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JUSIFOR : Jurnal Sistem Informasi dan Informatika
Published by Universitas Islam Raden Rahmat Malang
ISSN : 28303393     EISSN : 28302443     DOI : https://doi.org/10.33379/jusifor.v1i2.1444
Core Subject : Science, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Engineering Library & Information Science
JUSIFOR adalah jurnal akses terbuka di bidang Informatika dan Sistem Informasi. Jurnal ini tersedia bagi para peneliti yang ingin meningkatkan pengetahuan mereka dibidang tertentu dan dimaksudkan untuk menyebarkan pengalaman hasil studi. JUSIFOR merupakan Jurnal penelitian ilmiah bidang informatika dan system informasi. Terbuka bagi siapa saja yang ingin mengembangkan ilmu pengetahuan berdasarkan penelitian yang berkualitas dibidang apapun. Artikel penelitian yang dikirimkan ke jurnal online ini akan di-peer-review. Jurnal ini diterbitkan oleh Prodi Sistem Informasi dan Teknik Informatika Fakultas Sains dan Teknologi, Universitas Islam Raden Rahmat. Jurnal ini diterbitkan sebanyak 2 kali dalam satu tahun, yaitu di bulan Juni dan Desember.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 87 Documents
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Perancangan Sistem Pakar Penyakit Gigi Berbasis Website dengan Metode Certainty Factor Risky, Muhammad Arif Zikir
JUSIFOR : Jurnal Sistem Informasi dan Informatika Vol 4 No 2 (2025): JUSIFOR - Desember 2025
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/jusifor.v4i2.7233

Abstract

One of the organizations that provides dental health care is Klinik Ceria. The problems include the inability to provide information to patients about their dental conditions and challenges in scheduling appointments with dentists because dentist offices are only open during certain hours, and patients need to contact the dentist to find out when they can schedule a consultation. The purpose of this study is to make it easier for people to have dental consultations and also to help people find out the results of dental disease consultations so that people can easily get solutions. The method used is the certainty factor, where the design of this expert system is based on a website developed with the PHP programming language and a MySQL database. The architecture of this system tests the validity of the hypothesis known as the certainty factor using information in the form of facts. According to the findings of the study, this method can produce the name of the condition that damages the teeth and its treatment. Depending on the disease data entered by the user, this program will also offer suggestions for handling and treating the condition.
Implementasi GIS untuk Pemetaan UMKM Berbasis Mobile Menggunakan Metode A* di Sumenep Haq, Nabil Huda Rizalul
JUSIFOR : Jurnal Sistem Informasi dan Informatika Vol 4 No 2 (2025): JUSIFOR - Desember 2025
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/jusifor.v4i2.8240

Abstract

Sumenep Regency has great potential in culinary tourism, supported by rich local culture and the widespread presence of culinary MSMEs. However, the lack of integrated information and navigation systems hinders effective exploration of these destinations. This study aims to develop a mobile-based culinary MSME mapping application by integrating Geographic Information System (GIS) and the A Star (A*) algorithm. The system was developed using Flutter for the frontend and Laravel for the backend, with communication via RESTful API. Data were collected through observation, interviews, and literature study. The implementation results show that the application successfully displays MSME locations, calculates the shortest route in real-time, and assists users in quickly and accurately finding culinary spots. Black-box testing indicates that all system features function correctly. This application contributes to the digital promotion of local MSMEs and offers an innovative solution for culinary tourism development in the region.
Evaluasi Usability Aplikasi PAK RT Berbasis WebGIS Menggunakan Model Nielsen H., S. Candra Hastuti; Gunadi , Gunadi; Arissaputra, Ahmad Redha
JUSIFOR : Jurnal Sistem Informasi dan Informatika Vol 4 No 2 (2025): JUSIFOR - Desember 2025
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/jusifor.v4i2.8255

Abstract

Prajuritkulon District, located in the City of Mojokerto, utilizes an innovative application called PAK RT (Neighborhood Supervision) to collect, display, and map data related to public order and security conditions within the district. The system was initially developed in 2022; however, it did not function effectively and was ultimately not utilized. In 2024, the system underwent a redesign. To evaluate the usability of the redesigned system, this study employed usability testing based on the Nielsen model, which includes Learnability, Efficiency, Memorability, Errors, and Satisfaction. The evaluation followed a series of procedural steps, including scenario-based testing, administration of the Nielsen Attributes of Usability (NAU) questionnaire, and interviews with administrative village operators. The results indicate positive usability outcomes, with scores of 74,93% for Learnability, 66,65% for Efficiency, 83,33% for Memorability, 69,44% for Errors, and 85,89% for Satisfaction. These findings suggest that neighborhood operators are delighted with the features and benefits of the web-based PAK RT application. Consequently, the redesign is considered successful in meeting reporting needs and providing added value to users.
Analisis Sentimen Komentar YouTube terhadap Video “Purbaya Effect: Pertaruhan Ekonomi Indonesia” sebagai Cerminan Persepsi Publik Tahun 2025 Susanto, Adi; Octavia, Imelda
JUSIFOR : Jurnal Sistem Informasi dan Informatika Vol 4 No 2 (2025): JUSIFOR - Desember 2025
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/jusifor.v4i2.8262

Abstract

Social media, particularly YouTube, has become a crucial platform in shaping public opinion regarding national economic issues. This study aims to analyze public sentiment towards Indonesia's economic policies through YouTube comments using a machine learning approach. The dataset consists of 1,637 comments, divided into 1,309 training data and 328 testing data, with four sentiment categories: Positive, Negative, Neutral, and Mixed Sentiment. The Support Vector Machine (SVM) LinearSVC algorithm was implemented alongside TF-IDF feature extraction. The results indicate that the SVM model achieved an accuracy of 85.37% with an efficient training time of 0.04 seconds. The sentiment distribution was dominated by Neutral (75.32%), followed by Positive (14.42%), Negative (7.15%), and Mixed Sentiment (3.12%). The best performance was achieved in the Neutral category with a precision of 0.87 and a recall of 0.99 (F1-score 0.93). However, the model demonstrated significant weaknesses due to severe class imbalance: the model completely failed to classify Mixed Sentiment (F1-score 0.00) and showed low performance on Negative (Recall 0.25). The majority of the public exhibited a wait−and−see attitude toward economic policies, indicating the maturity of economic literacy among the Indonesian society in responding to national issues.
Sistem Rekomendasi Masjid Ramah Pemudik Menggunakan Hybrid Rating Aggregation dan Location Based Filtering Berbasis Ulasan Pengguna (Studi Kasus Kabupaten Situbondo) Rhomadon, Rifal Rifqi; Irawan, Joseph Dedy; Wahyuni, Febriana Santi
JUSIFOR : Jurnal Sistem Informasi dan Informatika Vol 4 No 2 (2025): JUSIFOR - Desember 2025
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/jusifor.v4i1.8339

Abstract

The tradition of mudik in Indonesia increases public mobility during the festive season, including in Situbondo Regency. This condition creates a need for information about traveler-friendly mosques that can serve as places of worship as well as rest areas. However, limited information regarding mosque facilities and comfort often makes it difficult for travelers to find suitable locations. This study aims to develop traveler-friendly mosque recommendation system using the Hybrid Rating Aggregation and Location-Based Filtering methods based on user reviews. Sentiment analysis on user reviews was carried out using the Lexicon-Based Sentiment Analysis method to determine the tendency of positive or negative opinions toward each mosque. The result of the sentiment analysis are incorporated into scoring mechanism to improve the accuracy nor suitability of those recommendations. Performance system was performed using blackbox testing approach to verify that each feature performs as expected based on user needs. The results indicate that system operates effectively and is able to deliver mosque recommendations that are informative, reliable, and user-friendly.
Sistem Rekomendasi Judul Skripsi Menggunakan Cosine Similarity Pada JATI ITN Malang Nabila, Marita Putri; Irawan, Joseph Dedy; Faisol, Ahmad
JUSIFOR : Jurnal Sistem Informasi dan Informatika Vol 4 No 2 (2025): JUSIFOR - Desember 2025
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/jusifor.v4i2.8340

Abstract

Pertumbuhan publikasi ilmiah yang meningkat di lingkungan kampus mendorong mahasiswa untuk menghasilkan skripsi yang orisinal dan relevan. Namun, meningkatnya jumlah publikasi sering membuat mahasiswa kesulitan menentukan judul skripsi karena pencarian referensi masih sederhana. Penelitian ini bertujuan untuk membangun sistem rekomendasi judul skripsi dengan algoritma Cosine similarity untuk membantu mahasiswa memperoleh referensi dalam menentukan judul skripsi serta mencegah duplikasi topik penelitian. Sistem ini menggunakan dataset publikasi JATI (Jurnal Mahasiswa Teknik Informatika) ITN Malang, melalui tahapan preprocessing teks, pembobotan TF-IDF, serta perhitungan cosine similarity dalam mengukur tingkat kemiripan judul publikasi di JATI ITN Malang. Evaluasi dilakukan dengan metode Confusion Matrix untuk menilai performa sistem dalam memberikan rekomendasi yang relevan. Hasil pengujian menunjukkan nilai akurasi sebesar 90%, precision 100%, recall 83,33%, dan F1-score 90,91%. Berdasarkan hasil yang diperoleh, sistem terbukti mampu merekomendasikan judul skripsi yang sesuai, sehingga dapat membantu mahasiswa dalam proses penentuan judul sebagai acuan penyusunan skripsi.
Perancangan Sistem Perencanaan Konten Media Sosial Berbasis Web Terintegrasi Artificial Intelligence (AI) Bagi UMKM Menggunakan Framework Next.js dengan Model Prototype Gunawan, Nasrullah; Nasution, Muhammad Irwan Padli
JUSIFOR : Jurnal Sistem Informasi dan Informatika Vol 4 No 2 (2025): JUSIFOR - Desember 2025
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/jusifor.v4i2.8343

Abstract

Digital marketing through social media is crucial for the sustainability of MSMEs, yet many business owners face challenges such as inconsistent schedules, difficulty finding content ideas, and limited time for drafting captions. The purpose of this study is to create a web-based social media content planning system utilizing AI to help MSMEs manage their marketing better. The system development method used is the Software Development Life Cycle (SDLC) with the Prototype model, comprising requirement gathering, quick design, prototype building, and user evaluation phases. The system utilizes the Next.js framework, TailwindCSS, and Supabase, along with the IBM Granite Instruct AI model for automated caption features. The results produced a system design featuring an interactive content calendar, publication status management, and an AI assistant. Evaluations indicate the system is proven effective in organizing content planning. Development of automated publishing features, multi-user collaboration support, and deeper content performance analytics are recommended for future research stages.
Redesign Sistem Karya Akhir Universitas Pendidikan Ganesha menggunakan Pendekatan Design Thinking Putra, Decky Pratama; Arthana, I Ketut Resika; Putra, I Nyoman Tri Anindia
JUSIFOR : Jurnal Sistem Informasi dan Informatika Vol 4 No 2 (2025): JUSIFOR - Desember 2025
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/jusifor.v4i2.8357

Abstract

The Final Project System at Undiksha plays an essential role in supporting academic administration; however, initial findings reveal issues related to navigation flow, interface clarity, and system feedback that reduce usability. This study analyzes the system’s usability and proposes a redesign using the Design Thinking approach through empathize, define, ideate, prototype, and test stages. The pre-test evaluation indicated an effectiveness and efficiency score of 79.99% and a QUIS satisfaction score of 3.70. After implementing improvements in navigation, progress visualization, layout consistency, and responsive feedback, post-test results increased effectiveness to 91.67% and efficiency to 91.67%, while the satisfaction score rose to 4.74, representing a 28.1% improvement. These results demonstrate that the proposed redesign significantly reduces user errors, accelerates task completion, and enhances overall interaction quality. The study contributes empirical evidence supporting iterative interface improvements to optimize academic web services.
Paradigma Epistemologis Kompresi Data Teks: Huffman, Arithmetic, dan Neural Language Model Affandi, Luqman; Prasetya, Didik Dwi; Patmanthara, Syaad
JUSIFOR : Jurnal Sistem Informasi dan Informatika Vol 4 No 2 (2025): JUSIFOR - Desember 2025
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/jusifor.v4i2.8384

Abstract

This study explores text data compression as an epistemological paradigm through a comparative analysis of three fundamental approaches: traditional methods (Huffman Coding + LZW), bit-based methods (Arithmetic Coding), and machine learning approaches (Neural Language Models). Using the Project Gutenberg dataset comprising 15,000 classical literary works with a total size of 8.5 GB and 2.1-billion-word tokens, the evaluation is conducted based on compression ratio, execution time, and memory usage. The results reveal fundamental trade-offs among the paradigms. Traditional methods achieve the fastest execution (8.3 seconds/GB, 482 MB/s, 52 MB) with a compression ratio of 3.2:1. Arithmetic coding attains near-optimal performance (99.5% of the Shannon bound) with a compression ratio of 3.8:1. Neural language models yield the highest compression ratio of 4.6:1 but require substantially higher execution time and memory. The epistemological analysis highlights distinct conceptions of information—mechanistic, mathematically optimal, and semantic-aware—and provides a conceptual framework for developing adaptive compression systems.
Identifikasi Penyakit Bercak Daun Kelapa Sawit Menggunakan Algoritma CNN dengan Arsitektur VGG19 Berbasis Citra Digital Fadllullah, Arif; Erdina, Sri
JUSIFOR : Jurnal Sistem Informasi dan Informatika Vol 4 No 2 (2025): JUSIFOR - Desember 2025
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/jusifor.v4i2.8391

Abstract

This study aims to develop a digital image-based system for identifying leaf spot diseases in oil palm plants using the CNN (Convolutional Neural Network) algorithm with the VGG19 architecture. The dataset consists of 330 primary oil palm leaf images categorized into three classes: leaves infected with leaf rust, healthy leaves, and leaves infected with curvularia. The dataset was divided into 64% training data, 16% validation data, and 20% testing data. The system development process includes preprocessing, data augmentation, data splitting, model training using the VGG19 architecture, and model evaluation. The training results over 200 epochs achieved an accuracy of 0.93 on the training data and 0.98 on the validation data. Model evaluation on the test data produced precision, recall, and F1-score values of 0.94, 0.81, and 0.87 for the “Leaf Rust” class; 0.84, 0.95, and 0.89 for the “Healthy Leaf” class; and 1.00 for the “Curvularia” class. The testing results indicate consistent performance, suggesting that the proposed system is effective in classifying oil palm leaf spot diseases. The developed system has the potential to be used as an early detection tool for leaf spot diseases to support the improvement of oil palm productivity.

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