## 1 Introduction
### Literature Review  
Coal-fired power generation is the largest source of electricity globally and the biggest emitter of all energy-related CO\({}_{2}\) emissions [4]. It prompted countries to adopt the goal of providing affordable, reliable, and clean energy for all [18]. Decarbonizing the power sector aims to achieve a zero-carbon world by increasing the deployment of RE systems to address energy demand [19]. RE is now considered a practical solution for greener energy and sustainable development, prompting most countries to transition from conventional fossil fuels to RE [20; 21; 22; 23]. The archipelagic nature of the Philippines makes RE implementation more convenient, where small islands can obtain increased electricity access and cleaner electricity generation with RE implementation. However, the intermittence of RE supply, particularly solar energy resources, is thought to be unable to meet the demand consistently. It necessitates careful planning and resource identification in small island communities to ensure that RE supply is capable of meeting energy demand. In recent years, the geographic information system (GIS) has grown in popularity as a tool for various site selection studies, particularly renewable energy planning [24]. There are several advantages when GIS is integrated with energy planning. One advantage is using spatial data to analyze demand in a particular location while creating forecasts that consider the location's unique characteristics and related energy access targets [25; 26; 27]. Likewise, GIS can assess renewable resource availability and energy potentials [28; 29; 30], finding the best suitable location for future energy infrastructure projects [31; 32], and mapping out the existing transmission lines, distribution networks, etc. [33; 34]. Using GIS in energy planning may help to avoid the sensitive areas that can cause adverse environmental and social impacts [35; 36]. GIS plays a significant role in energy planning, from exploring renewable resources and combining them with the existing system to identifying a suitable site for the system installation. Most researchers have proposed integration methods combining GIS with other techniques to improve the potential assessment accuracy and increase site selection precision [37; 38; 39]. When combined with multicriteria decision-making (MCDM) methods, these can be among the most effective methods for locating potential renewable energy project sites [12]. They handle the process of making decisions where multiple objectives are considered [40]. The application of MCDM methods used several techniques in many kinds of research [41; 42; 43]. Ref. [44] reviewed the previous literature from 2009 to 2018, and among them, the analytic hierarchy process (AHP) ranked first as the most employed MCDM method. It has been used frequently to solve complex decision problems by using pairwise comparisons of criteria to reduce bias in decision-making [45; 46]. AHP can also be combined with other MCDM methods such as the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) [47; 48; 49]. The results provided by AHP can be further enhanced by using TOPSIS [50]. It is widely used and can effectively rank feasible sites from best to worst [51]. It proposes an optimal alternative from a series of alternatives with the shortest geometric distance from the positive ideal solution [50]. This hybrid MCDM method enables a more reliable geospatial analysis for electrification planning and site selection. Table S1 [52; 53; 54; 55; 56; 57; 58; 59] summarizes research from 2017 to 2021 using GIS with different REs and applications used in electrification planning, while Figure 2 shows the percentage of each technology being studied. The top three RETs that gained so much attention among researchers worldwide are solar PV (36%), wind power (30%), and biomass (12%).