1,41612,284

Sept1,37011,730

Oct1,58001,991

Nov1,46001,840

Dec1,45501,833

Sheet2

Sheet3

Multiple RegressionMultiple Regression for Phoenix Factory Utilities Cost

Sheet1

Constant243.11

Std Err of Y Est55.51

R Squared0.97

No. of Observation12.00

Degrees of Freedom9.00

X Coefficient(s)1.10510.49

Std Err of Coef.0.2132.55

Sheet2

Sheet3

The results gives rise to the following equation:Utilities cost = $243.11 + $1.097(Machine hours) + ($510.49 x Summer)R2 = .967, or 96.7 percent of the variation in utilities cost is explained by the machine hours and summer variables.Multiple Regression

Managerial JudgmentManagerial judgment is critically important in determining cost behavior, and it is by far the most widely used method in practice.

The EndChapter Three

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