cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Richki Hardi
Contact Email
lp3m@universitasmulia.ac.id
Phone
+6281227224080
Journal Mail Official
lp3m@universitasmulia.ac.id
Editorial Address
LP3M Universitas Mulia Jl. Letjen Z.A. Maulani No. 9 Kelurahan Damai Bahagia Kecamatan Balikpapan Selatan Kota Balikpapan Provinsi Kalimantan Timur Indonesia
Location
Kota balikpapan,
Kalimantan timur
INDONESIA
METIK JURNAL
Published by Universitas Mulia
ISSN : 24429562     EISSN : 25801503     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Electrical & Electronics Engineering
Media Teknologi Informasi dan Komputer (METIK) Jurnal adalah jurnal teknologi dan informasi nasional berisi artikel-artikel ilmiah yang meliputi bidang-bidang: sistem informasi, informatika, multimedia, jaringan serta penelitian-penelitian lain yang terkait dengan bidang-bidang tersebut. Terbit dua kali dalam setahun bulan Juni dan Desember.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 243 Documents
 21   22   23   24   25 
Analisis Sentimen Pengguna Aplikasi Byond BSI Pada Google Play Store Menggunakan Algoritma SVM Dan Random Forest Firzatullah, Firdaus Naifah; Nuroji, Nuroji
METIK JURNAL (AKREDITASI SINTA 3) Vol. 9 No. 2 (2025): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/6vtc4567

Abstract

The development of digital technology has encouraged banks to provide application-based financial services, one of which is BYOND by BSI, which carries the concept of Islamic banking. However, various technical obstacles such as service disruptions and application errors in using this application have caused dissatisfaction among users. Therefore, sentiment analysis is needed to understand user responses comprehensively. This study aims to classify user sentiment towards the BYOND by BSI application by utilizing the Support Vector Machine (SVM) and Random Forest algorithms. The data used are 35,000 user reviews collected from the Google Play Store through crawling techniques, then automatically labeled using a rule-based method based on rating values. The analysis process was carried out using the SEMMA approach, which includes the stages of text cleaning, word weighting using TF-IDF, and dividing the data into 80% training data and 20% test data. The test results showed that the SVM algorithm had the best performance with an accuracy of 93.16%, while Random Forest obtained an accuracy of 90.33%. The majority of the analyzed reviews showed negative sentiment. These findings are expected to provide input in improving the quality of the BYOND by BSI application service.
Perancangan Sistem Presensi Wajah (SIWAJA) Berbasis Internet of Things dengan Notifikasi Telegram Muhammad Bagas Adi Pangestu; Nuroji, Nuroji
METIK JURNAL (AKREDITASI SINTA 3) Vol. 9 No. 2 (2025): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/88ctdw53

Abstract

Manual student attendance administration is prone to human error, inefficient, and hinders communication between schools and parents. This study aims to develop the Face Presence System (SIWAJA), an innovative solution integrating face recognition technology and the Internet of Things (IoT) to provide live attendance notifications to parents via Telegram. A key technological advantage of this system is the implementation of the YOLOv8 algorithm, which is emphasized for its high precision in face detection. The development method used is the prototype model, which includes stages of requirements identification, design, implementation, and evaluation. The system was built using an Orange Pi 5 Pro, the Python programming language with the OpenCV library, and the YOLOv8 algorithm for face detection. The research results show that the SIWAJA system was successfully developed and functions as expected, where the IoT-based design supports potential scalability for broader implementation. Black Box Testing validated all main functionalities, from presence-taking to notification delivery. The face detection model showed highly reliable performance with a precision (P) value of 0.97, recall (R) of 0.99, and mAP@.5 of 0.99. In conclusion, SIWAJA proves to be an effective and accurate solution for modernizing student attendance management and enhancing real-time parental involvement, offering significant contributions to the application of IoT in education.
Perancangan Sistem Pengenalan Tulisan Tangan pada Jawaban Esai Menggunakan Metode CNN-LSTM Berbasis Android Elsa Apriani; Pratiwi, Nunik
METIK JURNAL (AKREDITASI SINTA 3) Vol. 9 No. 2 (2025): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/wn518489

Abstract

Technological developments drive educational innovation, one of which is a handwriting recognition system to accelerate essay answer assessment. This study designs an Android application that recognizes students' handwriting using the Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) methods. The system was developed using a prototyping approach through the stages of identifying needs, designing interfaces, implementing features, and testing. The evaluation results showed an accuracy of 60.37%, Character Error Rate (CER) of 16.84%, and Word Error Rate (WER) of 78.41%. Although the WER is still high, character accuracy is good enough for the early stages of development and provides a promising basis for future system improvements. Testing using Black Box Testing ensures that all features run according to their functions. This system is expected to make it easier for teachers to correct essay answers more efficiently, quickly, and consistently, as well as support the digitalization of assessment in the educational environment.
Implementasi Sistem Irigasi Berbasis Internet of Things (IoT) Untuk Optimasi Penggunaan Air Pada Pertanian Haj, Shafly Ulya; Adek, Rizal Tjut; Suwanda, Rizki
METIK JURNAL (AKREDITASI SINTA 3) Vol. 9 No. 2 (2025): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/sqe99d72

Abstract

Traditional irrigation systems in Indonesia's agricultural sector still face obstacles in water use efficiency. This research aims to develop an Internet of things (IoT)-based automatic irrigation system capable of monitoring and controlling soil moisture and water level in real-time. The system is designed using an ESP32 microcontroller, two soil moisture sensors, and one ultrasonic sensor integrated with a servo motor actuator. Rule-based control logic is applied, where the sluice gates open when the moisture is < 50% and the water level is > 25 cm, and close again when the opposite condition occurs. The prototype was tested on two simulated paddy fields with glass aquarium media for three days and five recording cycles. Data was sent to the server and displayed via a web interface for remote monitoring and control. The test results show that the system is able to work responsively, with an average response time of 1.8 seconds, and can increase water use efficiency by 30%. The graph visualisation and manual-automatic control features provide ease of system management. The application of this system shows great potential in supporting the implementation of efficient, scalable, and sustainable precision agriculture.
Klasifikasi Ukuran Baju Berdasarkan Pengukuran Tubuh Menggunakan MediaPipe dan Support Vector Machine Nurul Laily, Tasya; Pratiwi, Nunik
METIK JURNAL (AKREDITASI SINTA 3) Vol. 9 No. 2 (2025): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/tqvapv07

Abstract

Inaccurate clothing size selection is a common issue in online shopping, as many consumers do not know their exact body measurements. This study developed an automatic clothing size recommendation system based on image processing using MediaPipe to detect body keypoints from user images. Body parameters such as height, shoulder width, and chest circumference were calculated using the Euclidean Distance method and converted into centimeters through height-based calibration. These values were then used as input for clothing size classification using the Support Vector Machine (SVM) algorithm with a Radial Basis Function (RBF) kernel. The system was built with a MATLAB-based interface. A total of 231 body image data were used as the dataset. The classification testing results showed an accuracy of 91%, with high precision, recall, and F1-score values. Based on the evaluation, the system’s Mean Absolute Error (MAE) was 1.66 cm for body height, 1.08 cm for shoulder width, and 2.99 cm for chest circumference. The system proved to be sufficiently accurate and can assist users in automatically and efficiently determining their clothing size.
Analisis Preferensi Genre Film dengan Collaborative Filtering Berbasis Gemini AI Dwi Fadlullah, Ardiningrum Ikram; Rizal, Erian
METIK JURNAL (AKREDITASI SINTA 3) Vol. 9 No. 2 (2025): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/9h881e08

Abstract

This study aims to analyze user preferences for Action, Horror, and Romance film genres in video streaming services by implementing a Gemini AI-based Collaborative Filtering algorithm. Data were obtained from 1,017 respondents through an online survey using a 1–5 Likert scale. The research stages include data cleansing, calculating genre similarity using cosine similarity, and implementing an item-based Collaborative Filtering algorithm. Furthermore, Gemini AI embedding was applied, which is the process of transforming each genre into a high-dimensional numerical vector representation to more accurately capture semantic relationships between genres. The results show that Action is the most preferred genre, while the highest similarity score between genres was found between Horror and Romance. The developed recommendation system successfully mapped genre similarities and provided relevant viewing suggestions based on other users’ preferences. The system achieved an effectiveness rate of 62.38%. These findings can serve as a foundation for developing more adaptive and personalized recommendation systems in the future.
Pengembangan Game 3D Menggunakan Batik Sido Mukti dalam Sentai’s Martial Mayhem Rahayu, Anida Sri; Pratiwi, Nunik
METIK JURNAL (AKREDITASI SINTA 3) Vol. 9 No. 2 (2025): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/zz98x012

Abstract

The main visual component of this project is the Sido Mukti batik motif, which will be used to design characters in Sentai's Martial Mayhem video game. This motif was chosen for its deep philosophical meaning and its ability to preserve regional culture through digital media. Research and Development (R&D) was the process employed, encompassing problem identification, data collection, graphic design, character implementation into a Unity-based game, and testing using black-box and System Usability Scale (SUS) approaches. Based on the test results, 14 out of 15 scenarios ran as planned, with an accuracy rate of 93.75%. The average SUS score was 68.25, or ‘sufficiently adequate,’ given by 20 respondents. Both technically and visually, the batik-themed Gold Ranger character was successfully integrated into the game. Based on these results, the addition of regional cultural elements to digital games enhances their visual appeal and serves as a useful educational tool for cultural preservation. As a result, this study significantly promotes the development of games that emphasise regional cultural values.  
Desain Protokol Keamanan Data Berbasis Blockchain pada Pengolahan Data Pengguna Aplikasi E-commerce Firdani, Ella; Hanif, Isa Faqihuddin
METIK JURNAL (AKREDITASI SINTA 3) Vol. 9 No. 2 (2025): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/whag4337

Abstract

This study aims to design the user interface (UI) and user experience (UX) of the Golkar Party National Witness Agency (BSNPG) website as a strategic medium in supporting public information disclosure and increasing public understanding of the institutional functions of BSNPG in the context of elections. To achieve this objective, a Design Thinking approach consisting of five stages was used: Empathize, Define, Ideate, Prototype, and Test. User needs were identified through interviews and surveys involving BSNPG members and the general public as potential users. Based on these results, a website prototype was designed and its usability was tested using the System Usability Scale (SUS) method. The evaluation was conducted by distributing questionnaires to 30 respondents, and the results showed an average score of 71.33%. This score falls into the good and acceptable category, indicating that the prototype successfully meets the aspects of comfort, ease of use, and functional effectiveness from the users' perspective. These findings indicate that the BSNPG website design not only enhances public access to information but also strengthens the institutional image of BSNPG as a professional, transparent, and inclusive organization supporting democratic processes. This study also underscores the importance of adopting a user-centered approach in the development of digital systems for political organizations.
Analisis Sentimen Menggunakan Metode IndoBERT Pada Ulasan Aplikasi Zoom Menggunakan Fitur Ekstrasi GloVe Andhika, Firza Rafiandi; Witanti, Wina; Nurul Sabrina, Puspita
METIK JURNAL (AKREDITASI SINTA 3) Vol. 9 No. 2 (2025): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/g38fxb78

Abstract

This research aims to conduct a sentiment analysis on Zoom application reviews by testing whether combining features from IndoBERT and GloVe can improve classification accuracy. The methodology begins with the collection of 5000 reviews from the Google Play Store, which then undergo a pre-processing stage. To address class imbalance, the Random Oversampling technique was applied. Features are extracted using IndoBERT for contextual meaning and GloVe for global semantic meaning, and their vectors are then combined through concatenation. The balanced dataset is divided into 80% training data and 20% testing data to train and evaluate the model. The test results show that the combined model achieved an overall accuracy of 91%, with a high precision value for the positive class (0.97) and a high recall value for the neutral class (0.95). For comparison, a model using only IndoBERT achieved 90% accuracy. Based on these results, it can be concluded that the combination of IndoBERT and GloVe is an effective and reliable approach for sentiment analysis, with its advantage lying in a richer feature representation due to the integration of global and contextual semantic information.
Evaluasi dan Perancangan Ulang UI/UX Aplikasi GoDentist Menggunakan Metode Double Diamond Susilowati, Merliana Tri; Umbara, Fajri Rakhmat; Ilyas, Ridwan
METIK JURNAL (AKREDITASI SINTA 3) Vol. 9 No. 2 (2025): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/vxk3f002

Abstract

GoDentist is a teledentistry application that supports dental healthcare services. Based on initial observations and evaluations using the User Experience Questionnaire (UEQ), issues were identified in the aspects of perspicuity, dependability, and novelty, such as monotonous design, confusing navigation, and features that did not meet user expectations. This study aims to evaluate and redesign the user interface (UI/UX) of the GoDentist application using the Double Diamond method, which consists of four stages: Discover, Define, Develop, and Deliver, integrated with UEQ and A/B Testing. The evaluation involved 100 respondents aged 15–58 years, the majority of whom were 18–35 years old with adequate digital literacy. Initial results showed low scores in perspicuity, dependability, and novelty. After redesign and prototyping, novelty increased from 0.49 to 1.62, perspicuity from 0.57 to 1.75, and dependability from 0.76 to 1.91. A/B Testing revealed that 59.08% of respondents preferred the new design. These findings indicate that integrating the Double Diamond method with UEQ and A/B Testing can significantly enhance user experience perceptions in terms of both aesthetics and functionality.

Page 24 of 25 | Total Record : 243

 21   22   23   24   25 

Filter by Year

2017 2025


Reset
Filter By Issues
All Issue Vol. 9 No. 2 (2025): METIK Jurnal Vol. 9 No. 1 (2025): METIK Jurnal Vol 8 No 2 (2024): METIK Jurnal Vol. 8 No. 2 (2024): METIK Jurnal Vol 8 No 1 (2024): METIK Jurnal Vol. 8 No. 1 (2024): METIK Jurnal Vol. 7 No. 2 (2023): METIK Jurnal Vol 7 No 2 (2023): METIK Jurnal Vol 7 No 1 (2023): METIK Jurnal Vol. 6 No. 2 (2022): METIK Jurnal Vol 6 No 2 (2022): METIK Jurnal Vol 6 No 1 (2022): METIK Jurnal Vol 5 No 2 (2021): METIK Jurnal Vol 5 No 1 (2021): METIK Jurnal Vol 4 No 2 (2020): METIK Jurnal Vol 4 No 1 (2020): METIK Jurnal Vol 3 No 2 (2019): METIK Jurnal Vol 3 No 1 (2019): JURNAL METIK Vol 3 No 1 (2019): METIK Jurnal Vol 2 No 2 (2018): METIK Jurnal Vol 2 No 1 (2018): METIK Jurnal Vol 1 No 2 (2017): METIK Jurnal Vol 1 No 1 (2017): METIK Jurnal More Issue