METODOLOGI RISET
AKUNTANSI
KARSAM SUNARYO,SE.,MAK.,AK.,QMSA.
K A R S A M S U N A R Y O
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© 2009 John Wiley & Sons Ltd.
Pertemuan Kesepuluh
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PROSES RISET
1 OBSERVASI
Identifikasi bidang Permasalahan
1 OBSERVASI
Identifikasi bidang Permasalahan
2
PENGUMPULAN DATA AWAL
• Interview
• Studi Pustaka
2
PENGUMPULAN DATA AWAL
• Interview
• Studi Pustaka
3
PENDEFINISI AN MASALAH
Pembatasan masalah
3
PENDEFINISI AN MASALAH
Pembatasan masalah
4 KERANGK
A TEORI
Variabel sdh
didefisikan dan diberi label
4 KERANGK
A TEORI
Variabel sdh
didefisikan dan diberi label
5
PERUMUSAN HIPOTESIS
5
PERUMUSAN HIPOTESIS
INTERPRETASI DATA
7 ANALISIS
DAN
INTERPRETASI DATA
8
PENGAMBILAN KESIMPULAN
DEDUCTIVE
8
PENGAMBILAN KESIMPULAN
DEDUCTIVE
YA TIDAK
9
PPENULISAN LAPORAN
9
PPENULISAN LAPORAN
10
PRESENTASI LAPORAN
10
PRESENTASI LAPORAN
11
PENGAMBILA N
KEPUTUSAN MANAJERIAL
11
PENGAMBILA N
TOPIK BAHASAN
Populasi, Elemen, Kerangka Populasi,
Sampel, Subyek dan Pengambilan
sampel
Alasan Pengambilan sampel
Keterwakilan Sampel
Probalility dan Non-Probability Sampling
Sampling in Cross-Cultural Research
Precision and Confidence
Data Sampel dan Pengujian Hipitesis
TUJUAN PEMBELAJARAN
Setelah mengikuti kuliah ini Sdr dapat :
Mendefinisikan tentang pengambilan sampel,
sampel, populasi, elemen, subyek dan kerangka
populasi.
Mendeskripsikan dan membahas perbedaan
berbagai rancangan sampel.
Mengidentifikasi pengambilan sampel yang tepat
untuk berbagai keperluan riset yang berbeda.
Menjelaskan mengapa data sampel digunakan
untuk menguji hipotesis.
Membahasan tentang presisi (ketepatan) dan
tiongkat kepercayaan (confidence).
TUJUAN PEMBELAJARAN
Memperkirakan ukuran sampel.
Mendiskusikan faktor-faktor yang perlu
dipertimbangkan dalam penentuan ukuran
sampel.
Mendiskusikan efisiensi dalam pengambilan
sampel.
Mendiskusikan kemampuan mengeneralisasi
dalam kontek rancangan sampel.
Menerapkan bahan ajar pada topik ini untuk
tugas dan proyek pada mata kuliah ini.
RANCANGAN RISET
Pengujian Hipotesis
Tipe
Investigasi Menetapk
• Minimal
• Manipulasi
• Control
• Simulasi
Setting Riset
• Contrieve d
• Non-contrived
Ukuran dan
• Organisa si
• Mesin
• dsb
Horison Waktu nal (time-series)
Rancangan Sampel
• Probability
• Non-probablity
• Size
Pengumpu lan Data
• Observasi
• Interview
• Kuisioner
• Pengukuran fisik
Analisis Data
• Feel for Data
• Goodness of Data
BEBERAPA PENGERTIAN
Populasi
population
:” the entire group of
people, events or things of interest that
researchers wishes to investigate”.
Unsur
element
: “
a single member of
population
”.
Kerangka Populasi
population frame :
“listing of all the element in the population
”.
Sampel
sample : “a subset of population
”.
Subyek
subject : “a single member of the
sample
”.
PENGERTIAN POPULASI
Populasi : wilayah generalisasi
yang berupa
obyek yang mempunyai
kuantitas, kualitas
dan
karakteristik
tertentu yang ditetapkan
untuk
dipelajari
dan ditarik
kesimpulannya.
Populasi :
bukan hanya
orang,
tetapi juga
segala macam
obyek.
Bukan sekadar
jumlah,
tetapi juga
karakter/sifat
yang ada pada
obyek tersebut.
Contoh :
Perusahaan X
sebagai obyek
penelitian, dimana perusahan X terdapat
sejumlah karyawan
, sehingga populasi adalah
jumlah karyawan. Tetapi perusahaan X juga
mempunyai
karakteristik
orang-orang,
misalnya :
motivasi kerja
,
disiplin kerja
, dls.
PENGERTIAN SAMPEL
Sampel
: bagian dari jumlah dan
karakteristik yang dimiliki populasi.
Bila populasi
besar
dan peneliti
mempunyai
keterbatasan sumberdaya
(dana, waktu dan tenaga) peneliti akan
menggunakan
sampel
yang diambil dari
populasi dan
kesimpulan
diberlakukan
untuk populasi.
Sample yang diambil harus
HUBUNGAN ANTARA POPULASI DAN
SAMPEL
Sampel
Populasi
Parameter
(µ, , )
Statistik
( , , )
estimates
KENORMALAN DISTRIBUSI
Apa saja target yang populasi yang
relevan terhadap fokus riset ?
Apa saja pastinya paramater-parameter
yang menarik bagi peneliti untuk diamati ?
Kerangka sampel seperti apa yang
tersedia ?
Berapa ukuran sampel yang dibutuhkan ?
Berapa biaya yang melekat dalam
rancangan sample ?
Berapa waktu yang tersedia untuk
TEKNIK SAMPLING
Probability Sampling
Unrestricted or Simple Random Sampling
Restricted or Complex Probability
Sampling
Systematic Sampling
Stratified Random Sampling
Proportionate or Disproporsionate
Random Sampling
Cluster Sampling
Single_stage and Multistage Cluster
Sampling
Area Sampling
Double Sampling
TEKNIK SAMPLING
Non-Probability Sampling
Convenience Sampling
Purposive Sampling : Judgment Sampling,
Quota Sampling
TEKNIK SAMPLING
Is REPRESENTATIVENESS
Of sample critical for the study ?
Yes No
Choose one of
The PROBABILITY
Sampling designs
Choose one of
The NON PROBABILITY
Sampling designs If the purpose of
The study mainly is for :
Generalisability
Assessing differtial parameter
Collecting information in a locatised area
TEKNIK SAMPLING
Generalisability
Assessing differtial parameter
Collecting information in a localised area
Gathering more information from a subset of sample
Simple random Systematic Random Cluster random
All subgroup have equal number of element ?
Yes No
Proportionate stratified random Disproportionate stratified random
Area random
Double random
TEKNIK SAMPLING
No
Choose one of
The NON PROBABILITY
Sampling designs
If the purpose of
The study mainly is for : To obtain quick,
Even if unreliable information
To obtain information Relevan to and available Only with certain groups
Convenience Sampling
Looking for information That only a few experts Can provide
Looking for information That only a few experts Can provide
Quota Sampling
Judgment Sampling Quota Sampling
KELEBIHAN DAN KEKURANGAN :
PROBABILITY DAN
NON-PROBABILITY
Sampling
Deskripsi
Kelebihan
Kekurangan
1. Simple Random
All elements in thepopulation are
considered and each element has an equal chance of being
chosen as the subject
High generalisability of finding.
Not as efficient as stratified sampling
2. Systematic
Random
Every nth element in the population is chosen starting from a random point in the population frame
Easy to use if
population frame is available
Systematic biased are possible
3a. Proportionate
Stratified Random
Population is first divided into
meaningful segments: subjects are drawn in proportion to their original number in the population
Most efficient among all probability design All groups are
adequately sampled and comparison among groups are possible ability design
Stratification must be meaningful More time
consuming than simple random
Population frame is essential
3b.
Disproportionate
Stratified Random
Based on criteria other than their original population number
KELEBIHAN DAN KEKURANGAN :
PROBABILITY DAN
NON-PROBABILITY
Sampling
Deskripsi
Kelebihan
Kekurangan
4. Cluster Random
Groups that haveheterogeneous members are first identified; then some are chosen at
random; all the members in each of the randomly chosen groups are studied
In geographic cluster, costs of data
collection are low
The least reliable and efficient among all probability sampling designs since subsets of cluster are more homogenous than heterogeneous
5. Area Sampling
Cluster samplingwithin a particular area or locality
Cost effective. Useful for decisions relating to a particular
location
Takes time to collect data from an area
6. Double
Sampling
The same sample or a subset of the
sample is studied twice
Offers more detailed information on the topic of study
Original biases, if any, will be carried over.
Individual may not be happy responding a second time
KELEBIHAN DAN KEKURANGAN :
PROBABILITY DAN
NON-PROBABILITY
Sampling
Deskripsi
Kelebihan
Kekurangan
Non-Probability
7. Convenience
The most easilyaccessible members are chosen as subject
Quick, convenient,
less expensive Not generalisable at all
8. Judgment
Subjects selected onthe basis of their expertise in the subject investigated
Sometimes, the only meaningful way to investigate.
Generalisability is questionable; not generalisable to entire population
9. Quota
Subjects areconveniently chosen from targeted group according to some predetermined number or quota
Very useful where minority participation in a study is critical
Not easily generalisable.
