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JITK (Jurnal Ilmu Pengetahuan dan Komputer)
Published by STMIK Nusa Mandiri
ISSN : -     EISSN : 25274864     DOI : -
Core Subject : Science,
Computer Science & IT
Kegiatan menonton film merupakan salah satu cara sederhana untuk menghibur diri dari rasa gundah gulana ataupun melepas rasa lelah setelah melakukan aktivitas sehari-hari. Akan tetapi, karena berbagai alasan terkadang seseorang tidak ada waktu untuk menonton film di bioskop. Dengan bantuan media internet, berbagai macam aplikasi nonton film android sangat mudah dicari. Hanya bermodalkan smartphone saja para penonton film dapat streaming berbagai macam jenis film di mana saja dan kapan saja mereka inginkan. Akan tetapi, karena banyaknya pilihan aplikasi nonton film android yang bisa digunakan, terkadang seseorang bingung memilihnya. Untuk itu, diperlukan suatu sistem pendukung keputusan yang dapat digunakan para pengguna sebagai alat bantu pengambilan keputusan untuk memilih dengan berbagai macam kriteria yang ada. Salah satu metode yang digunakan adalah metode Analytical Hierarchy Process (AHP). AHP melakukan perankingan dengan melalui penjumlahan antara vector bobot dengan matrik keputusan dengan tujuan agar hasil yang diberikan lebih baik dalam menentukan alternatif yang akan dipilih. Berdasarkan hasil penelitian yang dilakukan oleh 36 sampel responden didapatkan kriteria konten menjadi prioritas pertama pengguna untuk memilih aplikasi nonton film android dengan nilai bobot sebesar 0,224. Sedangkan Netflix menjadi alternatif dengan prioritas pertama keputusan pengguna dalam memilih aplikasi nonton film android dengan nilai bobot sebesar 0,352.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 543 Documents
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ADAPTIVE PATH ROUTING USING THE RYU CONTROLLER TO ENHANCE QUALITY OF SERVICE IN SOFTWARE-DEFINED NETWORKS Ade Davy Wiranata; Intan Murniasih; Soleman Soleman
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 12 No. 1 (2026): JITK Issue August 2026
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v12i1.8493

Abstract

Software-Defined Networking (SDN) separates the forwarding layer from a programmable control layer, enabling traffic management from a single logical control point. However, when the controller forwards along purely topological shortest paths, it cannot exploit the path diversity of multi-rooted data-centre fabrics, so flows are concentrated on a subset of links while equally short alternatives stay idle. This work introduces an Adaptive Path Routing (APR) application for the Ryu controller. At each monitoring tick APR queries the OpenFlow statistics interface and selects end-to-end paths that minimize a normalized composite cost combining residual bandwidth, one-way delay, and loss. APR and the default shortest-path-first (SPF) baseline were implemented on the same controller and evaluated in Mininet on a k=4 fat-tree (20 switches, 16 hosts; links shaped to 10 Mbps and 2 ms) across four workloads, each repeated ten times. Against SPF, APR more than doubles aggregate TCP goodput under light load (9.28 to 18.93 Mbps, +104.1%, p<0.01) by spreading flows across the four core switches through load-aware path placement, while under saturation it matches the baseline and, owing to a 30% hysteresis threshold, never increases jitter or packet loss. These results show that live-metric adaptive path selection yields large throughput gains where path diversity can be exploited and behaves as a safe drop-in replacement for shortest-path forwarding otherwise.
QUANTITATIVE ANALYSIS OF EMOTIONAL PERCEPTION IN 3D INTERIOR ANIMATION USING CINEMATIC LIGHTING AND FUZZY LOGIC Didit Prasetyo; Nugrahardi Ramadhani; Kartika Kusuma Wardani; Nurina Orta Darmawati
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 12 No. 1 (2026): JITK Issue August 2026
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v12i1.8022

Abstract

Cinematic visual aspects such as lighting, color, and camera framing play an important role in shaping emotional and narrative experiences in 3D animation. However, their translation into measurable computational emotional outputs remains limited. This study proposes a computational framework for modeling audience emotional perception in a static 3D animated environment by integrating visual hermeneutics, quantitative analysis, and fuzzy logic inference. A total of 450 animation frames from a single 3D interior setting were analyzed across three narrative phases: beginning, climax, and resolution. Qualitative shot-by-shot analysis was used to interpret the symbolic function of visual elements, while quantitative data were obtained from light intensity and color temperature measurements and an emotional perception questionnaire analyzed using repeated measures ANOVA. The results show significant differences in depression, tension, and hope across narrative phases (p < 0.001), corresponding to systematic changes in lighting, color, and framing. The study formalizes cinematic visual parameters as fuzzy input variables and produces a measurable emotional index through defuzzification, consistent with the ANOVA findings. The novelty of this study lies in integrating visual hermeneutics and fuzzy logic to model emotion in a static 3D environment and validate it statistically. Practically, the model can support animators and multimedia designers in planning emotion-oriented lighting strategies and evaluating visual scenes more systematically.
INTELLIGENT SYSTEM FOR EARLY DETECTION OF DIABETES MELLITUS IN CHILDREN USING SUPPORT VECTOR MACHINE METHOD Tachiyya Nailal Khusna Khusna; Intan Sekar Arumdani; Fadila Amanda; Ahmad Jazuli
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 12 No. 1 (2026): JITK Issue August 2026
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v12i1.8568

Abstract

Once viewed predominantly as a disease of adulthood, diabetes mellitus has become an escalating concern among Indonesian children and adolescents, with type-1 diabetes cases in the under-18 cohort rising approximately seventy-fold between 2010 and 2023. Against this backdrop, this study constructs a web-based clinical intelligent system that harnesses the Support Vector Machine (SVM) algorithm for early risk identification in patients aged 6–18 years. Unlike prior SVM-based diabetes detection studies, which have largely relied on adult benchmark datasets and treated the problem as standard binary classification, this study assembles a pediatric-specific dataset of 500 medical records, comprising 350 clinical records (70%) and 150 re-screened public records (30%), with 10 clinical features. The observed class imbalance (43% positive, 57% negative) is addressed using Synthetic Minority Over-sampling Technique (SMOTE), applied solely within the training partition, while feature thresholds are adjusted to WHO pediatric standards. Data preprocessing includes handling missing values, Min-Max normalization, and label encoding. The SVM model with a Radial Basis Function (RBF) kernel was optimized using Grid Search with 5-fold cross-validation, yielding optimal parameters of C=10 and gamma=0.1. On a held-out test set of 97 records, the model achieved 84.54% accuracy, 81.82% precision, 83.72% recall, and an 82.76% F1 score. The accompanying web application, developed using Python Flask and Bootstrap 5, passed all functional black-box tests. Targeted at frontline healthcare workers in primary care settings rather than lay users, the system provides a practical point-of-care screening instrument for clinicians managing pediatric diabetes risk.

Page 55 of 55 | Total Record : 543

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