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All Journal Jupiter Aisyah Journal of Informatics and Electrical Engineering Journal of Information Systems and Informatics Jurnal Teknik Informatika (JUTIF) Jurnal Algoritma IJOEM: Indonesian Journal of Elearning and Multimedia Finger : Jurnal Ilmiah Teknologi Pendidikan Jurnal Pengabdian Masyarakat Bangsa Jurnal Pendidikan Teknologi Informasi (J-Diteksi) Jurnal Rekayasa Perangkat Lunak
Ikna Awaliyani
Universitas Aisyah Pringsewu
Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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PENGEMBANGAN KONFIGURASI JARINGAN HOTSPOT DAN VOUCHER WIFI MENGGUNAKAN MIKROTIK CCR1009-7G-1C-1S+ PADA JALURDATA.NET IKNA AWALIYANI IKNA
Aisyah Journal Of Informatics and Electrical Engineering (A.J.I.E.E) Vol. 5 No. 2 (2023): Aisyah Journal Of Informatics and Electrical Engineering
Publisher : Aisyah Journal Of Informatics and Electrical Engineering (A.J.I.E.E)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30604/jti.v5i2.233

Abstract

Saat ini, permintaan akan akses internet telah mencapai tingkat yang sangat tinggi, karena banyak orang membutuhkan konektivitas untuk mencari informasi terkini, membaca artikel, dan menikmati berbagai hiburan. Salah satu tempat yang menyediakan akses internet adalah Jalurdata.net. Banyak Internet Service Provider (ISP) yang menawarkan fasilitas Wi-fi bagi pelanggan. Jalurdata.net, sebuah ISP di Adiluwih Kabupaten Lampung Tengah, juga menyediakan fasilitas hotspot menggunakan vouvher untuk para pelanggan. Namun, fasilitas Wi-fi ini belum memiliki batasan penggunaan. Jalurdata.net menggunakan hotspot dan sistem voucher untuk menghitung akses pengguna. Konfigurasi hotspot dengan menggunakan MikroTik dapat dilakukan untuk mencapai tujuan ini. MikroTik memiliki fitur hotspot dan tambahan fitur User Manager yang memungkinkan manajemen hotspot melalui antarmuka web. Penggunaan voucher dihitung berdasarkan periode waktu tertentu, dan setiap voucher hanya dapat dimanfaatkan oleh satu pengguna saja. Tujuan dari penelitian ini adalah menciptakan voucher hotspot yang dapat diisi ulang melalui situs web login hotspot, sehingga mempermudah konsumen dalam mengakses Wi-Fi, melakukan pengisian ulang voucher, serta mengurangi kelebihan penggunaan Wi-Fi oleh setiap pelanggan. Berdasarkan hasil penelitian, terungkap bahwa dalam pengujian menggunakan voucher yang memiliki batas waktu dan pengguna, satu voucher tidak dapat digunakan oleh lebih dari satu pengguna secara bersamaan. Selain itu, jika waktu voucher telah habis, voucher tersebut dapat diisi ulang kembali. Meskipun demikian, konsumen hanya diperbolehkan melakukan pengisian ulang voucher sekali dalam sehari. Kata Kunci: Hotspot, Voucher, Mikrotik,, Jalurdata.net.
Data Mining untuk Klasterisasi dan Klasifikasi Pelanggan Berdasarkan Pendapatan dan Transaksi Pembelanjaan Menggunakan Algoritma K-Means AWALIYANI, IKNA; Yudha Pratama, Rendy
Jurnal Rekayasa Perangkat Lunak Vol. 4 No. 1 (2025): Jurnal Rekayasa Perangkat Lunak (J-Rapa)
Publisher : Universitas Aisyah Pringsewu

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

Abstract

In the era of technology and business, handling customers is very important as consumers and a significant source of marketing information. Customer evaluations have a major impact on marketing and service quality can be a benefit or a loss to a seller's reputation. Knowing key customer profiles supports effective marketing strategies with a deep understanding of customer preferences and behavior. This approach is supported by clustering technology for better analysis of customer information, improving management, and designing IT technology according to current developments. The results of data processing form four clusters, forming customer profiles based on family structure and income/expense levels. Understanding cluster characteristics is the basis for an effective marketing strategy. By customizing marketing tactics, targeting specific offers, and optimizing promotions, companies can build strong relationships, increase retention, and achieve business success. This approach provides deep insight, enables targeted decision making, and is responsive to evolving market dynamics.
A User-Driven E-Audit System for Improving Transparency and Efficiency in Regional Government Supervision Aminudin, Nur; Hidayat, Nurul; Feriyanto, Dwi; Mukaromah, Hafsah; Septasari, Dita; Awaliyani, Ikna
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.5145

Abstract

Internal audit processes in regional government institutions often face challenges such as time inefficiency, low transparency, and poorly digitized documentation. This study aims to develop an E-Audit system to enhance the effectiveness of internal supervision in a regional inspectorate environment. Employing a user-centered design approach and a structured system development methodology, this research involved key roles—auditors, technical controllers, and follow-up teams—throughout the design and testing stages. The developed system integrates three core phases of the audit process—planning, reporting, and follow-up—into a single, modular, and interactive digital platform. Implementation results indicate a significant improvement in audit efficiency, with a reduction of more than 50% in process duration compared to manual methods. The system also enhances documentation consistency through digital audit trails, role-based dashboards, and automatic reporting features. User acceptance testing revealed a high level of satisfaction, with users highlighting the system’s ease of use, increased accuracy, and alignment with daily audit tasks. Additionally, user feedback emphasized the need for integrated notification features and inter-unit communication tools, indicating readiness for more advanced digital transformation. Overall, this study provides practical value as a model for digital audit implementation at the regional government level while contributing to the advancement of Computer Science through the application of software engineering principles and information systems to support digital government oversight. The developed E-Audit model can serve as a reference for designing real-time collaborative public auditing systems relevant to the development of information systems engineering and computational governance.
Optimizing Type 2 Diabetes Classification with Feature Selection and Class Balancing in Machine Learning Wantoro, Agus; Yuliana, Aviv Fitria; Andini, Dwi Yana Ayu; Awaliyani, Ikna; Caesarendra, Wahyu
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.5166

Abstract

Type 2 Diabetes (T2DM) is a crucial factor in patient survival and treatment effectiveness. Errors in diabetes detection lead to disease severity, high costs, prolonged healing time, and a decline in service quality. Additionally, a major challenge in developing Machine Learning (ML)-based detection decision support systems is the class imbalance in medical data as well as the high feature dimensionality that can affect the accuracy and efficiency of the model. This research proposes an approach based on feature selection (FS) and handling class imbalance to improve performance in type 2 diabetes. Several feature selection techniques such as Information Gain (IG), Gain Ratio (GR), Gini Decrease (GD), Chi-Square (CS), Relief-F, and FCBF can perform feature selection based on weighting ranking. Furthermore, to address the imbalanced class distribution, we utilize the Synthetic Minority Over-Sampling Technique (SMOTE). ML classification models such as Support Vector Machine (SVM), Gradient Boosting (GB), Tree, Neural Network (NN), Random Forest (RF), and AdaBoost were tested and evaluated based on the confusion matrix including accuracy, precision, recall, and time. The experimental results show that the combination of strategies for handling imbalanced classes significantly improves the predictive performance of ML algorithms. In addition, we found that the combination of feature selection techniques IG+AdaBoost consistently demonstrates optimal performance. This study emphasizes the importance of data preprocessing and the selection of the right algorithms in the development of machine learning-based T2DM detection systems. Accurate detection can reduce the severity of disease, lower treatment costs, speed up the healing process, and improve healthcare services.
Pelatihan Blender Untuk Pengembangan Media Pembelajaran Augmented Reality (AR) Bagi Mahasiswa Kurnia, Ulfa Isni; Septasari, Dita; Awaliyani, Ikna
Jurnal Pengabdian Masyarakat Bangsa Vol. 3 No. 7 (2025): September
Publisher : Amirul Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59837/jpmba.v3i7.2882

Abstract

Pelatihan ini bertujuan untuk meningkatkan kompetensi mahasiswa pendidikan dalam mengembangkan media pembelajaran berbasis Augmented Reality (AR) menggunakan perangkat lunak Blender. Dengan pesatnya perkembangan teknologi, AR menjadi solusi inovatif untuk menciptakan pengalaman belajar interaktif dan imersif. Metode pelatihan meliputi workshop, praktik langsung, dan pendampingan dalam pemodelan 3D, animasi, serta integrasi AR dengan aplikasi pendukung seperti Unity atau Spark AR. Peserta diajarkan langkah-langkah pembuatan objek 3D, tekstur, dan interaktivitas sederhana untuk materi pembelajaran. Evaluasi dilakukan melalui hasil projek mahasiswa. Hasil pelatihan menunjukkan peningkatan dalam keterampilan teknis mahasiswa serta kemampuan merancang media AR yang relevan. Pelatihan ini membuka peluang pemanfaatan teknologi AR dalam pembelajaran sekaligus mempersiapkan calon pendidik yang adaptif terhadap era digital.
Digital Landscape and Behavior in Indonesia 2024: A National Survey Analysis of Internet Penetration, Cybersecurity Risks, and User Segmentation Using K-Means Clustering and Logistic Regression Aminudin, Nur; Hidayat, Nurul; Feriyanto, Dwi; Septasari, Dita; Awaliyani, Ikna
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 5 (2025): JUTIF Volume 6, Number 5, Oktober 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.5.5117

Abstract

Digital transformation in Indonesia reveals significant disparities in internet access, digital behavior, and cybersecurity vulnerabilities. This study analyzes the digital landscape using national survey data from 8,720 respondents across 38 provinces. This research employs a quantitative approach, utilizing chi-square tests, logistic regression for risk analysis, and K-Means clustering for user segmentation, supported by Principal Component Analysis (PCA) for dimensionality reduction. The results show a national internet penetration rate of 79.5%, with significant disparities across regions and socio-economic segments. Logistic regression analysis reveals that higher education, greater income, and the use of fixed broadband are negatively correlated with cybersecurity risks. Furthermore, K-Means clustering identifies three distinct user profiles: 'Digital Savvy', 'Pragmatic Users', and the 'Vulnerable Segment', each with unique characteristics regarding digital access and literacy. This research provides a critical empirical basis for understanding digital transformation in a developing nation. The findings underscore the necessity of data-driven, segmented policies to foster digital inclusion and enhance national cybersecurity, offering actionable insights for policymakers and service providers.
Analisis Quality Of Service (QoS) Jaringan Internet Pelanggan Pada ISP Jalurdata.Net Menggunakan Metode Hierarchical Token Bucket (HTB) dan Per Connection Queue (PCQ) AWALIYANI, IKNA; Abdul Aziz, RZ
Jurnal Algoritma Vol 21 No 2 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-2.1792

Abstract

Problems regarding bandwidth continuity on an internet network often occur due to the lack of maximum utilization of Quality of Service. Without bandwidth management, problems will occur on a network. Quality of Service is the right way to allocate bandwidth in a network because it not only limits bandwidth but also maintains even and stable bandwidth quality. In this study, the methods used are the Hierarchical Token Bucket (HTB) and Per Connection Queue (PCQ) methods by calculating parameters such as Throughput, Delay, Jitter, and Packet loss. The benefit of this research is to compare the two bandwidth management methods and find the most effective method to implement in an ISP. The final comparison of QoS values using the HTB and PCQ methods based on the parameter index values is the same, but after comparing based on the actual parameter values, the PCQ (Peer Connection Queue) method shows superior performance with a higher throughput value of 84%, lower jitter at 13.0948%, and lower packet loss at 0.03%. Although HTB has lower delay at 76.758 ms, the PCQ method is more significant in network scenarios, particularly for stability and consistency in data transmission.
A Conceptual Framework for Technology-Enhanced Learning Design: Bridging Pedagogy and Digital Innovation Dita Septasari; Ikna Awaliyani; Nur Aminudin; Septika Ariyanti; Shima Asadi
FINGER : Jurnal Ilmiah Teknologi Pendidikan Vol. 5 No. 1 (2026): Finger : Jurnal Ilmiah Teknologi Pendidikan
Publisher : CV. Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/finger.v5i1.518

Abstract

Background: Learning designs must be grounded in pedagogical principles and make appropriate use of technical advancements in light of the digital transformation of education. Nonetheless, there is still a disconnect in many educational environments between the use of technology and pedagogical requirements.Aims: The research objective is to develop a conceptual framework for Technology-Enhanced Learning Design that bridges pedagogical principles with digital innovation. The research scope included a literature analysis, a review of best practices, and initial validation through education and technology experts.Methods: This research employed a qualitative approach with conceptual analysis and expert validation methods. Data were collected through a systematic literature review (2020–2025) and interviews with education and technology experts. Analysis was conducted using a thematic approach to identify the key dimensions of the technology-based learning design framework.Results: Pedagogical (learner-centered design, active engagement, personalization), technological (interoperability, scalability, AI integration), and implementation (continuous evaluation, institutional context, user readiness) are the three primary dimensions of the conceptual framework that emerged from the research. Compared to earlier studies, this framework has demonstrated the ability to more thoroughly integrate digital innovation with pedagogical concepts.Conclusion: The significance of combining technology and pedagogy in learning design is emphasized by this study. Researchers, educators, and legislators can use the conceptual framework that is produced as a guide for creating digital learning that is more sustainable and successful.
Design and Evaluation of AI-Enhanced Multimedia Learning Systems: Usability, Accessibility, and Engagement in Broadband-Based Online Education Ikna Awaliyani; Dita Septasari; Nur Aminudin; Septika Ariyanti
IJOEM: Indonesian Journal of E-learning and Multimedia Vol. 5 No. 2 (2026): Indonesian Journal of E-learning and Multimedia
Publisher : CV. Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/ijoem.v5i2.573

Abstract

Background: Artificial intelligence (AI) has increasingly been integrated into multimedia learning environments to support personalization, accessibility, and learner engagement in broadband-based online education. However, many existing systems still evaluate these dimensions separately, which limits their overall effectiveness and scalability.Aims: This study aims to design and empirically evaluate an AI-enhanced multimedia learning system using a unified evaluation framework that integrates system performance, usability, accessibility, and learner engagement within broadband-based higher education contexts.Methods: An explanatory sequential mixed-methods design was employed, involving quantitative analysis with 150 students and qualitative exploration with 12 participants. Data were collected through system performance logs, System Usability Scale (SUS) assessments, WCAG 2.1–based accessibility evaluations, and learner engagement metrics.Results: The findings indicate that AI-driven adaptivity improves system responsiveness, achieves high usability, supports digital accessibility, and enhances learner engagement in broadband-based learning environments. The results demonstrate the effectiveness of the system across technical, experiential, and behavioral dimensions.Conclusion: The key contribution of this study lies in proposing and validating an integrated evaluation framework that holistically captures the performance and user experience of AI-enhanced multimedia learning systems, an area that has been underexplored in prior research. These findings provide important theoretical and practical implications for the design of inclusive, adaptive, and user-centered online learning platforms.
Development and Evaluation of a Multi-Algorithm Application for Predicting Breast Cancer Patient Survival Zulkifli; Kraugusteeliana; Sukarni; Ikna Awaliyani; Nur Asini; Fitriana
Journal of Information System and Informatics Vol 8 No 3 (2026): June
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i3.1665

Abstract

This study developed a multi-algorithm machine learning prototype for multiclass breast cancer survival prediction using 1,980 patient records, classifying patients as Living, Died of Disease, or Died of Other Causes. The framework integrated NN, SVM, RF, NB, and KNN algorithms within a decision-support monitoring application, with preprocessing steps including data cleaning, normalization, feature preparation, and dataset partitioning. To prevent target leakage, survival-related variables were excluded from the predictor set. The revised evaluation results indicated that NB and KNN delivered the strongest performance, achieving weighted average F1-scores of 0.93 and 0.92, respectively, while NN and RF showed comparatively lower results. These findings highlight the potential of machine learning for breast cancer survival status monitoring, although the proposed system is designed as a decision-support prototype rather than a clinical diagnostic tool. Therefore, before actual healthcare deployment, more research incorporating explainable AI techniques, external validation, and real-world clinical testing is needed.
Co-Authors Abdul Aziz, RZ Agus Wantoro Andini, Dwi Yana Ayu Ariyanti, Septika Aviv Fitria Yulia Dita Septasari Dwi Feriyanto Fitriana Fitriana Kraugusteeliana Kraugusteeliana Mukaromah, Hafsah Nur Aminudin Nur Asini Nurul Hidayat rizky12 nurwahid Shima Asadi Sukarni Ulfa Isni Kurnia Wahyu Caesarendra Yudha Pratama, Rendy Zulkifli