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p-Index From 2021 - 2026
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All Journal Journal of Information Systems and Informatics bit-Tech
Noor Latifah
Muria Kudus University
Computer Science & IT

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Journal : Journal of Information Systems and Informatics

 1 
Application of the Key Performance Indicator Method in an Employee Information System Eva Putri Rosanti; Noor Latifah; Fajar Nugraha
Journal of Information System and Informatics Vol 8 No 1 (2026): February
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i1.1439

Abstract

The rapid development of information technology has significantly encouraged the integration of information systems in human resource management to enhance efficiency, effectiveness, and objectivity. However, performance appraisal systems that lack standardized indicators can lead to subjectivity and inconsistency, impacting employee productivity and managerial decision-making. This study proposes a web-based Personnel Management Information System (PMIS) that integrates Key Performance Indicators (KPIs) to provide an objective and measurable performance evaluation system. The system design incorporates KPIs, weights, and targets, supported by a structured, transparent process for performance assessments. The system was implemented at PT Kebon Agung Trangkil, a sugar industry company, to improve employee performance evaluations and managerial decision-making. This research adopts the Waterfall system development method and includes a User Acceptance Test (UAT) with 15 respondents, achieving an 88% acceptance rate. The results indicate that the developed system improves assessment efficiency, reduces subjectivity, and supports more transparent decision-making. The study concludes with recommendations for expanding the system’s capabilities and improving KPI validation through formal methods.
Time-Series Monitoring of Sentiment Dynamics in Reviews of Four Indonesian E-Wallet Applications Using a Hybrid TF-IDF and Bi-LSTM Framework Noor Latifah; Dias Henandra Eka Putra; Fajar Nugraha
Journal of Information System and Informatics Vol 8 No 2 (2026): April
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i2.1488

Abstract

This study proposes a hybrid sentiment analysis framework to examine user perceptions of four Indonesian e-wallet applications using Google Play Store reviews. The framework combines TF-IDF features reduced through Truncated SVD with a Bidirectional Long Short-Term Memory (Bi-LSTM) model within a two-stage evaluation design consisting of holdout classification and external temporal inference. For supervised classification, 20,000 raw reviews were filtered and labeled using a rating-based strategy, resulting in 13,823 labeled reviews. Reviews with ratings of 4–5 stars were assigned to the positive class and 1–2 stars to the negative class; these labels should be interpreted as sentiment proxies rather than fully human-validated ground truth. A second dataset of 24,000 reviews was constructed for balanced cross-application temporal comparison across 2024–2026. On the holdout test set, the proposed model achieved an accuracy of 0.881, with macro-F1 and weighted-F1 scores of 0.881. Under the external temporal setting, DANA remained relatively stable, GoPay improved markedly in 2025 and remained high in 2026, ShopeePay showed a gradual decline, and OVO exhibited the strongest negative trend. These results indicate that the proposed framework is useful not only for supervised sentiment classification but also for structured temporal monitoring across e-wallet platforms.
Co-Authors Dias Henandra Eka Putra Eva Putri Rosanti Fajar Nugraha Fariz Dermawan