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Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi)
Published by Universitas Udayana
ISSN : 22523006     EISSN : 26852411     DOI : https://doi.org/10.24843/JIM
Core Subject : Science,
Computer Science & IT
The journal publishes work from all disciplinary, theoretical and methodological perspectives. It is designed to be read by researchers, scholars, teachers and advanced students in the fields of Information Systems and Information Science, as well as IT developers, consultants, software vendors, and senior IT executives seeking an update on current experience and future prospects in relation to contemporary information and communications technology.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 280 Documents
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Implementation of Telegram Chatbot as Information Service of Madani Hospital Pekanbaru hariansyah, Aldi; Haerani, Elin; Novriyanto, Novriyanto; Affandes, Muhammad
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol 11 No 3 (2023): Vol. 11, No. 3, December 2023
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIM.2023.v11.i03.p05

Abstract

very institution or organization aims to create a positive image through information services. In Indonesia, many hospitals provide information through telephone or official websites. However, Madani Hospital in Pekanbaru requires improvement. This research developed a registration chatbot on Telegram, making it easier for patients to make doctor appointments, view schedules, and access important information. Telegram was chosen for being lightweight, fast, and popular. The research involved literature surveys, problem identification, literature review, and data collection. The results were used to design the chatbot flow. The system was developed using Sommerville's Waterfall method, covering requirement definition, design, implementation, testing, integration, operation, and improvement. User Acceptability Testing is a key stage in implementation. User Acceptability Testing questionnaires were distributed to 20 prospective patients with various questions. The chatbot implementation used the Python API for Telegram and a MySQL database, with Black Box testing covering patient access, registration, functions, admin authentication, create update read delete admin, and error handling. The results of User Acceptability Testing showed an accuracy achievement of 77.8%, which means it is Very Good.
Website Quality Analysis Using WebQual 4.0, Customer Satisfaction Index, and Importance Performance Analysis Adhigamika, Dewa Putu Surya; Pratama, I Putu Agus Eka; Raharja, I Made Sunia
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol 12 No 1 (2024): Vol. 12, No. 1, April 2024
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIM.2024.v12.i01.p02

Abstract

The development of technology is currently growing rapidly in various aspects of human life, including in the field of education such as the creation of academic information systems. The study aims to analyze the quality of service on the SISAKTI-NG website based on user expectations and website performance. Question indicators in making questionnaires refer to three dimensions, namely: usability, information quality and interaction quality in the WebQual 4.0 Method by distributing questionnaires to 100 respondents. Analysis of website quality using the Customer Satisfaction Index Method to analyze satisfaction with SISAKTI-NG services and the Importance Performance Analysis Method to analyze the quality of SISAKTI-NG services and obtain indicators that require improvement and are maintained based on the perceptions and expectations of website users. The results show that the satisfaction of SISAKTI-NG website users is "SATISFIED" with a percentage of 73.88%. The results of IPA analysis there are 2 priority improvement question items and 10 question items that need to be maintained by the SISAKTI-NG website manager. Recommendations are given to USDI UNUD based on indicators that require improvement to improve service quality which is still low.
Digitalization of Web-Based Notary and PPAT Office Service Management Pratama, I Putu Agus Eka; Putri, Gusti Agung Ayu; Wati, Ni Luh Made Adi Dharma
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol 11 No 3 (2023): Vol. 11, No. 3, December 2023
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIM.2023.v11.i03.p01

Abstract

Notaris dan Pejabat Pembuat Akta Tanah (PPAT) merupakan sebuah lembaga yang disebutkan dalam Kitab Undang-Undang Hukum Perdata memiliki kewenangan berkaitan dengan pembuatan akta autentik. Seperti halnya dengan lembaga lain, Notaris dan PPAT membutuhkan sistem informasi untuk membantu meningkatkan efektivitas dan efisiensi pelayanan jasa lembaga tersebut. Oleh karena itu, penelitian ini dibuat dengan tujuan menghasilkan sistem informasi yang dapat membantu proses manajemen, melakukan pemantauan, dan pelaporan terhadap pelayanan jasa yang dilakukan oleh Notaris dan PPAT. Penelitian ini dilakukan dengan memanfaatkan metode Waterfall sebagai metode pengembangan yang menghasilkan 7 modul diantaranya Modul Manajemen Data Pegawai, Modul Manajemen Data Client, Modul Manajemen Autentikasi, Modul Manajemen Pelayanan Notaris, Modul Manajemen Pelayanan Notaris, dan Modul Pelaporan serta telah diuji dengan menggunakan Metode Pengujian Blackbox dan Post-Study System Usability Questionnaire (PSSUQ) yang menunjukan bahwa sistem ini dapat berjalan baik dan tepat guna dengan skor keseluruhan (Overall) pengujian 1.27.
Comparison Of Decision Tree, Linear Regression, and Random Forest Regressor Models for Predicting House Prices Sutramiani, Ni Putu
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol 12 No 1 (2024): Vol. 12, No. 1, April 2024
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIM.2024.v12.i01.p06

Abstract

A home is a basic requirement that offers comfort and security to its occupants. Because they are subject to price fluctuations, houses are also a potential option in an investing setting. As a result, buyers and investors require a system that can forecast house values. This study compares the effectiveness of decision trees, linear regression, and random forest regressors as models for predicting home prices. The dataset for predicting home prices was used in this study to conduct data exploration, pre-processing, modeling, and model comparison stages. The study's findings demonstrate that the random forest regressor offers the best prediction performance with lower assessment metrics, including MAE, MSE, RMSE, and R2 Score, making it the best option for predicting house prices and other financial outcomes.
Strawberry Disease Detection Based on YOLOv8 and K-Fold Cross-Validation Pranata, I Made Dicky; Darma, I Wayan Agus Surya; Sandhiyasa, I Made Subrata; Wiguna, I Komang Arya Ganda
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol 11 No 3 (2023): Vol. 11, No. 3, December 2023
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIM.2023.v11.i03.p06

Abstract

Strawberry plant diseases can be detected by the condition of the strawberry leaves, flowers, and fruit, but farmers still need knowledge to identify the type of strawberry disease. This study aims to develop a detection model using YOLOv8. The detection model was trained using a dataset containing 3,243 images of strawberry plant leaves, fruit, and flowers, divided into seven disease classes and one healthy plant class. This study aims to develop a more effective strawberry plant disease detection technology. The proposed method is based on YOLOv8 by applying K-Fold Cross Validation to the detection model training and applied data albumentations to produce a robust model. Based on the experimental results, it shows that the YOLOv8s model obtained the highest precision, recall, F1-score, and mean average precision values of 1.00, 0.94, 0.84, and 0.885 respectively.
The Design of an Android-based Financial Recording and Investment Simulation Information System Saputra, Gede Rizky Chandra; Sukarsa, I Made; Andreyana, Putu Veda; Wira Buana, Putu; Wisswani, Ni Wayan
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol 12 No 3 (2024): Vol. 12, No. 3, December 2024
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIM.2024.v12.i03.p03

Abstract

Financial management and investment have become increasingly important in digital era, where many individuals and organizations face challenges in effectively recording and managing their finances. Address this issue, mobile application has been developed, offering features such as financial recording, investment simulation, loan simulation, and portfolio tracking. The application is designed with user-friendly interface, tailored to meet users' needs for more efficient financial management. Built using Flutter for Android platform and Laravel for backend, application adopts waterfall development method to ensure systematic progress at every stage and employs microservice architecture to support scalability. Testing was conducted using Black Box Testing method to verify application functionality and Post-Study Usability Questionnaire (PSSUQ) involving 30 users to evaluate satisfaction levels. Results show application performs well on its key features, achieving an average PSSUQ score of 1.9, which is better than satisfaction threshold of 2.57, indicating a high level of user satisfaction with this application.
AI-Driven Mobile Childrens Book Generator A Case Study of Tema Insani Psychology Consultancy Pasha Catra Parama, Anak Agung Ngurah; Ayu Wirdiani, Ni Kadek; Dwi Rusjayanthi, Ni Kadek
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol 13 No 1 (2025): Vol. 13, No. 1, April 2025
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIM.2025.v13.i01.p01

Abstract

The advancement of technology drivesving digitalization across various sectors, including psychology and literacy in Indonesia. This motivates children’s psychology consultant Tema Insani to enhance children’s literacy interest by considering psychological conditions, neurodevelopmental disorders, and developmental age, which have so far relied heavily on parents’ role in providing books. The issue presents a solution in the form of a mobile-based application that can generate bedtime stories tailored to children’s age, disorders, and preferences. The app includes a reading tracker to monitor children’s literacy progress based on reading frequency. The development uses the Agile methodology and Dart with Flutter SDK as the primary development language. The black box testing results show that using the app with children at night can increase reading frequency by replacing device usage with bedtime stories. The development of the app is expected to support Tema Insani’s efforts to bridge psychology, technology, and children’s literacy interest in Indonesia.
Automatic Pet Feeder Rotational Model Using MQTT and Mobile Application Mahadiputra, Putu Gede Krisna; Suarjaya, I Made Agus Dwi; Wibawa, Kadek Suar
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol 12 No 2 (2024): Vol. 12, No. 2, August 2024
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIM.2024.v12.i02.p04

Abstract

Automatic pet feeding systems with dispenser models have limitations on the type of feed that is only accomodate dry food, while pets (cats) with a tendency consuming dry food are prone to disease in the urinary system. This research focuses on designing a rotational model automatic pet feeding system that can accommodate both dry food and wet food, also set the feeding time through mobile applications via MQTT by utilizing an ESP32 microcontroller connected to a 5V stepper motor, RTC and load cell sensor. The system has success rate about 90% on pet feeding automation, but the container upper fold has difference angel about 5.4o with the expected position (error rate 6%). Every weight sensor has the successive error rates are 1.41% (1st feed block), 1.91% (2nd feed block), and 0.68% (3rd feed block). The Android application takes only 1-1.5 seconds to displaye the latest feed weight data.
Enhancing Breast Cancer Recognition in Histopathological Imaging Using Fine-Tuned CNN Darma, I Wayan Agus Surya; Sutramiani, Ni Putu
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol 12 No 3 (2024): Vol. 12, No. 3, December 2024
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIM.2024.v12.i03.p04

Abstract

Global Cancer Statistics reports that of the 2.3 million cases of breast cancer worldwide, 600,000 result in death. Factors contributing to breast cancer in women include both genetic and lifestyle influences. One method for recognizing breast cancer is through histopathology images. Recently, deep learning has gained significant attention in machine learning due to its powerful capabilities in modeling complex data, such as images. In this study, we classify breast cancer by training a Convolutional Neural Network (CNN) model on a dataset of histopathology images annotated and validated by experts, containing two classes. We propose an optimization strategy for CNN models to enhance breast cancer recognition performance, applying a fine-tuning strategy to MobileNetV2 and InceptionResNetV2 to evaluate CNN performance in classifying breast cancer within histopathological images. The experimental results demonstrate that the model achieves optimal performance with an accuracy of 96.22%.
Analysis of Measurement of the Quality of Using the Web-Based Computer Based Test (CBT) Application on User Satisfaction Using Servqual and CSI Methods at SMK PGRI 6 Denpasar Triwayuni, I Gusti Ayu; Sudarma, Made; Alit Swamardika, Ida Bagus
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol 13 No 1 (2025): Vol. 13, No. 1, April 2025
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIM.2025.v13.i01.p02

Abstract

The web-based Computer Based Test (CBT) application is an innovation in the academic assessment system that replaces the conventional paper-based exam method. This study aims to analyze the quality of CBT application services on user satisfaction at SMK PGRI 6 Denpasar using the Servqual and Customer Satisfaction Index (CSI) approaches. The research sample consisted of 152 students in grades XI and XII. Data were obtained through online questionnaires and analyzed using the Servqual method to identify gaps between user expectations and perceptions, as well as CSI calculations to measure overall satisfaction levels. The results of the analysis show that 90% of indicators have negative gap values ??indicating that user expectations are higher than actual experiences. However, the CSI value of 82.64% is included in the very satisfied category, indicating that the CBT application still provides significant benefits. Therefore, feature development and service improvements are needed to meet user expectations more optimally.

Page 27 of 28 | Total Record : 280

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