How to calculate haversine distance between 4 columns correctly

Question

I try to calculate haversine distance between 4 columns

cgi                     longitude_bts       latitude_bts    longitude_poi   latitude_poi
0   510-11-32111-7131       95.335142           5.565253        95.337588       5.563713
1   510-11-32111-7135       95.335142           5.565253        95.337588       5.563713

Here's my code

def haversine(lon1, lat1, lon2, lat2):
    """
    Calculate the great circle distance between two points 
    on the earth (specified in decimal degrees)
    """
    # convert decimal degrees to radians
    import numpy as np
    import math
    lon1, lat1, lon2, lat2 = map(np.radians, [lon1, lat1, lon2, lat2])
    # haversine formula 
    dlon = lon2 - lon1 
    dlat = lat2 - lat1 
    a = math.sin(dlat/2)**2 + math.cos(lat1) * math.cos(lat2) * math.sin(dlon/2)**2
    c = 2 * math.asin(math.sqrt(a)) 
    # Radius of earth in kilometers is 6371
    km = 6371008.799485213* c
    return km

ref_location_airport_hospital['radius'] = ref_location_airport_hospital.apply(lambda x: haversine(x['latitude_bts'], x['longitude_bts'], x['latitude_poi'], x['longitude_poi']), axis=1)

Here's the result

    cgi                 longitude_bts      latitude_bts longitude_poi   latitude_poi    radius
0   510-11-32111-7131   95.335142              5.565253     95.337588       5.563713    272.441676
1   510-11-32111-7135   95.335142              5.565253     95.337588       5.563713    272.441676

The result is not rational, the two points distasance is less than 0.004, so the radius should less than 1 km

Note: 1 longitude/latitide is arroun 111 km