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 — Tue, 30 Jun 2026 00:00:00 +0000

Background: Algorithmic governance is reshaping social protection, but the distributive consequences of automated welfare targeting in the Global South remain poorly understood.

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, a cross-sectional survey of 640 household heads in Palembang, Indonesia, and phenomenological interviews with false-negative cases.

Results: The audit found 72.3% accuracy and a 23.4% false-negative rate. Informality, misclassification, and digital visibility predicted exclusion, while procedural justice was protective; the model explained 52% of variance. Misclassification partially mediated the association, and non-digital informal workers had 4.27 times higher odds of exclusion.

Conclusion: Algorithmic unfairness reflected parameterization bias against informal livelihoods, supporting conditional human oversight 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 — Tue, 30 Jun 2026 00:00:00 +0000

Background: AI-generated synthetic media threatens democratic consolidation, but most evidence is Western, video-centred, and rarely models citizens' political attitudes.

Objective: To examine how illusion of authenticity, confirmation-bias acceleration, and Liar's Dividend perceptions relate to democratic cynicism among Indonesian voters, including mediation by confirmation bias and moderation by synthetic-media literacy.

Methods: A nested mixed-methods design combined computational extraction of 4,200 synthetic-media items, a cross-sectional survey of 3,000 adults across three Indonesian urban centres, and digital ethnography with 50 key informants.

Results: Cloned audio was trusted by 76.2% of respondents but detected by only 11.5%. Authenticity illusion, confirmation bias, and Liar's Dividend perception predicted cynicism, explaining 33.0% of variance. Confirmation bias partially mediated the authenticity-cynicism pathway; literacy lowered cynicism but did not buffer the pathway.

Conclusion: The findings extend deepfake scholarship to oral, messaging-centred Global-South publics and support targeted 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 — Tue, 30 Jun 2026 00:00:00 +0000

Background: Large-language-model AI companions invite reciprocal-seeming parasocial relationships, yet no integrated model explains why relational strain translates into machine attachment in a Global-South setting.

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

Methods: A cross-sectional survey of 1,200 young adults recruited through a public organization in Palembang measured burnout, loneliness, judgment apprehension, AI parasocial interaction, and emotional attachment using validated scales.

Results: The model explained 48% of attachment variance. Parasocial interaction, loneliness, and burnout were the strongest predictors. Parasocial interaction partially mediated the burnout-attachment path, and judgment apprehension strengthened the loneliness-attachment association.

Conclusion: The findings support an '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 article-processing-charge model has reorganized the political economy of knowledge production, while researcher-level perceptions of fairness remain under-measured in the Global South.

Objective: To test whether institutional publication pressure predicts perceived epistemic injustice and whether publication-cost privatization and research cannibalization mediate that relationship among Indonesian academics.

Methods: A cross-sectional survey of 312 academics used validated multi-item scales, multiple regression, parallel mediation with 5,000 bootstrap samples, moderation, common-method testing, and multicollinearity diagnostics.

Results: Publication pressure, cost privatization, and research cannibalization independently predicted epistemic injustice, explaining 34.6% of variance. Both mediators carried significant indirect effects, and perceived grant availability buffered the pressure-to-privatization path.

Conclusion: Publication mandates without adequate funding may generate perceived epistemic injustice; the findings formalize the 'illusion of inclusivity' as a measurable perception.

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

Jasmila Tanjung, Sarah Armalia, Zahra Amir — Tue, 30 Jun 2026 00:00:00 +0000

Background: Whether ecological anxiety paralyses or mobilises young people remains contested, and evidence from the Global South is limited.

Objective: To determine whether collective efficacy moderates the eco-anxiety-climate activism relationship and whether catalytic eco-anger mediates it among Indonesian Generation Z.

Methods: A cross-sectional survey included 1,500 participants aged 16-24 years recruited through public organizations in Palembang. Validated scales, regression, simple-slope analysis, and bootstrap mediation were used.

Results: Collective efficacy positively predicted activism and produced a crossover interaction: eco-anxiety predicted lower activism at low efficacy but higher activism at high efficacy. Catalytic eco-anger competitively mediated the association against a negative direct effect.

Conclusion: Collective efficacy conditions whether climate distress becomes organized activism, extending collective-action theory and informing Indonesian youth and climate policy.