This project develops an automated IDX Smart Money Detection System using Python and RapidAPI. The system is designed to analyze Indonesian stock market activity by combining three important market indicators:

1. Market Mover Analysis

2. Bandar Accumulation Detection

3. Bandar Distribution Detection

The objective of this project is to build a simple framework for identifying potential institutional activity, monitoring top-performing stocks, and detecting possible accumulation or distribution behavior from market participants.

The project uses Python libraries such as requests for API communication, pandas for data processing, json for handling API responses, and tabulate for generating structured reports.

The complete workflow is organized into five cells, starting from API configuration, retrieving market mover data, analyzing bandar activity, creating stock analysis functions, and generating an automated market report.

The five main components are:

• Cell 1: Library installation and API configuration

• Cell 2: Market mover (top gainer) retrieval

• Cell 3: Bandar accumulation and distribution analysis

• Cell 4: Automated bandar scanner

• Cell 5: Smart money report generation

Cell 1 - Install Library and API Configuration

# =====================================
# CELL 1 : SETUP
# =====================================

!pip install requests pandas tabulate -q

import requests
import pandas as pd
import json
from tabulate import tabulate


API_HOST = "indonesia-stock-exchange-idx.p.rapidapi.com"


HEADERS = {
    "Content-Type": "application/json",
    "x-rapidapi-host": API_HOST,
    "x-rapidapi-key": "YOUR_API_KEY"
}

Explanation

Cell 1 prepares the Python environment and configures the connection to the Indonesia Stock Exchange API.

The required libraries are installed and imported:

• requests is used for sending API requests.

• pandas is used for data processing.

• json is used for processing API responses.

• tabulate is used for generating structured table output.
  

The API configuration defines the RapidAPI host and authentication headers required to access IDX market data.

The API key should be stored securely and should not be publicly shared.

Cell 2 - Get Market Mover (Top Gainer)

# =====================================
# CELL 2 : MARKET MOVER
# =====================================


def getMarketMover():

    url = (
        "https://indonesia-stock-exchange-idx.p.rapidapi.com/"
        "api/movers/top-gainer?"
        "filterStocks=FILTER_STOCKS_TYPE_MAIN_BOARD,"
        "FILTER_STOCKS_TYPE_DEVELOPMENT_BOARD"
    )


    response = requests.get(
        url,
        headers=HEADERS
    )


    print(
        "Status:",
        response.status_code
    )


    data = response.json()


    return data



# Execute

market_mover = getMarketMover()

market_mover

Explanation

Cell 2 retrieves market mover data from the IDX API.

The function:

getMarketMover()

accesses the top gainer endpoint:

/api/movers/top-gainer

The analysis includes stocks from:

• Main Board

• Development Board
  

as defined in the API filter parameters.

The API response is stored in:

market_mover

which contains information about stocks experiencing significant price increases.

Market mover analysis is useful as an initial screening tool to identify stocks with strong short-term momentum.

Cell 3 - Bandar Distribution and Accumulation Analysis

# =====================================
# CELL 3 : BANDAR ANALYSIS
# =====================================


def getBandarDistribution(symbol="BUMI", days=30):

    url = (
        f"https://indonesia-stock-exchange-idx.p.rapidapi.com/"
        f"api/analysis/bandar/distribution/{symbol}?days={days}"
    )


    response = requests.get(
        url,
        headers=HEADERS
    )


    print(
        "Distribution Status:",
        response.status_code
    )


    return response.json()



def getBandarAccumulation(symbol="BUMI", days=30):

    url = (
        f"https://indonesia-stock-exchange-idx.p.rapidapi.com/"
        f"api/analysis/bandar/accumulation/{symbol}?days={days}"
    )


    response = requests.get(
        url,
        headers=HEADERS
    )


    print(
        "Accumulation Status:",
        response.status_code
    )


    return response.json()



# Test BUMI

symbol = "BUMI"


distribution = getBandarDistribution(symbol)

accumulation = getBandarAccumulation(symbol)


print("DISTRIBUTION")

display(distribution)


print("ACCUMULATION")

display(accumulation)

Explanation

Cell 3 analyzes bandar activity through two separate indicators:

1. Bandar Distribution
   

2. Bandar Accumulation
   

The function:

getBandarDistribution()

retrieves information about potential selling activity from large market participants.

The function:

getBandarAccumulation()

retrieves information about potential buying activity or accumulation behavior.

Both functions analyze the selected stock using a specific observation period:

days = 30

and default stock:

symbol = "BUMI"

The API endpoints used are:

/api/analysis/bandar/distribution/{symbol}

and

/api/analysis/bandar/accumulation/{symbol}

These indicators are useful for identifying possible smart money behavior.

Cell 4 - Simple Bandar Scanner

# =====================================
# CELL 4 : BANDAR SCANNER
# =====================================


def analyzeStock(symbol):

    acc = getBandarAccumulation(symbol)

    dist = getBandarDistribution(symbol)


    result = {

        "Symbol": symbol,

        "Accumulation": acc,

        "Distribution": dist

    }


    return result



# Example

stock_analysis = analyzeStock("BUMI")


stock_analysis

Explanation

Cell 4 creates an automated stock analysis function.

The function:

analyzeStock()

combines two separate analyses:

• Accumulation data

• Distribution data
  

into one dictionary output:

result

This approach simplifies the process because users only need to enter one stock symbol to retrieve both bandar indicators.

For example:

analyzeStock("BUMI")

will automatically retrieve accumulation and distribution information for BUMI.

Cell 5 - Smart Money Report Generator

# =====================================
# CELL 5 : REPORT TABLE
# =====================================


def extract_value(data):

    if isinstance(data, dict):

        if "data" in data:

            return data["data"]

        else:

            return data


    return data



def bandar_signal(acc, dist):

    acc_text = json.dumps(acc).lower()

    dist_text = json.dumps(dist).lower()



    if "exceeded" in acc_text or "429" in acc_text:

        acc_status = (
            "Data akumulasi tidak tersedia"
        )

    else:

        acc_status = (
            "Bandar terlihat melakukan akumulasi"
        )



    if "exceeded" in dist_text or "429" in dist_text:

        dist_status = (
            "Data distribusi tidak tersedia"
        )

    else:

        dist_status = (
            "Bandar terlihat melakukan distribusi"
        )



    if (
        "akumulasi" in acc_status.lower()
        and "tidak tersedia" not in acc_status
    ):

        conclusion = (
            "POTENSI SMART MONEY MASUK"
        )


    elif "distribusi" in dist_status.lower():

        conclusion = (
            "WASPADA DISTRIBUSI"
        )


    else:

        conclusion = (
            "WAIT / BELUM ADA SINYAL"
        )



    return (
        acc_status,
        dist_status,
        conclusion
    )



def create_easy_report(symbol):


    acc = getBandarAccumulation(symbol)

    dist = getBandarDistribution(symbol)



    acc_status, dist_status, conclusion = bandar_signal(
        acc,
        dist
    )



    report = {

        "symbol": symbol,

        "acc_status": acc_status,

        "dist_status": dist_status,

        "kesimpulan": conclusion

    }


    return report



# RUN

report = create_easy_report("BUMI")

report

Explanation

Cell 5 generates a simplified smart money report.

The function:

bandar_signal()

evaluates accumulation and distribution responses from the API.

The system checks:

• Availability of accumulation data.

• Availability of distribution data.

• Potential accumulation signals.

• Potential distribution signals.
  

Based on these conditions, the program generates three possible conclusions:

1. Potential Smart Money Entry

2. Warning Distribution

3. Wait / No Clear Signal
   

The final report is generated through:

create_easy_report()

which combines all information into a simple output containing:

• Stock symbol

• Accumulation status

• Distribution status

• Final conclusion

Conclusion

This project demonstrates how Python and RapidAPI can be used to build an automated IDX Smart Money Detection System.

The system integrates three important market analysis approaches:

1. Market Mover Analysis
   To identify stocks with strong price momentum.
   

2. Bandar Accumulation Analysis
   To detect potential buying activity from large market participants.
   

3. Bandar Distribution Analysis
   To identify possible selling pressure from major holders.
   

The generated report provides a simple framework for monitoring market behavior and identifying potential smart money signals.

However, accumulation and distribution indicators should not be used as standalone trading decisions. Additional confirmation using price action, trading volume, company fundamentals, valuation, and overall market conditions is still required before making investment decisions.