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All Journal Tech-E JURNAL LENTERA : Kajian Keagamaan, Keilmuan dan Teknologi Jurnal Sistem Informasi, Teknik Informatika dan Teknologi Pendidikan (JUSTIKPEN) Kesmas: Jurnal Kesehatan Masyarakat Nasional (National Public Health Journal)
Amin, Hasan
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Religion Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Health Professions Law, Crime, Criminology & Criminal Justice Mechanical Engineering Public Health Social Sciences Other

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Analisis Penerimaan E-Learning sebagai Media Perkuliahan melalui Pendekatan Technology Acceptance Model (TAM) Ana, Layli; Amin, Hasan
JURNAL LENTERA : Kajian Keagamaan, Keilmuan dan Teknologi Vol 24 No 2 (2025): Juni 2025
Publisher : LP2M STAI Miftahul 'Ula (STAIM) Nganjuk

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29138/lentera.v24i2.1676

Abstract

Technology Acceptance Model (TAM) is a conceptual framework developed from the Theory of Reasoned Action (TRA) to understand how people accept and use information systems. This model is designed to identify how external factors can influence an individual's beliefs, attitudes, and intentions in using technology. In TAM, there are two key components that are considered to be the main determinants of computer acceptance behavior, namely perceived usefulness (PU) which is the extent to which users believe that the technology can improve their performance, and perceived ease of use (PEOU) which is the level of user belief that the system is easy to operate. This study is a quantitative survey study with 150 active student respondents, data analysis using SEMPLS, the results of the study showed that Perceived Ease of Use (PEU) has a positive effect on Perceived Usefulness (PU) and Attitude Toward Using (ATU), perceived Usefulness (PU) has a positive effect on ATU and Behavioral Intention (BI), Attitude Toward Using (ATU) has a positive effect on Behavioral Intention (BI) and Behavioral Intention (BI) has a positive impact on Actual Use (AU).
Otomatisasi Deployment dan Manajemen Multi-Kontainer Docker untuk Skalabilitas dan Efisiensi Lingkungan Komputansi Terisolasi Amin, Hasan; Ana, Layli; Suhendi, Agus
Jurnal Sistem Informasi, Teknik Informatika dan Teknologi Pendidikan Vol. 5 No. 1 (2025): Jurnal Sistem Informasi, Teknik Informatika dan Teknologi Pendidikan
Publisher : Utiliti Project Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55338/justikpen.v5i1.261

Abstract

Penelitian ini bertujuan untuk merancang dan mengimplementasikan otomasi deployment aplikasi berbasis Docker guna meningkatkan efisiensi dan konsistensi pengelolaan layanan. Metode yang digunakan meliputi pembuatan Dockerfile untuk membangun image, penyusunan shell script untuk otomasi, serta pengujian pada skenario multi-container dengan Docker Compose. Evaluasi dilakukan dengan membandingkan waktu deployment otomatis dengan metode manual. Hasil penelitian menunjukkan bahwa pendekatan otomatis mampu menurunkan waktu deployment hingga 98,67% dibandingkan cara manual. Selain itu, sistem memberikan konsistensi lingkungan, memudahkan rollback, serta mendukung skala enterprise dengan integrasi ke alat orchestration seperti Kubernetes. Simpulan dari penelitian ini adalah otomasi berbasis Docker dapat menjadi solusi efektif untuk meningkatkan efisiensi, skalabilitas, dan keandalan dalam pengelolaan layanan teknologi informasi.
Infarct Diameter for Predicting Cognitive Dysfunction in Ischemic Stroke Survivors in West Nusa Tenggara, Indonesia Harahap, Herpan Syafii; Putri, Setyawati Asih; Indrayana, Yanna; Amin, Hasan; Mahardika, Fransisca Ika
Kesmas Vol. 17, No. 2
Publisher : UI Scholars Hub

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

Abstract

Cognitive dysfunction is an important consequence of ischemic stroke, which can progress in the first few years and is primarily determined by clinical factors. This study aimed to investigate the clinical determinants of cognitive dysfunction in stroke survivors in West Nusa Tenggara Province, Indonesia. This cross-sectional study assessed 255 ischemic stroke survivors with a mean age of 57.1±9.3 years old and 29–79 years old, recruited consecutively in three main hospitals in West Nusa Tenggara Province between March 2019 and October 2021. Categorical data collected included age, sex, education level, clinical determinants of ischemic stroke, and cognitive status of the patients. The association between the clinical determinants of ischemic stroke and the risk of cognitive dysfunction in patients was analyzed using logistic regression after adjusting for age, sex, and level of education. The final multiple logistic regression analysis models revealed infarct diameter as the only clinical determinant significantly associated with an increased risk of cognitive dysfunction (OR = 3.14;95% CI = 1.20–8.23). Thus, a larger infarct diameter is the only clinical determinant of cognitive dysfunction in ischemic stroke survivors in West Nusa Tenggara Province, Indonesia.
Clustering Analysis of Admission of New Students Using K-Means Clustering and K-Medoids Algorithms to Increase Campus Marketing Potential Amin, Hasan
Tech-E Vol. 7 No. 1 (2023): TECH-E (Technology Electronic)
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/te.v7i1.2264

Abstract

Acceptance of new students is a very important activity for a high school or university. The admissions data has not been utilized by the campus in making strategic decisions, marketing potential, and considering invitations through academic admissions. So, to assist in processing the new student admissions data, in this study the design and analysis of new student admissions data was carried out using stages in data mining. The clustering method approach can be applied in analyzing the potential level of PMB quality produced by utilizing the PMB recording dataset for the 2023 period. 86 data records. The K-Means and K-Medoids algorithm models that are applied have results that show a new insight, namely grouping based on 2 clusters, cluster 1 (C0) is a pass category while cluster 2 (C1) has not been determined. The results of the K-Medoids algorithm which has cluster 1 (C0) 60 results, cluster 2 (C1) has 26 results is a potential pass of 60 and has not yet been determined 26 of the data tested 86 while the results of the K-Means cluster 1 algorithm (C0) 40 , cluster 2 ( C1 ) 46 is a potential pass consisting of 40 and 46 undetermined data from the 86 datasets tested. Testing using the RapidMiner Studio application can also produce similar insights, namely each cluster has Davies Bouldin Index or DBI results from each K-Means and K-Medoids algorithm. K-Means has a Davies Bouldin Index result of -0.533 while K-Medoids has a Davies Bouldin Index result of -0.877
Co-Authors Ana, Layli Herpan Syafii Harahap Indrayana, Yanna Mahardika, Fransisca Ika Putri, Setyawati Asih Suhendi, Agus