Irvan Bastian Arief, PhD

Irvan Bastian Arief, PhD

Area DKI Jakarta
8 rb pengikut 500+ koneksi

Bergabung untuk mengikuti

Tentang

[The creator of RUP and DA-HOC machine learning algorithms]
I am an award-winning…

Artikel oleh Irvan Bastian

  • A Dawn of New Life and Work Style
    18 Apr 2020

    A Dawn of New Life and Work Style

    I like to talk and discuss the future, as it is a representative of hope. After COVID-19 pandemic has been dissolved…

    6 Komentar

Kontribusi

Bergabung sekarang untuk melihat semua kontribusi

Aktivitas

Bergabung sekarang untuk melihat semua aktivitas

Pengalaman

  • Gambar tiket.com

    tiket.com

  • -

  • -

  • -

  • -

  • -

  • -

  • -

  • -

    Melbourne, Australia

  • -

    Melbourne, Australia

  • -

    Melbourne, Australia

  • -

    Melbourne, Australia

  • -

    Melbourne, Australia

  • -

    Multicultural and Ethnicity Centre

  • -

  • -

    Taiwan

Pendidikan

  • Gambar Monash University

    Monash University

    -

    Aktivitas dan Kegiatan Sosial:President of Multicultural Student Fellowship (MSF), Student Representative of Monash University Master of Business Information Systems Professional, Member of Prestigious Golden Key International Honour Society, Mentor in Peer-Mentor Programme at Monash University, Executive Committee (Caulfield Representative Officer) at Monash Postgraduate Association (MPA), Treasurer at Caulfield Information Technology Association (CITA)

    High Distinction results achieved (the highest achievable) proven by congratulation letter from Monash University Caulfield School of I.T. Head of School, Obtain another congratulation letter about receiving the highest grade on the core unit

  • -

    Aktivitas dan Kegiatan Sosial:Vice President (VP) of National wide Indonesian Students Association of Australia (PPIA), Treasurer of National wide Indonesian Students Association of Australia (PPIA), Treasurer of RMIT University - Indonesian Students Association of Australia (PPIA-RMIT)

    Part of Sustainable Urban Precincts Program (SUPP) and iCO2mmunity Project in RMIT University. The SUPP Project will reduce electricity use over eight years by an estimated 263 million kilowatts, leading to a 30,000-tonne reduction in greenhouse gas emissions each year. Water use will be cut by an estimated 53 million litres each year.

    During this courses, I was granted with three different scholarships:
    - The Australian Government Research Training Program (RTP) Scholarship
    - SUPP…

    Part of Sustainable Urban Precincts Program (SUPP) and iCO2mmunity Project in RMIT University. The SUPP Project will reduce electricity use over eight years by an estimated 263 million kilowatts, leading to a 30,000-tonne reduction in greenhouse gas emissions each year. Water use will be cut by an estimated 53 million litres each year.

    During this courses, I was granted with three different scholarships:
    - The Australian Government Research Training Program (RTP) Scholarship
    - SUPP Scholarship: ‘iCO2mmunity: Personal and Community Monitoring for University-wide Engagement towards Greener, Healthier, and more Productive Living’
    - SUPP Scholarship: ‘The Greener Office and Classroom’

  • -

    Aktivitas dan Kegiatan Sosial:Member of National Cheng Kung University Library - Book Collection Department, Leader of Information and Internet Division at Tainan Indonesian Student Association (TISA), General Administrative President at National Cheng Kung University Overseas Chinese Student Association (NCKU-OCSA), President in ROVER-Scout Organisation, Webmaster and System Operator of Bulletin Board System at Indonesian Students Association in Taiwan (PERPITA)

    Secured scholarship 2nd and 3rd years

Lisensi dan Sertifikasi

Bergabung sekarang untuk melihat semua sertifikasi

Pengalaman Sukarela

  • Gambar City of Melbourne

    Act of Translation

    City of Melbourne

    - 1 tahun 1 tahun

    Hak Sipil dan Aksi Sosial

    Act of Translation’ was awarded Winner of the Community Innovation Award at the Victorian Multicultural Awards for Excellence 2018.

    Funded by the Victorian Government and led by the City of Melbourne, ‘Act of Translation’ was a theatre project involving local and international students from countries including China, Iraq, India, Indonesia, Pakistan, Vietnam, Brazil and Colombia. The project began with weekly theatre workshops in March 2017 to help students communicate and explore their…

    Act of Translation’ was awarded Winner of the Community Innovation Award at the Victorian Multicultural Awards for Excellence 2018.

    Funded by the Victorian Government and led by the City of Melbourne, ‘Act of Translation’ was a theatre project involving local and international students from countries including China, Iraq, India, Indonesia, Pakistan, Vietnam, Brazil and Colombia. The project began with weekly theatre workshops in March 2017 to help students communicate and explore their experiences and challenges, while also gaining skills in performance development. The works were performed at the Melbourne Writers Festival, Library at The Dock, RMIT University and the Immigration Museum and were attended by more than 600 people. They aimed to challenge locals’ perceptions of international students, and vice versa. The project culminated in May 2018 with the launch of a documentary about the experience, made by filmmaker Irene Metter.

  • Gambar City of Melbourne

    InterCOM3

    City of Melbourne

    - 3 bulan

    Pendidikan

    InterCOM3 are the leader and main committees for Lord Mayor Student Welcomer.

  • Food service officer

    The Big Umbrella

    Layanan Sosial

Penerbitan

  • From Data to Decisions: Leveraging AI to Enhance Online Travel Agency Operations

    Journal of Information Technology Teaching Cases (JITTC) / Sage Journals

    This case study explores the critical success factors (CSFs) that drive the effective utilisation of artificial intelligence at tiket.com, an established online travel agency in Indonesia. Through in-depth interviews with key employees, this case identifies and describes essential elements that contribute to the successful deployment of data science initiatives, which are essential for enhancing operational efficiency and competitive advantage in the digital travel industry. This study explores…

    This case study explores the critical success factors (CSFs) that drive the effective utilisation of artificial intelligence at tiket.com, an established online travel agency in Indonesia. Through in-depth interviews with key employees, this case identifies and describes essential elements that contribute to the successful deployment of data science initiatives, which are essential for enhancing operational efficiency and competitive advantage in the digital travel industry. This study explores how tiket.com leverages a problem-driven approach, cost–benefit analysis, data understanding, top management support, collaboration, communication, essential knowledge and skills, and operational agility to address specific business challenges and foster continuous innovation and customer-centric strategies. By analysing real-world applications and employee insights, this case highlights how tailored artificial intelligence strategies can significantly impact business outcomes, providing valuable lessons for the broader travelling and entertainment sector.

    Lihat penerbitan

  • A Scalable Room Occupancy Prediction with Transferable Time Series Decomposition of CO2 Sensor Data

    ACM Transactions on Sensor Networks (TOSN) / Association for Computing Machinery (ACM) New York, NY, USA

    Human occupancy counting is crucial for both space utilisation and building energy optimisation. In the current article, we present a semi-supervised domain adaptation method for carbon dioxide - Human Occupancy Counter Double Plus (DA-HOC++), a robust way to estimate the number of people within in one room by using data from a carbon dioxide sensor. In our previous work, the proposed Seasonal Decomposition for Human Occupancy Counting (SD-HOC) model can accurately predict the number of…

    Human occupancy counting is crucial for both space utilisation and building energy optimisation. In the current article, we present a semi-supervised domain adaptation method for carbon dioxide - Human Occupancy Counter Double Plus (DA-HOC++), a robust way to estimate the number of people within in one room by using data from a carbon dioxide sensor. In our previous work, the proposed Seasonal Decomposition for Human Occupancy Counting (SD-HOC) model can accurately predict the number of individuals when the training and labelled data are adequately available. DA-HOC++ is able to predict the number of occupancy with minimal training data, as little as one-day data. DA-HOC++ accurately predicts indoor human occupancy for five different rooms across different countries using a model trained from a small room and adapted to the other rooms. We evaluate DA-HOC++ with two baseline methods - support vector regression technique and SD-HOC model. The results demonstrate that DA-HOC++'s performance on average is better by 10.87% in comparison to SVR and 8.65% in comparison to SD-HOC.

    Lihat penerbitan

  • SD-HOC: Seasonal Decomposition Algorithm for Mining Lagged Time Series

    Communications in Computer and Information Science / Springer, Singapore

    Mining time series data is a difficult process due to the lag factor and different time of data arrival. In this paper, we present Seasonal Decomposition for Human Occupancy Counting (SD-HOC), a customised feature transformation decomposition, novel way to estimate the number of people within a closed space using only a single carbon dioxide sensor. SD-HOC integrates time lag and line of best fit model in the preprocessing algorithms. SD-HOC utilises seasonal-trend decomposition with moving…

    Mining time series data is a difficult process due to the lag factor and different time of data arrival. In this paper, we present Seasonal Decomposition for Human Occupancy Counting (SD-HOC), a customised feature transformation decomposition, novel way to estimate the number of people within a closed space using only a single carbon dioxide sensor. SD-HOC integrates time lag and line of best fit model in the preprocessing algorithms. SD-HOC utilises seasonal-trend decomposition with moving average to transform the preprocessed data and for each trend, seasonal and irregular component, different regression algorithms are modelled to predict each respective human occupancy component value. Utilising M5 method linear regression for trend and irregular component and dynamic time warping for seasonal component, a set of the prediction value for each component was obtained. Zero pattern adjustment model is infused to increase the accuracy and finally, additive decomposition is used to reconstruct the prediction value. The accuracy results are compared with other data mining algorithms such as decision tree, multi-layer perceptron, Gaussian processes - radial basis function, support vector machine, random forest, naïve Bayes and support vector regression in two different locations that have different contexts.

    Lihat penerbitan

  • RUP: Large Room Utilisation Prediction with Carbon Dioxide Sensor

    Pervasive and Mobile Computing / Elsevier

    Human occupancy information is crucial for any modern Building Management System (BMS). Implementing pervasive sensing and leveraging Carbon Dioxide data from BMS sensor, we present large Room Utilisation Prediction with carbon dioxide sensor (RUP), a novel way to estimate the number of people within a closed space from a single carbon dioxide sensor. RUP de-noises and pre-processes the carbon dioxide and indoor human occupancy data. We utilise both seasonal-trend decomposition based on Loess…

    Human occupancy information is crucial for any modern Building Management System (BMS). Implementing pervasive sensing and leveraging Carbon Dioxide data from BMS sensor, we present large Room Utilisation Prediction with carbon dioxide sensor (RUP), a novel way to estimate the number of people within a closed space from a single carbon dioxide sensor. RUP de-noises and pre-processes the carbon dioxide and indoor human occupancy data. We utilise both seasonal-trend decomposition based on Loess and seasonal-trend decomposition with moving average to factorise both datasets. For each trend, seasonal and irregular component, we model different regression algorithms to predict each respective human occupancy component value. We propose a zero pattern adjustment model to increase the accuracy and finally, we use additive decomposition to reconstruct the prediction value. We run our model in two different locations that have different contexts. The first location is an academic staff room and the second is a cinema theatre with up to 300 people. Our results show an average of 4.33% increment in accuracy for the small room with 94.68% indoor human occupancy counting and 8.46% increase for the cinema theatre in comparison to the accuracy of the baseline method, support vector regression.

    Lihat penerbitan

  • DA-HOC: Semi-supervised Domain Adaptation for Room Occupancy Prediction using CO2 Sensor Data

    In the Proceedings of the fourth ACM International Conference on Systems for Energy-Efficient Built Environments (BuildSys 2017) / ACM New York

    Human occupancy counting is crucial for both space utilisation and building energy optimisation. In the current article, we present a semi-supervised domain adaptation method for carbon dioxide - Human Occupancy Counter (DA-HOC), a robust way to estimate the number of people within in one room by using data from a carbon dioxide sensor. In our previous work, the proposed Seasonal Decomposition for Human Occupancy Counting (SD-HOC) model can accurately predict the number of individuals when the…

    Human occupancy counting is crucial for both space utilisation and building energy optimisation. In the current article, we present a semi-supervised domain adaptation method for carbon dioxide - Human Occupancy Counter (DA-HOC), a robust way to estimate the number of people within in one room by using data from a carbon dioxide sensor. In our previous work, the proposed Seasonal Decomposition for Human Occupancy Counting (SD-HOC) model can accurately predict the number of individuals when the training and labelled data are adequately available. DA-HOC is able to predict the number of occupancy with minimal training data, as little as one-day data. DA-HOC accurately predicts indoor human occupancy for a large room using a model trained from a small room and adapted to the larger room. We evaluate DA-HOC with two baseline methods - support vector regression technique and SD-HOC model. The results demonstrate that DA-HOC's performance is better by 12.29% in comparison to SVR and 10.14% in comparison to SD-HOC.

    Lihat penerbitan

  • Human Occupancy Recognition with Multivariate Ambient Sensors

    In the Proceedings of the fourteenth IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom 2016) / IEEE

    With advancement in sensors and Internet of Things, gathering spatiotemporal information from one's surroundings has become easier, to an extent that we can start to use sensor data to infer indoor occupancy patterns. This paper aims to identify which ambient sensor is the most dominant in recognising human presence. Four different types of off-the-shelf sensors from two manufacturers were deployed to ensure that we could collect the following data reliably: illumination, temperature, humidity,…

    With advancement in sensors and Internet of Things, gathering spatiotemporal information from one's surroundings has become easier, to an extent that we can start to use sensor data to infer indoor occupancy patterns. This paper aims to identify which ambient sensor is the most dominant in recognising human presence. Four different types of off-the-shelf sensors from two manufacturers were deployed to ensure that we could collect the following data reliably: illumination, temperature, humidity, levels of carbon dioxide, pressure and sound from within one staff office. Motion, power consumption, door opening and closing data and annotations from a self-developed mobile app were also collected as ground truth. We present our methods to preprocess the data and compute the number of people in the room with different classifiers, and identify sensors with strong and weak correlations. We explain our methodology for integrating large amounts of sensor data, discuss our experiments and findings in relation to the binary occupancy of a single person office, providing a baseline for recognising human occupancy.

    Lihat penerbitan

Proyek

  • Project O

    -

    A charity project to help people that do not have a proper education from third world country.

  • Social Marketing Working Group

    -

    Gambler's Help services selected several students to be part of the "International Students Working Group". The purpose of the group is to promote a closer linkage between the responsible gambling movement and international students. The team created an online poster competition as an initiative.

    • Conducted research on the issue of compulsive gambling on international students in Victoria
    • Identified target segments and methods of reaching the target group via social marketing…

    Gambler's Help services selected several students to be part of the "International Students Working Group". The purpose of the group is to promote a closer linkage between the responsible gambling movement and international students. The team created an online poster competition as an initiative.

    • Conducted research on the issue of compulsive gambling on international students in Victoria
    • Identified target segments and methods of reaching the target group via social marketing channel
    • Facilitated and executed an awareness campaign for Responsible Gambling Awareness Week (RGAW)
    • Implemented recruitment strategies of the poster competition and promoted of the online poster competition (Theme: Responsible Gambling and International Students) through social media.

    Kreator lainnya

Gelar Kehormatan dan Penghargaan

  • CIO100 Awards

    IDC Foundry

    CIO ASEAN is proud to announce the winners of the 2024 CIO100 Awards – recognising the top technology leaders and teams across Southeast Asia and Hong Kong who are driving innovation and influencing rapid change. Winners were unveiled during an in-person awards ceremony at Marina Bay Sands in Singapore, with more than 400 executives from across Southeast Asia and Hong Kong.

    Full Story:…

    CIO ASEAN is proud to announce the winners of the 2024 CIO100 Awards – recognising the top technology leaders and teams across Southeast Asia and Hong Kong who are driving innovation and influencing rapid change. Winners were unveiled during an in-person awards ceremony at Marina Bay Sands in Singapore, with more than 400 executives from across Southeast Asia and Hong Kong.

    Full Story: https://www.cio.com/article/3609333/cio100-2024-the-top-transformational-tech-leaders-and-teams-in-southeast-asia-and-hong-kong.html

  • Enterprise Security Leader of the Year

    IndoSec and TradePass

    It recognizes the top cybersecurity professional in the private sector who has been the driving force in stimulating growth and bringing new-age developments in cyber strategies to ensure that the world is a step ahead of the cyber criminals.

  • AI Innovative Leader of the Year

    BConnect Global

    AI Innovative Leader of the Year award 2024

  • The Most Influential Business Leaders to Watch in 2024

    The Enterprise World

    When we speak of modern leaders in the travel tech industry, Dr. Irvan Bastian Arief (VP of Data Science, Machine Learning Engineering, Tech Infrastructure, and Information Security at tiket.com) stands out with his unique leadership philosophy that prioritizes continuous learning, innovation, and a supportive environment where his team can thrive. He leverages his technical expertise with strong communication skills to translate complex concepts into actionable strategies, making him a…

    When we speak of modern leaders in the travel tech industry, Dr. Irvan Bastian Arief (VP of Data Science, Machine Learning Engineering, Tech Infrastructure, and Information Security at tiket.com) stands out with his unique leadership philosophy that prioritizes continuous learning, innovation, and a supportive environment where his team can thrive. He leverages his technical expertise with strong communication skills to translate complex concepts into actionable strategies, making him a transformational leader in the travel technology industry.

  • The World CIO 200 Summit (Category: Master)

    Global CIO Forum

    The recent World CIO 200 Summit, held in Indonesia marked a significant milestone in the global IT landscape, bringing together thought leaders, innovators, and industry experts to share insights, discuss challenges, and explore opportunities in the ever-evolving digital world.

    https://www.ec-mea.com/tech-titans-unite-world-cio-200-summit-in-indonesia-catalyzes-digital-innovation/

  • CIO100 Awards: Next CIO

    Foundry

    Irvan is the current VP of Data Science and Machine Learning Engineering at tiket.com and wins this award for pioneering advancements in AI and machine learning within his team, which have played a pivotal role in positioning the organisation as a leader in online travel agencies in Indonesia. He is well-positioned and recognised by his colleagues of all ranks as a transformative leader and mentor to create a positive impact on the business.

    The official news from CIO.com official…

    Irvan is the current VP of Data Science and Machine Learning Engineering at tiket.com and wins this award for pioneering advancements in AI and machine learning within his team, which have played a pivotal role in positioning the organisation as a leader in online travel agencies in Indonesia. He is well-positioned and recognised by his colleagues of all ranks as a transformative leader and mentor to create a positive impact on the business.

    The official news from CIO.com official website:
    https://www.cio.com/article/657854/cio100-2023-unveiling-the-top-transformational-tech-leaders-and-teams-in-asean-and-hong-kong.html

  • HAPPY Award: Category Hungry and Performance Driven

    tiket.com

  • 2022 Outstanding Taiwan Alumni of the Year <2022年度印尼留台校友會傑出校友>

    The Association of Taiwan Alumni in Indonesia (ICATI-Ikatan Citra Alumni Taiwan di Indonesia)

    The news from the media:
    1. https://www.medcom.id/cn/news/read/2022/08/29/27479
    2. https://www.hepingribao.id/home/2022/08/30/%E5%8D%8E%E7%A4%BE%E6%B4%BB%E5%8A%A8%EF%BC%9A%E5%8D%B0%E5%B0%BC%E7%95%99%E5%8F%B0%E6%A0%A1%E5%8F%8B%E4%BC%9A%E8%81%94%E5%90%88%E6%80%BB%E4%BC%9A-icati-%EF%BC%9A2022-%E5%B9%B4%E8%8B%8F/

  • 2020 Australian Alumni of the Year (The Innovation and Entrepreneurship Award)

    Australian Embassy for Indonesia and Australia Global Alumni

    The Innovation and Entrepreneurship Award was given to Dr Irvan Bastian Arief, Associate Vice President (AVP) of Data Science at Tiket.com, a Monash University and RMIT University alumni. Dr Irvan is the creator of RUP and DA-HOC machine learning algorithm and a digital executive with over than 15 years of commercial experience in technology, digital and data related domains with some of progressive multinational global companies in both Australia and Asia.

    Australia’s Ambassador to…

    The Innovation and Entrepreneurship Award was given to Dr Irvan Bastian Arief, Associate Vice President (AVP) of Data Science at Tiket.com, a Monash University and RMIT University alumni. Dr Irvan is the creator of RUP and DA-HOC machine learning algorithm and a digital executive with over than 15 years of commercial experience in technology, digital and data related domains with some of progressive multinational global companies in both Australia and Asia.

    Australia’s Ambassador to Indonesia, Gary Quinlan AO mentioned "Alumni Awards are the most distinguished honours given to Australian alumni who have made exemplary contributions in their profession and community through outstanding leadership, integrity and hard work."

    The official news from Australia Embassy's official website:
    - [English] https://indonesia.embassy.gov.au/jakt/MR20_030.html
    - [Indonesian] https://indonesia.embassy.gov.au/jaktindonesian/SM20_030.html

  • Community Innovation Award 2018 - Victorian Multicultural Awards for Excellence

    City of Melbourne

    This award is for Act of Translation.

  • SUPP Scholarship: ‘The Greener Office and Classroom’

    Sustainable Urban Precincts Program

  • SUPP Scholarship: ‘iCO2mmunity: Personal and Community Monitoring for University-wide Engagement towards Greener, Healthier, and more Productive Living’

    Sustainable Urban Precincts Program

  • The Australian Government Research Training Program (RTP) Scholarship

    Australian Government

Bahasa

  • English

    Tingkat profesional mahir

  • Chinese

    Tingkat profesional mahir

  • Indonesian

    Tingkat fasih atau penutur asli

  • Javanese

    Tingkat fasih atau penutur asli

Organisasi

  • Indonesian Student Association in Australia (PPIA)

    Vice President

    -

    Managing 13,000 Indonesian students around Australia and make decision for their benefits.

  • Indonesian Student Association in Australia (PPIA)

    Treasurer

    -

  • Indonesian Student Association in Australia - RMIT University Branch (PPIA RMIT)

    Treasurer

    -

  • Multicultural Student Fellowship (MSF)

    President

    -

  • Caulfield Information Technology Association (CITA)

    Treasurer

    -

Rekomendasi diterima

6 orang merekomendasikan Irvan Bastian

Gabung sekarang untuk melihat

Aktivitas lainnya oleh Irvan Bastian

Lihat profil lengkap Irvan Bastian

  • Melihat siapa yang sama-sama Anda kenal
  • Minta diperkenalkan
  • Hubungi langsung Irvan Bastian
Bergabung untuk melihat profil lengkap

Profil serupa lainnya

Jelajahi posting lainnya

Tambahkan keahlian baru dengan kursus ini

Lihat semua kursus