From Raw Data To Reliable Systems

Information Systems student at BINUS University, working across data analysis, business analysis, and quality assurance.

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Portrait of Benedictus Bagas

Tools I Work With

About

A Short Introduction

I study Information Systems at BINUS University with a GPA of 3.88/4.00. In 2025 I was named SIS Outstanding Student and made the Dean's List. I work where business processes, data, and software meet.

I like turning scattered data into something people can rely on. As an SSO part-timer I used Power Query, Power Pivot, and PivotTables in Excel and built a KPI table to improve task monitoring. As a QA tester in the ISPM program I design and run test cases for the IS Lab Management web app, document the results, and work with developers to close defects. As an FYP Leader I monitored the Freshmen Leaders and Freshmen Partners who mentor first-year students.

I am working toward a data analyst role. I build on SQL, Python, and database fundamentals, and I am learning machine learning so I can use data to support better business decisions. This site collects the projects and experience behind that.

What I Bring

Data Skills First, Then the Systems Around Them

How I Work

Four Steps, In This Order, Every Time

  1. Understand

    Start from the decision the numbers must support and who will read them, as with the KPI table I built for task monitoring.

  2. Clean

    Check raw exports for gaps and inconsistent names, map them to one standard, and reshape them in Power Query before any analysis.

  3. Build

    Model the clean data in Power Pivot and report it with PivotTables or a Tableau dashboard, using the simplest tool that answers the question.

  4. Verify

    Test the result against expected cases, document what passed and what failed, and follow defects through with stakeholders, as I do as a QA tester.

Selected Work

Case Studies, With the Limits Written Down

More Projects

Experience

Where I Have Worked With Data

  1. Feb 2026 – Present

    QA Tester, Information Systems Project Member (ISPM)

    School of Information Systems, BINUS University · Alam Sutera, Tangerang

    • Design and run test cases for CompSIS, the IS Lab Management web app, and document the results.
    • Report defects and work with developers and stakeholders to resolve them, as one of three QA testers in a 23-person team.
  2. Jul 2026 – Sep 2026

    Part-Time Staff, Freshmen Program

    Student Support Office (SSO), BINUS University · Alam Sutera, Tangerang

    • Turned raw program schedules (about 11,000 rows), FYP point records (about 3,000 rows), and attendance data into structured workbooks with Power Query, Power Pivot, and PivotTables, so SSO and FYP Leaders could monitor progress without manual recaps.
    • Built a KPI table for attendance and session completion that SSO used for monitoring instead of calculating the figures themselves.
    • Supported the planning and running of NEXT, AE, and the FYP B30 BINUS Inauguration, and helped Freshmen Leader and FYP Leader teams resolve operational issues on the ground.
  3. Mar 2025 – Jun 2026

    FYP Leader, Batch B29

    First Year Program, BINUS University · Alam Sutera, Tangerang

    • Monitored Information Systems freshmen's activities during the First Year Program, ensuring compliance with university tasks and rules.
    • Led a team of 38 Freshmen Leaders during the New Student Experience and Transitions period, delegating tasks and mentoring them to deliver high-quality peer onboarding.
    • Monitored 38 Freshmen Partners through the Excellence Program.

Education and Certificates

Study and Credentials

Education

  • 2024 – 2028 (expected)

    Bachelor of Information Systems (S.Kom.)

    BINUS University

    GPA 3.88/4.00. SIS Outstanding Student 2025 and Dean's List 2025.

Certificates

  • Applied Database Systems using Oracle AI Database

    Oracle Academy · 2026

  • Fundamental Algoritma

    Coding Studio · 2025

  • Fundamental Python

    Coding Studio · 2024

Awards

Recognition

Organizations

Organizations and Activities

Contact

Get In Touch

Open to opportunities and collaborations at the intersection of data, business, and technology.

Email benedictusbagas310@gmail.com

Case Studies In Full

CompletedReporting automation

FYP Program Monitoring

First Year Program, batch B30 (NEXT and Inauguration)

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The source workbook is not published to protect confidential data. Screenshots shown here use anonymized or sample data.

Role
SSO Part-Timer, data processing
Tools
Excel, Power Query, Power Pivot, PivotTables
Data
Program schedule (about 11,000 raw rows), FYP point records (about 3,000 rows), and Freshmen Leader attendance (about 300 rows). Names and student IDs in the screenshots are replaced with codes.
Duration
Jul to Sep 2026
schedule rows modelled
~11k
point sources compared
3

Problem

FYP points for each freshman were recorded in three places: the Freshmen Leader's manual log, the system, and the student's own device. SSO and FYP Leaders had no way to check that they matched. SSO also could not quickly see each Freshmen Leader's attendance or the share of sessions every freshman attended, and finding freshmen who never enrolled, duplicates, or other anomalies meant scanning by hand.

Approach

Raw exports go through Power Query, where activity names are normalised through a mapping table into one clean table and then recapped per class. Power Pivot models the FYP session schedule. A Point Comparison sheet lines up the three point sources side by side. KPI tables show attendance and session completion, and conditional formatting flags duplicates, missing freshmen, and other anomalies. Anomalous rows are flagged rather than deleted, because removing a record could cost a freshman their points.

Outcome

SSO used to calculate attendance and session percentages themselves. When they saw the KPI table already built, they read the figures straight from the workbook instead. SSO and FYP Leaders could compare point records in one sheet and find anomalies through highlighting rather than manual searches.

Limits

New raw data has to be processed before it reaches the workbook, so updates are not automatic. The real-points column in the Point Comparison sheet pulls from a separate workbook that Freshmen Leaders fill in, and entries often do not follow the format, so the comparison is only as clean as that input.

Time Per File

  • Point comparison workbook: about a week
  • Attendance template: about 3 to 4 hours
  • KPI table: about 1 to 2 hours
  • FYP session schedule (Power Pivot): about 1 to 2 hours
CompletedBI dashboard

Customer Base Analytics Dashboard

Tableau course project (ISYS6915003)

Links

Role
Solo
Tools
Tableau
Data
Customer churn dataset from Kaggle, already clean: 4,852 customers and 10 selected columns (signup date, age, gender, annual income, education, marital status, dependents, tenure, contract)
Duration
About 5 hours, semester 4
customers profiled
4,852
in their first 12 months
40%

Problem

A business team needs one view of who its customers are (age, income, education, family status, contract, and how long they stay) before it plans churn or marketing work.

Approach

Four views on one dashboard: an age histogram split by gender, a heatmap of customers by income and tenure, monthly signups against average tenure, and a treemap of education by marital status. Signup date and contract filters apply to every view. The data came clean from Kaggle, so the work went into choosing the views, bins, and filters.

Outcome

59% of customers are aged 30 to 54 (median 44), and gender is split almost evenly. Half earn between 2M and 6M a year. 98% are on one- or two-year contracts. 40% have a tenure of 12 months or less, so the base skews new. Income and tenure are unrelated (correlation near 0). Signups hold steady at 363 to 450 a month with no clear season. The largest segment is married bachelor degree holders at 15%.

Limits

Descriptive only. The selected columns leave out the churn label, so the dashboard profiles the customer base and does not explain churn.

In developmentForecasting prototype

KasFlow Pro

Cash-flow concept for multi-channel MSME sellers in Indonesia

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Links

Role
Team member: web developer (vibe-coded prototype), ideation, solution design, opportunity mapping, and business model canvas
Tools
JavaScript, Vite, Chart.js
Data
Synthetic data
Duration
From 8 Sep 2026, Venture Creation course
paying users to break even (estimate)
~510
blended ARPU (estimate)
~Rp123k

Problem

MSME sellers who sell on several marketplaces and other channels reconcile payments, fees, and held funds by hand from many reports. They lose time, miss hidden fee deductions, and struggle to forecast cash.

Approach

Holt-Winters forecast with calendar factors; anomaly detection that compares fees with a rate card and flags outliers with a robust z-score. KasFlow brings every channel into one view with a cash forecast and early warnings. Two early seller interviews led to five planned improvements.

Outcome

A working prototype and business model. Course estimates put break-even at about 510 paying users, with blended ARPU of about Rp123k and fixed costs of about Rp56M per month.

Limits

The prototype was vibe-coded with AI assistance for a campus project. Churn of 5% and CAC of Rp150k are assumptions, not measurements. The five iterations from the interviews are still planned. All data is synthetic.

Note: the KasFlow Pro website is vibe-coded, built with AI coding assistance.

Final stage · Data migration in progressQA testing

CompSIS: IS Lab Management

Information Systems Project Member (ISPM), School of Information Systems, BINUS University

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Links

Role
QA Tester (one of three)
Tools
HTML, CSS, JavaScript, PHP, Laravel, MySQL, Tailwind CSS, Figma, draw.io
Data
Dummy test data
Duration
Feb to Aug 2026, with QA and backend revisions until Oct 2026. On the team from the start.
test cases
108
people on the team
23

Problem

Students asked to join competitions by chatting with IS Lab and reaching out one by one, and IS Lab tracked competitions through its own internal process. CompSIS moves competition requests onto one platform.

Approach

Features: competition information, team registration and approval, submission tracking, resource sharing, and reporting. I wrote and ran test cases module by module, documented the results, and reported defects to the developers. I also contributed design ideas from the start of the project.

Outcome

The QA team covered 108 test cases across the modules, plus extra cases that stakeholders supplied directly.

Team of 23

  • Project Manager1
  • System Analyst4
  • UI/UX Designer5
  • Front End Developer4
  • Backend Developer6
  • QA Tester (my role)3
In developmentBusiness analysis

GITC Digital Training Record System

Role
Business analyst, team project
Tools
draw.io, Google Docs
Duration
In progress, course project

Approach

Wrote the current and proposed business narratives, then modelled both with use case diagrams, use case descriptions, and activity diagrams in draw.io. User stories cover the current process.

In developmentDesktop app

BetterMe

Role
Solo, personal project
Tools
Python, PySide6, SQLite
Duration
Ongoing

Problem

I wanted to build new habits and needed a tracker that fit how I work.

Approach

Started as a habit tracker and grew one feature at a time: a to-do list, finance, and a home page that shows completion stats for each. The code is generated with AI (vibe-coded).

Outcome

Habit tracker, to-do list, finance, and home stats work. A UI redesign for gamification, with an XP system and 10 levels, is in progress.

Limits

A personal tool built with AI-generated code, not production software.