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richardzefan

Hi, there!

  • 🔭 I'm a Undegraduated Student of Computer Science
  • ⚡ Interested in Data Science,Machine Learning, Data Analytics and Business Inteligence
  • 📩 How to recah me : LinkedIn Badge

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Python scikit-learn TensorFlow Pandas NumPy Plotly Jupyter Notebook

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Richardo Zefanya Damarjanan's Projects

amazon_stock_price_timeseries icon amazon_stock_price_timeseries

Amazon.com, Inc. adalah multinasional teknologi yang berfokus pada e-niaga, komputasi, streaming digital dan kecerdasan buatan. Amazon terlibat dalam penjualan eceran produk konsumen dan langganan di Amerika Utara serta internasional. Dataset ini terdiri dari rata-rata harga High,Low,Open,Close,Volume, dan Adj Close yang disesuaikan dan volume saham Amazon selama 6 tahun lebih mulai dari tahun 2016 hingga 2021. Namun tujuan utama kami ingin memprediksi harga penutupan saham Amazon dalam 1 minggu

credit-scoring icon credit-scoring

Tujuan utama Credit-Scoring Modeling ini adalah untuk melakukan prediksi terhadap suatu individu akan kemampuan mereka untuk melakukan pembayaran terhadap pinjaman/kredit yang diberikan

employee-absenteeism-hr-department icon employee-absenteeism-hr-department

Perusahaan The Look memiliki Karyawan sebanyak 8000++. Namun selama setahun terakhir tingkat produktivitas menurun. Untuk itu, HR ingin mengurangi rata-rata absensi staff perusahaan selama setahun maksimal 16 jam saja supaya dapat meningkatkan kontribusi , produktivitas, kedisiplinan staff perusahaan , serta meminimalisirkan kerugian pada perusahaan

home-credit-default-risk icon home-credit-default-risk

Many people struggle to get loans due to insufficient or non-existent credit histories. And, unfortunately, this population is often taken advantage of by untrustworthy lenders. Home Credit strives to broaden financial inclusion for the unbanked population by providing a positive and safe borrowing experience. In order to make sure this underserved population has a positive loan experience, Home Credit makes use of a variety of alternative data--including telco and transactional information--to predict their clients' repayment abilities.

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