Analisis Potensi Rebound Saham (compose view): Kode Python & colab.research.google.com
✅ Cara 1: Pakai Google Colab (Paling Mudah, Tanpa Instalasi)
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Klik tombol “+ New Notebook” (di bawah kiri)
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Salin kode (Python yang saya berikan ke dalam) sel kosong: Start coding or generate with AI
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Klik tombol ▶️ “Run all” di atas "kode disalin"
Hasil ada di bawah "kode disalin"
✅ Gratis, berbasis web, hanya perlu login Gmail.
Berikut adalah kode Python yang dapat kamu jalankan sendiri untuk mengetahui saham dengan potensi rebound tertinggi berdasarkan penurunan harga, frekuensi transaksi, dan volume:
import pandas as pd
from io import StringIO
data = """
Code,Last,Change,Prev,Open,High,Low,Freq,Vol,Val(K),Cap(M)
COCO,155,-14.84,182,165,188,155,3296,293019,4900472,137929
JATI,152,-5.59,161,161,165,152,3620,372057,5921223,495903
AMIN,149,-6.88,160,156,156,146,109,5737,85201,160920
APEX,130,-7.80,141,141,148,128,7803,1273949,17631745,461041
VERN,120,-4.76,126,125,126,120,249,17725,216145,571866
MPXL,114,-4.20,119,119,119,112,1662,103610,1194210,228002
IOTF,104,-6.31,111,111,115,104,12003,1615417,17456141,550191
DOOH,88,-4.35,92,92,92,88,2286,375527,3374133,681022
BSML,82,-5.75,87,87,91,82,1254,459853,4058603,151718
BUVA,77,-6.10,82,80,84,75,4331,984578,7825403,1585466
LEAD,73,-7.59,79,81,82,72,2535,479250,3600330,423372
FUTR,69,-4.17,72,72,72,68,578,166949,1159850,457853
CBRE,62,-8.82,68,74,74,62,487,179095,1194703,281360
BRRC,58,-4.92,61,61,61,57,662,162788,952367,56347
LMAX,38,-7.32,41,41,41,38,237,47480,185431,24700
CNKO,32,-5.88,34,34,34,32,127,32468,108920,286604
MARI,26,-7.14,28,26,26,26,111,21683,56376,136569
RELF,19,-5.00,20,20,20,18,98,12950,24107,108829
ANDI,16,-5.88,17,17,17,16,68,16114,26023,149600
PURA,14,-6.67,15,14,14,14,59,16550,23170,88227
TAMU,14,-6.67,15,15,15,14,287,232117,329880,525000
SAGE,13,-7.14,14,14,14,13,71,9657,12647,104436
PTBADRCN5A,13,-7.14,14,13,14,12,179,14379,18695,1040
ZINC,12,-7.69,13,13,13,12,85,40201,48417,303000
ISAP,10,-9.09,11,11,12,10,261,397278,409436,40201
KREN,9,-10.00,10,10,10,9,85,18688,17236,163876
MBMAHDCQ5A,7,-12.50,8,8,9,7,87,105313,89719,3500
BAIK-W,7,-22.22,9,8,8,7,325,30142,21453,1575
TAXI,6,-14.29,7,7,7,6,93,25209,16684,61342
ISAP-W,2,-33.33,3,3,4,2,230,17957,5366,1500
"""
df = pd.read_csv(StringIO(data))
# Hitung potensi rebound
df["ReboundPotential"] = (-df["Change"]) * (df["Freq"] + df["Vol"]/1000)
# Urutkan dari potensi tertinggi
top_potentials = df.sort_values(by="ReboundPotential", ascending=False).head(10)
# Tampilkan
print(top_potentials[["Code", "Last", "Change", "Freq", "Vol", "Cap(M)", "ReboundPotential"]])
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