Client: Ministry of Public Works and Housing (PUPR) & BKD East Java — Government of Indonesia Services: AI for Government · Custom Software Year: 2025 Technology: Next.js, Adaptive Testing Algorithm, Dashboard, Government
Background
The Indonesian government requires all civil servants (ASN) in managerial positions to undergo periodic competency assessments. These assessments cover 9 managerial competency dimensions mandated by national regulations: integrity, communication, national cohesion, results orientation, public service, teamwork, change management, decision-making, and self and others development. The Ministry of PUPR, with thousands of officials spread across Indonesia, needed an assessment system that was accurate, efficient, and capable of operating at scale.
Challenge
The existing ASN competency assessment system faced several fundamental problems:
- Inaccurate static exams: Exams with uniform difficulty levels failed to measure competency precisely — highly capable officials received questions that were too easy, while developing officials received questions that were too difficult
- Slow manual processes: Exam administration, grading, and report generation were done manually or semi-digitally, consuming significant time and resources
- Difficult to scale: Conducting assessments for thousands of officials across various organizational units and regions simultaneously presented a massive logistical challenge
- Results lacked actionability: Conventional exam reports provided only total scores without detailed per-dimension competency profiles, making it difficult to determine specific training needs
Solution
GTM built Kompetify, an adaptive testing platform that dynamically adjusts question difficulty based on test-taker performance in real-time.
Adaptive Exam Engine
Each exam consists of 27 dynamically selected questions. The adaptive algorithm adjusts difficulty levels (scale of 1–5) based on previous answer weights — ensuring each test-taker receives appropriately challenging questions for precise competency measurement.
9-Dimension Competency Assessment
The system scores each managerial competency dimension independently, producing detailed competency profiles — not just aggregate scores. These profiles clearly show each official's strengths and development areas.
Class and Batch Management
Organizers create exam classes linked to adaptive profiles, managing enrollment, scheduling, and access control. The batch system supports large-scale assessments across multiple organizational units simultaneously.
Structured Question Bank
A rich text editor with image support allows administrators to manage questions tagged with competency, indicator, and difficulty metadata. Bulk import via CSV and Excel streamlines question bank population.
Visual Reporting
Reports with interactive charts present individual competency profiles and aggregate results. PDF report generation enables offline distribution, while dashboard analytics help monitor completion rates and score distributions.
Development Process
- Regulatory and standards research: Studying the 9 managerial competency dimensions mandated by ASN regulations and adaptive testing best practices
- Adaptive algorithm design: Designing and validating an algorithm that adjusts question difficulty based on test-taker responses in real-time
- Platform development: Building the end-to-end platform including the exam engine, question bank management, and reporting dashboard
- Pilot at Ministry of PUPR: Initial trial with PUPR officials to validate adaptive assessment accuracy
- Expansion to BKD East Java: In October 2025, BKD East Java signed a cooperation agreement to adopt Kompetify for assessing ASN competencies across provincial agencies
Results
- Adopted by 2 government agencies — Ministry of PUPR and BKD East Java, demonstrating the platform's scalability and quality
- 9 competency dimensions assessed independently per participant, producing far more actionable profiles than conventional exams
- 27 adaptive questions per exam with dynamically adjusted difficulty (scale of 1–5)
- Large-scale assessments enabled through automated batch and class management systems
- Detailed competency reports with graphical visualizations for each individual and cohort
Technology Stack
- Next.js — Frontend framework for a responsive exam interface
- Adaptive Testing Algorithm — Proprietary algorithm for dynamic question difficulty adjustment
- Dashboard — Data visualization and interactive reporting
- Government — Architecture meeting government security and compliance standards