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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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Sistem Deteksi Objek Visual Sampah Organik Dan Anorganik Berbasis Algoritma YOL0v9 Adriansyah, Dedy; Putra, Muhammad Pajar Kharisma
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.v6i2.6454

Abstract

Efficiency in waste management is a major challenge in modern cities. With so many people throwing away organic and inorganic waste, a solution is needed so that the waste can be sorted properly. Therefore, in this research, researchers aim to utilize computer vision technology based on the YOLOv9 algorithm to detect and sort organic and inorganic waste. Using a dataset of 6,747 images from the Roboflow platform, this system was trained to recognize various types of waste using the bounding box labeling method. The YOLOv9 algorithm is equipped with Programmable Gradient Information (PGI) and Generalized Efficient Layer Aggregation Network (GELAN) features, which provide superior performance in terms of accuracy and speed of system performance. The model training results show that YOLOv9 has a precision value of 0.83%, recall of 0.85%, and mAP of 0.8%, making the model reliable in detecting objects. However, there are several weaknesses, such as decreasing accuracy in blurry images, overlapping objects, and colors that have similar similarities, which can affect detection results by up to 20-30%. Compared to SSD MobileNet v2, YOLOv9 is superior in accuracy, precision and F-1 Score with results in Accuracy values ​​of 58%, Precision 81%, F1-Score 69%. The Intersection over Union (IoU) test results produce excellent accuracy of 0.96%. This research recommends improvements through data augmentation and sensor integration to improve performance in various lighting conditions. This algorithm has great potential to be applied in technology-based waste management, supporting recycling efficiency, reducing human error, and providing a positive impact on the environment globally.
Klasifikasi Peminatan Skripsi Mahasiswa Ilmu Komputer dengan Algoritma K-Nearest Neighbor Gunawan, Helmi; Hasugian, Abdul Halim
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.v6i2.6457

Abstract

Technological advancements have made it easier for students to access information. However, many Computer Science students still struggle to determine a thesis specialization that aligns with their skills and interests. This study employs the K-Nearest Neighbor (KNN) algorithm to classify students' thesis specializations based on their academic data. The dataset consists of 100 students, with 80 used for training and 20 for testing. The KNN model was applied with parameters k=3k=3k=3 and k=5k=5k=5, generating predictions for thesis specializations such as Artificial Intelligence, Data Mining, and other fields. Model evaluation was conducted using accuracy, precision, recall, and confusion matrix metrics. The results show that the KNN model with k=3k=3k=3 achieved an accuracy of X%, precision of Y%, and recall of Z%. The implementation of KNN in this study demonstrated reasonably accurate results and can serve as a recommendation tool for students in selecting their thesis topics.
Sistem Pendukung Keputusan Pemilihan Laptop dengan Menerapkan Metode Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) Sussolaikah, Kelik; Lubis, Juanda Hakim; Sallaby, Achmad Fikri; Yuliani, Ega; Mesran, Mesran
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.v6i2.6525

Abstract

The lack of knowledge and information regarding laptop specifications makes ordinary people who want to buy a laptop feel confused about determining which laptop suits their needs. As a tool that can be used to select a laptop, a decision support system is needed. In decision support systems there are several methods, one of which can be used is the MOORA method (Multi-Objective Optimization on the basis of Ratio Analysis). In this research, the author will raise a case to find the best alternative from predetermined criteria to determine comparisons by rating existing alternatives using the MOORA (Multi-Objective Optimization on the basis of Ratio Analysis)method. Based on the relative performance scores, Asus Rog GL552JX (A9) obtained the highest score of 0.217 and ranked first. This was followed by Asus A455LD (A4) with a score of 0.21585 and second place, and Acer Aspire E5-551 (A2) with a score of 0.19785 and third place. Acer One 10 S100X (A10) received the lowest score of 0.1042 and ranked last. Thus, Asus Rog GL552JX (A9) can be considered as the best laptop based on the established criteria in this study.
Analisis Evaluasi Pengalaman Pengguna Pada Aplikasi Viu Menggunakan Metode User Experience Questionnaire Artanti, Freda Desfita; Widodo, Suprih
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.v6i2.6529

Abstract

The advancement of information technology has transformed media consumption patterns in Indonesia, particularly with the emergence of streaming platforms like Viu. As one of Asia's popular Video on Demand (VoD) providers, Viu offers a variety of content such as Asian dramas, anime, and entertainment news. Despite its significant user base, reviews on Google Play Store reveal negative comments and low ratings, with a score of only 2.6 out of 5 stars. This highlights the need to evaluate user experience to identify the application's strengths and weaknesses. This study aims to analyze the user experience of the Viu application using the User Experience Questionnaire (UEQ), which encompasses six main scales: attractiveness, perspicuity, efficiency, dependability, stimulation, and novelty. Data was collected through an online questionnaire completed by 30 valid respondents and processed using UEQ Tools. The results show that the Perspicuity aspect achieved the highest average score (1.817), followed by Dependability (1.558), receiving a Good benchmark category, indicating that the application is easy to understand and provides good interaction control. Attractiveness, Efficiency, and Novelty were rated as Above Average, with average scores of 1.511, 1.383, and 0.983, respectively, reflecting a satisfactory user experience. However, Stimulation had the lowest score (0.950), below the benchmark average, indicating the need for improvement in providing enjoyment and motivation to users. Recommendations focus on feature innovation, enhanced interaction, and a more enjoyable user experience to meet the needs of Viu users in the digital era.
Perancangan dan Implementasi Aplikasi Mobile BookMap Berbasis Android Alda, Muhamad; Salsabilla, Aulia Alsaf; Farhanuddin, Farhanuddin; Ath-Thoriq, M. Raihan; Zahidah, RA. Ghina
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.v6i2.6561

Abstract

In the digital era, e-books have become a popular choice due to their high accessibility and portability. However, many users face challenges in finding book-reading applications that align with their preferences. To address this issue, this study developed BookMap, an Android-based book reading application equipped with features such as bookmarking, night mode, text search, and book collection management. The application was developed using the waterfall method, which includes stages of requirement analysis, design, implementation, and testing. The Kodular platform was utilized to streamline the application development process without requiring extensive technical programming knowledge. The results show that BookMap provides a comfortable and flexible reading experience, supported by personalization features such as digital bookshelf organization and night mode. Black box testing confirmed that all features functioned as intended. This application not only facilitates access to digital literature but also contributes to promoting reading interest and digital literacy in society. With its various advantages, BookMap is expected to serve as an innovative solution to support modern reading needs anytime and anywhere.
Perbandingan Jarak Euclidean dan Manhattan pada Pemetaan Potensial Tanaman Padi Menggunakan K-Means Asrofi, Khoirul Rizky; Rusdyan, Risqi Darma; Tricahyo, Vion Age
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.v6i2.6582

Abstract

This research aims to analyze the potential of rice production in East Java by using 2 methods, namely Euclidean Distance and Manhattan Distance. By applying these two methods, the Department of Agriculture can gain a deeper understanding of the potential of rice production in each district or city. The analysis results show that K-Means with Euclidean Distance and Manhattan Distance can be used to identify areas with low, medium, and high rice potential. Comparison between the two methods using Silhouette Coefficient shows that Euclidean Distance has a superior value of 0.61, compared to Manhattan Distance which reaches 0.58. The findings provide practical solutions for the Department of Agriculture in an effort to improve food security and rice production in East Java, as well as making an academic contribution in the field of agricultural data analysis
Pendekatan MOORA dalam Rekomendasi Lulusan Terbaik Berbasis Optimalisasi Multi-Kriteria untuk Program Studi Informatika Herdiansyah, Moch Rizal; Purnomo, A. Sidiq
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.v6i2.6628

Abstract

This research aims to overcome the obstacles in selecting the best graduates in the Informatics Study Program, Faculty of Information Technology, Mercu Buana Yogyakarta University, which has been done manually. The proposed solution is the development of a Decision Support System (SPK) based on the MOORA approach to provide recommendations that are objective, efficient, and transparent. This system utilizes five main criteria, namely Grade Point Average (GPA), study period, organizational activity, academic achievement, and non-academic achievement. Analysis was conducted on six student data, with the results of Alternatives M2, M3, and M4 having the same final score, 0.4230. However, after reviewing the GPA, M4 was selected as the best graduate because it had the highest GPA among M2 and M3. This research proves the effectiveness of the MOORA approach in supporting decision-making, although there are limitations such as the limited amount of data and the absence of testing across study programs. In the future, system development can include additional data, large-scale testing, and integration of other methods to improve accuracy and application coverage in various educational institutions.
Implementasi Metode K-Means Clustering Sebagai Penentu Kelompok Belajar di SMA Khasanah, Alfi Nidaul; Tricahyo, Vion Age; Huda, Muhammat Maariful
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.v6i2.6631

Abstract

The way that students study has a big impact on how well they comprehend and retain the material. By creating uniform study groups according to students' learning preferences, this study seeks to maximize the learning process. It is anticipated that this study would use the K-Means Clustering Method to determine each student's preferred method of learning, which may be divided into three categories: kinesthetic, auditory, and visual. In this study, the K-Means technique is used to cluster 68 data points. Four academic value factors are added to the questionnaire, and testing is conducted by comparing the usage of three variables: the academic value of the choice of math, science, and English language. The results of the silhoutte test for three variables showed that 32 students were in cluster 1, 25 students were in cluster 2, and 11 students were in cluster 3. On the other hand, the results of the silhoutte test on four variables showed that there were 26 mahasiswa in cluster 1, about 11 in cluster 2, and approximately 36 in cluster 3. The study's findings indicate that using three variables results in three groups with different numbers of participants, while using four variables results in a somewhat different distribution of groups. Pembentukan kelompok belajar based on the aforementioned study's results is expected to help teachers in guiding siswa learners.
A PRISMA-based Thematic Analysis of Smart City Maturity Models: Mapping Key Dimensions and Maturity Levels Listianingsih, Widya; Susanto, Tony 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.v6i2.6639

Abstract

In the era of rapid urbanization and the increasing demand for sustainable urban development, smart cities have emerged as a critical focus for enhancing the quality of urban life. However, existing smart city maturity models lack standardization, making it challenging for cities to evaluate their progress comprehensively. This study addresses these challenges by identifying and analyzing the key dimensions and maturity levels across 11 smart city maturity models. Using a systematic literature review guided by the PRISMA approach and thematic analysis, this research uncovered significant insights. Eight key dimensions were identified, with the smart environment dimension appearing in 10 models, highlighting its centrality in addressing environmental and sustainability issues. Smart governance and smart society were also frequently highlighted, emphasizing their critical roles in fostering effective urban management and promoting social inclusion in smart city development. Additionally, 8 models employed a five-level maturity structure, demonstrating its widespread acceptance for balancing detail and simplicity in assessing a city's growth. These findings provide cities with a structured framework to evaluate and enhance their smart city strategies while facilitating comparisons among existing models. The results emphasize the need for a standardized yet flexible approach to smart city maturity, enabling cities to navigate their unique challenges effectively and achieve sustainable growth.
Penerapan Support Vector Machine untuk Analisis Sentimen pada Google Review Hotel Pratama, Harfin Ibna; Prasetyaningrum, Putri Taqwa
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.v6i2.6645

Abstract

This research aims to analyse customer sentiment towards Grand Rohan Hotel Yogyakarta using Google Reviews. Thus it can be a reference for hotel management to record customer reviews from internet users. Data was collected from user reviews during the period January to September 2024 in the form of 421 data. This research uses the Support Vector Machine (SVM) method to classify sentiment into positive and negative categories. The analysis process includes data collection using web scraping, data cleaning, text weighting using TF-IDF, and visualisation of analysis results. The results show that the SVM method is effective in analysing sentiment with an accuracy rate of 95%. Data visualisation through word clouds and pie charts provides additional insights for hotel management to improve service quality based on customer opinions. This research is implemented in a web application for real-time sentiment monitoring.

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