Open Access Indonesia Journal of Social Sciences

Digital Visibility, Algorithmic Misclassification, and Welfare Exclusion Among Informal Workers: A Mixed-Methods Study in Indonesia

Harun Urrashid, Fitriyanti Fitriyanti — Mon, 22 Jun 2026 00:00:00 +0000

Background: Algorithmic governance is reshaping social protection, yet the distributive consequences of automated welfare targeting in the Global South remain poorly understood. The study was grounded in street-level bureaucracy and procedural-justice theory.

Objective: To examine whether digital transaction visibility and employment informality predict false-negative welfare exclusion, whether perceived algorithmic misclassification mediates these effects, and whether algorithmic procedural justice moderates them.

Methods: An explanatory-sequential mixed-methods design combined an audit of 2,500 automated eligibility decisions with a cross-sectional survey of 640 household heads served by a public organization in Palembang, South Sumatera, Indonesia (response rate 84.2%), and phenomenological interviews with false-negative cases.

Results: All scales were reliable (Cronbach's alpha 0.79-0.88). The audit found 72.3% aggregate accuracy and a 23.4% false-negative rate, rising to 55.1% among undocumented households. Employment informality (beta=0.28), misclassification (beta=0.31), and digital transaction visibility (beta=0.19) positively predicted exclusion, while procedural justice was protective (beta=-0.22); the model explained 52% of variance (F(9,630)=75.84, p<0.001). Misclassification partially mediated the informality-exclusion link (indirect effect=0.17, 95% CI [0.12, 0.23]), procedural justice buffered it (interaction beta=-0.14, p=0.002), and non-digital informal workers had 4.27 times higher exclusion odds (95% CI [2.98, 6.12]). Interviews showed that gross e-wallet throughput was misread as income and frontline discretion collapsed into a computer-says-no bureaucracy.

Conclusion: Algorithmic unfairness in Indonesia reflects parameterization bias against informal livelihoods. Welfare systems should restore conditional human-in-the-loop discretion and accessible appeal mechanisms.

Synthetic Reality and the Erosion of Epistemic Trust: Deepfake Misinformation, Confirmation Bias, and Democratic Cynicism Among Indonesian Voters

Yuniarti Maretha Pasaribu, Aaliyah El-Hussaini — Mon, 22 Jun 2026 00:00:00 +0000

Background: Synthetic media generated by artificial intelligence (deepfakes) threatens democratic consolidation, yet most evidence is Western and video-centred and rarely models how such media shapes citizens' political attitudes.

Objective: Grounded in epistemic-trust theory, motivated-reasoning theory, and the Liar's Dividend thesis, this study examined how the illusion of authenticity, confirmation-bias acceleration, and perception of the Liar's Dividend relate to democratic cynicism among Indonesian voters, and whether confirmation bias mediates and synthetic-media literacy moderates these relationships.

Methods: A nested mixed-methods design combined computational extraction of 4,200 synthetic-media items (detector F1 = 0.92), a cross-sectional survey of 3,000 adults recruited by proportional random sampling across three urban centres in Indonesia, and digital ethnography with 50 key informants.

Results: The novel Epistemic Trust Erosion Scale demonstrated strong reliability (total alpha = 0.893; subscales 0.77 to 0.85) and sampling adequacy (KMO = 0.93). Cloned-audio deepfakes were trusted by 76.2% of respondents but consciously detected by only 11.5%, inverting the global assumption of video primacy. Illusion of authenticity (beta = 0.256), confirmation bias (beta = 0.269), and Liar's Dividend perception (beta = 0.212) each predicted democratic cynicism (all p < 0.001), explaining 33.0% of its variance (F(3, 2996) = 492.57, p < 0.001, f-squared = 0.493). Confirmation bias partially mediated the authenticity-cynicism pathway (indirect effect = 0.153, 95% CI [0.135, 0.172]). Synthetic-media literacy lowered cynicism but did not buffer the pathway.

Conclusion: The findings extend deepfake scholarship to oral, messaging-centred Global-South publics and inform electoral-integrity policy.

The Algorithmic Sanctuary: Social-Interaction Burnout, Loneliness, and Emotional Attachment to AI Companions Among Young Adults in Indonesia

Ni Made Nova Indriani, Immanuel Simbolon, Sophia Lucille Rodriguez — Mon, 22 Jun 2026 00:00:00 +0000

Background: Post-pandemic digital life has produced a new affective phenomenon: large-language-model “AI companions” that invite two-way parasocial relationships. Counter-intuitively, the most intense users in urban Indonesia appear to be not the physically isolated but socially active young adults experiencing interaction burnout, who treat AI as a refuge from the judgment costs of a collectivist culture. Yet no integrated model has tested why relational strain translates into machine attachment in a Global-South setting.

Objective: To examine whether social-interaction burnout and subjective loneliness predict emotional attachment to AI companions, whether AI parasocial interaction mediates the burnout-attachment path, and whether collectivist judgment apprehension moderates the loneliness-attachment link.

Methods: Drawing on Parasocial Interaction Theory, the Computers-Are-Social-Actors paradigm, and emotional-labor theory, this cross-sectional survey of 1,200 young adults recruited through a public organization in Palembang, South Sumatera, Indonesia, measured social-interaction burnout, subjective loneliness, collectivist judgment apprehension, AI parasocial interaction, and emotional attachment to AI using validated Likert scales analysed with reliability, correlation, multiple regression, bootstrap mediation, and moderation.

Results: All scales were reliable (α = 0.84–0.91; KMO = 0.96). The model explained 48% of variance in attachment (adjusted R² = 0.486, F = 284, p < 0.001). Parasocial interaction (β = 0.318), loneliness (β = 0.254), and burnout (β = 0.238) were the strongest predictors (all p < 0.001). Parasocial interaction partially mediated the burnout–attachment path (indirect = 0.160, 95% CI [0.132, 0.191]), and judgment apprehension moderated the loneliness–attachment link (β = 0.127, p < 0.001).

Conclusion: Findings introduce the “Algorithmic Sanctuary” account of AI companionship and inform digital-wellbeing policy in collectivist societies.

Institutional Publication Pressure and Perceived Epistemic Injustice: Mediating Roles of Cost Privatization and Research Cannibalization in Indonesia

Ahmad Erza, Dais Susilo, Gladys Putri — Tue, 23 Jun 2026 00:00:00 +0000

Background: The transition of scholarly publishing from a subscription model to an article-processing-charge (APC) model has reorganized the political economy of knowledge production, yet researcher-level perceptions of its fairness remain under-measured in the Global South.

Objective: Drawing on academic-capitalism and epistemic-injustice theory, this study examined whether institutional publication pressure predicts perceived epistemic injustice, and whether publication-cost privatization and research cannibalization mediate that relationship, among academics at a public organization in Palembang, South Sumatera, Indonesia.

Methods: A cross-sectional survey was administered to 312 academics using validated multi-item Likert scales. Reliability, a correlation matrix, multiple regression, parallel mediation with 5,000-sample bootstrap intervals, moderation, Harman’s single-factor test, and variance inflation factors were computed.

Results: All constructs were reliable (Cronbach’s α = 0.78–0.83). Institutional publication pressure (β = 0.219, 95% CI [0.116, 0.321], p < 0.001), publication-cost privatization (β = 0.298, 95% CI [0.201, 0.396], p < 0.001), and research cannibalization (β = 0.293, 95% CI [0.196, 0.390], p < 0.001) each independently predicted perceived epistemic injustice, explaining 34.6% of its variance (F = 54.38, p < 0.001). Both mediators carried significant indirect effects (via privatization 0.111, 95% CI [0.068, 0.163]; via cannibalization 0.105, 95% CI [0.064, 0.151]), indicating partial parallel mediation. Perceived grant availability moderated the pressure-to-privatization path (interaction β = −0.145, p = 0.006). Common method bias was not serious (Harman’s single factor = 33.3%).

Conclusion: Findings formalize the “illusion of inclusivity” as a measurable perception and suggest that publication mandates unaccompanied by adequate funding generate perceived epistemic injustice in Indonesian public institutions.

From Eco-Anxiety to Climate Activism: The Moderating Role of Collective Efficacy Among Generation Z in Indonesia

Jasmila Tanjung, Sarah Armalia, Zahra Amir — Tue, 23 Jun 2026 00:00:00 +0000

Background: Escalating environmental hazards across Indonesia have transformed the climate crisis into a collective mental-health and sociological concern, yet whether ecological anxiety paralyses or mobilises young people remains contested, and Global South evidence is scarce.

Objective: Drawing on the Social Identity Model of Collective Action integrated with collective-efficacy theory, this study examined whether collective efficacy moderates the eco-anxiety to climate activism relationship and whether catalytic eco-anger mediates it.

Methods: A cross-sectional survey was administered to 1,500 Generation Z respondents aged 16 to 24 years recruited through public organizations in Palembang, South Sumatera, Indonesia, using validated multi-item five-point Likert scales. Analyses comprised reliability and confirmatory measurement modelling, a correlation matrix, hierarchical moderated regression with simple-slope decomposition, bootstrapped mediation, and diagnostics for common-method bias, multicollinearity, and clustering.

Results: All constructs were reliable (Cronbach's alpha 0.84-0.88; McDonald's omega 0.84-0.87; composite reliability 0.84-0.87; average variance extracted 0.63-0.65) and discriminant validity was supported (heterotrait-monotrait ratios <=0.62). Common-method bias was not a threat (Harman first factor 36.96%). Collective efficacy positively predicted activism (beta = 0.39, 95% CI [0.35, 0.43], p < 0.001) and significantly moderated the eco-anxiety to activism path (interaction beta = 0.57, 95% CI [0.53, 0.60], p < 0.001; Delta-R2 = 0.32; f2 = 0.55). Simple slopes showed a crossover: eco-anxiety was associated with lower activism at low efficacy (-0.56) but higher activism at high efficacy (0.57). Catalytic eco-anger competitively mediated the association (indirect = 0.33, 95% CI [0.29, 0.38]) against a negative direct effect (-0.24).

Conclusion: Collective efficacy conditions whether climate distress becomes organised activism, extending collective-action theory to the Global South and informing Indonesian youth and climate policy.