ISU PENELITIAN AKUNTANSI
DI MASA DISRUPSI DIGITAL
Disampaikan pada : Accounting Webinar Series Vol.1, 31 Januari 2022
Oleh : Zaldy Adrianto, Universitas Padjadjaran.
INOVASI DIGITAL
• “AT LEAST 40% OF ALL BUSINESS WILL DIE IN THE NEXT 10 YEARS... IF THEY
DON’T FIGURE OUT HOW TO CHANGE THEIR ENTIRE COMPANY TO
ACCOMODATE NEW TECHNOLOGIES.”
JOHN CHAMBERS,
EXECUTIVE CHAIRMAN
& CEO CISCO SYSTEMS
Perkembangan
teknologi Lebih
Cepat dari
sebelumnya
DISRUPSI TEKNOLOGI TERHADAP
AKUNTANSI DALAM RI 4.0
• Data Analytics and Visualization
• Artificial Intelligence / Machine Learning
• Internet of Things and Cloud Computing
• Robotics Process Automation
• Blockchain and Distributed Ledger (incl. NFT)
DISRUPSI TEKNOLOGI TERHADAP
AKUNTANSI DALAM RI 4.0
SHARING ECONOMY
• Desentralisasi
• Kekuatan ekonomi di setiap individu
• Memaksimalkan aset ‘idle’
• Menghilangkan peran perantara
• Memfasilitasi komunikasi antara individu
yang hendak melakukan pertukaran barang
dengan uang.
EVOLUSI PASAR
MODAL
• Tahun 1100an di buka
bursa komoditi pertama di
Perancis
• Bursa Saham Pertama
dibuka di Antwerpen,
Belgia tahun 1400an
• Saat ini bursa saham dan
bursa komoditas telah
tersebar di seluruh dunia
dengan konektivitas real
time.
• Perdagangan saham
memulai digitalisasi sejak
tahun 1970an hingga saat
ini bisa menggunakan
personal gadget
• Kegiatan pinjam meminjam
telah ada sejak ribuan
tahun sebelum masehi
• Bank pertama didirikan
pada abad 14 di Italia
• Pemrosesan transaksi pada
awal perbankan sangat
tradisional
• Banking digital 2.0
menggunakan teknologi
dalam menciptakan proses
yang cepat.
EVOLUSI PERBANKAN
DIGITAL AND MOBILE PAYMENT
BIG DATA
• Every day, we create 2.5 quintillion bytes of data — so much
that 90% of the data in the world today has been created in
the last two years alone. This data comes from everywhere:
sensors used to gather climate information, posts to social
media sites, digital pictures and videos, purchase
transaction records, and cell phone GPS signals to name a
few. -IBM-
BIG DATA
Veracity
Setiap hari di hasilkan 2,5 exabytes data, dan
berlipat ganda setiap 40 bulan (tahun 2012).
Rata – rata perusahaan menyimpan data 100
terabytes
Kecepatan penciptaan data / informasi (sensors,
IoT)
Data dalam berbagai bentuk (messages, picture,
video, GPS Signal, dan lain – lain). 30 Milyar konten
di upload di Facebook tiap bulan.
Kerentanan dari sisi akurasi dan validitas.
Value
Memiliki value apabila di olah dengan tepat
Volume
Velocity
Variety
MANFAAT BIG DATA ANALYTICS
• Dalam transaksi e-commerce, retailer online memiliki
kemampuan untuk membuat rekomendasi produk secara
personal bagi setiap konsumen, sehingga memicu
pembelian serta memandu setiap konsumennya.
• Beberapa retailer online bahkan telah mengolah data
yang besar dari transaksi internal dengan data dari media
social.
• Di sektor publik, Big data analytic adalah faktor utama dari
‘smart cities’ dalam pemanfaatan teknologi digital secara
intensif untuk membuat keputusan.
CONTOH IMPLEMENTASI BIG DATA
UOB Bank
Singapore
The big data risk management system enables the bank to reduce the
calculation time of the value at risk. Initially, it took about 18 hours, but with
the risk management system that uses big data, it only takes a few
minutes. Through this initiative, the bank will possibly be able to carry out
real-time risk analysis in the near future
hunch.com
Analyzes massive database with data from customer purchases, social
networks, and signals from around the web
German World Cup Analyzed very large amounts of video and numeric data about individual
Soccer Team
player and team performance on itself and competing team
PREDICTIVE ANALYTICS
• Predictive analytics menggunakan analisa statistik, data
historis, data mining, serta asumsi kondisi masa depan
dalam memprediksi trends di masa depan.
• Contoh: perusahaan asuransi menggunakan berbagai
variable untuk memprediksi pembayaran polis.
• Predictive analytics mengunakan big data dari sektor
private dan public, termasuk data dari media social,
transaksi konsumen dan output dari sensor serta mesin.
TOOLS
WHAT IS INTERNET OF THINGS?
•The Internet of things (IoT) describes
physical objects (or groups of such objects)
that are embedded with sensors,
processing ability, software, and other
technologies that connect and exchange
data with other devices and systems over
the Internet or other communications
networks
HOW DOES IT?
HOW THIS IS IMPACT
YOU
IOT-BASED SMART FARMING
• Utilize wireless IoT applications to
collect data regarding the
location, well-being, and health
of their livestock
• Monitor pregnant cows:
• Sensor powered by battery is
expelled when its water breaks.
• This sends an information via
the Internet to the rancher.
IOT PROVIDER
IOT IMPLEMENTATION BY FINTECH
COMPANIES
• Wireless Self-Checkout
• Amazon Go is one of the most popular IoT in Fintech
examples. Its self-checkout service is already expanding
across other brands. Instead of waiting in line and dealing
with a cashier, the customers get their cards scanned by IoT
devices at the exit.
IOT IMPLEMENTATION BY FINTECH
COMPANIES
• IoT-Driven Car Insurance Plans
Car insurance is getting more fair than ever.
Metromile started offering per-mile plans, which are
based on the mileage. The IoT devices count the
mileage, and the users pay an adequate amount on
a monthly basis.
WHAT IS BLOCKCHAIN?
• “The blockchain is an incorruptible digital ledger of
economic transactions that can be programmed to
record not just financial transactions but virtually
everything of value.”
• Don & Alex Tapscott, authors Blockchain Revolution
(2016)
WHAT IS BLOCKCHAIN
• Information held on a blockchain exists as a shared — and
continually reconciled — database. This is a way of using
the network that has obvious benefits.
• The blockchain database isn’t stored in any single
location, meaning the records it keeps are truly public
and easily verifiable.
• No centralized version of this information exists for a
hacker to corrupt.
• Hosted by millions of computers simultaneously, its data is
accessible to anyone on the same blockchain
WHAT IS BLOCKCHAIN
• A distributed database.
• Picture a spreadsheet that is duplicated thousands
of times across a network of computers.
• Then imagine that this network is designed to
regularly update this spreadsheet.
• Then you have a basic understanding of the
blockchain.
BRIEF HISTORY
• On October 31st 2008, Satoshi Nakamoto released
the blockchain white paper, outlining a purely peer
to peer electronic cash / digital assets transfer system
• This is the first popular implementation of blockchain
and is attributed as birthing today’s blockchain
industry
• Since then, additional blockchain have been
popularized, Ethereum, various hyperledger solution
as well as numerous others ‘blockchain like’ solutions
SIMPLY DEFINED, BLOCKCHAIN IS..
•
•
•
•
•
•
•
•
P2P distributed architecture
Decentralized Peers
Transaction
Encryption process
Immutable logfile (called ‘ ledger’)
Consensus mechanism
Optional smart contract
By allowing digital information to be distributed but not copied, blockchain
technology created the backbone of a new type of internet.
CENTRALIZED VS DISTRIBUTED
Blockchain is a programming
language that allows users to write
more sophisticated smart
contracts, thus creating invoices
that pay themselves when
shipment arrives or share
certificates which automatically
send their owners dividends if profit
reach a certain level
The economist
Blockchain adalah sebuah sistem
penyimpanan digital yang terdiri
dari banyak server (multiserver).
Pada teknologi blockchain, data
yang dibuat oleh satu server
dapat di replikasi dan verifikasi
oleh server yang lain.
Online pajak
Blockchain adalah suatu sistem transaksi manajemen data digital yang tersebar dimana semua
pengguna sistem tersebut mempunyai satu konsensus bersama
APPLICATIONS OF THE BLOCKCHAIN
TECHNOLOGY
BLOCKCHAIN DI INDONESIA
BLOCKCHAIN DALAM BISNIS
PROS OF BLOCKCHAIN
• Immutability
• Fault tolerance
• less likely to fail accidentally
• Attack Resistance
• more expensive to attack
• once data is stored, it cannot manipulated
• much harder to collude and to act in fraudulent
way
CONS OF BLOCKCHAIN
• Because of the nature of blockchains, it will always be slower
than centralized databases.
• Signature verification. Every blockchain transaction must be
digitally signed - computationally complex, and constitutes the
primary bottleneck.
• Consensus mechanisms. In a distributed database such as a
blockchain, effort must be expended in ensuring that nodes in
the network reach consensus.
• Redundancy. This is about the total amount of computation that
a blockchain requires. Whereas centralized databases process
transactions once (or twice), in a block chain they must be
processed independently by every node in the network.
ARTIFICIAL INTELLIGENCE/
MACHINE LEARNING
• Dalam bentuk yang paling ambisius, AI merupakan upaya
membangun sistem computer yang dapat berpikir dan berperilaku
seperti manusia.
• Ilmuwan komputer Alan Turing di tahun 1950 mendefinisikan komputer
dengan kecerdasan adalah saat manusia berdialog dengan
komputer tersebut dan tidak mampu membedakannya.
EVOLUSI AI
• Tingkat kesalahan Image recognition programs turun dari 25 persen
menjadi 3 percent in 2018;
• Kesalahan natural language speech recognition turun dari from 15
persen menjadi 6 persen
• Google’s Translate program mencapai 85 persen akurasi
• personal assistants seperti Siri (Apple), Alexa (Amazon), Cortana
(Microsoft), dan Now (Google), serta aktivasi sistem mobil
menggunakan suara.
MACHINE LEARNING
• ML dimulai dari dataset yang luar biasa besar dari
pupuhan ribu hingga jutaan data points secara
otomatis mencari pola tersembunyi atau relasi
antara data tersebut.
• Facebook menggunakan machine learning untuk
mengidentifikasikan pola dari data, serta melakukan
estimasi kemungkinan seorang user akan mengklik
iklan tertentu berdasarkan pola perilaku.
IMPLEMENTASI AI/ML
• Computer Vision,
• Speech recognition
• Language translation
• Transaction analysis
• Targeted online ads
• robotics
BANK OF TOKYO MITSUBISHI
CUSTOMER SERVICE MENGGUNAKAN
AI
FACE IDENTIFICATION APPS FROM
HSBC.
ROBOTICS PROCESS AUTOMATION
• RPA is a form of business process automation
technology based on metaphorical software
robots (bots) or on artificial intelligence
(AI)/digital workers
https://www.newscientist.com/article/mg22630151-700-ai-interns-software-alreadytaking-jobs-from-humans/?ignored=irrelevant#.VY2CxPlViko
BENEFIT OF RPA
• Keuntungan utama dari robotic automation
adalah penurunan biaya, meningkatkan
kecepatan dan akurasi serta konsistensi, serta
memperbaiki kualitas dan skala produksi.
• Automation menyediakan keamanan ekstra,
khususnya untuk data penting dan di industry
jasa keuangan
RPA ACTUAL DEPLOYMENT
• Banking and Finance Process Automation
• Mortgage and Lending Process
• Customer Care Automation
• e-Commerce Merchandising Operation
• Optical Character Recognition Application
• Data Extraction Process
E-GOVERNMENT
• Sistem Pemerintahan Berbasis
Elektronik (SPBE)
• Perpres no. 95 tahun 2018 tentang
Sistem Pemerintahan Berbasis
Elektronik
• SPBE adalah Penyelenggaraan
pemerintahan yang
memanfaatkan teknologi informasi
dan komunikasi untuk memberikan
layanan kepada pengguna SPBE
• Penyelenggaraan SPBE Mencakup
pengaturan unsur – unsur SPBE
dan manajemen SPBE
DOMAIN SPBE
(PERMENPANRB NO 59 TAHUN 2020)
• Kebijakan tata kelola
Kebijakan
Tata Kelola
• Perencanaan strategis SPBE
• Teknologi Informasi dan Komunikasi
• Penyelenggara SPBE
Manajemen
• Penerapan Manajemen SPBE
• AUDIT TIK
Layanan
• Layanan Administrasi Pemerintahan
• Layanan Publik
PELUANG – PELUANG RISET
• Landasan Teori
1. Basis Literatur terdahulu
2. Perlu mempertimbangkan konteks
3. Ada kemungkinan mengembangkan teori
baru
• Pilihan Publikasi
• Melihat paper dan penulis terkait
https://www.connectedpapers.com
PILIHAN METODE RISET
1. Studi literature sistematis (SLR)
2. Empiris, eksperimen, survey, kasus.
3. Konseptual
4. Desain dan Pengembangan (Design Science)
5. Bibliometrix, metadata, content analysis
6. etc
IS/ IT INTERACTION MODEL
SISTEM INFORMASI DI DUNIA BISNIS
(LAUDON, 2018)
DESIGN SCIENCE
Hevner, A.R., March, S.T., Park.,J., & Ram.,S.(2004). Design Science in Information System
Research. MIS Quarterly, 75-105
DESIGN SCIENCE RESEARCH
INFORMATION SYSTEM RESEARCH THEMES: A SEVEN-TEEN
YEARS DATA DRIVEN TEMPORAL ANALYSIS
Goyal, Sandeep; Ahuja, Manju; Guan, Jian. (2018). Communications of the
Association for Information Systems. (vol.43). Article 23.
INFORMATION SYSTEM RESEARCH THEMES: A SEVEN-TEEN
YEARS DATA DRIVEN TEMPORAL ANALYSIS
Goyal, Sandeep; Ahuja, Manju; Guan, Jian. (2018). Communications of the
Association for Information Systems. (vol.43). Article 23.
Information systems, Dominant Paradigms, And Emerging Concept: A Community
Clustering Analysis of the Highest Impact Topic in Information Systems Research.
Allen, P. Jonathan, Entrepreneurship, Innovation, and Strategy
• Solid Arrow indicate a direct
citation relationship
• Dashed arrow, more indirect
relationship
• ‘Design Science’ and ‘Knowledge
sharing’ are the highest impact
topic outside the dominant
paradigms
A Bibliometric analysis of Accounting Information systems Journals and
Their emerging technologies contributions
Chiu, Victoria; Liu, Qi; Muehlmann, Bridgette; Baldwin, Amelia Annette. (2019).
International Journal Of Accounting Information Systems Vol 32, page 24-43.
JOURNAL
• European Journal of Information Systems
• Information System Journal
• Information System Research
• Journal of AIS
• Journal of Information Technology
• Journal of MIS
• Journal of Strategic Information System
• MIS Quarterly.
BEBERAPA RESEARCH QUESTION
• Bagaimana Dampak Teknologi pada Keputusan akuntansi?
• Karakteristik teknologi yang akan meningkatkan keandalan
informasi?
• Bagaimana teknologi monitoring (IoT) mempengaruhi
manajemen, akuntansi manajemen, audit, atau internal
audit?
• Bagaimana adopsi perusahaan (besar, kecil, menengah)
terhadap teknologi blockchain?
• Bagaimana peranan AI dalam meningkatkan prosedur
audit?
TERIMAKASIH
Isaac Newton
BIODATA SINGKAT
Nama
Zaldy Adrianto, SE., M.ProfAcc., Ak.
Dosen dan Peneliti Departemen Akuntansi,
Universitas Padjadjaran.
Asessor Sistem Pemerintahan berbasis Elektronik
(SPBE) tahun 2021.
S1: Jurusan Akuntansi, Universitas Padjadjaran;
Riwayat
Pendidikan S2: Faculty of Profession, The University Of Adelaide
Pekerjaan
Bidang
keahlian
Sistem Informasi Akuntansi, IT GRC, System Analysis
and Design, Internal Control, Analisa Proses Bisnis