Data, code & some magic
Hello! I am Faaris Muda
Data Scientist
System Analyst
Web Developer
Technical Writer
"The difference between a successful person and others is not a lack of strength, not a lack of knowledge, but rather a lack of will." – Vince Lombardi
Online Gambling Promotion Detector
OGPD is a system developed to detect and classify online gambling-related content on social media platforms.
SPOT V2.0
A revamp and redesign version of online learning Website of Indonesia Education University (UPI).
E-commerce Analysis
Analyzed delivery times across cities in 2017, identifying delays impacting customer satisfaction. Used Python and data visualization for insights.
Search UI Tools
Tools to enhances keyword audits in Search UI with features like sorting, highlighting ads, and detailed metrics.
Online Gambling Promotion Detector
Type
Data Science
Date
14.06.2024
Technology
Python & Streamlit
Role
Full Stack
OGPD is designed to assist in classifying content related
to online gambling promotions on social media platforms.
It utilizes a
Support Vector Machine (SVM) algorithm to process and analyze data collected from
social media platform X. By gathering and processing tens of thousands of posts
labeled as positive for containing promotions and negative for not containing
promotions, a model was developed and trained so that this system can classify
whether a social media post promotes online gambling or not.
The challenge
In the current digital era, social media has become the primary platform for disseminating various types of information, including harmful online gambling information. The spread of online gambling information via social media has become a serious issue that requires effective handling because it can negatively impact the community's morals and mental health.
My solution
In response to this challenge, this study implements a
Support Vector Machine (SVM) algorithm to classify content related to online
gambling on social media platforms. The objective is to develop an accurate
classification system and present the results in an easily interpretable form to
support decision-making by authorities. The urgency of this research lies in the
need for an effective tool to detect and prevent the increasingly troubling spread
of online gambling information.
To achieve this goal, the SVM algorithm with
an RBF kernel was applied to a dataset consisting of 42,623 social media posts, with
20.3% positive content (containing online gambling information) and 79.7% negative
content.
Conclusion
The model evaluation results showed a classification
performance with an accuracy rate of 96.91%. Specifically, the model has high
precision and recall for the negative class, each at 97% and 99%, respectively, with
an F1-score of 98%, while for the positive class, the model's precision is 98%,
recall is 87%, and F1-score is 92%.
These findings indicate that the
developed SVM model is highly effective in identifying and distinguishing online
gambling-related content from normal content. The implementation of the research
results is realized in the form of an interactive website capable of collecting,
classifying, and displaying classification results along with data visualizations,
including label distribution, word frequency, and word clouds.
SPOT V2.0
Type
Web Development
Date
10.05.2022
Technology
PHP
Role
Front-End
SPOT, or the Integrated Online Learning System, is an LMS developed by Universitas Pendidikan Indonesia to meet the needs of indirect learning. On the other hand, SPOT V2.0 serves as an alternative to complement the features not available in the original version of SPOT.
The challenge
The original version of SPOT has several drawbacks. First, in terms of the interface, users find it difficult to navigate from one menu to another. Second, users struggle to determine whether there are assigned tasks, as they have to open each modal one by one. Third, the score information for completed tasks is not centralized in one place.
My solution
Redesigning the SPOT interface to make it more attractive and user-friendly. Creating a task page in SPOT that lists all assigned tasks to help students easily track their assignments. Developing a comprehensive grade page to display grades for each enrolled course. All of these features are integrated into a new website called SPOT V2.0. The website is built using the PHP programming language and MySQL database.
E-commerce Analysis
Type
Data Science
Date
18.11.2024
Technology
Jupyter Notebook & Python
Role
Data Engineer & Analyst
E-commerce is rapidly growing, and one of the key factors
in customer satisfaction is delivery time. In this project, I analyzed a public
e-commerce dataset to determine the average delivery time across various cities in
2017 and identify cities with delivery times exceeding 10 days, which could
negatively impact the customer experience.
Business Question:
How is the
average delivery time performing in each city in 2017, and are there any cities with
delivery times exceeding 10 days that could negatively affect customer satisfaction?
Dataset & methodology
Dataset:
A public e-commerce dataset containing
information about customer orders, including order creation date, shipping date, and
destination city.
Methods Used:
The data cleaning process involved
removing missing values, handling duplicates, and converting date formats to ensure
data consistency. Feature engineering was applied to calculate delivery time by
measuring the difference between order_purchase_timestamp and
order_delivered_customer_date. Additionally, exploratory data analysis (EDA) was
conducted to examine the distribution of delivery times, identify cities with the
highest average delivery time, and visualize insights using Seaborn and Matplotlib.
Analysis results & insights
The analysis of delivery time highlights a significant
variation in shipping durations, with an average delivery time of 12.26 days. The
median delivery time is 10 days, indicating that half of the orders are delivered
within this timeframe. However, there are extreme cases, with delivery times
reaching up to 195 days, which are likely outliers or data errors. Additionally, the
standard deviation of 9.41 days suggests a high level of variability in delivery
performance.
Most orders fall within the 7 to 15-day range, which aligns with
the average customer expectation. However, instances of delivery delays exceeding 20
days strongly correlate with low customer review scores, particularly 1-star
ratings. On the other hand, customers who receive their orders in less than 11 days
are more likely to give 5-star ratings, reinforcing the importance of timely
deliveries for customer satisfaction.
Conclusion & recommendations
Conclusion:
The analysis reveals that delivery time
significantly impacts customer satisfaction, with longer delivery durations
correlating with lower review scores. While the average delivery time is 12.26 days,
a large variation exists, with extreme cases reaching 195 days. A standard deviation
of 9.41 days indicates inconsistent delivery performance, which could lead to
customer dissatisfaction. Most customers expect their orders within 7 to 15 days,
and deliveries beyond 20 days are strongly associated with 1-star ratings.
Conversely, deliveries completed in under 11 days tend to receive higher
ratings.
Recommendations:
To improve customer experience and maintain high
ratings, the company should focus on reducing delivery time variability by
optimizing logistics and fulfillment processes, ensuring most deliveries are
completed within 7–11 days. Improving inventory management can also help minimize
processing delays. Additionally, investigating extreme delays, such as cases where
delivery takes up to 195 days, is crucial. Identifying the root causes of these
outliers—whether due to system errors or operational inefficiencies—will allow for
corrective actions to prevent similar occurrences in the future. Furthermore,
enhancing regional delivery strategies by assessing geographical variations in
delivery performance can help optimize routes for high-delay areas. Collaborating
with local logistics providers may further expedite shipments in regions prone to
significant delays. Lastly, setting clear customer expectations regarding delivery
times is essential to minimize dissatisfaction. Providing accurate estimated
delivery times, proactive updates, and alternative solutions for delayed shipments
can improve transparency and customer trust. By implementing these measures, the
company can enhance delivery consistency, boost customer satisfaction, and reduce
negative reviews caused by long shipping times.
Search UI Tools
Type
Web Extension Development
Date
06.02.2025
Technology
JavaScript
Role
Full Stack
Blibli.com has a search audit system designed to evaluate and improve the performance of its search engine. However, auditors often face limitations in conducting in-depth analyses and efficiently extracting information from search results. To address this issue, I developed Search UI Tools, a browser extension that adds additional features to streamline and accelerate the search audit process on Blibli.com.
The challenge
The search audit process at Blibli.com faces several key challenges that hinder efficiency and accuracy in analysis. Visibility into search UI elements remains limited, making it difficult for auditors to evaluate crucial aspects. Additionally, the available analysis tools lack depth, forcing auditors to conduct time-consuming manual inspections. The audit process also relies heavily on multiple manual steps, which not only slow down the workflow but also increase the risk of human error. Furthermore, limitations in real-time UI data extraction and analysis make it challenging for auditors to quickly gain the necessary insights. These challenges make the search audit process less effective in identifying and resolving search-related issues.
My solution
Search UI Tools is a browser extension designed to enhance the search audit experience by providing additional features beyond the built-in audit system. This extension allows auditors to easily display key product metrics, enabling faster and more efficient analysis. Additionally, Search UI Tools offers highlighting and sorting features to simplify decision-making. With this solution, auditors can perform audits more efficiently, accurately, and quickly, helping Blibli.com improve its search engine performance and overall user experience.
Passion meets
technology
As a Software Engineer, I focus on creating innovative and impactful solutions. With expertise in data science, system analysis, web development, and technical writing, I dedicate myself to projects that deliver meaningful results.
I have managed various projects, analyzed software requirements, and consulted for companies to enhance operational standards. My experience includes ERP system design and deployment, ensuring effective client communication and providing post-implementation support.
Recently, I worked as a Search Auditor at Blibli.com, where I analyzed over 300 search results per week to optimize relevance and quality, improving customer experience by 30%. I also identified and resolved over 100 search algorithm anomalies monthly to ensure more accurate search results, supporting better purchasing decisions. Additionally, I developed a browser-based system to accelerate search analysis and auditing, increasing team efficiency by 20% through process automation.
I am continually refining my skills in data science while seeking opportunities to contribute to technology-driven environments. Passionate about technology and eager to learn, I look forward to the next steps in my professional journey and the challenges ahead.
4+
Years of education
10+
Months of experience
6+
Projects done
What
can i do?
Data
science
I analyze data to uncover insights, build predictive models, and create data-driven solutions using machine learning and statistical techniques.
System
analysis
I bridge the gap between business needs and technology, conducting system requirements analysis, designing solutions, and optimizing workflows.
Web
development
I develop responsive, user-friendly websites and applications, focusing on both frontend and backend functionality to deliver seamless user experiences.
Technical
writer
I create clear, concise, and informative documentation, including user guides, technical manuals, and articles, making complex topics easy to understand.
The digital
journey
My education
2017 - 2020
Science
SMA Negeri 10 Kota BekasiDuring my time at Senior High
School 10, Kota Bekasi, I developed a strong foundation in science, particularly in Biology
and Chemistry. It was also here that my passion for technology truly began, thanks to my
involvement in the IT club, where I gained valuable technical skills and developed a keen
interest in the digital world.
As the Vice Chairperson of the Student Organization, I
further honed my leadership and organizational abilities by overseeing five divisions and
achieving a 95% program implementation rate. These experiences have equipped me with a
well-rounded skill set, balancing academic excellence with practical, hands-on application.
Fun fact: I was also the first person to add my school to Wikipedia!
2020 - 2024
Software Engineering
Universitas Pendidikan IndonesiaI graduated from Universitas
Pendidikan Indonesia with a degree in Software Engineering (Rekayasa Perangkat Lunak) from
2020 to 2024, where I gained in-depth knowledge of the Software Development Life Cycle (SDLC),
including software design, implementation, and quality assurance. In my later semesters, I
specialized in Data Engineering and Business Intelligence, focusing on data-driven
decision-making and machine learning applications.
Alongside my studies, I was
actively involved in student organizations, serving as Head of the Department of
Organizational Resource Development in the Student Association of Software Engineering, and
later becoming Vice Chairperson of PERSLIMA, the student press organization. Despite these
commitments, I maintained a high academic standard, graduating with a GPA of 3.84.
My
thesis project involved developing a system for data collection and classification using a
Support Vector Machine (SVM) to detect online gambling content on social media, showcasing my
skills in machine learning and data processing.
Work experience
November 2024 - Now
Search Auditor
As a Search Auditor Intern at
Blibli.com, I was responsible for auditing search keywords, analyzing search-related issues,
and proposing improvements to enhance search relevance and quality. My role involved
evaluating over 300 search results per week to optimize the accuracy of search algorithms,
leading to a 30% improvement in customer experience.
Additionally, I identified and resolved over 100 search algorithm anomalies per month,
ensuring that search results were more accurate and aligned with user intent, ultimately
supporting better purchasing decisions. I also contributed to the development of a
browser-based system to streamline search audits, increasing team efficiency by 20% through
automation.
This experience strengthened my analytical skills in search engine optimization (SEO), data
analysis, and algorithm evaluation. It also allowed me to work closely with cross-functional
teams to improve search functionalities, reinforcing my ability to translate technical
analysis into meaningful business improvements.
February 2023 - June 2023
Software Implementation Consultant
During my internship at HashMicro,
a leading ERP solutions provider, I worked as a Software Implementation Consultant. My primary
responsibilities included advising clients on operational standards and best business
practices, while conducting in-depth software requirements analysis to align ERP system
implementations with specific business needs. I played a key role in planning and executing
ERP deployments, ensuring seamless integration into clients' operational environments.
I collaborated closely with various teams, including Software Programmers, Business
Analysts, and Project Managers, to ensure the successful implementation of ERP systems
tailored to the unique requirements of each client. I was also responsible for testing and
validating the system, providing user training, and offering post-deployment IT support to
resolve any technical issues and maintain system stability.
As part of my internship,
I gained hands-on experience with HashMicro’s cloud-based ERP solutions, working across
modules such as inventory, sales, accounting, and manufacturing. I also enhanced my knowledge
of the Software Development Life Cycle (SDLC) and methodologies like Waterfall, Scrum, and
Agile. The internship allowed me to further develop my technical consulting skills,
problem-solving abilities, and expertise in system analysis and project management. Despite
the complexity of the projects, I maintained regular communication with clients, keeping them
informed about project progress and addressing their concerns promptly.
Licences and Certifications
2025
AI Beginner
Certified in foundational AI concepts, including machine learning, neural networks, and data analysis, demonstrating a solid understanding of AI principles and applications.
2024
Proficiency Test of English to Speakers of Other Languages
Certified proficiency in English, assessing listening, reading, writing, and speaking skills for non-native speakers.
2023
Microsoft Office Specialist: Word Associate (Word and Word 2019)
Demonstrated proficiency in Microsoft Word, including document creation, formatting, and collaboration tools in Word 2019.
2022
Android Java for Mobile Developer
Developed skills in native Android development using Java, focusing on creating robust mobile applications.
2021
AWS Cloud Practitioner Essentials
Acquired foundational knowledge of AWS cloud services, including storage, networking, and security, and how to apply them to cloud-based solutions.
2020
UI/UX Design
Gained expertise in designing user interfaces and user experiences, creating visually appealing and functional digital products.
2020
React Native Mobile App Development
Learned to build mobile applications using React Native, focusing on cross-platform development for iOS and Android.
My favourite tools and languages
Visual Studio Code
GitHub
Docker
Figma
Excel
HTML
CSS
JavaScript
PHP
Python
MySQL
React
Tailwind CSS
Bootstrap
Firebase
Streamlit
Just say hello!
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