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Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi)
Published by Lembaga Komunitas Informasi Teknologi Aceh
ISSN : -     EISSN : 25801643     DOI : https://doi.org/10.35870/jtik
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi), e-ISSN: 2580-1643 is a free and open-access journal published by the Research Division, KITA Institute, Indonesia. JTIK Journal provides media to publish scientific articles from scholars and experts around the world related to Hardware Products, Software Products, IT Security, Mobile, Storage, Networking, and Review An application service. All published article URLs will have a digital object identifier (DOI).
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 1,017 Documents
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Containerized Runtime Berbasis Docker untuk Lingkungan Praktikum Pemrograman yang Seragam dan Terisolasi Bima Cakra Bara Karebet; Angger Binuko Paksi; Tri Septianto
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 11 No 1 (2026): JANUARY
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v11i1.7467

Abstract

Algorithm and Programming practicum requires a uniform execution environment so that students can run code and participate in practicum activities consistently. Differences in devices, operating systems, and software versions often cause installation problems, inconsistent execution results, and difficulties in preparing practicum requirements. This study implements a Docker-based containerized runtime in a web-based interactive practicum platform using the Rapid Application Development (RAD) method, covering requirements planning, system design, development, implementation, and testing. The platform provides registration, login, practicum material management, a web-based code editor, real-time answer checking, and practicum result reports. Implementation and testing results using black box testing show that all 13 core features, verified through 63 test scenarios covering both the student and lecturer roles, ran according to the defined success criteria (100% suitable). These results indicate that Docker can provide an isolated, stable, and accessible practicum environment without requiring manual software installation on students’ devices, thereby supporting a more structured and consistent programming practicum process.
Pengaruh Literasi Digital terhadap Etika Penggunaan Artificial Intelligence pada Mahasiswa Perguruan Tinggi Yusuf Unggul Budiman; Ahmad Jurnaidi Wahidin; Daz Vholasky Anggraini
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 11 No 1 (2026): JANUARY
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v11i1.7479

Abstract

The development of Artificial Intelligence (AI) in higher education has transformed the way students seek information, complete assignments, and understand academic materials. However, AI use also raises ethical issues, including plagiarism, overreliance on instant answers, and a lack of transparency in acknowledging AI assistance. This study aims to analyze the effect of digital literacy on the ethical use of AI among university students. A quantitative survey method was employed. Data were collected using a 1–5 Likert-scale questionnaire from 125 respondents, with 119 complete responses analyzed. Digital literacy was measured using 12 items, while ethical AI use was measured using 12 items. Data were analyzed using descriptive statistics, validity testing, reliability testing, correlation, and simple linear regression. The results show that digital literacy has a positive and significant effect on ethical AI use. The correlation coefficient of 0.638 indicates a strong relationship, while the coefficient of determination of 0.406 indicates that digital literacy explains 40.6% of the variation in ethical AI use. The regression equation is Y = 1.196 + 0.706X. These findings indicate that students with higher digital literacy tend to use AI more ethically, responsibly, and transparently. This study recommends strengthening digital literacy programs with an emphasis on AI ethics in higher education.
Narsisme yang Berkuasa dalam Representasi Relasi Kuasa Pada Film “The Housemaid” (2025) Tafannya Syawaluna Faradibah; Farikha Rachmawati
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 11 No 1 (2026): JANUARY
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v11i1.7515

Abstract

This study analyzes how Narcissistic Personality Disorder (NPD) power relations are represented through the character Andrew in the film “The Housemaid” (2025). Employing a qualitative approach based on John Fiske’s semiotic analysis, the research examines 23 scenes across three levels, reality, representation, and ideology, focusing on Andrew's marital relationship with Nina and his employer-domestic worker dynamics with Millie. The findings reveal that at the reality level, Andrew's NPD power relations manifest through repetitive patterns of love bombing, gaslighting, verbal manipulation, and arbitrary punishment. At the representation level, his dominance is constructed through cinematographic techniques, specifically low-angle shots of Andrew and high-angle shots of Nina and Millie. Ideologically, the film reproduces and deconstructs patriarchy, social class, and gender-based violence, which are ultimately challenged by the women's resistance. In conclusion, the film systematically exposes normalized psychological abuse, highlighting the crucial role of media literacy.
Analisis Perbandingan Algoritma Naïve Bayes dan Support Vector Machine dalam Klasifikasi Opini dan Fakta pada Berita Banjir Sumatera Dessy Natalia Reba; Lilis Indrayani; Christian Dwi Suhendra
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 11 No 1 (2026): JANUARY
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v11i1.7526

Abstract

The rapid growth of online media has accelerated the dissemination of information related to flood disasters, creating the need for an automatic method to classify news into factual and opinion categories. This study aims to compare the performance of the Naïve Bayes and Support Vector Machine (SVM) algorithms in classifying factual and opinion-based news on flood events in Sumatra using Term Frequency–Inverse Document Frequency (TF-IDF) weighting. The research employed several text preprocessing stages, including cleaning, case folding, tokenization, stopword removal, and stemming, followed by TF-IDF weighting, classification, and model evaluation using accuracy, precision, recall, and F1-score. The experimental results showed that the Naïve Bayes algorithm achieved an accuracy of 92.34%, outperforming the Support Vector Machine algorithm, which achieved an accuracy of 91.88%. In addition, Naïve Bayes obtained higher precision, recall, and F1-score values for the opinion class. These findings indicate that Naïve Bayes is more effective than Support Vector Machine in classifying factual and opinion-based news related to flood events in Sumatra.
Peran Konten Aplikasi Sedekah Sampah pada Partisipasi Karyawan PT Indocement Tunggal Prakarsa Tbk Nabila Cikawati; Amiruddin Saleh; Fajar Fathoni
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 11 No 1 (2026): JANUARY
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v11i1.7542

Abstract

This driven by the low participation of employees in the environmental CSR program at PT Indocement Tunggal Prakarsa Tbk through the sedekah sampah application. The core problem centers on digital communication content management strategies that overlook cross-generational demographic gaps as a determining variable for user angagement. This research utilizes a descriptive qualitative approach analyzed through the lens of the Fogg Behavior Model formula (B=M A P). The results indicate that visual content successfully triggers the motivation of active employees through the concept of alms. However, the ability chain of senior employees is disrupted due to text-heavy external promotional content formats and a lack of prompt types that facilitate action. In conclusion, corporate environmental communication management must be transformed from a one-way pattern into tactical audio-visual materials, and sustainable content production.
Prediksi Hasil Tanaman Padi Menggunakan Random Forest dengan Seleksi Fitur Berbasis Feature Importance dan Optimasi Hyperparameter GridSearchCV Steven Andrian Pranata Wicaksono; Mutaqin Akbar
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 11 No 1 (2026): JANUARY
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v11i1.7567

Abstract

Rice production in Indonesia fluctuates due to agronomic, spatial, and climatic factors. This study develops a rice production validation model using Random Forest Regressor with feature importance-based feature selection and GridSearchCV hyperparameter optimization. Agricultural data from BPS for 2018-2024 were combined with annual NASA POWER weather data from 37 provinces in Indonesia. The model predicts rice productivity and converts the prediction into production using actual harvested area. Feature selection reduced 32 initial predictors to 16 final features. The optimized model achieved production R² of 99.79%, adjusted R² of 99.73%, RMSE of 115,600.28 tons, MAE of 61,194.75 tons, MAPE of 6.95%, and SMAPE of 6.86%. It is important to note that the high production R² of 99.79% is substantially driven by the mathematical dominance of actual harvested area as a multiplier in the production conversion formula, rather than solely reflecting the predictive power of the climate model. The core predictive performance of the model at the productivity level (R² = 75.45%, MAPE = 6.95%) more accurately represents the model’s generalization capability. Research limitations include limited historical data for newly established provinces in Papua and the relatively short study period of 2018-2024. These results indicate that the proposed method provides accurate validation for rice production analysis.
Analisis Pengaruh Durasi Live Selling Produk Fashion terhadap Total Penjualan Menggunakan Decision Tree Nely Ayu Verda; Heru Saputro; Joko Minardi
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 11 No 1 (2026): JANUARY
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v11i1.7629

Abstract

The growth of live selling on e-commerce platforms has encouraged sellers to understand the factors influencing sales performance. However, many sellers are still unaware of which variables most significantly affect total sales during live sessions. This study aims to develop a web-based visualization system called RekomLive to analyze the influence of broadcast duration, number of viewers, and interactions on total fashion product sales using the Decision Tree algorithm. The dataset consists of 122 data collected through direct observation of live selling sessions on the Shopee platform. Numerical data were transformed using the Equal Width Binning method into three categories, namely low, medium, and high, then split at a 70:30 ratio into 85 training data and 37 testing data. The results show that the viewers variable is the most influential factor, with the highest information gain value of 0.1288 and a contribution of 84.3%, followed by interaction at 15.7%, while duration does not have a significant influence. The model achieved an accuracy of 89.19%, precision of 91.67%, and recall of 97.06%. The RekomLive system successfully presents the analysis results visually and recommends a minimum broadcast duration of 240 minutes to maximize high sales opportunities. These findings can be used as an evaluation basis for sellers in developing live selling strategies for fashion products.
Autentikasi Pilot Berbasis Pengenalan Wajah Menggunakan Convolutional Neural Network Kustom dengan Deployment TFLite Wirpan Atmaja Putra; Heri Setiawan; Yohanes Dwi Cahyono
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 11 No 1 (2026): JANUARY
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v11i1.7689

Abstract

Most commercial UAV platforms still lack a mandatory pre-flight identity check, leaving ground control stations exposed to impersonation and unauthorized takeover. This paper proposes a facial recognition-based pilot authentication system using a custom four-block Convolutional Neural Network (CNN) to classify three identity classes: Pilot 1, Pilot 2, and Stranger. Trained on 2,125 facial images with data augmentation, Batch Normalization, MaxPooling, and Dropout regularization, the model achieves a test accuracy of 99.07% with a loss of 0.0613. The model is further converted into TensorFlow Lite (TFLite) format for efficient deployment on resource-constrained embedded devices, offering a computationally light alternative to conventional authentication methods as an embedded pre-flight security checkpoint for UAV ground control stations.
Directional Robustness Asymmetry in Indonesian Sarcasm Detection: A Cross-Platform Evaluation of IndoRoBERTa on X and Reddit Marcellinus Brendan Hananta; Wiwin Sulistyo
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 11 No 1 (2026): JANUARY
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v11i1.7711

Abstract

Sarcasm can reverse sentence polarity, making it one of the hardest problems in natural language processing and a persistent obstacle to reliable sentiment analysis on social media, where models are often deployed on platforms they were not trained on. Research on Indonesian sarcasm has largely stayed within a single domain or tested transfer in only one direction, leaving the cross-domain robustness of the IndoRoBERTa family on the IdSarcasm benchmark unclear. This study measures and compares the cross-domain robustness of IndoRoBERTa-small and IndoRoBERTa-base, with IndoBERT as a baseline, across X (Twitter) and Reddit, using the F1 gap (ΔF1) after cleaning anonymization artifacts, adding a data-size control, and running Stratified 5-Fold cross-validation. The results reveal a one-sided asymmetry: X → Reddit transfer is far more fragile (ΔF1 0.345–0.400) than Reddit → X (0.135–0.240), failing by missing sarcasm (false negatives) rather than over-flagging it (false positives). Practically, training on the context-rich domain (Reddit) and choosing IndoRoBERTa-base give the most reliable cross-platform sarcasm detection, with direction-specific mitigation recommended for robust deployment.
Rancang Bangun Sistem Irigasi Otomatis Berbasis Jaringan Sensor Nirkabel dan Monitoring Web Laravel Ilham Padia; Risan Fathan; Muhammad Irzi Suryanto Putra; Muhammad Nizar; Ade Rukmana; Sipa Nurpadillah; Andika Muhammad Nur Kholiq
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 11 No 1 (2026): JANUARY
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v11i1.7838

Abstract

Conventional irrigation often triggers water waste or crop failure due to inaccurate manual scheduling. This study aims to design, implement, and evaluate a web-based smart irrigation system prototype to optimize water management using Wireless Sensor Networks (WSN). The methodology utilizes a star topology with two YL-69 sensor nodes transmitting data via the ESP-NOW communication protocol directly to an ESP32 Gateway integrated with a Laravel website. The calibration procedure was strictly conducted through 30 independent reading repetitions for each soil variant sample. Experimental results show high accuracy with a Mean Absolute Percentage Error (MAPE) of 1.58% and a minimum error of 0.04% in extreme water-saturated conditions. The hardware system successfully controls a 12V solenoid valve based on an inverted active-low threshold control algorithm of < 40%. The Laravel platform achieves real-time telemetry synchronization without data lag, supported by network performance with a Packet Delivery Ratio (PDR) above 99% and stable latency between 242–252 ms. In conclusion, this system provides an efficient, fail-safe, and automated remote monitoring solution to support precision farming.

Page 101 of 102 | Total Record : 1017

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