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Gita Damayanti
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Humanities Computer Science & IT Education Social Sciences

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Hubungan Kualitas Pelayanan Kesehatan Dengan Kepuasan Pasien Rawat Jalan BPJS Kesehatan Afip Sultoni; Gita Damayanti; Ani, Ani; Hartanto, Sri
J-CEKI : Jurnal Cendekia Ilmiah Vol. 4 No. 3: April 2025
Publisher : CV. ULIL ALBAB CORP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56799/jceki.v4i3.7722

Abstract

Perkembangan sistem pelayanan kesehatan terfokus pada tanggung jawab pemerintah untuk menjaga kesejahteraan masyarakat paska kemerdekaan Indonesia, Meskipun kualitas perawatan medis sangat penting, data dari peserta BPJS menunjukkan adanya ketidakpuasan terhadap layanan yang diberikan. Tujuan penelitian ini menganalisis hubungan antara faktor kualitas pelayanan dan pada tingkat kepuasan pasien di Klinik Fahmi Husada, Kabupaten Madiun, Jawa Timur, pada tahun 2024. Sistem ini menggunakan adalah kuantitatif dengan desain cross-sectional, di mana data ini disatukan melalui kuesioner dari 30 pasien rawat jalan. Telaah data dilakukan dengan pengujian statistik chi-square dan sampel diambil menggunakan metode purposive sampling. Hasil analisis bivariat ini menunjukkan bahwa tidak ada hubungan yang relevan antara dimensi “tangible” (P-value 0,053) dan “reliability” (P-value 1,000) dengan kepuasan pada pasien. Sebaliknya, diperoleh hubungan yang signifikan antara dimensi “responsiveness” (P-value 0,024) dan “empathy” (P-value 0,034) dengan tingkat kepuasan pada pasien. Sementara itu, dimensi “assurance” tidak menunjukkan hubungan yang signifikan (P-value 0,988). Penelitian ini menyimpulkan bahwa hanya dua variabel yaitu “daya tanggap” dan “empati” yang berhubungan dengan kepuasan pasien, sedangkan tiga variabel lainnya tidak menunjukkan hubungan yang signifikan. Temuan ini dapat menjadi panduan untuk meningkatkan kualitas pelayanan di Klinik Fahmi Husada Madiun dengan fokus pada kepuasan pasien.
Development of an Android-Based Educational Game with Gamification for Algorithms and Data Structures Gita Damayanti; Miraekel Lebang Malik; Firdayani Syarifuddin; Ibnu Hajar Manippi; Eva Ulfiani; Era Fasira
Information Technology Education Journal Vol. 3, No. 2, Mei (2024)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v3i2.2401

Abstract

This study aims to develop and evaluate an Android-based educational game incorporating gamification elements for teaching Algorithms and Data Structures (ADS). ADS is recognized as a fundamental yet challenging subject in computer science education due to its abstract concepts and dynamic processes. Traditional lecture-based instruction often results in low engagement and limited conceptual understanding. Therefore, this study proposes a gamified mobile learning solution to enhance student motivation and learning outcomes. A Research and Development (R&D) approach using the ADDIE model was employed to design and develop the application, followed by a quasi-experimental non-equivalent control group pretest–posttest design to evaluate its effectiveness. Participants consisted of 74 undergraduate students divided into an experimental group (n = 38) using the Android-based gamified application and a control group (n = 36) receiving conventional instruction. Data were analyzed using paired and independent samples t-tests with a significance level of 0.05. Results indicated a significant difference in posttest scores (t = 6.64, p < 0.001), with the experimental group achieving a higher mean (M = 82.47) compared to the control group (M = 71.28). The effect size was large (Cohen’s d = 1.54). Motivation scores were also higher in the experimental group (M = 4.31), and usability evaluation yielded an excellent System Usability Scale (SUS) score of 81.45. The study is limited to a single institution and short intervention duration. This research contributes empirical evidence that gamified Android-based learning can significantly improve cognitive achievement and motivation in ADS courses.
Development of an Inclusive Computer Vision–Based Learning Media for Gesture Recognition among Deaf and Hard of Hearing Students Andi Sriwangi B; Abdul Riyadi Lessy; Aswar Munandar; Ade Ayu Permataleli; Eka Srijayarni; Gita Damayanti
Information Technology Education Journal Vol. 3, No. 1, Januari (2024)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v3i1.02419

Abstract

This study aimed to develop and evaluate an inclusive computer vision–based learning media for gesture recognition among deaf and hard-of-hearing (DHH) students. The motivation was to address the lack of interactive, curriculum-aligned tools for BISINDO gesture acquisition, enhancing both learning accuracy and engagement. The research followed a research and development (R&D) design using the ADDIE model, integrated with a quasi-experimental evaluation. The system employed a CNN-LSTM hybrid model with MediaPipe pose estimation for real-time gesture recognition. A purposive sample of 60 junior secondary DHH students in Makassar, Indonesia, participated in the study. Pretest–posttest scores, learning engagement questionnaires, and system usability scales were administered. Data analysis included paired and independent samples t-tests, descriptive statistics, and Pearson correlation. The developed media demonstrated high recognition accuracy (93.4%) and excellent usability (SUS = 84.3/100). Students using the system significantly outperformed the control group in posttest scores (Mean gain = 8.36 vs. 3.54, p < 0.001, Cohen’s d = 1.56). Engagement positively correlated with learning gains (r = 0.68, p < 0.01), indicating that interactive feedback mechanisms enhanced motivation and gesture mastery. The study highlights the pedagogical value of AI-assisted gesture learning for DHH students, but is limited to isolated gesture recognition, one geographic region, and quasi-experimental design constraints. Environmental lighting and camera quality may also affect system performance. This study bridges the gap between computer vision–based sign recognition research and inclusive pedagogy, demonstrating both technological feasibility and educational impact. Future research could extend the system to continuous sign sequences, multimodal feedback, and cloud-based deployment for broader scalability.
Co-Authors Abdul Riyadi Lessy Ade Ayu Permataleli Afip Sultoni Alifta, Alifta Luluk Nur Fu'aidah Andi Sriwangi B ani ani Aswar Munandar Eka Srijayarni Era Fasira Eva Ulfiani Firdayani Syarifuddin Ibnu Hajar Manippi Miraekel Lebang Malik Qulud Dwitika Kusuma Rochmat aldy Purnomo Sri Hartanto