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JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH)
Published by Forum Kerjasama Pendidikan TInggi
ISSN : -     EISSN : 2686228X     DOI : -
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
Artikel yang dimuat melalui proses Blind Review oleh Jurnal JOSH, dengan mempertimbangkan antara lain: terpenuhinya persyaratan baku publikasi jurnal, metodologi riset yang digunakan, dan signifikansi kontribusi hasil riset terhadap pengembangan keilmuan bidang teknologi dan informasi. Fokus Journal of Information System Research (JOSH)
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 795 Documents
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Pengembangan Sistem Identifikasi Penyakit Tanaman Anggur Berdasarkan Citra Daun Menggunakan Algoritma Yolov8 (You Only Look Once) Bonitalia, Bonitalia; Alfonsius, Eric
Journal of Information System Research (JOSH) Vol 6 No 2 (2025): January 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i2.6235

Abstract

This research focuses on the development of a grapevine disease identification system based on leaf imagery using the YOLO (You Only Look Once) algorithm. Disease identification in grapevines presents a significant challenge in agriculture due to its impact on productivity and harvest quality. The primary issues in this identification include dataset limitations, variability in leaf imagery, and similarities in symptoms between diseases, which can reduce detection accuracy. Additionally, the computational demands of YOLO models pose challenges for IoT devices with limited processing capabilities, while the lack of integration with environmental data further complicates the system. This study offers a solution by developing a YOLO model trained on a dataset of 480 leaf image samples. The dataset includes various grapevine leaf diseases under different lighting conditions, image angles, and diverse backgrounds. This dataset was used to train the model to detect and identify specific diseases in grapevine leaves. The system was subsequently tested with unseen leaf images to evaluate accuracy, precision, sensitivity, and processing speed. The results demonstrate that the YOLO model achieved an average accuracy of 86.8% and a precision of 73.6%, with fast processing times suitable for real-time application. However, challenges such as dependency on dataset quality and hardware requirements remain key concerns. The system proved capable of recognizing and classifying several types of grapevine leaf diseases effectively, making it a valuable tool for early disease detection. With broader implementation and adjustments to local conditions, this technology is expected to reduce production losses and enhance harvest quality.
Perancangan Aplikasi Rental Skuter Malioboro Berbasis Mobile Menggunakan Metode User Centered Design (UCD) Novanto, Bandrio Ilham; Sancoko, Sulistyo Dwi
Journal of Information System Research (JOSH) Vol 6 No 2 (2025): January 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i2.6255

Abstract

Along Malioboro street, there are electric scooter rental services that make it easier for tourists to explore the surrounding area. By renting an electric scooter, visitors can enjoy the nighttime atmosphere with a gentle breeze and a beautiful view of the city lights. This service is in high demand, especially by young people, as it provides a unique and fun traveling experience. Although the scooter rental service in Malioboro provides convenience for tourists, there are some problems faced in its implementation. One of the main problems is the absence of a dedicated platform for scooter rental. Travelers can only rent directly, so there is often a scramble. In addition, some users leave the scooters carelessly on sidewalks or pedestrian areas, thus disrupting pedestrian comfort and accessibility. To solve the problem of tourists renting scooters in Malioboro, the service provider provides a rental system that includes a short training on riding rules and safety before users rent the scooter in the form of a mobile application. This application was developed using the User Centered Design method by focusing on user problems and needs. Kotlin and MySQL were also used in its development, while testing was carried out using the Black Box Testing method. Based on the testing conducted, it can be concluded that the application can run well and produce a percentage of 91.6%. The resulting application can handle problems that exist in Scooter Rental in Malioboro such as ordering scooters and information on their use.
Prediksi Penyakit Getah Bening dengan Algoritma Linear Regresi Berganda Dondan, Christofael Natalio; Mailoa, Evangs
Journal of Information System Research (JOSH) Vol 6 No 2 (2025): January 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i2.6277

Abstract

This study aims to evaluate the performance of the multiple linear regression algorithm in predicting lymph node diseases by utilizing a multivariate dataset. This algorithm was chosen for its ability to analyze complex relationships between independent and dependent variables, which is expected to provide accurate prediction results. The model evaluation was conducted using three key metrics: Mean Absolute Error (MAE), Mean Squared Error (MSE), and Root Mean Square Error (RMSE), to measure prediction error levels and model reliability. The study results indicate that the multiple linear regression algorithm achieved MAE of 0.3, MSE of 0.3, and RMSE of 0.5. These values demonstrate low prediction error and acceptable accuracy, suggesting the algorithm's potential for application in assisting the diagnosis of lymph node diseases.
Rancang Bangun Aplikasi Web Career Upgrade Bagi Calon Profesional dengan Metode Extreme Programming Dzurriati, Chusnia; Wibowo, Feri; Wicaksono, Agung Purwo; Muktiadi, Ridho
Journal of Information System Research (JOSH) Vol 6 No 2 (2025): January 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i2.6353

Abstract

The limitations of applications that can integrate job search features, Curriculum Vitae (CV) development and workshop training are the main drivers in the development of the Career Upgrade application. This study aims to create a web-based application that combines aspects of job search, Curriculum Vitae (CV) development and workshop training in one comprehensive system. The Extreme Programming (XP) method used in the development of the Career Upgrade Application has proven effective in producing an adaptive and responsive system. Extreme Programming (XP) has four stages, namely planning, design, coding, and testing. The Next.js framework is used as the basis for frontend development because of its speed and flexibility, while Firebase is used for data management. This study produces the Career Upgrade web application that integrates job search, Curriculum Vitae (CV) development, and workshop training in one application. The black-box testing technique is used in the development of the Career Upgrade Application, black-box testing carried out on the application shows that all main features function properly and shows that the application can operate effectively without any interference or errors. This application is expected to provide real contribution in providing comprehensive digital solutions for users who are looking for job vacancies, Curriculum Vitae (CV) development and workshop training.
Klasifikasi Jenis Madu Akasia dan Madu Hutan Berdasarkan Warna RGB Menggunakan Metode Multilayer Perceptron Halim, Ridwan; Wibowo, Adityo Permana
Journal of Information System Research (JOSH) Vol 6 No 2 (2025): January 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i2.6366

Abstract

The advancement of technology has driven the agricultural industry to become more advanced and modern. Distinguishing honey with nearly identical colors is a challenging task. However, The ability to differentiate the color of acacia and forest honey is the simplest approach to ensuring the authenticity and quality of honey products. This study aims to develop a honey color classification model using Multilayer Perceptron (MLP). Image data were collected from various angles under natural lighting, followed by ninety experiments using parameter combinations, including data imbalance handling methods, dense layer structures, and training settings. The results showed that the MLP model with an optimal configuration, utilizing the Adaptive Synthetic Sampling (ADASYN) method for data imbalance, achieved a validation accuracy of 90.63%. This accuracy highlights the potential of the model to support industrial automation processes in reliably distinguishing honey colors.
Implementasi Model Waterfall dalam Aplikasi Manajemen Keuangan Berbasis Android Fernanda, Niko; Wibowo, Adityo Permana
Journal of Information System Research (JOSH) Vol 6 No 2 (2025): January 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i2.6370

Abstract

One of the main components in maintaining the stability and financial well-being of people and families is effective financial management. The myth that expenses will always increase along with income is one of the common misconceptions in society. This study aims to address this by creating financial management software for Android that facilitates effective and efficient financial management for users. The research methodology uses the waterfall model, which means that every step from needs analysis to implementation is completed systematically. The development process of this application utilizes Android Studio with the Kotlin programming language which is known to be efficient, while MySQL is used as a database for secure financial information management. The application system is designed using the Unified Modeling Language (UML) to define workflows and processes in a structured manner. The results of the application test use the blackbox testing method to test this application to ensure that all features such as recording financial information, income and expense transactions, and creating financial reports function as they should. In addition, this application also provides additional features in the form of investments to help users monitor their investment assets. From the tests carried out, all application features showed a success rate of 100%, indicating that the application functions according to the designed specifications. This application allows users to optimize financial management, so they can improve their standard of living in a more planned and systematic way.
Implementasi Aplikasi Pemantauan dan Reservasi Layanan Laundry Self-Service Berbasis Mobile Menggunakan Metode Waterfall Mahzarena, Salma; Asriningtyas, Yuli
Journal of Information System Research (JOSH) Vol 6 No 2 (2025): January 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i2.6377

Abstract

In today's digital era, mobile application-based services have become essential for consumers, including in the realm of self-service laundry. One common challenge for users is the uncertainty of washing machine availability upon arriving at the location. This study aims to design and develop a mobile-based monitoring and reservation application for self-service laundry. The application was developed using Flutter for the mobile platform and Laravel for the backend, utilizing the Waterfall software development methodology. The application allows users to monitor real-time washing machine availability and reserve vacant machines, thereby reducing waiting times and improving service efficiency. Data collection was carried out through direct observation at laundry locations and a literature review related to reservation systems. The test results indicate that the application accurately provides machine availability information and simplifies the reservation process. In conclusion, the application enhances user convenience and satisfaction in using self-service laundry services.
Sistem Informasi Geografis Potensi Pertanian GISELA Menggunakan Arcgis Mafahir, Muhammad Alil; Cahyono, Rokhmad Eko; Ridlwan, Ah. Afif
Journal of Information System Research (JOSH) Vol 6 No 2 (2025): January 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i2.6399

Abstract

Lamongan Regency is a district where the majority of the population is engaged in farming, making it the largest agricultural area located in East Java. As an agrarian region, the main livelihood of its residents is in the agricultural sector. Development in the agricultural sector is primarily aimed at meeting the needs of the community, given the diversity of food sources which presents a significant potential for land use. Lamongan Regency was divided into two categories: agricultural areas and non-agricultural areas. The Food Security and Agriculture Service of Lamongan Regency in 2023 divided land into 2 criteria, namely agricultural areas and non-agricultural areas. Agricultural areas consisting of rice fields, fields, and plantations covering an area of ​​95,460.35 hectares. While non-agricultural areas consist of settlements, industry, rivers, swamps, and forests covering an area of ​​8,022.85 hectares [1].Currently, the main issue is the lack of agricultural information available to the public, making it difficult for residents to access information about agriculture in Lamongan Regency. Therefore, there is a need for a geographic information system that can provide information about agricultural land potential and maps of agricultural opportunities in Lamongan Regency, enabling residents to quickly and easily obtain information about the agricultural land potential in their area.The research methodology used in developing the Gisela application is the waterfall method. Agriculture impacts the community of Lamongan Regency by providing quick and easy access to information about the agricultural land potential in the region. This application features an interface that is easy for the public to understand. Additionally, it can generate recommendations for determining suitable crops to plant and establish as leading commodities in their respective areas.
Pemasaran Vendor Wedding Organizer Melalui Aplikasi Moore Berbasis Web Mobile Menggunakan Metode Agile Nurhadi, Muhammad; Sancoko, Sulistyo Dwi
Journal of Information System Research (JOSH) Vol 6 No 2 (2025): January 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i2.6406

Abstract

The wedding industry in Indonesia has undergone a significant transformation thanks to technological advancements and changing consumer behavior. Today, brides-to-be are increasingly utilizing digital platforms to search and book wedding services. Many vendors still manage the booking system conventionally. The booking system at vendors still uses regular telephone calls so there are often errors in recording bookings because the vendors often forget to record the booking schedule in the ledger. Promotional activities are also still very limited. This research aims to develop a mobile web-based application that facilitates wedding vendors in offering their services and products more efficiently. This application is designed to overcome various challenges faced by vendors, such as difficulties in promoting vendors to prospective brides, managing bookings, communicating with clients, and improving operational efficiency to achieve client satisfaction with the services provided. The application development involved collecting wedding package data, product data (such as physical souvenirs and invitations), system design, technology selection, and implementation and evaluation strategies. The technologies used include React JS for web application development and React Native for mobile applications, both using the JavaScript programming language. The database uses MongoDB, with the support of platforms such as Stripe as a payment gateway. The software development method applied is Agile, to ensure flexibility and responsiveness to user needs. The interim result of this research is an application that provides a source of information for prospective brides related to vendors of wedding organizer products and services with a wide scope. In addition, the Moore App has been tested by 30 respondents with an average success rate of 100%, indicating that all features function properly according to user needs and established specifications.
Klasifikasi Penyakit Daun Kopi Arabika Berbasis Gambar Menggunakan Model Convolutional Neural Networks DenseNet121 Solehudin, Muhammad Alwy; Gerhana, Yana Aditia; Taufik, Ichsan
Journal of Information System Research (JOSH) Vol 6 No 2 (2025): January 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i2.6407

Abstract

Detection of Arabica coffee leaf diseases is crucial for improving the quality and yield of coffee crops. This study aims to apply the DenseNet121 Convolutional Neural Network model to identify three types of diseases on Arabica coffee leaves, namely Rust, Phoma, and Miner. The data used consists of images of Arabica coffee leaves, which are divided into training, validation, and test sets. The model was trained using the Adamax optimizer with hyperparameters such as a maximum of 30 epochs and a batch size of 32. During training, the model achieved a validation accuracy of 98.86% before being stopped by the early stopping callback at epoch 28 to prevent overfitting. Model evaluation using a confusion matrix resulted in 97% accuracy on the test data, with excellent precision, recall, and F1-score values for most categories, particularly for the Healthy, Miner, and Phoma classes. The Rust class showed lower recall due to data imbalance in the test set. The results of this study demonstrate that the DenseNet121 model is reliable for detecting diseases on Arabica coffee leaves with high accuracy and provides an important contribution to the technology of plant health monitoring, which can assist farmers in early detection and improve coffee crop productivity.

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