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PREDIKSI HARGA INDEKS SAHAM KOMPAS 100 DENGAN MODEL LONG SHORT-TERM MEMORY DA…
ULPAH, MARIAZULKARNAIN, AMMAR ISKANDAR

Penelitian ini bertujuan untuk menganalisis dan membandingkan kinerja dua model deep learning, yaitu Long Short-Term Memory (LSTM) dan Convolutional Neural Network (CNN), dalam memprediksi harga sa…

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-
Call Number
7790
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NEURAL NETWORKS AND THE FINANCIAL MARKETS: PREDICTING, COMBINING AND PORTFOLI…
SHADBOLT, JIMMYTAYLOR, JOHN G.

This book looks at how research into predicting the financial markets has progressed in recent years. The first section of the book describes the financial markets and asks whether they are indeed …

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Call Number
006.32 SHA n
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NEURAL NETWORKS IN FINANCE: GAINING PREDICTIVE EDGE IN THE MARKET
MCNELIS, PAUL D.

This book explores the intuitive appeal of neural networks and the genetic algorithm in finance. It demonstrates how neural networks used in combination with evolutionary computation outperform cla…

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Call Number
332.0285 MCN n
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BURNOUT KARYAWAN DI TENGAH PANDEMI COVID-19: PREDIKSI TINGKAT BURNOUT MENGGUN…
HANIF, IMAM RAFIFALVERSIA, YESHIKA

Burnout mengacu pada reaksi psikologis terhadap stres kerja kronis. Fenomena burnout merupakan fenomena yang harus diatasi oleh perusahaan karena membawa pengaruh negatif terhadap produktivitas dan…

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-
Call Number
6799
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OPTIMALISASI PORTOFOLIO INVESTASI SAHAM-SAHAM LQ45 DENGAN MENGGUNAKAN MODEL MARKOWITZ
WARDANI, BUDI SETYO
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PENGARUH TIPE PERTUMBUHAN DAN GENDER TERHADAP PERSISTENSI STRUKTUR MODAL PERUSAHAAN NON KEUANGAN
DEWI, RHEINY PUSPITA
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ANALISIS PERBEDAAN STRES TUNTUTAN PERAN PEKERJAAN ANTAR DEMOGRAFI PADA PT. X
SETIAWAN, RYAN
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ANALISIS ELECTRONIC SERVICE QUALITY (E-SERVQUAL): HUBUNGAN TERHADAP E-CUSTOMER SATISFACTION, REUSE INTENTION, SERTA WORD-OF-MOUTH
SETYOWARDHANI, HAPSARI - SITOMPUL, JOSHUA ENRICO
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STRATEGI BERSAING PT. ANDHI CHANDRA AP. TBK. DALAM MENGHADAPI ERA PERDAGANGAN BEBAS
SYAHABUDDIN, AGUS - ASSAURI, SOFJAN
RLC MM FEB-UI
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RLC MM-FEBUI (Library) occupies the right side of the ground floor of the MM FEB UI Building with a reading room capacity of more than 60 people.
 
The MM-FEB UI library service system is closed (closed access); where the user does not have direct access to the collection shelf. Or in other words, users are not allowed to take their own books from the collection shelf

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