Dataset on the sustainable smart city development in Indonesia

Smart city movements are growing all over the world. The undertaking is expected to solve a plethora of problems arising from urbanization. Indonesia is one of the countries who march toward the development of sustainable smart cities. However, before the government can start a smart city project, they need to assess the readiness of each target city. Data in this article illustrate the readiness of six major cities in Indonesia, which are Semarang, Makassar, Jakarta, Samarinda, Medan, and Surabaya. They represent the four biggest islands in Indonesia. The readiness assessment was based on three main elements and six Smart City Pillars taken from Smart City Master Plan Preparation Guidance Book prepared by Ministry of Communication and Information Technology of the Republic of Indonesia. Those elements serve as a checklist to determine the readiness of the cities. Data for qualitative analysis were gathered through interviews and triangulated through secondary sources, such as publication from Statistics Indonesia and the assessment reports. The dataset contains information on the readiness assessment is presented in this article. The indices of the six region's readiness assessment are presented in percentages.


a b s t r a c t
Smart city movements are growing all over the world. The undertaking is expected to solve a plethora of problems arising from urbanization. Indonesia is one of the countries who march toward the development of sustainable smart cities. However, before the government can start a smart city project, they need to assess the readiness of each target city. Data in this article illustrate the readiness of six major cities in Indonesia, which are Semarang, Makassar, Jakarta, Samarinda, Medan, and Surabaya. They represent the four biggest islands in Indonesia. The readiness assessment was based on three main elements and six Smart City Pillars taken from Smart City Master Plan Preparation Guidance Book prepared by Ministry of Communication and Information Technology of the Republic of Indonesia. Those elements serve as a checklist to determine the readiness of the cities. Data for qualitative analysis were gathered through interviews and triangulated through secondary sources, such as publication from Statistics Indonesia and the assessment reports. The dataset contains information on the readiness assessment is presented in this article. The indices of the six region's readiness assessment are presented in percentages.

Data
Seventy-five cities have been actively engaged in the development of smart city in Indonesia. The group comprises of twenty-four cities that have been selected in the first phase and fifty cities in the second phase. They were a part of the Indonesia 100 Smart Cities Movement initiated by Ministry of Communication and Information Technology of the Republic of Indonesia in 2017 and 2018, and Jakarta as the capital city of Indonesia. The urban features of seventy-five smart cities are presented in Table 1, which provides data on area, population, densities, Human Development Index (HDI), Gross Regional Domestic Product (GRDP), and the ethnic groups. Fig. 1 shows Indonesian map and the location of seventy-five smart cities development.
The readiness assessment datasets on six major smart cities are presented in this article. Data measurements were conducted based on three main elements and six smart city pillars. Table 2 shows the example of category assignment on the readiness assessment. The dataset of assessment based on three main elements is presented in Table 3 and assessment based on the six smart city pillars is presented Table 4. The summary of the dataset readiness can be seen in Table 5 and Table 6. Final assessment dataset of smart city index is shown in Table 7. Table 8 shows the correlation between city   Specifications table   Subject area  Management  More specific subject area  Innovation Management  Type of data  Tables and figures  How data was acquired  Data were acquired from In-depth interviews with several Indonesian governmental  ministries and observations  Value of the data Our dataset provides the features of seventy-five smart cities development in Indonesia and readiness assessment of six major smart cities based on three main elements and six smart city pillars. The dataset within this article can be used by the scientific community as comparison materials with other data obtained from other cities, regions, or countries. The dataset will enable the stakeholders to have more understanding about the progress of smart city development in Indonesia and it helps identifying improvement gaps. Academics and practitioners from all disciplines can employ the detailed indicators as an assessment checklist for other cities.
The data availability will help policymakers in governments to design responsive policies in terms of sustainable smart city development. Data in this article can also be used by researchers to study the relationships between urban features of smart city (densities, HDI, and GRDP) and readiness level.
densities and HDI, while Table 9 demonstrates the correlation between city densities and GRDP. The corresponding scatterplots can be seen in Figs. 2 and 3.

Regional readiness measures
The essence of the Smart City concept is the city and all its components can manage existing resources to support and maintain the continuity of the ecosystems. Two steps were used to assess regional readiness. First step, the regions were assessed on three main elements based on the Smart City Master Plan Preparation Guidance Book [1]. The elements used are:

Samples
The dataset in this article relates to the concept of Indonesia Smart Cities Platform Ecosystems which discussed the effort of the Indonesian government to implement the Smart City concept in all national development aspects [2]. This paper has a mission to present a dataset of the readiness assessment of smart cities chosen by the Ministry of Communication and Information Technology of The Republic of Indonesia for the 100 Smart City program. The Ministry, up until this article is written, has held two selection phases since 2017. They have chosen seventy-four cities (see Table 1). The selection process was expected to be fully accomplished in late 2019 or early 2020. The Ministry's panelists which consisted of academics, private sectors, and members of local/central governments were required to adhere to the Smart City Master Plan Preparation Guidance Book. This dataset has six major cities (i.e. samples) that represent Indonesia's main islands, which are Medan, Jakarta, Semarang, Surabaya, Samarinda, and Makassar. The Ministry did not include Jakarta in Table 1 (continued) their 100 Smart City Program because the city is a Special Region which does not belong to West Java, Central Java, or East Java province. However, Jakarta was selected as sample because this city, along with Bandung and Surabaya, is a pioneer in the development of smart cities in Indonesia and its effort towards sustainable smart cities has not ceased.
The six major cities were also chosen because of the availability of regional logistical support facilities and infrastructure, such as airports, seaports, container terminals, warehousing, and access to the main road. The availability of seaport became one of the most important considerations because seaport has roles that cannot be replaced by other modes, such as airports, highways, and trains [2]. Seaport has essential functions because Indonesia is an archipelago. The unavailability of a seaport was the reason why this study excluded several cities like Bandung and Bogor.

Data gathering and analysis
The qualitative data were gathered through a series of interviews. To ensure the validity of the data, the interviewers questioned members of the central governments and academics. Each interview was transcribed. Content analysis was done to interpret and code textual material (i.e., raw texts from interviews transcriptions). The data in the form of interview quotes were then categorized based on the pre-determined theme and theoretical constructs (i.e., the three main elements and the six smart city pillars). The data were further corroborated using secondary data, such as publications from Statistics   Table 2 Example of category assignment.

Components
Regional Readiness to Implement Smart City Concepts Semarang

Regional Structure Analysis
Quality of the Human Capital [HC] e Available/yes ¼ 1, Unavailable/no ¼ 0 The availability of community that focuses on developing interests in talent, creativity, and culture 1 The availability of community that focuses on developing interests in talent, creativity, and culture The existence of software developers' community 1 The existence of digital technology startup or another rising business startup Availability higher education The availability of student Scholarship program from the government The availability of highly educated volunteers 1 Staffs with medium to high computer literacy Staffs with medium to high foreign language literacy 1 1 1 1 1 1 5 Broadband access in every public office The availability of LAN/WAN in every public office The availability of Wireless Internet Hotspot in every public office The availability of Independent Data Center services/ management The availability of SOP regarding disaster mitigation of governmental data 0 0 0 0 0 0 10 Interoperability of Information Systems regarding regional planning and development Good percentage of local revenue value towards total regional revenue Good percentage of staffing budget spending towards total regional spending The availability of Smart City Development Program budget allocation per year Local/foreign investment to support regional development The availability of alternative financing resources to support Smart City Development Program  In accordance to Yin's recommendation [3], the qualitative data in this research were quantified to obtain sample's regional readiness. After procuring data from interviews and secondary sources, points were assigned to those answers. For example (see Table 2), one of the readiness indicators is "the availability of community that focuses on developing interests in talent, creativity, and culture." The interviewees both indicated that such community existed in Semarang, and the secondary data verified it. Thus, Semarang is given "1" point under this specific indicator.
After gathering data for all sample cities, the readiness of each city was calculated by using an equation (see Eq.1) based on works of Atmojo et al. [4] and Chang and Huang [5].

Regional Readiness
Eq. (1) generated the benchmarked regional readiness dataset of six cities in percentages. In this dataset, the regional readiness is the ratio between a city's total score on three main elements and six Smart City Pillars and the maximum point a city can reach (i.e., 144).