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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 754 Documents
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Analisis Sentiment Ulasan Aplikasi Riliv di Google Playstore dengan Algoritma SVM Andriani, Vivi; Hasan, Firman Noor
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): Juli 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.7860

Abstract

This study aims to conduct sentiment analysis on user reviews of the Riliv: Mental Health App on Google Play Store using the Support Vector Machine (SVM) algorithm. The analysis process includes review data collection via web scraping, text cleaning using text preprocessing, automatic labeling based on rating scores, data transformation using the TF-IDF method, data splitting with Stratified K-Fold Cross Validation, SVM model training, and performance evaluation. The dataset comprises 2,000 reviews with an imbalanced label distribution: positive (75,3%), netral (5,3%), and negative (19,4%). The classification results show that the SVM model achieved an accuracy of 85.56%. It performed well in identifying positive sentiment with an f1-score of 0.96 and negative sentiment with 0.69. However, the model failed to classify neutral sentiment due to the small number of data, which was insufficient for meaningful pattern recognition. Evaluation and visualization results indicate that label imbalance is a major challenge. Therefore, additional strategies such as data balancing, class weighting, or the use of alternative algorithms are necessary. This research is expected to serve as a foundation for developing a more accurate and fair sentiment analysis system across all sentiment categories in the context of digital mental health services.
Penerapan Naïve Bayes untuk Mengklasifikasikan Sentimen Tidak Seimbang pada Ulasan Aplikasi Berbasis Etika Konsumen Lingga, Lingga; Hasan, Firman Noor
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): Juli 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.7867

Abstract

This study aims to classify user sentiment toward an ethics-based consumption application using the Multinomial Naïve Bayes algorithm. The application examined contains social and moral content, often provoking complex opinion expressions. A total of 2,000 user reviews were collected from Google Play Store using web scraping and processed through a series of text preprocessing steps: case folding, cleansing, tokenizing, stopword removal, and stemming. The data were converted into numerical form using the Term Frequency–Inverse Document Frequency (TF-IDF) method and labeled into three sentiment categories: positive, neutral, and negative. The evaluation results show that the model achieved a precision of 92%, recall of 100%, and an f1-score of 96% for positive sentiment. However, the model underperformed in recognizing neutral and negative sentiments due to class imbalance. This study contributes to understanding the limitations of probabilistic classification models in handling imbalanced public opinion in socially driven digital spaces.
Analisis Usability Website Sistem Informasi Perpustakaan dengan System Usability Scale (SUS) dan Heuristic Evaluation (HE) Maulana, Fadly Safyuddin; Wibowo, Feri; Badharudin, Abid Yanuar; Wicaksono, Agung Purwo
Journal of Information System Research (JOSH) Vol 7 No 1 (2025): Oktober 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i1.8179

Abstract

This study aims to analyze the usability level of the Library Information System website of Muhammadiyah University of Purwokerto (SIPUS UMP) by combining two evaluation approaches, namely the System Usability Scale (SUS) and Heuristic Evaluation (HE). The evaluation was conducted by involving 30 active UMP student respondents for the SUS method and 5 expert evaluators from various professional backgrounds for the HE method. The HE evaluation results showed that the most significant problem was in the Help and Documentation aspect with the highest Severity Rating score of 3.10, while the Aesthetic and Minimalist Design aspect had the lowest score. Meanwhile, the results of the SUS method obtained an average score of 57.58%, which was categorized as Grade “D”, Adjective Rating “Good”, Acceptability “Marginal”, and Net Promoter Score (NPS) “Detractor”. These findings indicate that although the system is still acceptable to users, several improvements are needed in terms of appearance, documentation, and usage flow to improve the overall user experience. The combination of the HE and SUS methods in this study provides a comprehensive analysis both qualitatively and quantitatively as a basis for developing a more optimal system.
Sistem Penunjang Keputusan Penerima Bantuan Rumah Tidak Layak Huni (RTLH) Menggunakan Metode Swara Ardiansyah, Maulana; Fahmi, Hairul; Imtihan, Khairul
Journal of Information System Research (JOSH) Vol 7 No 1 (2025): Oktober 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i1.8235

Abstract

The Rumah Tidak Layak Huni (RTLH) Assistance Program is a government initiative aimed at improving the quality of life of low-income communities through the renovation of houses that do not meet livability standards. However, the selection process for beneficiaries still faces several challenges, particularly the lack of objectivity, potential subjectivity of field officers, and limitations in accurate assessment methods. This study aims to develop a Decision Support System (DSS) using the Step-wise Weight Assessment Ratio Analysis (SWARA) method to determine the weight of criteria in a structured manner based on expert judgment. SWARA was chosen because it systematically accommodates expert preferences through simple steps, producing more consistent and transparent weighting compared to other approaches.Five main criteria were considered: family income (C1), number of dependents (C2), physical condition of the house (C3), ownership status (C4), and occupation of the head of household (C5). The SWARA results generated the following weights: C1 = 0.288, C2 = 0.240, C3 = 0.185, C4 = 0.168, and C5 = 0.120. Data were collected from 13 respondents using a 1–4 scale questionnaire. Final scores were calculated by multiplying responses with the respective weights, yielding a maximum score of 3.160 and a minimum of 2.160. Using quantile-based classification, four eligibility categories were determined: Not Eligible, Less Eligible, Eligible, and Highly Eligible.The results showed that 3 respondents were classified as Not Eligible, 4 as Less Eligible, 3 as Eligible, and 3 as Highly Eligible. This study demonstrates that SWARA can be effectively applied in DSS to enhance the accuracy, objectivity, and transparency of RTLH beneficiary selection.
Sistem Pendukung Keputusan Penerima Bantuan Pangan Non Tunai (BPNT) Menggunakan Metode SMART Wirnama, Moh. Izhar; Fahmi, Hairul; Bagye, Wire
Journal of Information System Research (JOSH) Vol 7 No 1 (2025): Oktober 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i1.8276

Abstract

The Non-Cash Food Assistance Program (BPNT) is one of the government’s social policies aimed at improving food security for low-income households. However, the beneficiary selection process in the field is often carried out manually and subjectively, which may lead to mistargeting. This study develops a Decision Support System (DSS) model based on the Simple Multi Attribute Rating Technique (SMART) to assist village officials in objectively determining the eligibility of prospective BPNT recipients, particularly in areas not yet supported by digital technology. The assessment was conducted using five main criteria, namely income, employment status, number of dependents, housing condition, and asset ownership. Eligibility determination was carried out by setting an average threshold value (≥ 0.305), where candidates with a final score equal to or above the threshold were categorized as eligible, while those below it were deemed ineligible. The analysis results showed that out of 11 prospective recipients, four candidates with scores of A4 = 0.925, A9 = 0.900, A5 = 0.700, and A1 = 0.450 were declared eligible to receive BPNT, while the remaining seven were deemed ineligible. The application of the SMART method has proven effective in improving transparency, objectivity, and proportionality in the selection process, making it a practical guideline for village governments or social service agencies in distributing aid fairly and accurately. In the future, this manual model can be integrated into web-based or mobile applications to enhance efficiency, accuracy, and data documentation, accompanied by regular evaluations to ensure that the criteria remain relevant to the socioeconomic dynamics of the community.
Developing the Interface of HaoSpace Mood Tracking Application Using Design Thinking Saraswati, Desak Putu Mahadewi; Seputra, Ketut Agus; Dewi, Luh Joni Erawati
Journal of Information System Research (JOSH) Vol 7 No 1 (2025): Oktober 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i1.8365

Abstract

Mental health problems, particularly mood disorders, remain a major concern among adolescents and young adults, as they can affect academic performance, social interactions, and emotional well-being. Despite growing awareness, many adolescents still lack accessible tools to effectively monitor and manage their moods. The objective of this research is to design and develop a prototype of a mood tracking application called “HaoSpace” to address this gap. The research employed the Design Thinking methodology, which emphasizes a user-centered approach and involves five stages: empathize, define, ideate, prototype, and test, with participants consisting of students, workers, and a psychology expert. The resulting prototype includes features such as journaling, reminders, daily reports, and interactive visualizations in the form of graphs and mood-based calendars to facilitate self-monitoring and reflection. User testing showed positive responses regarding navigation, interface design, and feature relevance, while the psychology expert assessed the prototype as a feasible tool for self-reflection and emotional regulation among adolescents and young adults. In conclusion, HaoSpace demonstrates potential as a digital intervention to enhance mood awareness and promote mental well-being among adolescents and young adults.
Implementasi Chatbot Berbasis Aturan untuk Layanan Customer Service E-commerce pada Platform WhatsApp Ibrahim, Surya Rizky Maulana; Handayani, Dede
Journal of Information System Research (JOSH) Vol 7 No 1 (2025): Oktober 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i1.8443

Abstract

The high intensity of repetitive questions regarding product information, order status, and store policies in e-commerce businesses creates an additional workload for customer service and delays responses to customers. This research aims to implement a rule-based chatbot on the WhatsApp platform to automate customer service. The method used is the Waterfall software engineering model with stages of needs analysis, design, implementation, testing, and evaluation. The chatbot was implemented using Python integrated with WhatsApp Business API utilizing quick reply features. Functional testing results on 100 question samples show 87% accuracy. Usability testing using the System Usability Scale (SUS) on 30 users yielded a score of 78.5 (category "Good"). These results indicate that the proposed solution is effective in handling routine inquiries and can reduce customer service operational burden by 40% based on response time measurements. The main limitation lies in handling complex questions that require real-time data checking from external inventory systems.
Analisis Prediktif Harga Penutupan Harian Bitcoin Menggunakan Arsitektur Jaringan Saraf Tiruan Long Short-Term Memory Suyanti, Suyanti; Ophelia S, Chandy; Aryani, Lies
Journal of Information System Research (JOSH) Vol 7 No 1 (2025): Oktober 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i1.7485

Abstract

The highly volatile price of Bitcoin makes it difficult for financial market players. This research aims to build a Bitcoin daily closing price prediction model using Long Short-Term Memory (LSTM) neural network. Bitcoin price data from January 1, 2014 to May 9, 2025 was taken from Yahoo Finance, normalized with MinMaxScaler, and divided into 80% training data and 20% testing data. The LSTM model, which consists of two LSTM layers (50 units each) and two dense layers, was trained with Adam optimization and mean squared error loss function. The model uses the 60-day price sequence to predict the next day's price. The evaluation results show high accuracy with Root Mean Squared Error (RMSE) 105.80, Mean Squared Error (MSE) 2,822,880.74, Mean Absolute Error (MAE) 1,103.42, and R-squared (R²) 0.995. This model becomes one of the reliable prediction tools for financial decisions using historical data. This research enriches machine learning-based bitcoin price prediction solutions.
Sistem Pendukung Keputusan Pemilihan Pasta Gigi Terbaik untuk Gigi Berlubang dengan Metode PSI Widyana, Silva; Siregar, Filzah Naura; Putri, Nurma Wadda; Audi, Femy Ines; Hartama, Dedy
Journal of Information System Research (JOSH) Vol 7 No 1 (2025): Oktober 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i1.7606

Abstract

Tooth decay, or caries, is a common dental health problem that can have a serious impact on quality of life. This study aims to evaluate the effectiveness of various brands of toothpaste in the prevention and treatment of tooth decay. The methods used included analysis of active ingredients, laboratory tests, and consumer surveys. The toothpastes analyzed included products containing fluoride, calcium phosphate, and xylitol. Laboratory tests were conducted to assess each toothpaste's ability to reduce plaque, inhibit bacterial growth, and support tooth enamel remineralization. Consumer surveys collected data on user experiences and preferences. Based on the results of the analysis using the Preference Selection Index (PSI) method, it can be concluded that Pepsodent (A1) is the best alternative among the toothpaste products evaluated. Pepsodent obtained the highest preference score of 0.824, indicating that this product best suits consumer preferences and needs in addressing cavities. The results of the study show that toothpastes with high fluoride content, such as sodium fluoride and stannous fluoride, are significantly more effective in reducing the risk of caries than other products. In addition, toothpastes containing calcium phosphate show good ability to repair damaged enamel. Conversely, products marketed as “natural” are often less effective in preventing caries. This study provides important insights for consumers in choosing the right toothpaste, especially for individuals at high risk of cavities. These findings can also serve as a reference for manufacturers in developing more effective and safer products for dental health.
Penerapan Metode ORESTE dalam Menentukan Paket Internet yang Ideal di Kalangan Mahasiswa (Kasus Siantar-Simalungun) Khadafi, Farhan; Wiratama, Firman Dwi; Aryaputra, Safa; Parinduri, Syawaluddin Kadafi
Journal of Information System Research (JOSH) Vol 7 No 1 (2025): Oktober 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i1.7607

Abstract

Choosing the ideal internet package is a challenge for students in the Siantar-Simalungun region. Stable and affordable internet access is essential to support various academic activities, ranging from literature searches and assignment collection to online learning activities. When choosing an internet package, students generally consider several key factors such as price, network speed, signal strength, bonus quotas, and user satisfaction levels. This study uses the ORESTE (Organization, Rangement Et Synthèse De Données Relationnelles Extérieures) method as a multi-criteria decision-making approach to determine the most ideal internet package for students' needs. The research data was collected through a questionnaire distributed to more than 1,217 students from various educational institutions in the region. Through the calculation and analysis process using the ORESTE method, it was found that Telkomsel was the most ideal internet package choice with the lowest preference value of 1.774, which indicates the highest level of preference compared to other alternatives. The results of this study are expected to serve as a reference in helping students choose the internet package that best suits their needs, thereby increasing the efficiency of internet spending while supporting productivity and smooth academic activities with optimal internet access.

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