DOI: https://doi.org/10.18196/jgp.113124 http://journal.umy.ac.id/index.php/jsp JURNAL STUDI PEMERINTAHAN How to Design Qualitative Research with NVivo 12 Plus for Local Government Corruption Issue in Indonesia? SALAHUDIN1 ACHMAD NURMANDI2 MOHAMMAD JAFAR LOILATU3 ABSTRACT This paper utilizes NVivo 12 Plus, a type of qualitative data analysis software, for qualitative document content analysis as a means of understanding informal fiscal policymaking practices, including bribery, corruption, collusion, lobbying, negotiation, and transactional politics. Use of NVivo 12 Plus for qualitative document content analysis facilitated the management, analysis, and visualiza- tion of data on informal fiscal policymaking. More specifically, qualitative con- tent analysis of decisions of the Supreme Court of Indonesia revealed that informal fiscal policymaking in Malang City, Malang Regency, and Batu City, Indonesia, involved the practices of bribery, corruption, collusion, lobbying, negotiation, and transactional politics between regional leaders, bureaucrats, private actors, and political brokers. This paper contributes a qualitative re- search designthatcan be usedto explaininformal practices infiscalpolicymaking and budget management. Keywords: Qualitative Data Analysis Software, Informal Policymaking, Fiscal Politics, Content Analysis INTRODUCTION Understanding informal policymaking practices poses unique challenges to Indonesianists around the world (Bardhan & Mookherjee, 2012; Dorotinsky & Pradhan, 2007). The greatest challenge to researchers investigat- ing informal policymaking practices is difficulty obtain- ing data on these practices (Dutta, 2009). Informal policymaking practices refer to the political processes through which collusive, corruptive, and transactional fiscal policies are produced (Dorotinsky & Pradhan, 2007). Most commonly, such informal fiscal policymaking 369 AFFILIATION: 1Department of Government Studies, Universitas Muhammadiyah Malang 2&3Department of Government Affairs and Administration Universitas Muhammadiyah Yogyakarta CORRESPONDENCE: udin.pemerintahan@gmail.com CITATION: Salahudin, Nurmandi, A., & Loilatu, M. J. (2020). How to Design Qualitative Research with Nvivo 12 for LocalGovernment Corruption Issue in Indonesia? Jurnal Studi Pemerintahan, 11(3), 369–398 ARTICLE HISTORY: Received: August, 31st 2020 Accepted: November, 04th 2020 https://doi.org/10.18196/jgp.113124 http://journal.umy.ac.id/index.php/jsp https://orcid.org/0000-0001-5687-0812 https://orcid.org/0000-0002-6730-0273 https://orcid.org/0000-0001-6921-6879 mailto:udin.pemerintahan@gmail.com 370 processes are perpetrated by politicians and bureaucrats who wield authority and political power (Montambeault & Goirand, 2016). These actors communicate, interact, and make political agree- ments in order to promote the formulation of fiscal policies that promote their own interests (Rubin, 2019). Also involved in informal fiscal policymaking are private sec- tor actors with political influence (Farhan, 2018), which they gain by establishing strong politico-economic relationships with politicians and bureaucrats in order to advance their own inter- ests. From a rent-seeking perspective, these private-sector actors are capable of exerting dominance over politicians and bureau- crats (Adi, 2018), thereby influencing policymaking and ensur- ing their interests are accommodated (Asher & Novosad, 2019). Also involved in informal fiscal policymaking are political bro- kers and criminals, who become involved in the process by bridg- ing political, government, and private-sector actors. Informal fiscal policymaking occurs behind closed doors, open to and involving only actors with sufficient politico-economic power, authority, and influence (Lambsdorff, 2018). In such a situation, it is difficult—if not impossible—to guarantee budget transparency. Data on informal fiscal policymaking cannot eas- ily be obtained, and as such researchers have been unable to provide a detailed and comprehensive understanding of the practice (Flick, 2009). Earlier studies have investigated infor- mal fiscal policymaking processes through interviews with in- formants who are not directly involved in these practices, in- cluding activists, social figures, politicians, and journalists as their informants (Montambeault & Goirand, 2016). These interviews are generally complemented by observation of formal fiscal policymaking processes, i.e. those that occur in accordance with established mechanisms and procedures. Several studies have taken policy documents as data in their investigation of infor- mal fiscal policymaking (Rumbul, Parsons, & Bramley, 2018). Such studies are significantly limited by their data, which are incapable of providing a detailed understanding of thepolitical processes involved informal fiscal policymaking, including the roles, communications, and collusive, corruptive, and transac- tional interactions between politicians, bureaucrats, and private- sector actors. As such, this paper seeks to produce a qualitative research design that is capable of understanding informal fiscal policymaking. This paper offers a research design that emphasizes the use of qualitative document content analysis through NVivo 12 Plus, a qualitative data analysis software. Qualitative document con- tent analysis facilitates the study of informal fiscal policymaking, as it does not require data to be collected in the field (i.e. through interviews, observations, and focus group discussions). Rather, it reveals informal fiscal policymaking practices by exploring the practices of corruption and bribery revealed within decisions of the Supreme Court of Indonesia. In the current era of open information, all court documents regarding cases of corruption are published through official government websites. Research- ers thus accessed court documents regarding cases of budget cor- ruption, then analyzed said documents using NVivo 12 Plus. This analysis produced quality data, the validity of which could be proven scientifically (Woods, Paulus, Atkins, & Macklin, 2016). Through NVivo 12 Plus, the researchers were able to produce data regarding informal fiscal policymaking processes, includ- ing the practices of corruption and bribery involved. LITERATURE REVIEW INFORMAL FISCAL POLICYMAKING Fiscal policymaking refers to the political process through which fiscal policy is produced, and involves political actors such as elected officials, legislators, party elites, and civil society (Yandra, Nasution, Harsini, & Wekke, 2018). These actors be- come involved in in the policymaking process to ensure that the policy produced accommodates their specific interests (Rubin, 2010). As part of the political process, fiscal policymaking in- volves the distribution of money between actors with an inter- 371 372 est in fiscal policy (Montambeault & Goirand, 2016). As such, the question of how funds are distributed to all involved actors is fundamental in studies of fiscal policymaking (Rubin, 2019). Studies must consider how government, political, and informal actors prepare fiscal policy through political negotiations and transactions, as well as how they exchange resources in order to advance their own interests (Rumbul et al., 2018). Studies of fiscal policymaking must also consider the involve- ment of formal and informal institutions in various parts of the process (Montambeault & Goirand, 2016; Alatas et al., 2013). Formal institutions are those actors whose involvement in the policymaking process is provided by existing systems, mechanisms, and laws, while informal institutions are those actors whose in- volvement is not legally mandated (Trantidis & Tsagkroni, 2017; Farrell & Héritier, 2003). Such informal institutions are more prone to practices of clientelism, patronage, rent-seeking, and corruption (Farhan, 2018; Slater & Simmons, 2013). In general, the interactions between executive and legislative actors in fiscal policymaking are used as arenas for transactional politics, resulting in practices of bribery and corruption (Grillos, 2017). Executive and legislative institutions have their own spe- cific interests, with the former generally seeking to use public funds for infrastructure development and the latter often pri- oritizing social empowerment activities. In many cases, legisla- tive institutions are only willing to accommodate the interests of executive institutions when they are offered bribes (Basri & Nabiha, 2014). Where legislative institutions are willing to ac- commodate executive proposals and allocate funds for them, fiscal policymaking processes initially follow the legally mandated mechanisms and processes. Ultimately, however, they often re- sort to informal political transactions and compromises, thereby providing fertile ground for bribery and corruption (Montambeault & Goirand, 2016). For governments and politicians, fiscal policy is a political tool, as controlling fiscal policy enables them to maintain their power. They use their power and authority to create fiscal poli- cies that advance the political interests of themselves and their supporters (Lucas, 2016; Wong, 2010). They fund political pro- grams and activities, or distribute money directly to constitu- ents, who are expected to provide their political support in re- turn (Bardhan & Mookherjee, 2012; Rumbul et al., 2018). In this context, Hallerberg (2019) writes ―for individual politicians … the budget is a resource deployed to enhance political sup- port. A politician can attempt to influence budget allocation in order to gain political support from particular groups. Thus, from this perspective also, budget-making is necessarily a political pro- cess.‖ Politicians, from executive leaders to legislators, thereby attempt to prepare fiscal policies that enable them to maintain their political power. The above discussion of fiscal policymaking shows that the process involves informal actors and institutions, and is replete with cartelism, clientelism, and elite capture. A range of politi- cal actors, including civic groups, political parties, private sector, non-government organizations, and governments, are jointly involved in the political process, with their communications and negotiations being used to determine and formulate fiscal policy that represents their own political interests. This process is domi- nated by actors who have the power and influence to advance their specific interests (Rumbul et al., 2018). 373 QUALITATIVE STUDIES OF INFORMAL FISCAL POLICYMAKING Scholars have employed a wide range of research approaches to understand informal fiscal policymaking, both in developing and developed nations. One commonly used approach is the qualitative approach, through which researchers examine the subject based on qualitative data collected through interviews, observations, government reports, non-governmental analyses, and participatory action research (Montambeault & Goirand, 2016; Rumbul et al., 2018). Numerous studies have employed a 374 qualitative approach to show that informal fiscal policymaking is common in Africa, Brazil, and China, where government of- ficials, politicians, and private-sector actors often establish pa- ternalistic relationships (Bardhan & Mookherjee, 2012; Dorotinsky & Pradhan, 2007). Although these studies have shown that informal actors are frequently involved in fiscal policymaking, their findings have been derived primarily from observations of and interviews with local residents, whether or not they are involved in informal fiscal policymaking (Montambeault & Goirand, 2016; Rebecca Rumbul et al., 2018). As such, there may be bias in their depic- tions of the paternalistic relationship between politicians, gov- ernment officials, citizens, and private-sector actors (Flick, 2009). Another shortcoming of these studies lies in their data analysis, which generally employs conventional techniques to read and understand informal fiscal policymaking practices in regions or countries that have received previous academic interest. Previous studies have yet to implement an innovative research design, such as software-based qualitative document content analysis, to understand informal fiscal policymaking. As such, their analytical results and findings have been unable to com- prehensively illustrate the informal practices such as cor- ruption, bribery, and transactional politics involved in infor- mal fiscal policymaking (Woods et al., 2016). NVivo 12 offers significant benefits for analyzing qualitative data, including docu- ment content, by producing data of sufficient quality to explain the practices of bribery, corruption, collusion, lobbying, nego- tiation, and transactional politics (involving politicians, bureau- crats, private sector actors, and political brokers). RESEARCH LOCATION SETTING Research was conducted in Batu City, Malang City, and Malang Regency. These three autonomous municipalities are located in East Java, Indonesia (Figure 1). FIGURE 1. MAP OF BATU CITY, MALANG CITY, AND MALANG REGENCY Together, these three municipalities are known as Greater Malang, with Malang City (previously the administrative center of Malang Regency) gaining autonomy in 1999 and Batu City having been produced through the administrative division of Malang Regency in 2001. Executive officials from all three mu- nicipalities have been found guilty of corruption, having em- bezzled money from the municipal budget. Such cases of corrup- tion have also involved other actors. In Batu City, for example, embezzlement involved bureaucrats and private-sector actors; in Malang City, it involved bureaucrats, legislators, and private- sector actors; and in Malang Regency it involved bureaucrats, political communities, and private-sector actors. This study investigates the involvement of executive officials, bureaucrats, legislators, and private-sector actors in practices of corruption and bribery during fiscal policymaking processes in Batu City, Malang City, and Malang Regency. As such, it seeks to answer the following research question: How are the informal fiscal policymaking processes in Batu City, Malang City, and Malang Regency, Indonesia? 375 376 QUALITATIVE DATA ANALYSIS SOFTWARE IN DOCU- MENT ANALYSIS This study employs a qualitative approach to examine budget corruption in Greater Malang, with a focus on the embezzle- ment of funds from the local budgets of Malang City, Malang Regency, and Batu City. For its data, it draws from the decisions of the Supreme Court of Indonesia regarding the criminal prac- tice of budget corruption in Greater Malang. Qualitative con- tent analysis of these documents provides an understanding of budget corruption in Greater Malang. In qualitative research, documents are defined as artifacts that are produced and access by human beings (Flick, 2009). The documents discussed in this paper are the decisions of the Supreme Court of Indonesia regarding the criminal practice of budget corruption in Greater Malang, were produced by the Supreme Court of Indonesia in accordance with applicable In- donesian legal processes and procedures. Since the passage of the Law on Public Information Openness (Law No. 14 of 2008), all of the Supreme Court’s decisions have been published online through the Directory of Supreme Court Decisions (https:// putusan3.mahkamahagung.go.id/). The documents discussed in this study were accessed from this directory. The selected documents fulfilled the criteria of authenticity, credibility, representativeness, and meaningfulness (Flick, 2009). The authenticity criterion is fulfilled by these documents’ hav- ing been produced by the Supreme Court of Indonesia through a process of investigation and advocacy. These documents also fulfill the credibility criterion, having been produced in accor- dance with applicable procedures and processes. They were iden- tified as representative, and thereby able to provide the data necessary to answer the research question. Finally, the decisions used for this analysis were meaningful, as they are capable of describing the practice of budget corruption in Greater Malang. This study employs qualitative document content analysis, analyzing Supreme Court decisions throughscientific processes and procedures. Document analysis requires the capability and skill to interpret and translate data as a means of answering the research question (Flick, 2009). To facilitate the collection, man- agement, and qualitative analysis of data, thereby improving the credibility of the data and subsequent findings, qualitative data analysis software has been developed (Wallmeier, Helmig, & Feeney, 2019). In this case, such software has been employed to analyze the Supreme Court decisions and produce an under- standing of corruption in Greater Malang. Analysis was conducted using NVivo 12 Plus, a qualitative data analysis software that facilitates the collection, categoriza- tion, mapping, analysis, and visualization of qualitative data, including that collected from documents (memos, reports, legis- lations, and photographic documents) and through interviews (Bazely & Richards, 2013). NVivo 12 Plus was used to analyze the decisions of the Supreme Court of Indonesia regarding the criminal practice of budget corruption in Greater Malang through data management, actor network mapping, data classi- fication, and research demographic management. Research involved several stages, as follows: research topic determination, research design, research approach determina- tion, data analysis design, interpretative data analysis, and re- search result discussion. This process is presented in Figure 2 below. FIGURE 2. RESEARCH PROCESS As shown by Figure 2, the first stage of the research pro- cess involved the determination of the research topic by prepar- ing a review of the literature. Second, the research design was decided, with qualitative content analysis of Supreme Court 377 378 decisions ultimately being chosen. Third, the research approach— a content analysis approach involving frame/concept/theme/ node coding—was chosen. Fourth, a software-based data analysis technique was chosen. Finally, the collected data were interpre- tatively analyzed and the findings were discussed. QUALITATIVE DOCUMENT CONTENT ANALYSIS This study employs qualitative content analysis, a research method that emphasizes the textual analysis of documents such as government regulations and public opinion pieces as well as the results of observations, interviews, and focus group discus- sions. Qualitative content analysis is intended to systematically describe, translate, and interpret data (Krippendorff, 2004). As such, it requires the ability to translate, interpret, and give mean- ing to textual data, and this ability informs data quality. This study employs a qualitative approach to analyze decisions of the Supreme Court of Indonesia regarding the criminal practice of budget corruption in Batu City, Malang City, and Malang Re- gency. One principle of qualitative content analysis is that the sum- mary of a document can be used to understand it as a compre- hensive textual unit. In this context, the original text of the document is defined and understood through a particular frame/ concept, with said frame/concept showing the meaning and sig- nificance of the original text (Flick, 2009). A frame/concept may be formulated based on a review of prior studies (deductive frame) or based on data collected in the field (inductive frame) (Neuendorf, 2020). Content analysis involves several stages, namely research ques- tion determination, data selection, frame/concept formulation, interpretation and classification of data within the frame/con- cept, data analysis, data elucidation, and finding interpretation (Flick, 2009). This is clarified further in Table 1 below. TABLE 1. STAGES OF DOCUMENT ANALYSIS 379 CONTENT ANALYSIS PROCESS Research question determination CONTENT ANALYSIS OF SUPREME COURT DECISIONS How are the informal fiscal policymaking processes in Batu City, Malang City, and Malang Regency, Indonesia? Data Selection Decisions of the Supreme Court of Indonesia regarding the Criminal Practice of Budget Corruption in Greater Malang Frame/Concept/Theme/Node Formulation Data Interpretation and Classification Data Evaluation and Modification Frame/Concept/Theme/Node formulated based on a review of the literature and the Supreme Court decisions. Node formatting was done using NVivo 12 Plus. The Supreme Court decisions were coded into specific nodes/themes. Data coding was done using NVivo 12 Plus. Coded data were evaluated and modified using NVivo 12 Plus. Data Analysis Coded data were analyzed using Nvivo 12 Plus. Presentation and Interpretation of Findings Results of data analysis were analyzed and discussed DOCUMENT COLLECTION TECHNIQUE Research data in the form of Supreme Court decision docu- ments regarding criminal acts of budget corruption in Malang City, Malang Regency, and Batu City are accessed in the Su- preme Court decision directory https://putusan3. mahka- 027mahagung.go.id/. The Supreme Court Decision Directory provides a search page for decision documents of all courts in Indonesia and provides files of all types of decisions including decisions on corruption in Malang City, Malang Regency and Batu City (table 2). DATA ANALYSIS USING NVIVO 12 PLUS This study employs the spiral data analysis technique devel- oped by Creswell (2014), which consists of five stages: (1) data organization, (2) document reading and preparation, (3) descrip- tion, classification, and interpretation of data as code/theme, No. Name Case Number Office Practice Territory 37/Pid.sus- N Sby. Regent of Malang Regency, Budget of Malang Regency 2021 Ali N Sby. Actor Bribing government of Malang officials to gain Regency access to government projects Moch Anton 94/Pid.Sus/T Mayor of Malang, 2013– Sby. 2018 Bribing legislators to shape budget policy Government of Malang City Jarot Edy Head of the Office of N.Sby and Bribing legislators to of Malang shape budget City policy Monitoring Eddy Mayor ofBatu, Budget 2007–2012 of Batu City .Sby. 2017 Edi Head of Service and Receiving bribes to determine access to of Batu City Sby. Office, Batu City projects 252 Djap Giving bribes to gain access to government projects of Batu City Actor SBY. 380 TABLE 2. DECISIONS OF THE SUPREME COURT OF INDONESIA Source: Supreme Court of Indonesia, 2019. (4) data interpretation, and (5) data presentation and visualiza- tion. Spiral analysis thereby requires a researcher to continu- ously analyze and organize qualitative data. This approach will produce a report or conclusion regarding budget corruption and political networks in Greater Malang. NVivo 12 Plus was used for the five stages of spiral analysis, as shown in Table 3 below: TABLE 3. STAGES OF QUALITATIVE DATA ANALYSIS 381 Stage of Analysis Data Analysis Technique NVivo 12 Plus Feature Data Management • Data Importing • Data Folder Creation IMPORT, DATA Data • Data Classification File Classification Classification • Data Attribute Entry Case Classification Data Coding • Research Node/Theme Code and Case Creation • Case (Actor, Organization, and Location) Creation • Nodal/Thematic Categorization of Text Data Analysis • Nodal/Thematic Analysis per Case (Organization) • Nodal/Thematic Analysis per Case Attribute (Type of Institution and Type of Organization). Explore Chart DATA MANAGEMENT USING NVIVO 12 PLUS The import feature of NVivo 12 Plus was used to input the collected Supreme Court decisions into an NVivo 12 Plus DATA file. The process involved three stages: 1. Three folders were created through the DATA menu. These folders were named in accordance with the research loca- tion: Malang Regency, Malang City, and Batu City. 2. The research data (Supreme Court decisions) were imported into the three folders using NVivo 12 Plus’ IMPORT fea- ture, as made available through the DATA menu. 3. The imported research data (Supreme Court decisions) were classified as Government Documents using the FILE CLAS- SIFICATION menu. 382 TABLE 4. FOLDERS, FILES, AND CLASSES OF RESEARCH DATA DATA CLASSIFICATION USING NVIVO 12 PLUS The Supreme Court documents were classified based on the organizations involved in budget corruption in Batu City, Malang City, and Malang Regency. Data classification involved the fol- lowing stages. 1. Case folders were created, being named in accordance with the research location. Each case was classified through Case Folder Organization (Table 5). TABLE 5. CASE FOLDER OR GANIZA TION FOR ANALYZIN G BUD GE T CORR UPTION IN GREA TER MALAN G CASEFOLDERNAME CASE FOLDER CLASSIFICATION Malang Regency Organization Batu City Organization Malang City Organization 2. Folders for Case Organizations was created. Then, name of the Cases in the Organizational Cases folders was in accor- dance with the name of the organization in the Supreme Court decision (table 6). 3. Fill in the Case / demographic attributes of the study. All the cases were given their respective identities titled Institution Type and Organization Type (table 6) FOLDER NAME DATA FILE NAME FILE CLASSIFICATION Malang Regency Ali Murtopo Government Document Rendra Kresna Government Document Batu City Eddy Rumpoko Government Document Edi Setiawan Government Document Filipus Djap Government Document Malang City Moch Anton Government Document Jarot Edy Sulistiyono Government Document Source: Exported from NVivo 12 Plus TABEL 6. CASE ORGANIZATIONS IN THE POLITICAL CORRUP TION NETWORKS OF GREATER MALA NG 383 CLASS OF CASE ORGAN NAME OF CASE ORGANIZATION TYPE OF INSTITUTION IZATION TYPEOFORGANIZATION Gerindra Faction Commission C, Local Parliament Commission Chairman Golkar Faction PKB Faction PAN Faction PDIP Faction Faction Leader Mayor PUPPB Regional Secretary Speaker, Local Parliament PT Sentratama Global Solusindo PT Agrajaya CV Amarta Wisena PT Dailbana Prima Indonesia 384 I Source: Exported from Nvivo 12 Plus CODING TECHNIQUE AND DATA ANALYSIS WITH NVIVO 12 PLUS One of the most important elements of qualitative content analysis is the coding of the document text. For this study, docu- ment coding involved the categorization of Supreme Court de- cisions based on the concepts presented through the literature review (deducative coding) and based on the findings of coding process (inductivecoding). Coding involved the following stages: (1) Node creation, with the name of each node reflecting the research concepts identified in the literature review and find- NAME OF CASE ORGANIZATION CLASS OF CASE ORGAN TYPE OF INSTITUTION ZATION TYPEOFORGANIZATION Office of Expenditure, Revenue, and Asset Management Official Government Government Agriculture Office Official Government Government Malang Regency Government (Treasurer) Official Government Government Contractors' Association Private Sector Private Sector Office of Public Works Official Government Government CV Tunjang Langit Private Sector Private Sector CV Adhijaya Sakti Private Sector Private Sector CV Sawunggaling Private Sector Private Sector CV Karya Mandiri Private Sector Private Sector CV Kartika Fajar Utama Private Sector Private Sector CV Adhikersa Private Sector Private Sector Auction Committee Official Government Government Information Technology Team Official Government Government Bureau of Electronic Data Management, Electronic Procurement Service Official Government Government Office of Education Official Government Government Rendra–Subhan Campaign Team Political Groups Political Groups Regent Elected Official Elected Official ings of the coding process; and (2) Reading, understanding, and inputting the text of the Supreme Court decisions in accordance with the nodes used. TA BL E 7. NO DE F O R M AT/ RE S EA RC H T H E M ES NODE NAME NOTE 385 • Corruption • Bribery • Collutive Relations • Transactional Relations • Political Lobbying • Political Negotiation Six nodes used to answer questions regarding informal fiscal policymaking processes in Malang City, Malang Regency, and Batu City, Indonesia. Data were analyzed using Nvivo 12 Plus through its Explore Chart feature, which offered values for each node (theme) based on the Case (Organization) and Attribute (type of institution dan type of organization). The values obtained through the Ex- plore Chart feature were used to understand the informal fiscal policymaking processes of Malang City, Malang Regency, and Batu City, Indonesia. RESULTS OF DATA ANALYSIS WITH NVIVO 12 PLUS Informal Fiscal Policymaking Practices in Malang City, Malang Regency, and Batu City Analysis of the Supreme Court decisions regarding the crimi- nal practice of budget corruption in Batu City, Malang City, and Malang Regency shows that a range of informal political activities were involved in fiscal policymaking. These included corruption, lobbying, and collusive relationships between actors with power, access, and authority in local government agencies. Figure 3 shows that Malang City had the highest value of informal fiscal policymaking (81.51%), followed by Batu City (11.78%) and Malang Regency (5.89%). Collusive relationships between actors were highest in Malang City (38.27%), followed by Batu City (31.54%) and Malang Regency (30.17%). Corrup- tion was most prevalent in Malang City (57.53%), followed by Malang Regency (20.58%) and Batu City (20.07%). Lobbying was most common in Malang City (96.48%), followed by Batu 386 City (1.88%) and Malang Regency (1.61%). Political negotiations were highest in Malang City (74.80%), followed by Malang Re- gency (15.05%) and Batu City (8.77%). Finally, transactional political practices were most prevalent in Malang City (56.61%), Malang Regency (22.10%), and Batu City (21.27%). FIGU RE 3. INFOR MAL FISCAL POLICY MAKING PRA CTICES IN MALAN G CITY, MA LA NG RE GEN CY, AND BATU CITY FIGURE 4. ACTORS INVOLVED IN INFORMAL FISCAL POLICYMAKING IN MALANG CITY ACTORS INVOLVED IN INFORMAL FISCAL POLICYMAKING IN MALANG CITY The actors involved in informal fiscal policymaking included the government, political organizations, and the private sector. These actors were actively involved in the informal fiscal policymaking processes through acts of bribery, collusion, cor- ruption, political lobbying, political negotiations, and transac- tional politics. From Figure 4, it is evident that political organizations were the most dominant actor in informal fiscal policymaking in Malang City, followed by government organizations and private- sector actors. Bribery amongst political organizations had a value of 134.17%, while values of 43.47% and 0.91%. were recorded amongst government organizations and private-sector actors, respectively. Collusive relationships were most prevalent amongst political organizations (63.29%), followed by govern- ment organizations (54.96%) and private-sector actors (5.67%). Budget corruption is dominated by political organizations (99.55%), followed by government organizations (53.12%) and private-sector actors (1.65%). This was also true for political lob- bying, where political organizations had a value of 168.86%, government organizations had a value of 114.41%, and private- sector actors had a value of 5.00%. Political organizations played an active role in political negotiations at every stage of the in- formal fiscal policymaking process, returning a value of 108.54%; this was followed by government organizations (85.25%) and private-sector actors (3.91%). Finally, transactional politics was intensively used by political (92.12%) and government organiza- tions (72.70%), but less intensively by private-sector actors (6.06%). The involvement of these organizational actors in informal fiscal policymaking processes in Malang City was represented by the involvement of individual actors, including the members and leaders of these organizations. In Malang City, political or- ganizations were represented by members of parliament. Gov- ernment organizations were represented by the mayor and by bureaucrats, while private-sector actors were represented bycor- porations that worked in conjunction with the government. 387 388 Figure 5 shows that members of parliament, representing political organizations, were more heavily involved in informal fiscal policymaking in Malang City than bureaucrats (govern- ment officials), political officials/the mayor (elected officials), and private-sector actors. Amongst the members of parliament in Malang City, the practice of bribery had a value of 131.11%, followed by bureaucrats (43.47%), the mayor (3.00%), and pri- vate-sector actors (0.91%). Meanwhile, bureaucrats were more actively involved in establishing collusive relationships, followed by members of parliament (53.72%), the mayor (9.57%), and private-sector actors (5.67%). In regards to budget corruption, a value of 90.65% was found for members of parliament, followed by 53.12% for bureaucrats, 8.90% for the mayor, and 1.65% for private-sector actors. The political lobbying value for members of parliament was 135.52%, with lower values found for bu- reaucrats (114.01%), the mayor (33.33%), and private-sector ac- tors (5.00%). Political negotiations were dominated by members of parliament (92.26%), followed by bureaucrats (85.25%), the mayor (16.26%), and private-sector actors (3.91%). Finally, trans- actional politics was most common amongst members of parlia- FIGURE 5. TYPES OF ACTORS INVOLVED IN INFORMAL FISCAL POLICYMAKING IN MALANG CITY ment (74.36%) and bureaucrats (72.70%), followed by the mayor (17.76%) and private-sector actors (6.06%). Actors in Informal Fiscal Policymaking in Malang Regency In Malang Regency, informal fiscal policymaking involved government organizations, private-sector actors, and political brokers/political communities. These organizations utilized col- lusive relationships, corrupt practices, political negotiations, and transactional interactions in their policymaking activities. FIGURE 6. ACTORS INVOLVED IN INFORMAL FISCAL POLICYMAKING IN MALANG REGENCY Figure 6 shows that, government organizations had a value of 102.06% in establishing collusive relationships, followed by private-sector actors (45.39%) and political communities (9.27%). Government organizations also dominated the practice of cor- ruption (62.89%), followed by private-sector actors (24.03%) and political communities (6.13%). Meanwhile, while government organizations also dominated active political negotiations (51.82%), political communities were more active than private- sector actors (10.80% versus 1.44%). Transactional relationships were widespread in informal fiscal policymaking in Malang Re- gency, with government organizations taking a dominant role (65.22%) followed by private-sector actors (39.36%) and politi- cal communities (6.34%). 389 390 In this case, government organizations were represented by the Regent (an elected official) and bureaucrats (government officials); private-sector actors were represented by entrepreneurs; and political communities were represented by campaign teams and political brokers. Bureaucrats were dominant in all stages of the informal fiscal policymaking process, being supported by private-sector actors, campaign teams, political brokers, and the regent. FIGURE 7. TYPES OF ACTORS INVOLVED IN INFORMAL FISCAL POLICYMAKING IN MALANG REGENCY Government officials, including office heads and project staff, established collusive communications and relationships with other actors. These bureaucrats were most active (with a value of 59.59%), followed by private-sector actors (45.39%), the re- gent (13.98%), and political communities (2.27%). Practices of budget corruption in Malang Regency predominantly involved government officials (34.52%) and private-sector actors (24.03%), followed by the regent (10.30%) and political communities (6.13%). In their political negotiations, government officials re- ceived a value of 29.99%; in this, they were supportedby politi- cal communities (10.80%), the regent (8.22%), and private-sec- tor actors (1.44%). Transactional politics most commonly in- volved private-sector actors (39.36%) and government officials (36.87%), but at times political communities (6.34%) and the regent (6.25%) were involved (Figure 7). Actors in Informal Fiscal Policymaking in Batu City Unlike in Malang City and Malang Regency, where infor- mal fiscal policymaking involved government organizations, political organizations, and private-sector actors, in Batu City the process only involved government organizations and private- sector actors (Figure 8). These organizations were actively involved in all types of informal fiscal policymaking, including bribery, collusive relationships, corruption, political lobbying, and trans- actional politics. FIGURE 8. ACTORS INVOLVED IN INFORMAL FISCAL POLICYMAKING IN BATU CITY In Batu City, bribery was predominantly practiced by the pri- vate sector (11.78%), followed by government organizations (5.72%). Meanwhile, the establishment of collusive relationships most commonly involved government organizations (43.79%), followed by private-sector actors (33.22%). Corruption values were higher amongst government organizations (27.35%) than amongst private-sector actors (16.96%). Both used political lob- bying in their informal fiscal policymaking processes, receiving a value of 1.88%. In political negotiations, government organi- zations (11.55%) were more active than private-sector actors (8.76%); this reinforces the view that the government provided lobbying spaces for private-sector actors. Finally, in their trans- actional practices, government actors in Batu City dominated 391 392 private-sector actors (27.32% versus 2.26%) (Figure 8). Government organizations involved in informal policymaking practices included the mayor (an elected official) and bureau- crats (government officials); meanwhile, the private-sector ac- tors involved in corruption, collusion, negotiation, transactional politics, and bribery in Batu City were local entrepreneurs. These organizations were mutually complementary in informal fiscal policymaking activities in Batu City. FIGURE 9. TYPES OF ACTORS INVOLVED IN INFORMAL FISCAL POLICYMAKING IN BATU CITY Figure 9 above shows that private-sector actors dominated the informal fiscal policymaking activities in Batu City, followed by bureaucrats and the mayor. Bureaucrats and entrepreneurs had almost equal opportunities to commit bribery, the latter actors were slightly more active (11.78% versus 11.70%); mean- while, the mayor was less involved (5.72%). Entrepreneurs were also the most active (33.22%) in establishing collusive relation- ships during informal fiscal policymaking activities, followed by bureaucrats (28.40%) and the mayor. Meanwhile, bureaucrats contributed most significantly to budget corruption (20.13%), followed by private-sector actors (16.96%) and the mayor (11.52%). Bureaucrats and entrepreneurs were equally involved in political lobbying (1.88%); the mayor, conversely, was not di- rectly involved in lobbying. Nonetheless, the mayor was involved in the process of political negotiations (4.48%), which is an in- trinsic part of the lobbying process. Bureaucrats and private-sec- tor actors were almost equally involved in such negotiations, with the former slightly more active (8.77% versus 8.76%). Pri- vate-sector actors (21.26%) were heavily involved in creating transactional politics with government officials (17.39%) and the mayor (16.75%), with such transactions being used to advance their interests in the informal fiscal policymaking process. DISCUSSION OF RESULTS A qualitative document content analysis of Supreme Court decisions regarding the practice of corruption in Malang City, Malang Regency, and Batu City using Nvivo 12 Plus has shown that the informal policymaking processes in these municipali- ties have involved bribery, corruption, collusion, lobbying, po- litical negotiations, and transactional politics (Basri & Nabiha, 2014). In Malang City, the informal fiscal policymaking process involved all of these practices intensively. Meanwhile, while these practices were less intensive in Batu City and Malang Regency, they occurred in both municipalities’ informal fiscal policymaking processes (Rebecca Rumbul et al., 2018). The intensiveness of informal fiscal policymaking practices in Malang City can be attributed to the number and diversity of the actors involved, including political organizations, government organizations, the mayor, and private-sector actors. Most domi- nant in the informal fiscal policymaking process in Malang City were political organizations, followed by government organiza- tions and private-sector actors; this is evidenced by these politi- cal organizations’ involvement in practices of bribery, corrup- tion, lobbying, negotiation, and transactional politics (Montambeault & Goirand, 2016). Members of parliament were more commonly involved in informal fiscal policymaking activi- ties than government officials, elected officials, and private-sec- 393 394 tor actors (Dorotinsky & Pradhan, 2007); as such, they positioned themselves as having greater influence in the informal fiscal policymaking process. Under their influence, the mayor, bureau- crats, and entrepreneurs became involved in the informal fiscal policymaking process (Yandra et al., 2018). In Malang Regency, meanwhile, the informal fiscal policymaking process involved government organizations, pri- vate-sector actors, and political communities (Montambeault & Goirand, 2016). In this case, the regent—an elected official—regu- lated and controlled the informal fiscal policymaking process (Adi, 2018). He instructed government officials, including the leaders of local government offices, to commit informal policymaking practices such as negotiation, lobbying, political transactions, and providing private-sector actors access to gov- ernment projects (Adi, 2018; Montambeault & Goirand, 2016). Furthermore, the regent instructed local bureaucrats to work with the political communities that supported him and to in- clude them in fiscal policymaking (Trantidis & Tsagkroni, 2017). Private-sector actors (i.e. entrepreneurs) worked in conjunc- tion with the Malang Regency government to formulate fiscal policy, doing so by establishing collusive relationships with the regent, bureaucrats, and political communities (Arias, 2018; Wong, 2010). In order to facilitate access to government-funded development projects (Berenschot, 2018), during the informal fiscal policymaking process entrepreneurs practiced bribery, lob- bying, corruption, and political negotiation with the regent, bureaucrats, and project brokers. This was positively received by the regent and by local bureaucrats, and supported by political communities. Ultimately, corruption, bribery, and transactional politics were widely practiced during the budgeting process (Arias, 2018; Kostiuchenko, 2014). In Malang Regency, the dominant political community was the regent’s campaign team, a group of elites that acted collec- tively as a project and fiscal broker (Jones, 2013). This political community was established during the regional election, when it campaigned for the regent, accumulated political power, and raised funds from entrepreneurs with their own specific inter- ests in the election and in the regional budget (Auriol & Flochel, 2015). After the conclusion of the election, this political com- munity served as a project and fiscal broker, working to connect the regent with entrepreneurs and to control bureaucrats’ for- mal fiscal policymaking activities (Arias, 2018). In Malang Regency’s informal fiscal policymaking activities, government organizations were more dominant than private- sector actors and political communities. Meanwhile, private-sec- tor actors were more active than political communities, as illus- trated by their willingness to work in conjunction with govern- ment officials. Political communities, finally, served as project and fiscal brokers in Malang Regency (Bardhan & Mookherjee, 2012). Finally, two types of actors were involved in the informal fiscal policymaking process in Batu Regency, namely government organizations and private-sector actors (Montambeault & Goirand, 2016). Private-sector actors dominated this process, with the support of bureaucrats and the mayor. At the same time, the mayor provided spaces for informal fiscal policymaking ac- tivities, while bureaucrats enabled entrepreneurs’ practice of bribery, collusion, corruption, lobbying, negotiation, and trans- actional politics (Farhan, 2018; Montambeault & Goirand, 2016; Rubin, 2019). As such, although the Mayor of Batu did not domi- nate the informal fiscal policymaking process in the city, he was a major source of the bribery, corruption, collusion, lobbying, negotiation, and transactional politics that occurred during the informal fiscal policymaking process (Rumbul et al., 2018). 395 CONCLUSION Qualitative content analysis was conducted using NVivo 12 Plus, which was involved in document collection, data manage- ment, data classification, node creation, and thematic/topical coding of Supreme Court decisions regarding practices of cor- 396 ruption in Malang City, Malang Regency, and Batu City. It found that informal policymaking activities involved the practices of bribery, corruption, collusion, lobbying, negotiation, and trans- actional politics. Such activities were more prominent in Malang City than in Batu City and Malang Regency. In Malang City, the informal fiscal policymaking process was dominated by po- litical organizations, as represented by members of parliament. Meanwhile, in Malang Regency, the process was dominated by government organizations, as seen by the active involvement of the regent and local bureaucrats. Finally, in Batu City, the in- formal fiscal policymaking process was dominated by private- sector actors, though the practice itself was rooted in the mayor’s promotion of informal approaches to fiscal policymaking amongst the municipality’s bureaucrats. In analyzing informal fiscal policymaking processes, the main strength of NVivo 12 Plus is its ability to ensure that data are well organized. In this case, Supreme Court decisions were orga- nized well; informal fiscal policymaking activities were clearly identified; informal fiscal policymaking practices such as brib- ery, corruption, collusion, lobbying, negotiation, and transac- tional politics were mapped systematically; analytical results were clearly visualized; and research findings were organized well, enabling the researchers to understand the informal fiscal policymaking processes in Malang City, Malang Regency, and Batu City. Nonetheless, the use of NVivo 12 Plus for content analysis is limited in its ability to triangulate data, as the results of its analysis of Supreme Court documents could not be con- firmed with other primary data (i.e. interviews and observa- tions). 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