Hallo Guys,
Jumpa lagi dengan saya… 🙂
Pada artikel kali ini saya mau berbagi pengalaman dari proyek pribadi saya. Walaupun proyek ini masih dalam tahap pengembangan, mungkin ada diantara kalian yang mau berpartisipasi untuk mengembangkannya lebih serius hingga proyek ini bisa bermanfaat buat banyak orang.
Seperti kita semua sudah merasakan dan mengalaminya, di era informasi digital saat ini, data menjadi inti dari keputusan investasi, baik di pasar saham dan forex. Menganalisis sentimen pasar merupakan salah satu cara yang sangat berguna untuk memahami pergerakan harga saham atau mata uang. Dalam proyek ini, kita akan menjelajahi langkah-langkah untuk melakukan News Sentiment Analysis pada data pasar keuangan menggunakan Python.
Apa Itu “News Sentiment Analysis” ?
News Sentiment Analysis atau Analisis Sentimen Berita adalah teknik pemrosesan bahasa alami yang digunakan untuk mengekstrak dan menilai sentimen atau pendapat dari teks berita atau news. Dalam konteks pasar keuangan, ini berarti menganalisis opini, berita, atau tweet untuk memahami emosi atau sentimen investor terhadap suatu aset.
Apa saja langkah-langkah utama dalam Proyek Ini ?
Tentu saja diperlukan beberapa langkah atau tahapan dalam mengerjakan proyek ini. Berikut adalah gambaran umum dari tahapan pengerjaan proyek ini:
- Pengumpulan Data: Mengumpulkan data dari sumber-sumber seperti Twitter, situs berita keuangan, atau platform khusus yang menyediakan data sentiment terkait pasar. Tapi dalam proyek ini, kami menggunakan teknik pengumpulan data menggunakan ‘web scraping‘. Website yang menjadi target adalah https://www.forexfactory.com/calendar.
- Preprocessing Data: Membersihkan dan mempersiapkan data untuk analisis, termasuk langkah-langkah seperti menghapus kolom yang tidak digunakan, menghilangkan karakter (stop words, symbols), mengkonversi data, dan normalisasi teks.
- Analisis Sentimen: Menggunakan algoritma atau model machine learning untuk mengevaluasi sentimen berita, seperti Logistic Regression, Random Forest, atau teknik Pipeline.
- Visualisasi Hasil: Menampilkan hasil analisis dalam bentuk grafik atau visualisasi yang dapat dimengerti untuk mendapatkan wawasan yang lebih dalam.
- Membangun Machine Learning: Memprediksi sentimen berita secara manual dapat memakan waktu dan rentan terhadap bias subjektif. Dengan Machine Learning, kita dapat memanfaatkan algoritma untuk secara otomatis menganalisis teks berita, mengekstrak pola, dan memprediksi sentimen dengan tingkat akurasi yang cukup tinggi.
Langkah-langkah tersebut akan saya jelaskan lebih detil nanti.
Apa saja alat (tools) dan bahasa pemrograman yang digunakan ?
Dalam proyek ini, kita akan menggunakan Python sebagai bahasa pemrograman utama, dan beberapa library seperti:
- NLTK (Natural Language Toolkit), untuk melakukan preprocessing pada teks.
- Scikit-learn, Untuk pembangunan model Sentiment Analysis.
- Pandas dan Matplotlib/Seaborn, untuk manipulasi data dan visualisasi.
Saya akan jelaskan step-by-step menggunakan Python untuk proyek ini.
OK, penasaran…seperti apa proyek ini ? Yuk, lanjut ke Part #2.
Tapi sebelum itu, biar makin semangat, kita nonton bule’ orang Prancis nyanyi lagu Indonesia, “Separuh Nafas – DEWA 19”.
Colmar, 18 Dec 2023, Winter
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