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All Journal IKRA-ITH Informatika : Jurnal Komputer dan Informatika JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Information Systems and Technology Research Journal of Artificial Intelligence and Digital Business Jurnal Sistem Informasi, Sains Data, dan Informatika
Saelan, Athia
Universitas Indonesia Membangun
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering

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Analysis of SIPD Acceptance at Bappeda Bulungan Regency Using the Technology Acceptance Model Method Juani, Elisabet; Harahap, Dian Pransisko; Saelan, Athia
IKRA-ITH Informatika : Jurnal Komputer dan Informatika Vol. 10 No. 1 (2026): IKRAITH-INFORMATIKA Vol 10 No 1 Maret 2026
Publisher : Fakultas Teknik Universitas Persada Indonesia YAI

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Digital transformation in local government governance requires effective use of information systems, particularly in regional development planning, control, and evaluation. One of the nationally implemented systems is the Regional Government Information System (SIPD). This study aims to analyze user acceptance and actual usage of SIPD among employees of the PPEPD Division at the Regional Development Planning Agency (Bappeda) of Bulungan Regency using the Technology Acceptance Model (TAM). This research employed a descriptive quantitative method with a survey approach involving 51 active SIPD users. Data were collected through a five-point Likert scale questionnaire measuring Perceived Usefulness (PU), Perceived Ease of Use (PEOU), Attitude Toward Using (ATU), Behavioral Intention to Use (BITU), and Actual System Use (ASU). The results indicate that all TAM variables fall into good to very good categories, with an overall mean score of 4.14. PU achieved the highest score (4.20), indicating that SIPD is perceived as highly beneficial, while PEOU recorded the lowest score (4.09), although still categorized as good. These findings suggest that SIPD has been well accepted and practically implemented, yet improvements in system usability are still required.
Pengembangan Sistem Informasi Monitoring Checklist Maintenance untuk Efisiensi Pemeliharaan Pada Divisi General Affair Priyadi, Angga; Fernando, Daniel; Irawan, Debi; Saelan, Athia
Journal of Information System Research (JOSH) Vol 7 No 2 (2026): January 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i2.8723

Abstract

The General Affair (GA) Division at a telecommunications company faces problems in the maintenance checklist process, which is still carried out manually using paper and simple worksheets. This process often result in data duplication, inaccurate documentation, and delays in reporting. This research aims to develop a web-based maintenance checklist monitoring information system to support the digitalization and improve the efficiency of the facility maintenance process in the GA Division. The system development was carried out using the waterfall method through the steps of needs analysis, system design, implementation, and testing. The system was developed using the CodeIgniter 4 framework, Metronic UI interface, and MySQL as the database. Testing was conducted using the Black Box Testing method on 12 functional testing scenarios covering the main functions of the system for the roles of GA Admin and GA Officer, and all main functions of the system showed a 100% success rate according to specifications. In addition, a limited User Acceptance Test (UAT) was conducted involving GA Admin as expert judgment and GA Officers, showing that the system is easy to use, helps speed up the monitoring and reporting process, and improves the accuracy of checklist data. The research results are in the form of a web-based system that is capable of integrating the activities of various field officer roles, providing centralized data access, increasing maintenance efficiency, and supporting real-time monitoring and maintenance reporting.
Studi Literatur Penerapan Teori Graf Dalam Rekomendasi Teman di Media Sosial Muhammad Raffa Abdillah; Athia Saelan; Ismail Ismail
Jurnal Sistem Informasi, Sains Data, dan Informatika Vol 1 No 1 (2026): Volume 1 No. 1, Januari 2026
Publisher : Universitas Indonesia Membangun (Inaba)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56956/1kz89d13

Abstract

Social media is a platform for a vast network of friends. Friendship networks on social media are usually represented in the form of graphs. One of the main features of social media is friend recommendations. This research is a literature study on methods that can be used to provide friend recommendations on social media. To provide accurate friend recommendations on social media, certain methods derived from graph theory are required. Some of the methods discussed include centrality, similarity, trust value, and community detection. Based on the literature study, the steps for building a friend recommendation system include data collection, graph construction, graph structure analysis, application of similarity and trust value, and system evaluation. With these methods, it is hoped that the recommended friends will be more accurate and suit the user needs.
Effect of Information System Quality on Administration via E-Office Applications: Evaluation of E-Office Performance at the KBB Manpower Office Ayu, Difta; Nurrohman, Aldy; Saelan, Athia; Supriana, Fadhlanrashif Ibrahim
Journal of Information Systems and Technology Research Vol. 5 No. 1 (2026): January 2026
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/jistr.v5i1.1475

Abstract

The implementation of digital administrative systems in public sector institutions is expected to enhance efficiency, transparency, and accountability; however, partial system adoption and varying levels of user acceptance often limit their effectiveness. This study evaluates the implementation of a web-based E-Office application in public sector administration by examining how system quality, information quality, and service quality influence administrative management and employee acceptance. This research employs a descriptive qualitative approach by integrating the Information System Success Model and the Technology Acceptance Model (TAM). Qualitative data were collected through in-depth interviews with selected employees, direct observation of administrative workflows, and documentation analysis related to E-Office utilization in a local government institution. The findings indicate that system quality, information quality, and service quality positively contribute to administrative management effectiveness by accelerating document processing, improving information accessibility, and strengthening administrative accountability. In addition, perceived usefulness and perceived ease of use significantly influence employee acceptance of the E-Office application. Nevertheless, several challenges remain, including an outdated user interface, limited document search functionality, and the coexistence of manual and digital administrative processes. The novelty of this study lies in its qualitative integration of information system quality dimensions and the Technology Acceptance Model within a local government administrative context, providing empirical insights into both technical system performance and user acceptance to support public sector digital transformation.
Analisis Akurasi Dua Metode Klasifikasi: K-Nearest Neighbor vs Naïve Bayes pada Data Diabetes Fidalina Nirigi; Mochammad Triyanto; Mohammad Rezza Pahlevi; Athia Saelan; Fadhlanrashif Ibrahim Supriana
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 5 No. 2 (2026): Mei-Juli
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v5i2.8671

Abstract

Diabetes merupakan kondisi metabolik yang ditandai oleh tingginya kadar glukosa darah dan telah menjadi masalah kesehatan global. Apabila tidak ditangani dengan tepat, diabetes dapat menyebabkan komplikasi serius seperti penyakit kardiovaskular, stroke, kerusakan ginjal, mata, dan sistem saraf. Perkembangan teknologi machine learning memberikan peluang dalam membantu proses klasifikasi dan prediksi penyakit diabetes secara lebih cepat dan akurat. Penelitian ini bertujuan untuk menganalisis tingkat akurasi dua metode klasifikasi, yaitu K-Nearest Neighbor (KNN) dan Naïve Bayes pada data diabetes. Dataset yang digunakan adalah Pima Indians Diabetes Database dengan pembagian data sebesar 80% untuk data latih dan 20% untuk data uji. Tahapan penelitian meliputi preprocessing data, pelatihan model, dan pengujian klasifikasi. Variabel yang digunakan meliputi kadar glukosa, usia, indeks massa tubuh (BMI), tekanan darah, serta riwayat diabetes. Hasil penelitian menunjukkan bahwa kedua algoritma mampu melakukan klasifikasi data diabetes dengan baik. Namun, algoritma K-Nearest Neighbor memperoleh tingkat akurasi lebih tinggi sebesar 81%, sedangkan Naïve Bayes memperoleh akurasi sebesar 77%. Berdasarkan hasil tersebut, metode K-Nearest Neighbor dinilai lebih efektif dalam proses prediksi penyakit diabetes dibandingkan metode Naïve Bayes. Penelitian ini diharapkan dapat menjadi referensi dalam pengembangan sistem pendukung keputusan berbasis machine learning di bidang kesehatan, khususnya untuk deteksi dini penyakit diabetes.
Co-Authors Ayu, Difta Daniel Fernando Debi Irawan Fadhlanrashif Ibrahim Supriana Fidalina Nirigi Harahap, Dian Pransisko Ismail Juani, Elisabet Mochammad Triyanto Mohammad Rezza Pahlevi Muhammad Raffa Abdillah Nurrohman, Aldy Priyadi, Angga Supriana, Fadhlanrashif Ibrahim