Analisis Statistik Pendidikan Guru Sekolah Dasarr

📊 Statistik Deskriptif Institusi Skala Besar

Animo (Interest)

Mean:648.44

Median:683

Std Dev:268.44

Range:300 - 1,070

CV:41.4%

Shape:Symmetric (0.087)

Daya Tampung

Mean:300.22

Median:338

Std Dev:155.91

Range:45 - 480

CV:51.93%

Shape:Symmetric (-0.377)

Hasil Seleksi

Mean:482.56

Median:542

Std Dev:268.39

Range:109 - 807

CV:55.62%

Shape:Symmetric (-0.242)

Mhs Baru

Mean:412.00

Median:421

Std Dev:220.27

Range:97 - 676

CV:53.46%

Shape:Symmetric (-0.209)

Mhs Aktif

Mean:2,733.56

Median:2,905

Std Dev:1,991.22

Range:688 - 6,592

CV:72.84% (HIGH)

Shape:Mod. Skew (0.527)

Wisuda

Mean:602.78

Median:418

Std Dev:388.02

Range:281 - 1,369

CV:64.37%

Shape:Mod. Skew (0.818)

📈 Time Series Analysis: Dramatic Growth Trajectory

🚀 EXTRAORDINARY GROWTH: Hasil +529%, Mhs_Baru +531%, Animo +166% dalam 8 tahun! Namun Wisuda menurun -52.5% - menunjukkan graduation bottleneck yang perlu segera ditangani.

🔗 Matriks Korelasi: Strong Relationships Identified

Variable	Animo	Daya_Tampung	Hasil	Mhs_Baru	Mhs_Aktif	Wisuda
Animo	1.000	0.791	0.910	0.908	0.694	-0.642
Daya_Tampung	0.791	1.000	0.696	0.625	0.393	-0.427
Hasil	0.910	0.696	1.000	0.977	0.816	-0.756
Mhs_Baru	0.908	0.625	0.977	1.000	0.833	-0.684
Mhs_Aktif	0.694	0.393	0.816	0.833	1.000	-0.452
Wisuda	-0.642	-0.427	-0.756	-0.684	-0.452	1.000

🔍 CORRELATION HIGHLIGHTS: Hasil ↔ Mhs_Baru (0.977) = Near Perfect! Namun ALL variables berkorelasi NEGATIF dengan Wisuda - indikasi system bottleneck graduation.

🏆 Flagship Regression Model: Excellence Achievement

⭐ MODEL TERBAIK: HASIL → MHS_BARU

Mhs_Baru = 25.115 + 0.802 × Hasil

95.4%

R² Accuracy

80.2%

Conversion Rate

8:10

Success Ratio

Excellence Interpretation: Every 10 hasil seleksi produces exactly 8 new enrolled students. This model explains 95.4% of variance - nearly perfect predictive power!

Animo → Hasil (r = 0.91)

Hasil = -107.12 + 0.909 × Animo

R² = 0.827 • Selection Rate: 90.9%

Interpretation: Outstanding conversion dari interest ke acceptance. Setiap 100 animo menghasilkan 91 hasil seleksi.

Mhs_Baru → Mhs_Aktif (r = 0.833)

Mhs_Aktif = -370.11 + 7.533 × Mhs_Baru

R² = 0.694 • Accumulation Factor: 7.53x

Interpretation: Setiap mahasiswa baru berkontribusi 7.53x pada total mahasiswa aktif - menunjukkan akumulasi tinggi.

⚠️ CRITICAL: Hasil → Wisuda (r = -0.756)

Wisuda = 1129.89 + (-1.092) × Hasil

R² = 0.571 • NEGATIVE Correlation!

PARADOX: Semakin tinggi hasil seleksi, semakin rendah wisuda! Possible system bottleneck atau timing effect.

📊 Multiple Regression Analysis

Multi-Variable Predictive Models

1. Daya_Tampung vs (Animo + Hasil)

Daya_Tampung = -6 + 0.531×Animo + (-0.079)×Hasil

R² = 0.629 • Adj R² = 0.506 (Good Quality)

Insight: Animo positively influences capacity planning, namun hasil seleksi berpengaruh negatif.

2. Daya_Tampung vs (Hasil + Mhs_Baru)

Daya_Tampung = 127 + 1.095×Hasil + (-0.862)×Mhs_Baru

R² = 0.553 • Adj R² = 0.403 (Moderate)

Insight: Trade-off relationship - tinggi hasil tapi rendah enrollment memicu capacity expansion.

3. Wisuda vs (Mhs_Baru + Mhs_Aktif)

Wisuda = 1127 + (-1.771)×Mhs_Baru + 0.075×Mhs_Aktif

R² = 0.513 • Adj R² = 0.351

Complex Dynamics: New students negatively correlate, active students positively - graduation timing effects.

4. Simple: Wisuda vs Mhs_Aktif

Wisuda = 843.45 + (-0.088) × Mhs_Aktif

R² = 0.204 (Weak - Complex Dynamics)

Challenge: Weak relationship indicates complex graduation factors beyond active student count.

🔮 Prediksi Trend Linear 2025-2027: Massive Scale Ahead

Proyeksi Berdasarkan Trend Analysis

Variable	2025	2026	2027	Growth Trend
Animo	1,056	1,138	1,219	📈 +81.55/year
Daya_Tampung	447	477	507	📈 +29.58/year
Hasil	896	979	1,061	📈 +82.78/year
Mhs_Baru	752	819	887	📈 +67.77/year
Mhs_Aktif	5,579	6,148	6,717	🚀 +569.13/year
Wisuda	221	144	68	📉 -76.4/year

💡 Critical Insights & Strategic Implications

🏆 Admission Excellence Achievement

World-Class Performance: Model hasil→mhs_baru dengan akurasi 95.4% menunjukkan sistem admission yang sudah mencapai excellence level. Conversion rate 80.2% dan selection rate 90.9% menunjukkan efficiency luar biasa.

Predictable Pipeline: Relationship yang sangat kuat (r=0.977) memberikan kemampuan forecasting yang sangat akurat untuk resource planning.

⚠️ Graduation Crisis Identified

Critical Finding: Semua admission metrics berkorelasi NEGATIF dengan wisuda. Hasil seleksi naik 529%, namun wisuda turun 52.5% - menunjukkan system bottleneck yang parah.

Urgent Action: Dengan proyeksi 6,717 mahasiswa aktif di 2027 namun wisuda hanya 68, rasio throughput menjadi 1.01% - completely unsustainable!

📈 Exponential Growth Trajectory

Massive Scaling: Institusi mengalami pertumbuhan eksponensial dengan accumulation factor 7.53x. Setiap mahasiswa baru berkontribusi 7.53 pada total mahasiswa aktif.

Infrastructure Challenge: Dari 1,114 (2016) ke proyeksi 6,717 (2027) = 503% growth dalam 11 tahun memerlukan proportional infrastructure investment.

🎯 Strategic Opportunity

Excellence Foundation: Sistem admission sudah excellent, tinggal optimize graduation pipeline. With flagship model accuracy 95.4%, focus dapat dialihkan ke throughput efficiency.

Competitive Advantage: Conversion rate 80.2% dan selection rate 90.9% memberikan competitive advantage yang sustainable jika graduation bottleneck dapat diatasi.

🏛️ Analisis Statistik Pendidikan Guru Sekolah Dasar