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All Journal Jiko (Jurnal Informatika dan komputer) Jurnal ABDINUS : Jurnal Pengabdian Nusantara EXPLORER
Frangky, Frangky
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Computer Science & IT Economics, Econometrics & Finance Education Environmental Science Industrial & Manufacturing Engineering

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Analisis Segmentasi Pasien Berdasarkan Persepsi Kualitas Pelayanan dengan Algoritma Clustering Frangky, Frangky; Sinaga, Rudolf; Raihansyah, M.
Explorer Vol 5 No 1 (2025): January 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/explorer.v5i1.1818

Abstract

Patient segmentation based on perceptions of service quality is a crucial step in improving patient experiences, optimizing resources, and enhancing healthcare service quality. However, understanding patients' needs and priorities in depth poses a challenge, particularly for hospitals serving populations with diverse demographic backgrounds. This study aims to cluster patients in a private hospital in Jambi City based on their perceptions of service quality using the K-Means algorithm. Data were collected from a 2022-2023 survey, covering patient demographics and perceptions of service quality. The data were processed through preprocessing steps, including missing value imputation, normalization, and encoding. The optimal number of clusters was determined using the Elbow and Silhouette Score methods. The results revealed three main clusters with distinct characteristics. The first cluster (34.29%) includes patients prioritizing service speed and procedural ease. The second cluster (46.12%) consists of patients who emphasize staff competence and cost fairness as their main priorities. The third cluster (19.59%) comprises patients with higher educational backgrounds who are more critical of facility quality and complaint handling. Evaluation using the Davies-Bouldin index demonstrated good cluster separation (score -0.645). This study concludes that patient segmentation based on perceptions of service quality can serve as a foundation for strategic decision-making to improve hospital service quality. Recommendations for future research include applying other algorithms such as DBSCAN, integrating sentiment analysis, and employing a hybrid approach to predict patient needs. These approaches are expected to provide a deeper understanding and more effective personalization of patient care.
Pelatihan Pemanfaatan Artificial Inteligence dalam Membuat Media Pembelajaran N, Renny Afriany; Sinaga, Rudolf; Samsinar, Samsinar; Frangky, Frangky
Jurnal ABDINUS : Jurnal Pengabdian Nusantara Vol 9 No 2 (2025): Volume 9 Nomor 2 Tahun 2025
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/ja.v9i2.24911

Abstract

Education in Indonesia faces challenges in adopting modern technology, particularly in developing effective and engaging learning media. Teachers in the Cross-School Learning Community of Cluster II Anggrek in Jambi City still use conventional methods that are less adaptive to student needs. The utilization of AI technology such as Gamma AI can help create more efficient, innovative, and interactive learning media. The training was carried out systematically with four main modules: Introduction to Gamma AI, Creating Presentations, Tips and Tricks, and Evaluation and Application. The methods used included demonstrations, hands-on practice, interactive discussions, and evaluation of training outcomes. The activity involved 30 teacher participants from the community and was conducted on July 16, 2024, at the SD Negeri 96 Kota Jambi hall. This training successfully improved teachers' competencies in utilizing Gamma AI to create more engaging and interactive learning media. Teachers were able to save time in creating materials, use data for personalized learning, and enhance student engagement through AI-based content. The main output of the activity was the improvement of learning quality in schools within the community and the strengthening of teachers' digital competencies.
ANALYSIS OF SECURITY CHALLENGES IN REST API IN EDGE COMPUTING-BASED IOT ECOSYSTEM: A REVIEW Sinaga, Rudolf; Samsinar, Samsinar; Fatima, Soomal; Frangky, Frangky
JIKO (Jurnal Informatika dan Komputer) Vol 8, No 2 (2025)
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v8i2.10097

Abstract

REST APIs are the backbone of data communication in the Internet of Things (IoT)-based edge computing ecosystem because they are lightweight and flexible. However, the REST architecture's openness and the edge devices' limited resources give rise to security challenges such as MITM, spoofing, and replay attacks. This study aims to identify the key challenges of REST API security in IoT edge environments, evaluate the limitations of conventional solutions such as TLS and RSA/ECDSA algorithms, and explore the potential of Post-Quantum Signature-based digital authentication approaches (PQS). Through a comprehensive narrative literature review of 43 peer-reviewed publications (2020-2025), this research reveals two key findings: the results show that TLS generates significant overhead in memory and energy, while classical algorithms do not resist quantum threats. PQS schemes such as Falcon and Dilithium have proven more efficient and secure in limited devices. The study concludes that PQS-based lightweight authentication approaches have strong prospects for implementation in future REST API gateway architectures, particularly in supporting electronic-based governance systems (SPBEs).
Co-Authors Fatima, Soomal N, Renny Afriany Raihansyah, M. Rudolf Sinaga Samsinar Samsinar