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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 53 Documents
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Search results for , issue "Vol 6 No 4 (2025): July 2025" : 53 Documents clear
Geospatial-Based Information System for Visitor Management in the Baduy Region Rahmadini, Asyifa Catur; Tharsini, Priya; Singgalen, Yerik Afrianto
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.7186

Abstract

This research presents the development of a Geospatial-Based Information System prototype for visitor management in Indonesia's culturally sensitive Baduy indigenous region. The study addresses the critical challenge of balancing cultural preservation with sustainable tourism development through an innovative technological framework that respects indigenous sovereignty. Utilizing Rapid Application Development (RAD) methodology, the research integrates traditional knowledge systems with modern geospatial technologies to create a governance tool that enhances rather than displaces traditional decision-making structures. The prototype system architecture incorporates permit management workflows, GPS-enabled check-in protocols, and spatial monitoring capabilities that enable Jaro authorities to regulate visitor access, monitor distribution patterns, and enforce culturally appropriate boundaries. Black box testing validated the prototype's functionality across multiple operational scenarios, confirming its feasibility as a protective mechanism against unregulated tourism activities. This methodological approach to cross-cultural information system design establishes a foundational framework demonstrating how thoughtfully implemented geospatial technologies amplify Indigenous governance capabilities while creating sustainable economic opportunities aligned with traditional values and cultural preservation imperatives. The research contributes significantly to the discourse on Indigenous digital sovereignty and culturally appropriate technological interventions in heritage management.
Pengembangan Model Decision Tree Menggunakan Particle Swarm Optimization untuk Klasifikasi Popularitas, Infrastruktur, dan Potensi Pasar Wilayah Jabodetabek Ambarsari, Erlin Windia; Kustian, Nunu; Mardika, Putri Dina
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.7216

Abstract

Traditional markets play a vital role in local economies; however, they face challenges related to competitiveness, infrastructure quality, and legal operational status. This study aims to develop a classification model for traditional markets in the Greater Jakarta (Jabodetabek) region based on three main aspects: popularity, infrastructure readiness, and market potential. The model utilizes a Decision Tree (DT) algorithm optimized with Particle Swarm Optimization (PSO) to enhance classification accuracy while maintaining model interpretability. The dataset comprises 1,253 market entries with 15 predictive features. The classification model categorizes markets into popular or unpopular, infrastructure-ready or not-ready, and potential or non-potential groups. Experimental results demonstrate that the model achieves an average accuracy of 97.48%. Key factors influencing the classification outcomes include the number of vendors, the availability of basic facilities (electricity, clean water, toilets, and drainage), the age of the market, and the presence of an official operating license (IUP2T). The findings provide valuable insights for local governments and policymakers to prioritize market revitalization efforts based on data-driven classification results. Furthermore, this study opens future research opportunities to integrate spatial data and real-time market analytics to improve classification accuracy further and support more adaptive and effective policy-making.
Optimizing Insurance Customer Segmentation with C4.5 Decision Tree Algorithm Setya, Sigit Candra; Perangin-angin, Moch. Iswan; Marsono, Marsono; Nasyuha, Asyahri Hadi; Harnaningrum, Lucia Nugraheni
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.7358

Abstract

Insurance companies rely on premium payments as their primary source of revenue. However, economic instability often causes delays in premium payments, impacting revenue recording. This study applies the C4.5 Decision Tree algorithm to classify insurance customers based on premium amount, age, income, and claim history, thereby improving product recommendations. The research utilizes data mining techniques to analyze customer attributes and generate decision rules for optimal insurance product selection. The findings indicate that customers with a premium of IDR 500,000 are best suited for PRUMed Cover (PMC), while those with IDR 1,000,000 are recommended PRUCritical Benefit 88 (PCB88). For customers with IDR 750,000, additional factors such as age and income level influence the recommended insurance type. The entropy and information gain calculations identify premium amount as the most significant attribute for decision-making, followed by age, income, and claim history. By implementing this method, insurance companies can enhance customer segmentation, streamline product selection, and optimize marketing strategies. The transparent and interpretable decision tree structure ensures regulatory compliance while improving customer satisfaction. Future research should explore additional variables, such as behavioral data and regional trends, and compare C4.5 with other classification algorithms like Random Forest or Support Vector Machines (SVM) to enhance accuracy and scalability.
nalisis Sentimen Berbasis Aspek Ulasan Aplikasi Ruangguru Pada Platform Android dan iOS menggunakan BiLSTM Mutmainah, Siti; Citra, Erin Eka; Lorosae, Teguh Ansyor; Fathir, Fathir
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.7475

Abstract

Analysis of user reviews can provide valuable insights for app developers in improving quality, but conventional sentiment analysis only categorizes sentiment in general terms. Aspect-based Sentiment Analysis (ABSA) is a method that can be used to extract specific opinions from various aspects of user reviews. This study compares ABSA on user reviews of Ruangguru app on Android and iOS platforms. Review data was collected from Google Play Store and Apple App Store, processed, and classified into sentiment polarity using deep learning models such as BiLSTM with Word2Vec. The analysis was conducted to find out the aspects talked about by users and the sentiment associated with each aspect. The evaluation results show that the BiLSTM model with Word2Vec features performs well on the sentiment analysis task achieving 84% accuracy. In the aspect extraction task, the model performs very well with accuracy, precision, recall, and F1 Score values of 97%. These results show that the combination of BiLSTM and Word2Vec is an effective approach in understanding user opinions and preferences from Ruangguru app review text data and has the potential to be applied in the development of automated opinion analysis systems. Price aspect extraction results are the most dominant topic discussed on both platforms, followed by features and materials. Positive sentiment towards the price aspect dominates, but there is also a significant proportion of negative sentiment, especially on the Android platform.
Implementasi Algoritma YOLOv11 untuk Sistem Klasifikasi Kelayakan Setor Sampah Anorganik dalam Pengelolaan Bank Sampah Saputro, Fredy; Witanti, Arita
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.7486

Abstract

Inorganic waste management in waste banks faces challenges in sorting and quality evaluation processes that still rely on manual methods with high levels of subjectivity. Bank Sampah 34 Ngasemrejo experiences problems with community uncertainty regarding waste eligibility standards, causing high material rejection rates and suboptimal community behavior in waste deposit. Therefore, this research aims to develop an automatic inorganic waste eligibility detection system before depositing to waste banks. This research develops an inorganic waste eligibility detection system based on computer vision using the You Only Look Once version 11 (YOLOv11) algorithm to classify plastic bottles, duplex, and newspaper waste based on eligible and ineligible physical conditions for deposit. The research dataset consists of 2,800 images divided into 70% training data, 20% validation data, and 10% testing data. Data preprocessing was performed using the Roboflow platform including annotation, augmentation, and resize to 640x640 pixels. The YOLOv11n model was trained for 50 epochs with optimized hyperparameters. Evaluation results show excellent performance with mAP50 of 99.4%, mAP50-95 of 95.8%, precision rate of 98.3%, and recall of 98.6%. Testing on testing data shows that the system can accurately classify the eligibility of inorganic waste according to waste bank standards. This system is expected to help residents sort waste independently, improve waste bank operational efficiency, and support higher quality and sustainable recycling processes.
Optimalisasi Penyaluran Bantuan Program Keluarga Harapan Menggunakan Metode Fuzzy SAW pada Sistem Pendukung Keputusan Syahputri, Nita; Tahel, Fithry; Siregar, Elida Tuti; Ginting, Erwin
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.7524

Abstract

This study aims to design and implement a decision support system (DSS) used on the Fuzzy Simple Additive Weighting (Fuzzy SAW) method to improve the accuracy and objectivity of the selection process for recipients of the Family Hope Program (PKH) in Hamparan Perak Village. The system was developed to address the limitations of manual selection, which remains subjective and inefficient. The research involved several stages, including needs analysis, system design using Unified Modeling Language (UML), and testing through the black-box method. The system utilizes social criteria data such as housing conditions, number of dependents, and informal employment status, which are processed using a fuzzy approach to produce structured recommendations. The main innovation of this system lies in the integration of localized indicators and a mobile-based data update module, enabling real-time verification and validation in the field. The implementation results indicate that the system operates optimally and can be utilized by village officials with limited digital literacy. This research contributes to strengthening data-driven governance in social assistance distribution and has the potential to be replicated in other regions with similar socio-demographic characteristics.
Sistem Informasi Sidang Seminar Proposal dan Skripsi Berbasis Web dengan Pendekatan Metode Waterfall Arshal Afandi, Muhammad Farid; Jazuli, Ahmad; Wijayanti, Esti
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.7575

Abstract

The scheduling of proposal seminars and thesis defenses is a crucial process completely of student studies in the informatics engineering study program. However, this process often faces several challenges, such as delayed information, manual data accumulation, and a lack of transparency in schedule and examiner selection. To address these issues, the Laravel framework was chosen for the design of this web-based system, aiming to simplify the administration and scheduling processes for proposal seminars and thesis defenses. Laravel was selected due to its support for structured, secure, and efficient system development. This web-based system utilizes PHP and SQL for database management. The development methodology used is Waterfall, which adopts a sequential and systematic approach, starting from the requirement, design, implementation, verification, and maintenance stages. Each stage is done in a structured manner to ensure that all needs have been met before moving on to the next stage. System implementation using the Laravel framework as the backend foundation with responsive interface design. The case study was conducted at the Informatics Engineering Study Program of Universitas Muria Kudus. The results of testing indicate that the system improves data processing efficiency, accelerates information delivery, and minimizes errors in the registration and scheduling processes. With implementation of this system, academic procedures are expected to become more orderly, transparent, and well-structured. The test results show that the system is able to improve efficiency, as well as reduce administrative errors in the registration and scheduling process. All users are already interrelated in this registration process, starting from students, lecturers, coordinators, operators.
Sistem Pendukung Keputusan Pemilihan Bibit Padi Unggul Menggunakan Metode Simple Additive Weighting (SAW) Febriyani, Fina; Nasyuha, Asyahri Hadi; Kurniawati, Deborah
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.7627

Abstract

The selection of superior rice seeds is a crucial stage in improving agricultural productivity in Indonesia. However, farmers often select seeds subjectively without systematically considering important factors. To address this issue, this study designs and develops a Decision Support System (DSS) based on the Simple Additive Weighting (SAW) method to assist farmers in selecting the best rice seeds using six criteria: pest resistance, harvest age, amylose content, yield, irrigation water efficiency, and rice texture. Data were collected through interviews with five farmers in Mangir Lor. The results showed that the rice variety Inpari 32 achieved the highest score of 0.87, thus recommended as the best alternative. The SAW method proved effective in managing multicriteria data and producing objective and accurate results. This DSS is expected to serve as a practical decision-making tool for farmers in selecting high-quality rice seeds and contribute to the achievement of sustainable national food security.
Penerapan Metode Trend Moment Dalam Sistem Forecasting Untuk Memprediksi Jumlah Penjualan Smartphone dan Aksesoris Louis, Kevin; Sinaga, Christina Julia; Mujahid, Putra Edi
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.7666

Abstract

Trend Moment and Forecasting are data retrieval methods that have accurate and effective suitability to handle problems such as large amounts of data. The Trend Moment method is an approach that uses special statistical and mathematical calculation techniques to replace broken lines formed from the company's historical data with a straight line function. The Star Communicator store is one of the stores in the city of Medan that is engaged in selling various brands of smartphones and their accessories. Currently, the Star Communicator store still uses a conventional system to record its sales data. The admin staff will record product sales data. Then, at the end of the month, a sales recapitulation will be made to the store owner. The implementation of this system has a weakness where the company owner cannot know which products are more in demand by customers in a certain period. This information is needed so that the company owner can control smartphone stock in the company. Therefore, it is necessary to apply a smartphone prediction system. The result of this research is a desktop application that can be used to predict the number of smartphone sales in a certain period. From the results of the tests carried out, information was obtained that the average level of accuracy of the Trend Moment method was 70.22%. This means that the level of accuracy of the prediction results from the Trend Moment method is still not good. To improve the accuracy of the prediction results, the Trend Moment method can be combined with other methods, such as the Linear Regression method. In addition, other supporting factors for predictions can also be added, such as holiday factors or certain holidays which are often known as the holiday effect.
Implementasi Sistem Pendukung Keputusan Berbasis MOORA untuk Pemilihan Domba Qurban Terbaik Berdasarkan Kesesuaian dengan Prinsip Syariah Malela, Prabu Aji; Purnomo, A Sidiq
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.7709

Abstract

The selection of sacrificial lambs that comply with Islamic law is an important aspect in the implementation of the Eid al-Adha worship. At Prabu Star Farm, the selection process is still done manually and subjectively, potentially resulting in less accurate decisions. This research aims to develop a web-based Decision Support System (SPK) with the Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) method to support the selection process objectively and measurably. The system evaluates five main criteria, namely weight, age, health, price, and horn ownership. The MOORA method process includes the formation of a decision matrix, data normalization, weighting based on the type of criteria (benefit or cost), and calculation of the optimization value (Yi) to determine the ranking. Test results on ten alternatives showed that D8 sheep ranked highest (Yi = 0.3021), followed by D1 and D6. The recommendation of D8 was supported by a combination of superior attributes: ideal weight (45 kg), sharia-compliant age (≥ 2 years), healthy condition, rational price, and horn ownership that matched buyer preferences. The system showed high consistency with the manual assessment, and was able to increase efficiency and transparency in the selection process. Thus, the MOORA method is effectively applied in multicriteria decision making for the selection of Sharia-compliant qurban animals.

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