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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 Pakar Berbasis Fuzzy MADM dengan Metode SAW untuk Prioritas Penanganan Gejala Depresi Putri Vina, Febrian Sania; Sutarman, Sutarman
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.v6i2.6463

Abstract

Depression is a mental health disorder that is often unrecognized and can develop into a more serious issue if not addressed properly. One of the main challenges in managing depression is the lack of tools that can objectively measure the severity of symptoms and determine who requires immediate treatment. This study aims to develop an expert system based on Fuzzy Multiple Attribute Decision Making (MADM) with the Simple Additive Weighting (SAW) method to prioritize the treatment of depression symptoms based on criteria such as intensity, duration, and impact on daily life. The system goes through several stages, including data pre-processing, fuzzification, criterion weighting, decision matrix normalization, and ranking calculation using SAW, resulting in an accurate treatment priority ranking. The research findings show that this system can assist healthcare professionals in identifying individuals with the most severe symptoms who require immediate intervention, thereby speeding up treatment and improving the effectiveness of therapy provided.
Perancangan Sistem E-Parking Berbasis Arduino dengan Kartu RFID Herdiansyah, Muhammad Ferdi; Danny, Muhtajuddin; Astuti, Retno Fitri
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.v6i2.6467

Abstract

Security and efficiency of parking management are crucial aspects in the operations of companies and educational institutions. At Pelita Bangsa University, the conventional parking system still uses manual methods and paper-based tickets, which is inefficient and potentially creates security issues. In addition, the lack of integration between the parking system and vehicle identification increases the risk of theft. This research aims to design an RFID-based parking system that can be accessed using a Student Identity Card. The system uses RFID at low frequencies to ensure the security and accuracy of vehicle identification. The results show that the RFID system is able to efficiently replace conventional methods, reduce paper usage, and increase parking access speed. The system is also integrated with the student database, enabling better access control and automatic recording of vehicles. The implementation of the system in Pelita Bangsa University's parking area not only improves security but also user experience, with a faster payment process and structured vehicle data management. Hopefully, this system can be an innovative solution that can be applied in various institutions to face the challenges of parking security and efficiency in the digital age.
Perbandingan Algoritma Naïve Bayes dan K-Nearest Neighbor (K-NN) Untuk Klasifikasi Penyakit Gagal Jantung Zahri, Firman; Insani, Fitri; Jasril, Jasril; Oktavia, Lola
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.v6i2.6480

Abstract

A condition known as heart failure, where the heart is unable to pump enough blood to meet the body's needs for oxygen and nutrients, should not be taken lightly. This can result in a number of symptoms, such as fatigue, fluid retention, and dyspnea. The World Heart Federation estimates that up to 1.8 million people in Southeast Asia suffered from heart failure in 2014. For prompt and efficient treatment, heart failure is a medical problem that needs to be identified. This disease has the potential to worsen if not treated immediately. Several machine learning methods can be used to help diagnose and categorize this disease. One of them is the popular algorithm, namely Naive Bayes and K-Nearest Neighbors. Naive Bayes is a simple but very efficient probability-based machine learning algorithm, especially in classification applications. K-Nearest Neighbors is comparing the data to be predicted with a number of its closest data in a feature space based on a certain distance, such as Euclidean distance, Manhattan, or others. This study was conducted using Confusion Matrix to evaluate and compare the Naive Bayes and K-Nearest Neighbor algorithms in the categorization of heart failure disease by collecting data totaling 918 heart failure patient data from kaggle. Based on the research findings, the K-Nearest Neighbor method achieved an accuracy score of 76%, while the Naive Bayes approach achieved 90% accuracy using a ratio of 80:20.
Marketplace Pemasaran Produk Pertanian Berbasis Mobile Menggunakan Pendekatan Waterfall Qowiim, Asyhar; 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.v6i2.6484

Abstract

The current agricultural industry is still minimal in utilising technology so that limited access to information related to market demand and means of direct sales to consumers is a major obstacle in improving the welfare of farmers. The distribution process of agricultural products is still carried out conventionally through direct interaction, making it less effective and efficient. The development of information and communication technology, especially in the use of mobile devices, provides new opportunities to overcome existing problems. This research aims to solve the existing problems by creating a mobile-based application to increase sales of agricultural products. The application is developed using the waterfall approach method with several stages such as needs analysis, design, implementation, testing to maintenance. Flutter programming language is also used in coding the application system. Based on the design and implementation carried out in this study, an application is produced with features that display products and effective payment features. The existing features are then tested by 30 respondents with the black box testing method and the results obtained are 100% the application can run well. The application can increase transparency and efficiency in the sale of agricultural products. The application also provides convenience for farmers as consumers.
Performance Analysis of IndoBERT for Sentiment Classification in Indonesian Hotel Review Data Singgalen, Yerik Afrianto
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.v6i2.6505

Abstract

This study investigates the performance of a sentiment classification model leveraging IndoBERT to analyze Indonesian hotel review data. Sentiment analysis is crucial for extracting actionable insights from customer reviews, yet challenges such as linguistic diversity and imbalanced datasets complicate accurate classification. The dataset comprises 90% Positive, 5% Neutral, and 5% Negative sentiments, reflecting significant class imbalance. A fine-tuned IndoBERT model was trained over three epochs, with performance assessed using metrics such as accuracy, precision, recall, F1-score, confusion matrices, and ROC and Precision-Recall curves. The results indicate high global accuracy (92.52%) and robust performance for the Positive class (F1-score: 96.09%, AUC: 0.90). However, significant limitations were observed for minority classes, with the Neutral class achieving precision, recall, and F1-scores of 0.00, and the Negative class obtaining a low F1-score of 28.57%. These findings underscore the influence of dataset imbalance, where the dominance of the Positive class skews model predictions. Future research should explore techniques such as oversampling SMOTE, reweighting loss functions, or hybrid architectures to mitigate imbalance and improve performance across all sentiment categories. This research contributes to advancing sentiment classification methodologies for Indonesian text, offering practical implications for enhancing customer feedback analysis in the hospitality industry.
Analisis Perbandingan Algoritma Klasifikasi Data Mining untuk Penentuan Lokasi Perumahan Ernawati, Andi; Iqbal, Muhammad
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.v6i2.6516

Abstract

This study aims to analyze the application of C5.0 and K-Nearest Neighbor (K-NN) algorithms in the classification process for determining the optimal location for housing. The classification process involves several factors such as land price, accessibility, public facilities, crime rate, infrastructure, land availability, and consumer preferences. The research conducted tests on both algorithms to compare their performance in generating accurate predictions. The results show that the C5.0 algorithm outperforms K-NN, achieving an accuracy rate of 100%, compared to K-NN, which achieved an accuracy of 66.67%. This demonstrates that C5.0 is more effective in modeling data and producing more precise classifications. Therefore, it can be concluded that the use of data mining algorithms, particularly C5.0, greatly assists in the classification process for determining housing locations, providing more optimal results compared to K-NN.
Perancangan UI/UX Aplikasi Mobile Untuk Meningkatkan Efisiesi Pembayaran Air Perumda Tirta Musi Menggunakan Metode Design Thinking Noveni, Aldino Putra; Hardiyanti, Dinna Yunika
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.v6i2.6521

Abstract

Perumda Tirta Musi is a regional company that provides clean water services to the people of Palembang City and its surrounding areas. However, the current payment system is still dominated by conventional methods, such as payments at branch offices or through third-party payment counters, which are considered inefficient. To address this issue, this study aims to design the user interface (UI) and user experience (UX) of the Perumda Tirta Musi mobile water payment application using the Design Thinking approach. This method is applied to produce a design that is more effective and efficient in meeting user needs. Additionally, usability evaluation was conducted using the System Usability Scale (SUS) method to assess the quality of the interface and user experience. The study results show that the Perumda Tirta Musi mobile water payment application achieved an average usability score of 90.5, which is above the average score of 68. This score places the application in Grade A with an Excellent rating. With a high level of usability, the application enables users to complete tasks faster, reduce errors, and enhance user satisfaction and loyalty. The implementation of this application is expected to improve the efficiency of the payment process and enhance the quality of Perumda Tirta Musi's services.
Pemanfaatan Artificial Intelligence dan Cognitive Behavioral Therapy Untuk Pengembangan Chatbot Pembelajaran Matematika Sekolah Menengah Risqi, Yoga Alfa; Susilawati, Indah
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.v6i2.6523

Abstract

Artificial intelligence has brought great innovation in the world of education, one of which is through chatbots based on natural language processing. This technology allows computers to understand human language naturally. However, educational chatbots generally only provide question-and-answer-based information without considering students' psychological aspects, such as math learning anxiety, which can have a significant impact on learning outcomes. Therefore, this study aims to compare the performance of Long Short-Term Memory and Neural Network models in the development of a chatbot to support learning mathematical opportunities based on CBT emotional solutions. The Cognitive Behavioral Therapy (CBT) approach, a psychological technique aimed at changing negative mindsets into positive ones, provides an opportunity to address this challenge by integrating it into educational chatbots. The method used is through data preprocessing with NLP techniques, training and model assessment utilizing metrics such as accuracy, precision, recall, and F1-score, the results show the NN model is superior. Training the NN model resulted in an accuracy value reaching 99.15% with 88.98% validation, higher than the LSTM which recorded 96.88% and 87.29% respectively. The NN model offers more effective responses and emotionally supports students in interactive learning. These results indicate that NN and CBT-based chatbots have great potential to enhance the mathematics learning experience if further developed, especially on the topic of chance, by supporting concept understanding and reducing student anxiety.
Perancangan Sistem Point of Sale (POS) untuk Meningkatkan Efisiensi Pengelolaan Penjualan dan Stok Barang Maridaningsih, Siti; Setiawan, Agus; Nugroho, Setiya
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.v6i2.6526

Abstract

Effective information delivery is crucial in business, especially in managing transactions and inventory. Multi Ban Secang Motorcycle Tire Shop still relies on conventional methods for transaction recording and inventory management, leading to errors in data entry, inventory discrepancies, and delayed reporting, which result in decreased customer satisfaction and revenue. To address these issues, this study designs and develops a Point of Sale (POS) system expected to enhance operational efficiency and support strategic decision-making. The aim of this research is to design a POS application that can be implemented at Multi Ban Secang Motorcycle Tire Shop to resolve various problems in inventory and transaction management. The developed POS system will provide more accurate data management, speed up transaction processes, and generate real-time sales and inventory reports. The research follows the SDLC waterfall model, consisting of five stages, from requirements analysis to system evaluation and maintenance. The results of the study show that the implementation of the POS system improves efficiency in transaction recording and inventory management, as well as accelerates report generation. The system also enables users to monitor data in real-time and minimizes recording errors. Testing with the User Acceptance Testing (UAT) method showed a high user acceptance rate, indicating that the POS application is effective in improving store operations and strengthening business competitiveness.
Penerapan Metode SAW untuk Mengurangi Subjektivitas dalam Menentukan Kelayakan Penerima PKH Rochanah, Rochanah; Nuryanto, Nuryanto; hanafi, Mukhtar
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.v6i2.6556

Abstract

This study aims to determine the priority scale for families eligible to receive benefits from the Family Hope Program (PKH) using the Simple Additive Weighting (SAW) method. The primary issue addressed is the limited allocation of assistance, which necessitates an objective and transparent selection process to ensure that aid reaches the families most in need. This research aims to provide a decision support system-based solution to assist in the selection process.The research employs the SAW approach, which involves several key steps: collecting data on prospective beneficiary families, normalizing the data to standardize the criteria scale, assigning weights to each criterion according to its importance, and calculating the final scores to rank each family. The criteria used include the number of family members, the presence of young children, the educational level of family members, disability status, elderly status, and pregnancy, with weights determined based on policy. The results indicate that the SAW method effectively identifies the families most in need based on objectively calculated total scores. From the total data tested, 75% of families were categorized as "Eligible" to receive assistance based on total scores exceeding the threshold, while 25% were categorized as "Not Eligible."This study contributes to improving the accuracy and transparency of the PKH beneficiary selection process. The generated data can be adopted by local governments to optimize the distribution of social assistance, minimize potential errors, and enhance fairness in aid distribution to the community.

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