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All Journal Journal of Information Systems and Informatics Abdimas Toddopuli: Jurnal Pengabdian Pada Masyarakat INOVTEK Polbeng - Seri Informatika
Fajar Nugraha
Muria Kudus University
Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Other

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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.
Student Performance Classification Using Academic, Socioeconomic, and Digital Behavior Features: A Comparative Study Muhammad Arifin; Fajar Nugraha; Diana Laily Fithri
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.v8i1.1460

Abstract

Accurate prediction of student academic performance is essential for universities seeking to improve learning outcomes and deliver timely, data-driven support. Prior work commonly uses regression to estimate Grade Point Average (GPA), yet numeric predictions can be difficult for administrators to translate into actionable risk levels. This study reframes the task as binary classification, categorizing students as good (GPA ≥ 3.00) or poor (GPA < 3.00) performers. Using 2,423 records from multiple programs at an Indonesian university, we combine academic indicators from the learning management system (login frequency, assignment submission, and forum activity) with socio-economic and digital behavioral variables (parental income, extracurricular participation, study-group involvement, and social media use). Seven machine learning models—Naïve Bayes, Generalized Linear Model, Logistic Regression, Deep Learning, Decision Tree, Random Forest, and Gradient Boosted Trees (GBT)—are benchmarked under a consistent evaluation design. Results indicate that integrating academic, socio-economic, and digital behavioral features improves classification performance, and ensemble methods outperform single, traditional models. GBT yields the best accuracy of 0.75, offering a practical basis for early-warning dashboards and targeted interventions. The study provides comparative evidence from Indonesian higher education and highlights the value of incorporating digital engagement signals alongside conventional academic data for more effective student support services.
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.
Penerapan Sistem Informasi Rekrutmen Karyawan Sebagai Upaya Digitalisasi Proses SDM di CV King EV Kabupaten Kudus Muhammad Wifqi Aufal Maulana; Fajar Nugraha
Abdimas Toddopuli: Jurnal Pengabdian Pada Masyarakat Vol. 7 No. 1 (2025): Volume 7, No 1, Desember 2025
Publisher : Universitas Cokroaminoto Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30605/atjpm.v7i1.7332

Abstract

Dalam era digital yang terus berkembang, proses rekrutmen karyawan yang masih dilakukan secara manual sering menimbulkan kendala seperti keterlambatan seleksi, kesalahan administrasi, serta kesulitan dalam pelacakan data pelamar. Kondisi tersebut juga dialami oleh CV King EV, perusahaan penjualan dan perawatan sepeda listrik di Kabupaten Kudus. Untuk mengatasi permasalahan tersebut, dilakukan kegiatan pengabdian kepada masyarakat berupa pendampingan dan penerapan Sistem Informasi Rekrutmen Karyawan Berbasis Web. Kegiatan ini bertujuan membantu mitra mendigitalisasi proses rekrutmen agar lebih efisien, akurat, dan transparan. Metode pelaksanaan meliputi sosialisasi, pelatihan, penerapan, pendampingan, dan evaluasi serta pengembangan system. Perancangan system rekrutmen karyawan berbasis web dengan pendekatan Waterfall, implementasi menggunakan PHP dan MySQL. Data dikumpulkan melalui wawancara dan observasi langsung guna memastikan kesesuaian sistem dengan kebutuhan pengguna. Hasil kegiatan menunjukkan bahwa sistem yang dikembangkan mampu mempercepat proses administrasi rekrutmen, meningkatkan akurasi pengelolaan data pelamar, serta mempermudah komunikasi antara pelamar dan pihak HRD. Selain itu, sistem ini mendukung transparansi, efisiensi kerja, dan meningkatkan citra profesional perusahaan di mata calon karyawan. Dengan demikian, penerapan sistem informasi rekrutmen berbasis web di CV King EV tidak hanya memberikan solusi atas permasalahan mitra, tetapi juga menjadi wujud nyata kontribusi perguruan tinggi dalam mendukung transformasi digital pada sektor industri kecil dan menengah.
Sistem Informasi Pencatatan Poin Pelanggaran Siswa Berbasis Web di SMP N 1 Kaliwungu Rosalva Denisia Yulia Yahya; Fajar Nugraha
Abdimas Toddopuli: Jurnal Pengabdian Pada Masyarakat Vol. 7 No. 1 (2025): Volume 7, No 1, Desember 2025
Publisher : Universitas Cokroaminoto Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30605/atjpm.v7i1.7539

Abstract

Penelitian ini dilakukan dengan merancang dan mengembangkan sistem informasi penulisan poin pelanggaran mahasiswa berbasis web di SMP Negeri 1 Kaliwungu Kudus. Tujuan dari sistem ini dirancang dan dikembangkan bagi guru yang BK melakukan penulisan poin data siswa yang tidak dilakukan secara etis, penulisannya cukup panjang, dan sistem pemantauan tidak dapat dilaksanakan dengan benar. Dengan adanya sistem berbasis web ini, penulisan berlangsung dengan cepat, penulisan sudah ditulis, poin dapat dihitung secara manual dengan kesalahan sehingga data yang dihasilkan jauh lebih akurat. Guru wali BK, wali kelas, dan orang tua siswa akan dipantau dengan metode pencatatan yang tepat dengan sistem aplikasi web. Sistem ini disusun menggunakan pendekatan waterfall yang meliputi analisis, desain, implementasi, pengujian, dan pemeliharaan sistem. Analisis kebutuhan sistem melibatkan pengamatan proses penulisan yang sedang berlangsung dan wawancara guru BK dilakukan untuk menemukan alur sistem yang ada. Hasil wawancara ini digunakan untuk merancang struktur sistem, antarmuka, dll. Kemudian implementasi sistem menggunakan Laravel dan MySQL dan diuji menggunakan metode black box. Hasil penelitian ini memberikan gambaran bahwa sistem informasi berbasis web dapat meningkatkan efisiensi dan transparansi pengelolaan data pelanggaran di sekolah. Selain membantu proses administrasi guru BK, sistem ini juga memperkuat komunikasi antara sekolah dan orang tua dalam memantau perkembangan perilaku siswa. Penelitian ini diharapkan menjadi kontribusi positif dalam penerapan teknologi informasi di lingkungan pendidikan serta referensi untuk pengembangan sistem serupa di sekolah lain.
LoRA Enhanced Sentiment Aware Topic Modeling for Indonesian Generative AI Perception Wisnu Ginanjar Saputra; Noor Latifah; Fajar Nugraha
Journal of Innovation and Technology Polbeng Series on Informatics (INOVTEK Polbeng - Seri Informatika) Vol. 11 No. 1 (2026): February
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/4m8w7t49

Abstract

Public understanding of generative AI in low-resource language contexts remains underexplored, particularly in relation to how sentiment aligns with thematic discussions on social media. In Indonesia, empirical studies examining this interaction at scale are still limited. This study introduces a sentiment-aware topic modeling framework that integrates parameter-efficient fine-tuning of IndoBERT using low-rank adaptation with topic discovery via BERTopic. The approach enables large-scale analysis of Indonesian social media data under constrained computational settings. Analysis of Indonesian Twitter discourse shows that general discussions of generative AI are largely neutral and cautious, contrasting with more optimistic trends reported in Western contexts. In comparison, enthusiast communities exhibit predominantly positive sentiment, while ethics-related discussions display balanced polarization. These results highlight the contextual nature of public perception across different discussion domains. The findings demonstrate the applicability of parameter-efficient NLP methods for sentiment and topic analysis in under-resourced languages and provide insights relevant to technology development and policy formulation.
Co-Authors Diana Laily Fithri Dias Henandra Eka Putra Eva Putri Rosanti Muhammad Arifin Muhammad Wifqi Aufal Maulana Noor Latifah Rosalva Denisia Yulia Yahya Wisnu Ginanjar Saputra