Analisis Potensi Rebound Saham (HTML view): Kode Python & colab.research.google.com

✅ Cara 1: Pakai Google Colab (Paling Mudah, Tanpa Instalasi)

1. Buka https://colab.research.google.com

2. Login dengan akun Google (Gmail) jika diminta

3. Klik Google Drive

4. Klik tombol “+ New Notebook” (di bawah kiri)

5. Salin kode Python (yang saya berikan) ke dalam sel kosong: Start coding or generate with AI

6. Klik tombol ▶️ “Run all” di atas kode disalin

7. Hasil akan muncul 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 (kode python tidak di escape hanya tambah pre code di awal dan di akhir):

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"]])