Background Information

Hendra Bunyamin is a lecturer who graduated from Mathematics department Bandung Institute of Technology and Software Engineering, Informatics department from the same university.

He is very passionate about teaching. Mainly, he teaches mathematics and programming.

His research interests are techniques on how to apply machine learning algorithms.

Research

2021

Utilizing Indonesian Universal Language Model Fine-tuning for Text Classification
Journal of Information Technology and Computer Science (JITeCS)

2020

Classical and Deep Learning Time Series Prediction Techniques in the Case of Indonesian Economic Growth
The 5th International Conference on Information Technology and Digital Applications (ICITDA)

2019

Topic Clustering and Classification on Final Project Reports: a Comparison of Traditional and Modern Approaches
IAENG International Journal of Computer Science, vol. 46, no. 3, pp 506-511, 2019

2018

Analisis Performa dan Pengembangan Sistem Deteksi Ras Anjing pada Gambar dengan Menggunakan Pre-Trained CNN Model
Jurnal Teknik Informatika dan Sistem Informasi Volume 4 Nomor 2 Agustus 2018

2018

The Relationship between Country Risk and Company Performance in Southeast Asia
Journal of Business & Retail Management Research Vol-12, Issue 3, April 2018

2018

Pemanfaatan Inverted Index pada Proses Penelusuran Kesamaan Isi File Dokumen pdf Tugas Akhir Mahasiswa
Seminar Nasional Teknologi Informasi dan Komunikasi (SENTIKA)

2017

Automatic Topic Clustering Using Latent Dirichlet Allocation with Skip-gram Model on Final Project Abstracts
The 21st International Computer Science and Engineering Conference (ICSEC)

2016

A Comparison of Retweet Prediction Approaches: The Superiority of Random Forest Learning Method
TELKOMNIKA (Telecommunication Computing Electronics and Control)

2013

Sentiment Classification Menggunakan Machine Learning: Metode Naive-Bayes dan Support Vector Machines (Studi Kasus: Movie Reviews imdb.com)
Seminar Teknologi Informasi dan Sistem Informasi (SETISI)

2008

Aplikasi Information Retrieval (IR) CATA dengan Metode Generalized Vector Space Model
Maranatha Informatics Journal

2005

Information Retrieval System dengan Metode Latent Semantic Indexing
Master Thesis at Bandung Institute of Technology
Courses

8 September 2021

IN035 Matematika Diskrit
Semester Antara 2020/2021

Kelas Matematika Diskrit yang diadakan pada Semester Antara 2020/2021. Playlist ini terdiri dari 13 video. Sebagian besar materi diambil dari buku Susanna S. Epp (Discrete Mathematics with Applications 5th Edition) dan Kenneth Rosen (Discrete Mathematics and Its Applications 8th Edition)

(Youtube playlist)

12 April 2021

Interpretable Machine Learning: The Basics
My Talk at NUNI IT Online Seminar Phase #2

The session introduces supervised learning which emphasizes the four components of machine learning (dataset, model/hypothesis, cost function, and optimization algorithm). Furthermore, the session shows machine learning interpretability with a linear regression as a running example.

(slides & codes) (video)

17 November 2020

Interpretable Machine Learning
My Talk at Binus University for Global Learning System

I follow closely to what is presented by the online bookInterpretable Machine Learning” by Christoph Molnar. “Interpretable Machine Learning” is quite a good book. Thank you for writing this book Mr. Molnar!

(slides)

July 2020

IN046 Statistika
Semester Antara 2019/2020

The course follows closely to “Elementary Statistics” book by Ron Larson and Elizabeth Farber. Thank you so much Mr. Larson dan Ms. Farber for writing such a wonderful book!

(Youtube playlist)

List of MOOCs

March 2021

AI for Everyone
Provided by Coursera

November 2020

Specialized Data Processing in R: Strings and Dates Course
Provided by Dataquest.io

23 October 2020 - 22 October 2023

Competency in the area of : Software Development with Qualification : Programmer
Provided by Indonesian Professional Certification Authority

November 2020

Control Flow, Iteration, and Functions in R
Provided by Dataquest.io

November 2020

Data Structures in R
Provided by Dataquest.io

November 2020

Introduction to Data Analysis in R
Provided by Dataquest.io

14 September 2020 - 15 September 2023

HCIA - Artificial Intelligence
Provided by Huawei

August 2020

Improving Deep Neural Networks: Hyperparameter tuning, Regularization, and Optimization
Provided by Deeplearning.ai

January 2020

Neural Networks and Deep Learning
Provided by Deeplearning.ai

September 2019

Probabilistic Graphical Models 1: Representation
Provided by Stanford Online

May 2019

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
Provided by Deeplearning.ai

January 2019

Coursera Mentor Community and Training Course
Provided by Coursera

November 2018

Machine Learning
Provided by Stanford Online

July 2018

Natural Language Processing
Provided by Higher School of Economics, National Research University

April 2018

Deep Learning Nanodegree
Provided by Udacity

Contact

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