Video summary
[Asah 2026] Team Meeting #1
Main summary
Key takeaways
Business-focused Summary (Team Meeting #1 — Asah 2026)
1) Learning Motivation & Operating Philosophy (How to Execute as a Learner)
Moderator Nada used a graduate story as a motivational “KPI-by-proxy”: Brother Melvin Leonardo (ASA 2025 graduate) became an IT intern at PT HM Sampoerna Tbk (People & Culture), reportedly within ~4 months after ASA. He leveraged Capstone learning that led into AI engineering work (e.g., machine learning/automation projects for the department).
Learning philosophy / execution playbook
- Grow through each process: optimize for professional execution, not only outcomes.
- Learn with curiosity: understand concepts + application; don’t “rush to the deadline.”
- Find an effective study method: combine reading, practice, discussion, reflection; use audio/listening tools if helpful.
- Use support networks: PECE (participants + instructors/facilitators); ask meaningful questions.
- Use mistakes as learning input: apply ILT feedback to improve both delivery and learning quality.
Active learning requirement (capacity planning)
- Allocate 30–40 hours/week (6–8 hours/day).
- Completion activities include:
- Read platform modules (e.g., Decoding materials)
- Watch videos / attend ILT sessions fully
- Do exercises/submissions on the platform
- Join study groups and consult facilitators when stuck
ILT-specific operating rules
- Pre-prepare: read required preamble for soft skills.
- During ILT: stay engaged (camera on), ask/answer actively.
- After ILT: complete quiz + feedback form, and re-study based on insights.
Grade/recording risk
- If you participate passively or don’t get recorded as “active” during ALT/ILT, you may lose allocated scoring portions.
“Literacy” process (information retrieval + compliance)
- Before asking questions, search provided documents first to reduce latency and improve self-sufficiency.
- Referenced documents:
- Cohort guide
- Welcome kit
- Welcome guide
- Assessment system
- Code of ethics
- “Jem(in)ai notebook” was mentioned as an information-finding tool.
Submission quality control
- Don’t submit without meeting requirements—review rejection slows you down.
- Review turnaround: ~3 working days
- Common rejection cause: incomplete requirement fulfillment
- Action rule:
- Read requirements, verify format + purpose + checklist before submitting, and re-check before sending.
2) Program Progress Management (MA1 → MA2) with Deadlines & Drop-out Risk
Moderator Nada and team discuss Mandatory Achievements (MA) with focus on MA2 timing and consequences.
MA1 results (performance snapshot)
- 85.2% passed MA1
- 14.98% did not pass
- Participants who passed are advised to start building MA2 targets immediately (even though MA2 officially starts later).
MA2 operating timeline (hard constraints)
- MA2 access/anticipation notice: around Oct 12–13, 2026
- Sent to participants + supervising lecturers
- MA2 cut-off: Oct 20, 2026 at 23:59 WIB
- Results announcement: Oct 21–22, 2026
- Appeal & consolidation window: Oct 22–25, 2026
- Final results after appeals: Oct 26–27, 2026
Consequence
- If MA2 requirements aren’t met by cut-off: dropout (cannot continue Asah 2026).
KPIs / thresholds during MA2
- Daily check-ins
- Minimum cumulative: 29 check-ins
- Accumulation period: since Aug 18 (not reset to MA2 period)
- ALT feedback
- Complete at least 3 out of 4 ILT/ALT feedback items
- Soft skills tasks
- Must complete Soft Skills 1–3
- Soft Skills 3 appears to land next week per meeting flow
- ILT sessions attendance
- Must attend multiple soft-skill and ILT sessions (total stated: 6 sessions)
Mandatory achievement “failure factors” from MA1 (root-cause themes)
- Two primary failure drivers:
- Daily check-in issues
- ALT/ILT attendance problems
Daily check-in mechanics vs daily streak
- Daily check-in: manual learning reflection/logbook used for MA requirements.
- Daily streak: automated rhythm/discipline signal based on module progress/submission completion.
- Compliance note: wrong check-in entries may be visible to supervisors via the dashboard.
Cohort mechanics & non-real-time updates
- Attendance/dashboard updates are periodic, not instant.
- If not updated:
- Don’t immediately appeal; first validate in tracker/sheets
- Soft skills assignment updates occur 3x/week (Mon/Wed/Fri).
3) MA2 Learning-Pad Targets (Assignment Portfolio & Submission Targets)
The team lists Learning Pads (ALP/Learning Pad tracks) and what to complete for MA2.
Submission portfolio target date
- Ideal submission cutoff for MA2 learning pads: Oct 12, 2026
- Note: allowance exists as long as submission is before the cut-off.
ALP / Learning Pad specifics (examples given)
AI Full Stack Developer
- Learn JavaScript basics
- Build web front-end basics
- Create web app with React
- React fundamentals for web apps
- Minimum requirement: at least 1 React single-page application submission
- First submission accepted as meeting requirements.
Specialist Data Science
- Start Python programming
- Data analysis beginner
- Machine learning beginner
- Aligned with Gen AI Engineer / AI Engineer path.
Data science class change note
- As of Aug 3, 2026, completion mechanism changed from final exam → submission-based scoring.
- If completed before the mechanism change: renew certificate to get the updated submission score.
4) Governance: Grading Model, Academic Dashboard, and Compliance Risks
Graduation/assessment scoring model (grading rubric) — presented by Desi
Four assessment activity criteria:
- ALT quiz
- Activities during ILT
- Average/project submission
- Soft skills assignment
Weighting mentioned (for final grade calculations)
- ALT quiz: 25%
- ILT activities/submission: 10–15%
- Also described earlier as “activities 10 to 15,” and earlier indicates submission 65% (wording varied across references)
- Project/ex submission: 65%
- Soft skills: 60%
- Later clarified as part of soft skills breakdown
Important execution rule (retry submissions)
- When repeating submissions, the system takes the first passed grade (not the highest retry score) for the submission-weighted component.
Soft skills breakdown
- Soft skills score:
- 25% quizzes
- 15% activities
- 60% assignments
- Soft skills completion must be on time.
Dashboard governance rules (academic program dashboard)
- Attendance, progress, and soft skills assignment status updates are periodic.
- If inconsistent:
- verify renewal certificate requirement flags
- ask via Discord/official channels after checking tracker.
5) Academic Integrity Operations: Plagiarism + Sanctions + Appeal Workflows
Plagiarism policy (Desi)
- Use official references from official coding platforms and docs (not GitHub/YouTube/StackOverflow/other codebases).
- Don’t reuse/share identical code (“send the same code” / “unofficial tutorials”).
Sanctions if plagiarism is detected
- 3-day suspension, with escalating steps mentioned (exact repetition: “3-day suspension, and the last is suspension…”).
- Progress may be reset to zero.
Soft skills plagiarism sanction
- Soft skills score becomes 0.
Appeal workflow (if incorrectly flagged)
- Submit appeal via specified emails:
- submission@doding.com
- reviewer@dcoding.com
- Rules for successful appeal:
- Appeal supports only one submission
- Provide evidence/screenshots with clarity, including session/time details
- Use correct email formatting (subject vs body)
- Don’t upload code to GitHub before acceptance to avoid trace inconsistencies.
6) Attendance Governance & Rescheduling / Abstract Appeal Processes
ALT rescheduling
- Reschedule before submitting the abstract (only if truly unable to attend).
- Steps:
- Check weekly schedule availability first
- Submit reschedule form
- Receive email confirmation
- Send requests at least one business day before the session if possible
- Dashboard updates are periodic and may take ~hours after email.
Abstract (when unable to attend)
- Must watch ALT session recording after submitting abstract.
- Abstract does not replace ALT quiz score—attendance still matters.
Abstract validity rule (example)
- Repetitive keyword “productivity” repeated excessively → abstract invalid.
Attendance appeals
- Only possible if attendance status is absent.
- File appeal ~1 week after the session.
- Evidence requirements:
- Proof you attended: photo with name/time/session (not blurry)
- Join using correct email credentials
- Invalid evidence examples:
- Missing session details, missing timestamp, generic selfies
- Don’t appeal before the “one-week-later” window.
7) Capstone Project Preview (MSME Impact Track) — Entrepreneurship/Productization Pipeline
Presented by Mas Fikri (with moderator guidance).
What Capstone is (definition + business rationale)
- Final-stage group project with structured criteria.
- Benefits framed as business execution capabilities:
- Problem-solving with technology
- Team collaboration leadership experience
- Applying learning to real situations
- Demo outcomes + feedback from MSMEs/mentors
Capstone theme
- MSME Impact Track
- Each capstone team develops solutions for business problems from MSMEs
- Adoption feedback loop is encouraged.
Capstone workflow / value chain
- Form capstone team
- Identify and recruit MSME candidates
- Eligibility criteria shared later
- Register MSMEs for Decoding; ASA validates:
- MSME eligibility
- business problem suitability
- Then:
- Plan → build digital solution → demo to MSME → collect feedback
- If MSME adopts the solution:
- additional collaboration opportunities beyond Decoding.
Kickoff timing
- Capstone kickoff session: Thursday, Oct 1
- Before kickoff emphasis:
- Network across learning packs so the team is ready
- Map MSMEs nearby (start identifying candidates)
- Keep learning progress on track so MA2 doesn’t block capstone readiness
8) Q&A Highlights (Operational Clarifications)
- MA1 passed but MA2 late/failed
- If MA2 not passed by cut-off → can still be expelled/dropout
- 0% progress on dashboard after class passed
- Check if class was completed before July 15; otherwise certificate renewal may be needed
- If requirements unchanged, previous submission may be reusable
- If changed, redo from scratch
- Capstone team formation
- Team composition and registration details released at kickoff
- If you don’t get a team by end, ASA team may assign/team-build participants
- Team based on learning packs combination (e.g., DSS + GenAI engineer + AI full stack)
- Transcripts for credit conversion
- Two transcript types:
- Interim transcript (class grades so far; may change)
- Final transcript
- Interim used for earlier needs; ensure class completion speed for better final outcomes.
- Two transcript types:
- Deadline vs MA cut-off
- You may exceed module “class deadline” as long as you finish before MA cut-off
- Daily check-ins on holidays
- Weekdays preferred, but studying on holidays can count if filled out.
Presenters / Sources Mentioned
- Nada — Moderator; presented agendas 1 & 2
- Desi — Presented Agenda 3 (grading/academic policies); also participated in Q&A
- Fikri / Mas Fikri — Presented Agenda 4 (Capstone preview); participated in Q&A
- Brother Melvin Leonardo — Graduate example motivating learning & AI engineering path
- Mas Radityya Gumay (Goto Engineering) — Guest speaker (future-proofing care in the age of AI)