Long Short-Term Memory (LSTM) dengan Algoritma Pemrosesan untuk Peramalan Kedatangan Wisatawan pada Data Time Series

Buku Long Short-Term Memory (LSTM) untuk Peramalan Kedatangan Wisatawan pada Data Time Series ditujukan bagi mahasiswa, dosen, dan masyarakat umum dari berbagai tingkat pemahaman, membahas konsep, metode, tantangan, dan implementasi peramalan data wisata berbasis LSTM dan model hibrida. Dimulai dengan landasan filosofis dari kisah Nabi Yusuf AS, buku ini menguraikan perkembangan metode dari teknik statistik tradisional hingga deep learning, alasan pemilihan LSTM, serta integrasinya dengan Hilbert-Huang Transform (HHT) dan algoritma lain untuk meningkatkan akurasi. Disertai pembahasan dataset BPS dan Google Trends, teknik pra-pemrosesan, evaluasi model dengan berbagai metrik, hasil eksperimen, dan implementasi di Google Colab, buku ini menunjukkan bahwa kombinasi LSTM dan HHT mampu meningkatkan akurasi prediksi, mengurangi noise, dan mendukung pengambilan keputusan strategis di sektor pariwisata, serta memberikan rekomendasi untuk pengembangan model prediktif yang lebih adaptif di masa depan.

Kata Pengantar......................................................................................v

Daftar Isi.............................................................................................vii

Daftar Tabel...........................................................................................x

Daftar Gambar.....................................................................................xii

Daftar Singkatan................................................................................xiii

Bab 1. Informasi Buku dan Sistematika Penulisan...............................1

1.1. Informasi Buku..........................................................................1

1.2. Sistematika Penulisan................................................................1

Bab 2. Pendahuluan.............................................................................12

2.1. Ayat peralaman dalam Al – Qur’an.........................................12

2.1. Pariwisata merupakan industri yang menjanjikan...................16

2.2. Permasalahan yang dibahas.....................................................22

Bab 3. Metode untuk Peramalan Kedatangan Turis............................29

3.1. Machine Learning (ML)..........................................................32

3.2. Deep Learning (DL)................................................................34

3.3. Metode Hybrid.........................................................................37

Bab 4. Masalah Peramalan Kedatangan Wisatawan dan Solusinya....45

4.1. Overfitting...............................................................................45

4.2. Noise / bias..............................................................................46

4.3. Strategi untuk Meningkatkan Akurasi.....................................50

Bab 5. Alasan Memilih LSTM sebagai Metode Peramalan Unggul...55

5.1. Kesimpulan Temuan Studi.......................................................57

5.2. Analisis Kesenjangan...............................................................58

5.3. Pentingnya mengatasi kesenjangan.........................................60

5.4. Hubungan antara kesenjangan dengan permasalahan.............61

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Bab 6. Long Short-Term Memory (LSTM).........................................63

Bab 7. Tren dan Arah DL untuk Peramalan Kedatangan Wisatawan..74

7.1. Big data untuk peramalan........................................................75

7.2. Data Indeks Pencarian Internet................................................79

Bab 8. Dataset.....................................................................................81

Bab 9. Evaluasi Model Peramalan......................................................85

9.1. Root Mean Squared Error (RMSE).........................................89

9.2. Mean Square Error (MSE).......................................................90

9.3. Mean Absolute Percentage Error (MAPE)..............................91

9.4. Mean Absolute Error (MAE)...................................................92

9.5. Mengukur Akurasi Peramalan dengan Confusion Matrix.......93

Bab 10. Algoritma DL dengan Teknik Pemrosesan............................95

10.1. Proses Pembentukan Dataset.................................................96

10.2. Pengurangan Noise dengan HHT........................................101

Bab 11. Hasil Percobaan...................................................................104

11.1. Dataset dan pengaturan eksperimen....................................104

11.2. Pembersihan data Hilbert - Huang Transform (HHT).........105

11.3. Pembahasan.........................................................................107

Bab 12. DL untuk Peramalan dengan Algoritma Pemrosesan..........112

Bab 13. Efektivitas DL Berbasis LSTM yang ditingkatkan..............117

13.1. Pengantar LSTM untuk peramlan........................................117

13.2. LSTM untuk peramlan dengan HHT...................................118

13.3. Evaluasi Hasil Peramalan....................................................125

Bab 14. Implementasi dengan Colab.................................................129

14.1. Idenfitikasi dan pembentukan data......................................129

14.2. Peramalan menggunakan LSTM.........................................139

Bab 15. Kesimpulan Pekerjaan Masa Depan....................................153

15.1. Kontribusi keilmuan............................................................154

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15.2. Detail Kontribusi.................................................................155

15.3. Pekerjaan Masa Depan........................................................157

15.4. Ringkasan kontribusi...........................................................158

Daftar Pustaka...................................................................................160

Lampiran A........................................................................................180

Lampiran B........................................................................................183

Biografi Penulis.................................................................................188

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