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Algorithm Documentation

Enhanced Confix-Stripping (ECS)

This stemmer implements the Enhanced Confix-Stripping (ECS) variant of the Nazief-Adriani algorithm as described in Asian et al., 2007.

Overview

The ECS algorithm improves upon the original Nazief-Adriani (1996) by:

  1. Iterative confix-stripping (up to 4 passes)
  2. Nasal-assimilation restoration
  3. Phonotactic validity guards
  4. Two-path candidate generation

Algorithm Steps

1. Clitic Removal

First, remove the possessive/determiner clitic -nya:

bukunya → buku
merekan → mereka

2. Iterative Confix-Stripping

For up to 4 passes, the algorithm strips:

  • One prefix family
  • One derivational suffix

Prefix Families (in priority order)

Family Examples
me(N)- membaca, menulis, mengambil
pe(N)- pembaca, penulis, pengambil
ber- berjalan, bertanya
ter- terlihat, terkenal
se- selesai, serupa
ke- kesalahan, kebersihan
di- dibaca, ditulis

The N in me(N)- and pe(N)- represents nasal assimilation:

  • meng- → g before vowels: mengambil → ambil
  • men- → t before vowels: menulis → tulis
  • men- → s before vowels: menyapu → sapu
  • meny- → s before vowels: menyanyi → nyanyi

Derivational Suffixes (in priority order)

  1. -kan
  2. -an
  3. -i

3. Inflectional Suffix Fallback

If no prefix matched, remove inflectional suffixes:

  • -lah
  • -kah
  • -tah
  • -pun

4. Nasal-Assimilation Restoration

When a prefix with nasal assimilation is stripped, the algorithm reconstructs the dropped consonant:

menulis → (strip men-) → nulis → (restore t) → tulis
mengambil → (strip meng-) → ngambil → (restore g) → ambil

Without a dictionary, the algorithm prefers the longer candidate when ambiguous.

With a dictionary, the first candidate found in the FST wins.

5. Phonotactic Validity Guards

Indonesian phonotactics forbid CC-onset (consonant clusters at word start). The algorithm discards candidates that would create invalid CC-onsets:

Valid: baca, tulis, jalan
Invalid: blajar (from belajar), ktulis (from ketulis)

This prevents over-stemming.

Two-Path Candidate Generation

The algorithm explores both orderings:

  1. Prefix-first then suffix
  2. Suffix-first then prefix

Candidates from both paths are combined and ranked. The longer candidate is preferred when no dictionary is available.

Example Walkthrough

Example: mempertimbangkan

Pass 1:

  • Strip memper- → timbangan
  • Strip suffix -an → timbang

Pass 2:

  • No more prefixes/suffixes to strip

Result: timbang

Example: pembelajaran

Pass 1:

  • Strip pem- → belajaran
  • Strip suffix -an → belajar

Pass 2:

  • Strip be- → lajar
  • No suffix

Result: lajar (but with dictionary, ajar might be preferred)

Accuracy

Without dictionary: ~85-90% accuracy on common Indonesian words With dictionary: ~95-98% accuracy

The dictionary helps resolve ambiguous cases, especially with nasal-assimilation prefixes before vowel-initial roots.