cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
DARSONO NABABAN
Contact Email
darsono.nababan@unimor.ac.id
Phone
+628116186822
Journal Mail Official
jitu.unimor@gmail.com
Editorial Address
Department of Information and Technology, Universitas Timor Sasi, Kefamenanu City, North Timor Tengah Regency, East Nusa Tenggara
Location
Kab. timor tengah utara,
Nusa tenggara timur
INDONESIA
Journal Of Information And Technology Unimor (JITU)
Published by Universitas Timor
ISSN : 27752775     EISSN : 27752775     DOI : https://doi.org/10.32938/jitu.v1i1
Core Subject : Science,
Computer Science & IT
Journal of information and Technology Unimor ( JITU) provides a forum for publishing the original research articles from contributors related to Big Data Research, Web Science, network and infrastructure, and computing algorithms. The scope of JITU starting from Volume 1 (2021) is as follows: Embedded system based on microcomputer/microcontroller; Robotics; Control systems; Cloud computing; Sensor network and IoT; Computer networks and security; Algorithms and artificial intelligence; Computer vision and pattern recognition, and Mobile computing. E-Business/E-commerce E-Government E-learning Human-Computer Interaction Information Assurance & Intelligent Information Security & Risk Management IS/IT Operations Management IS/IT Strategic Planning IT Governance IT Project Management Web Science Social Media in Business Multimedia Application Big Data Research New Technology Acceptance and Diffusion Green Information Systems Innovation Management/Technopreneurship
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 61 Documents
 3   4   5   6   7 
Analisa Sistem Manajemen Keamanan Informasi (SMKI) Organisasi Menggunakan Indeks KAMI Sidabutar, Jeckson
Journal of Information and Technology Vol. 4 No. 2 (2024): Journal of Information and Technology Unimor (JITU)
Publisher : Department of Information Technology, Universitas Timor, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32938/jitu.v4i2.7747

Abstract

Jumlah data yang tinggi dan tingkat keamanan yang rendah akan membahayakan proses bisnis dari suatu organisasi. Peran penting pemimpin organisasi dibenarkan dalam mengelola situasi dengan sikap baru yang diusulkan. Pemimpin organisasi memiliki tangung jawab dan komitmen atas kebijakan Sistem Manajemen Keamanan Informasi (SMKI), serta memberikan pengetahuan kepada karyawan tentang “disiplin” SMKI. Dengan disiplin SMKI yang baik membuat organisasi dapat secara sistematis melindungi dirinya dari bahaya dan potensi kerugian akibat penyalahgunaaan komputer dan kejahatan dunia maya. Penelitian ini memberikan cara yang komprehensif dengan menerapkan Analisa Gap SMKI menggunakan Indeks KAMI. Indeks KAMI merupakan alat evaluasi untuk menganalisa tingkat kesiapan SMKI disuatu organisasi dengan menggunakan standar ISO/IEC 27001:2022 dan COBIT. Dari penelitian ini diketahui Identitas Responden pada Nilai 41 yaitu Strategis. Hasil Analisa yang diperoleh berdasarkan evaluasi Indeks KAMI yaitu kesenjangan rentang kelengkapan pengamanan Gap Faktual (Memenuhi Kerangka Kerja Dasar) dengan Gap Kesesuaian (Cukup Baik) dengan rentang 1 Tingkat. Sedangkan kesenjangan Gap Faktual (Memenuhi Kerangka Kerja Dasar) dengan Gap Ideal (Baik) dengan rentang 2 Tingkat. Hasil ini memberikan gambaran kesiapan SMKI kepada pimpinan organisasi dalam meningkatkan kesadaran mengenai kebutuhan keamanan informasi dan sikap baru dalam “disiplin” SMKI kepada organisasi.
The Expert System for Determining Manual Brew Coffee Techniques and Coffee Beans Using the Forward Chaining Method Fajarlestari, Maria Karmelia; Dwi Yulianto, Bagas
Journal of Information and Technology Vol. 4 No. 2 (2024): Journal of Information and Technology Unimor (JITU)
Publisher : Department of Information Technology, Universitas Timor, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32938/jitu.v4i2.7761

Abstract

An expert system for determining coffee types and brewing techniques was developed using the forward chaining method. All related data, including coffee types, brewing techniques, and coffee flavors and characteristics, were collected. From this data, rules were created for the decision-making process. The decisions made in these rules are derived from expert knowledge. The expert in this research is a barista who works as a coffee maker. The decision-making process is expressed in the form of IF(condition)-ELSE(action). The condition represents the initial facts, consisting of data used in the decision-making process, namely coffee flavors and characteristics. The action represents the conclusion, which is the result: the brewing technique to be used based on the coffee's characteristics and the recommended coffee types based on the coffee flavors. Therefore, this expert system will recommend brewing techniques and coffee types according to the desired coffee flavors and characteristics.
Pengembangan Platform Web Pengelolaan Informasi Pemasaran Rumah Bersubsidi Di Perumahan Biinmaffo Residence Menggunakan Metode Pendekatan RAD Gelu, Leonard Peter
Journal of Information and Technology Vol. 4 No. 2 (2024): Journal of Information and Technology Unimor (JITU)
Publisher : Department of Information Technology, Universitas Timor, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32938/jitu.v4i2.7778

Abstract

Abstract - The advancement of information technology has had a significant impact on entrepreneurs, including those in the housing sector, by facilitating business monitoring and marketing. Information technology overcomes the constraints of distance and time, allowing customers to access information via websites without needing to visit offices directly, thus saving time and enhancing efficiency. Housing, as a basic human need, plays a crucial role in improving dignity and status, as well as serving strategic functions such as educational centers, cultural adaptation, and the development of future generations. Cities, as densely populated and heterogeneous centers, face challenges related to increasing housing needs due to population growth. In Indonesia, the annual housing demand reaches 2.6 million units, driven by a population growth rate of 1.3% per year. PT. Risky Putra Griya Permai, a subsidized housing developer, faces challenges in manual data processing, such as checking stock, area, and house types, affecting report generation. Efforts to transition to a computerized archiving system are expected to improve efficiency and accuracy in housing data management.
Implementasi Deep Learning Berbasis Convolutional Neural Network untuk Klasifikasi Motif Tenun Timor Baso, Budiman; Muhammad Akhyar, Ramaulvi
Journal of Information and Technology Vol. 4 No. 1 (2024): Journal of Information and Technology Unimor (JITU)
Publisher : Department of Information Technology, Universitas Timor, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32938/jitu.v4i1.7971

Abstract

This research develops a classification model for Timorese weaving motifs, including Buna, Kaimafafa, Kemak, and Nunkolo motifs, using Deep Learning method based on Convolutional Neural Network (CNN). Timor's diverse weaving motifs reflect the richness of the local culture, but manual classification is often time-consuming. To overcome this challenge, we applied CNN with transfer learning techniques to a dataset of pre-processed Timorese weaving images. Based on the experimental results, the developed model achieved an accuracy of 95.00% on the test data with the use of 20 epochs, demonstrating the effectiveness of CNN in classifying weaving motifs automatically and efficiently. This research has the potential to support cultural preservation and the development of the weaving industry through technology-based practical applications that are optimal in terms of performance and computational efficiency.
Application of Simple Additive Weighting Method in Choosing the Best-Selling CCTV Based on Website Sitohang, Hotmian; Damaini, Amaya Andri
Journal of Information and Technology Vol. 4 No. 2 (2024): Journal of Information and Technology Unimor (JITU)
Publisher : Department of Information Technology, Universitas Timor, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32938/jitu.v4i2.8019

Abstract

As crime increases, such as theft, murder, and accidents make it difficult for people to find out who the perpetrators are. With the development of technology, the above problems are easily revealed if the scene is equipped with Closed Circuit Television (CCTV). However, currently there are many types of CCTV models sold on the market, making people confused about choosing which one is good. Likewise, sellers have difficulty in stocking CCTV. This problem requires an application and SAW method to select the best-selling CCTV. The application is built web-based using visual studio code software and the Xampp database. Where later this algorithm can add up the weighted performance ratings on each alternative with ranking. All attributes can be completed simply, so that the best-selling product is obtained. From the results of the study, the best-selling CCTVs were the hikvision, yosse with, and V380 brands.
Perancangan Sistem Pintu Otomatis Berbasis Arduino Menggunakan Bluetooth Di Cv.Aabc Software Karawang Kurnia, Okto; Rahmadiani, Ulfa Siti
Journal of Information and Technology Vol. 4 No. 2 (2024): Journal of Information and Technology Unimor (JITU)
Publisher : Department of Information Technology, Universitas Timor, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32938/jitu.v4i2.8985

Abstract

Technological advances require humans to further increase effectiveness and efficiency in various things. Therefore, humans are expected to be able to carry out activities efficiently in a relatively short time. The door is a medium used as a way to enter or exit. So an automatic door system design is needed so that it can be controlled remotely. The purpose of this study is to create a prototype of an Arduino-based automatic door. This automatic door is designed using the HC-05 Bluetooth Module, Arduino Uno microcontroller, LCD, I2C, LED and Servo motor. And also using the Waterfall method, the microcontroller receives input from the HC-05 Bluetooth, then the microcontroller provides output to the I2C and LCD by entering the Password on the Boarduino Application via an Android Smartphone. Furthermore, the output from the LCD and LED goes to the Servo motor which functions to open and close the door if the Password is correct. And also using the prototype method and the results of this automatic door prototype can provide convenience for opening and closing the door so that it can save time and energy.
Analisis Pengaruh Data Augmentasi Pada Klasifikasi Tenun Menggunakan Deep Learning Berbasis Convolutional Neural Network: Analisis Pengaruh Data Augmentasi Pada Klasifikasi Tenun Menggunakan Deep Learning Berbasis Convolutional Neural Network Baso, Budiman; Risald, Risald; Muhammad Akhyar, Ramaulvi
Journal of Information and Technology Vol. 5 No. 1 (2025): Journal of Information and Technology Unimor (JITU)
Publisher : Department of Information Technology, Universitas Timor, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32938/jitu.v5i1.9209

Abstract

This research develops a classification model of Timorese weaving motifs using Deep Learning method based on Convolutional Neural Network (CNN). Timor's diverse weaving motifs reflect the richness of local culture, but manual classification takes a long time and is prone to subjectivity. To improve model performance, Data Augmentation techniques, such as flipping, rotation, and zooming,, are applied to enrich the variety of pre-processed Timor weaving image datasets. In addition, the CNN model was developed using Transfer Learning techniques to improve training efficiency. Experimental results show that CNN without augmentation achieves 95.00% accuracy, 95.00% precision, 95.08% recall, and 95.04% F1-score, with a computation time of 2.37 minutes at 30 epochs. Meanwhile, applying Data Augmentation increased the model accuracy to 96.66%, precision 96.66%, recall 96.87%, and F1-score 96.77%, and reduced the computation time to 2.11 minutes. Analysis of the effect of augmentation data shows that increasing the variety of images contributes to the improvement of model generalization. Therefore, the use of CNN with Data Augmentation is a more optimal solution in the classification of Timorese weaving motifs. This research has the potential to support cultural preservation as well as the development of an artificial intelligence-based weaving motif identification system.
Mapping of Flood-Prone Areas in Malaka Regency Based on WebGIS Using the Simple Additive Weighting (SAW) Method Dety Lestari, Anastasia Kadek; Bria, Adriana Laurensia
Journal of Information and Technology Vol. 5 No. 1 (2025): Journal of Information and Technology Unimor (JITU)
Publisher : Department of Information Technology, Universitas Timor, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32938/jitu.v5i1.10101

Abstract

Malaka Regency in East Nusa Tenggara Province is a flood-prone area, mainly due to high rainfall and the overflow of the Benenain River, the largest watershed in the province. This study aims to map flood-prone areas using the Simple Additive Weighting (SAW) method integrated into a WebGIS-based decision support system. The variables considered include rainfall, land use, slope, topography, and river flow. The analysis resulted in three flood vulnerability classifications: low (Laenmanen, Iokafeu, Botinleobele, Sasitamean), moderate (Kobalima, Kobalima Timur, Malaka Timur, Rinhat), and high (Malaka Tengah, Malaka Barat, Weliman, Wewiku). This system is expected to assist local governments in making timely and accurate decisions for flood disaster management and mitigation
Media Edukasi Pengenalan Kain Tenun Nusa Tenggara Timur Dengan Artificial Intelligence Akhyar, Ramaulvi Muhammad; Baso, Budiman; Haeruddin; Yunita, Elisa
Journal of Information and Technology Vol. 5 No. 1 (2025): Journal of Information and Technology Unimor (JITU)
Publisher : Department of Information Technology, Universitas Timor, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32938/jitu.v5i1.8421

Abstract

Kain tenun Nusa Tenggara Timur (NTT) merupakan warisan budaya Indonesia yang kaya akan nilai artistik, filosofi, dan makna simbolik. Setiap motif pada kain ini mencerminkan identitas budaya daerah yang menjadi bagian integral dari kehidupan masyarakat NTT. Penelitian ini bertujuan untuk mengembangkan media edukasi berbasis kecerdasan buatan (AI) untuk mengenali motif kain tenun khas Nusa Tenggara Timur (NTT) menggunakan model MobileNetV2. Dataset yang digunakan mencakup 180 gambar dari delapan motif kain, yaitu Ayotupas, Boti, Buna, Mengger, Naisa, Pahikung, Pasolla, Rose, dan Rote, yang masing-masing terdiri dari 20 gambar dengan berbagai kondisi pencahayaan dan sudut pandang. Model dilatih dengan pembagian data 80% untuk pelatihan, 10% untuk validasi, dan 10% untuk pengujian. Hasil pengujian menunjukkan bahwa model mencapai akurasi 100% pada motif Naisa dan 80–90% untuk motif lainnya. Meskipun model menunjukkan performa tinggi, faktor eksternal seperti pencahayaan dan perbedaan tipe kamera mempengaruhi klasifikasi. Penelitian ini menunjukkan potensi penggunaan AI dalam media edukasi untuk mengenalkan budaya lokal dan memberikan rekomendasi untuk pengembangan lebih lanjut, termasuk augmentasi gambar dan penambahan dataset
Analisis Pengaruh Pola Penggunaan Gadget Terhadap Computer Vision Syndrome Menggunakan Algoritma Machine Learning Ahmad, Hamna Izzatunnisa; Abdullah, Syahid; Chusyairi, Ahmad
Journal of Information and Technology Vol. 5 No. 1 (2025): Journal of Information and Technology Unimor (JITU)
Publisher : Department of Information Technology, Universitas Timor, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32938/jitu.v5i1.9138

Abstract

This research aims to analyze the impact of gadget usage on eye health using Decision Tree, Random Forest, and Naive Bayes algorithms. The increasing use of gadgets in society potentially causes eye health disorders, specifically Computer Vision Syndrome (CVS) symptoms that require in-depth investigation. Data was collected through a survey questionnaire about gadget usage habits and respondents' eye conditions. The OSEMN method was used to process and analyze data by applying three classification algorithms. Research findings showed the Random Forest algorithm provided the best performance with 73 % accuracy, followed by Naive Bayes at 65 %, and Decision Tree at 64 %. The study provides insights into the impact of gadget usage on eye health and recommendations for maintaining usage balance to prevent health disruptions.

Page 6 of 7 | Total Record : 61

 3   4   5   6   7 

Filter by Year

2021 2025


Reset
Filter By Issues
All Issue Vol. 5 No. 1 (2025): Journal of Information and Technology Unimor (JITU) Vol. 4 No. 2 (2024): Journal of Information and Technology Unimor (JITU) Vol. 4 No. 1 (2024): Journal of Information and Technology Unimor (JITU) Vol. 3 No. 2 (2023): Journal of Information and Technology Unimor (JITU) Vol. 3 No. 1 (2023): Journal of Information and Technology Unimor (JITU) Vol 2 No 2 (2022): Journal of Information and Technology Unimor (JITU) Vol. 2 No. 2 (2022): Journal of Information and Technology Unimor (JITU) Vol 2 No 1 (2022): Journal of Information and Technology Unimor (JITU) Vol 1 No 2 (2021): Journal of Information and Technology Unimor (JITU) Vol 1 No 1 (2021): Journal Of Information And Technology Unimor (JITU)