SPPN (Sistem Penilaian Pembinaan Narapidana) at the Crossroads of Rehabilitation: A CIPP–TPB (Context, Input, Process, Product- Theory of Planned Behavior) Analysis of Behavioral Change at Kendal Class IIA Correctional Institution

Abstract

Indonesia’s correctional paradigm has shifted from retribution to rehabilitation, placing behavioral change and social reintegration at the center of prison programming. The Inmate Development Assessment System (Sistem Penilaian Pembinaan Narapidana - SPPN) is mandated to appraise inmates’ progress and to support decisions on integration rights. To examine how SPPN is implemented at Kendal Class IIA Correctional Institution and to assess its effect on inmates’ behavioral change, while identifying instrument context mismatches and operational bottlenecks. We employed a descriptive qualitative design using interviews, observations, and document review. Participants comprised 10 informants (4 inmates, 4 correctional officers, 1 Head of Bimkemaswat, 1 SPPN instrument team member). Data were analyzed with the Miles & Huberman flow (collection, reduction, display, conclusion) and organized in NVivo 12. Analytical lenses combined CIPP (Context, Input, Process, Product) and the Theory of Planned Behavior (TPB). SPPN is in routine use but falls short of its intended objectivity and coverage due to: (i) insufficient staffing and heavy caseloads (1:19, 17 counselors for 326 inmates); (ii) limited SPPN specific training; and (iii) indicator program misalignment (some indicators cannot be scored fairly because supportive programs are absent or sporadic). While compliance and participation increased within custody (attitudes, norms, perceived control improved), recidivism rose (12%→18%→28% in 2022–2024), indicating gains may be situational rather than sustained post release. SPPN contributes to in prison order and engagement, but its validity in capturing true behavioral change is constrained by structural factors and design–context gaps. We propose targeted indicator refinement, routine inter rater training, manageable caseloads, and integration with post release supports to enhance reliability, fairness, and policy utility.