Indonesia is a country that is along the equator. If an area approaches the equator, it will have a tropical climate, or in other words, it only has two seasons, namely the dry season and the rainy season. The difference between tropical and non-tropical countries is the time of solar irradiation. Non-tropical countries usually have 4 seasons (spring, summer, fall, and winter) where the highest solar irradiation time is during summer, which usually lasts 3 months (December to March). While in tropical countries have the highest solar irradiation time during the dry season which can last 6-7 months (March to September) with a peak period of around 4 months.

The application of GIS is very encompassing. Various industries can use GIS in different ways; to help them answer a spatial inquiry, to expand the reach of their business, and even to communicate and engage with the public. While most of the pioneer industries and foremost users of GIS are those that are into research, the digital age is slowly bringing in GIS to power up business operations. And in recent years, we’ve been seeing how government agencies are also starting to use GIS to improve public service and develop innovative ways to promote public engagement.

We are living in the age of technological advancement essentially driven by data. Whether making a decision, looking into a cause or an effect, or forecasting a scenario-data gathering, management, and interpretation is the mainstay. This has driven companies and individuals to collect and manage humongous quantities of data to perform various tasks. As this data is stored in the form of databases generated through space and time, which might go up to gigabytes in extent. This enormity renders meaningful derivation and presentation of data a daunting task.

There are a lot of ways to gather information and business data nowadays. Unlike before, technological advancement in this modern age allows companies to generate and collect almost everything they need for business modeling, strategic research, forecasting, and many others. While this has been the case, oftentimes this kind of data generation involves a lot of cost and investment, which may not be desirable for some.