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Jurnal Publikasi Teknik Informatika
Published by Universitas Sains Dan Teknologi Komputer
ISSN : 28089367     EISSN : 28088972     DOI : 10.55606
Core Subject : Science,
Computer Science & IT
Jurnal Publikasi Teknik Informatika diterbitkan oleh Universitas Sains dan Teknologi Komputer Semarang. Jurnal Publikasi Teknik Informatika memuat naskah hasil-hasil penelitian di bidang Teknik Informatika, Teknik Komputer, Teknik Elektro. JUPTI berkomitmen untuk memuat artikel berbahasa Indonesia yang berkualitas dan dapat menjadi rujukan utama para peneliti dalam bidang ilmu Teknik Informatika, Teknik Komputer, Teknik Elektro
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 151 Documents
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Klasifikasi Penyakit pada Daun Padi Menggunakan Teknik Pengolahan Citra dan Convolutional Neural Network
Jurnal Publikasi Teknik Informatika Vol. 5 No. 1 (2026): Januari: Jurnal Publikasi Teknik Informatika
Publisher : Universitas Sains dan Teknologi Komputer Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupti.v5i1.6694

Abstract

Rice cultivation plays a crucial role in national food security, but is often hampered by leaf disease attacks that significantly impact production decline. To address this challenge, this study designed an application based on the Convolutional Neural Network (CNN) algorithm to classify rice leaf diseases automatically and accurately. Data collection was conducted through direct observation at Gapoktan (Farmer Group Association) in Kuningan Regency, interviews with farmers, literature studies, and system development using the Rapid Application Development (RAD) approach, which enables rapid and structured application development. The CNN model was tested using 480 sample images and achieved a high accuracy of 97.75%. The F1-Score values ​​obtained were 0.97 for Brown Spot, 0.921 for Blast, 0.871 for Hispa, and 0.952 for healthy leaves. These results indicate that the application is capable of early disease detection, enabling farmers to take immediate preventive measures to minimize crop losses. To improve performance, it is recommended to apply optimization techniques to the CNN model, such as dataset expansion, various dataset augmentation techniques, and evaluation of high-complexity images. Development into other disease classifications is also highly potential. Overall, this application has significant potential to support digital agriculture and realize a more sustainable and modern rice farming system.
Sistem Rekomendasi Komponen Rakit PC dengan Algoritma Greedy dan Rule-Based Filtering Samuel Yahya; Prasetiyo, Daniel; Putra, Gabriel; Christian, Timothy; Tundjungsari, Vitri
Jurnal Publikasi Teknik Informatika Vol. 5 No. 2 (2026): Mei: Jurnal Publikasi Teknik Informatika
Publisher : Universitas Sains dan Teknologi Komputer Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupti.v5i2.6527

Abstract

Beragam komponen komputer berkembang dengan pesat karena meningkatnya kebutuhan pengguna merakit PC atau personal computer untuk sesuai kebutuhan pekerjaan seperti pekerjaan 3D, desain grafis, video editing, gaming, dan lain-lain. Namun variasi, kompatibilitas, dan harga sering membuat banyak pengguna kesulitan menentukan kombinasi yang optimal dan sebanding dengan biaya yang dikeluarkan. Penelitian ini bertujuan membangun sistem rekomendasi komponen rakit pc sederhana yang dapat memberikan saran komponen terbaik sesuai anggaran pengguna. Sistem ini menerapkan Algoritma Greedy dengan tambahan konteks untuk memilih komponen. Pemilihan diprioritaskan berdasarkan skor CPU Mark dan G3D Mark. Rule-based filtering yang ketat diterapkan di awal untuk menyaring komponen berkualitas rendah, memastikan hanya ada komponen yang modern dan andal. Sistem dikembangkan dengan memanfaatkan dataset komponen PC yang didapat dari PCPartPicker yang mencakup komponen inti dari PC seperti CPU, RAM, storage, case, dan PSU. Hasil pengujian menunjukan sistem rekomendasi sederhana yang dibangun dengan algoritma Greedy dan Rule-Based Filtering dapat menghasilkan rakitan PC yang efisien dan sesuai anggaran. Kombinasi antara kedua metode menghasilkan sistem rekomendasi yang cepat, akurat, dan relevan dengan hasil yang dikeluarkan.
Implementasi IoT untuk Otomatisasi Proses Peminjaman Buku Menggunakan NodeMCU dan RFID Terintegrasi REST API Ulil Albab; Muhamad Bakhar; Dany Sucipto; Qirom Qirom
Jurnal Publikasi Teknik Informatika Vol. 5 No. 2 (2026): Mei: Jurnal Publikasi Teknik Informatika
Publisher : Universitas Sains dan Teknologi Komputer Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupti.v5i2.7031

Abstract

Library management at SMK Muhammadiyah Adiwerna still faces obstacles in the manual book lending process, making it less efficient and potentially leading to recording errors. This study aims to implement an Internet of Things (IoT)-based system using NodeMCU ESP8266 and RFID RC522 to automate the book identification and lending process integrated with REST API. The research methods include hardware design, firmware development using Arduino IDE, and system integration via the HTTP POST protocol with a backend based on the Yii2 framework. The results show that the system is able to read the UID of RFID cards, send data to the server, and process verification in real-time. Verification results are displayed via an I2C-based LCD as direct feedback to users. The implementation of this system has been proven to increase efficiency and accuracy in the book lending process, as well as reduce dependence on manual input. In addition, the system provides convenience in monitoring borrowing data in a centralized and integrated manner. The use of this technology supports the digitalization of library services in a more modern way. Therefore, the developed system has the potential to be implemented more widely in other educational institutions.
Implementasi Teknologi Internet of Things (IoT) pada Pengawasan Kualitas Air Sungai Mahakam Secara Real-Time Putri Nur Halizah; Dwi Titi Maesaroh; Ansar Rizal
Jurnal Publikasi Teknik Informatika Vol. 5 No. 2 (2026): Mei: Jurnal Publikasi Teknik Informatika
Publisher : Universitas Sains dan Teknologi Komputer Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupti.v5i2.7054

Abstract

River water quality acts as a key benchmark for preserving ecological harmony and community well-being, particularly for the Mahakam River, which plays a vital role in everyday activities across East Kalimantan. That said, traditional manual monitoring falls short on time savings and steady data flow. This research focuses on deploying Internet of Things (IoT) tech for a real-time water quality tracking system on the Mahakam River. The approach involves designing and setting up a system with a NodeMCU ESP8266 microcontroller linked to a pH sensor for acidity levels, a Total Dissolved Solids (TDS) sensor for dissolved particles, and a DS18B20 temperature sensor. Measurement data gets sent over the internet, letting users check water status right away on a monitoring device or OLED screen. Testing shows the system runs reliably, delivering ongoing water quality metrics. Recorded pH levels sat between 6.5 and 7.2, with TDS from 120 to 350 ppm—meaning the water stays within safe norms, though affected by nearby environmental actions. This setup simplifies automatic, ongoing water quality oversight and boosts smart tech-driven resource management.
Implementasi Chatbot Berbasis RAG pada Sistem Informasi Rawat Jalan Klinik Putu Surya Jaya Permana; Ni Luh Putu Ika Candrawengi
Jurnal Publikasi Teknik Informatika Vol. 5 No. 2 (2026): Mei: Jurnal Publikasi Teknik Informatika
Publisher : Universitas Sains dan Teknologi Komputer Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupti.v5i2.7063

Abstract

Healthcare services require fast and accurate access to operational information such as doctor schedules, drug availability, patient registration procedures, and outpatient administration. Conventional information systems often require users to manually search through menus, which can reduce efficiency and slow service processes. This study aims to implement a Retrieval-Augmented Generation (RAG)-based chatbot integrated into an outpatient information system at Bina Usada Clinic. The system was developed using the Waterfall method and implemented through the Laravel framework with MySQL as the primary database. Internal clinic data were processed as a knowledge base using text chunking, vector embeddings, and semantic retrieval to enable context-aware responses. The chatbot also applied role-based guardrails to ensure secure access between clinic staff and patients. System functionality was evaluated using Black Box Testing, while chatbot performance was assessed through comfort and utility dimensions involving 25 respondents consisting of clinic staff and patients. The results showed that all system functions operated successfully with a 100% validity rate. In addition, the chatbot obtained an average score of 88.24%, indicating a high level of user acceptance and usefulness. The implementation of the RAG chatbot improved information accessibility, reduced manual search time, and supported digital transformation in outpatient healthcare services. These findings indicate that integrating chatbot technology into healthcare information systems can enhance operational efficiency and user experience.
Rancang Bangun Aplikasi Pengelolaan Data Statistik Sosial Berbasis Web menggunakan Metode Kanban Odista Dwi Putra; Ulfa Khaira; Rizqa Raaiqa Bintana
Jurnal Publikasi Teknik Informatika Vol. 5 No. 2 (2026): Mei: Jurnal Publikasi Teknik Informatika
Publisher : Universitas Sains dan Teknologi Komputer Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupti.v5i2.7101

Abstract

Statistical data is a crucial foundation for evidence-based government policymaking and public accountability. The Social Statistics Division of Badan Pusat Statistik (BPS) Jambi Province currently manages its data through fragmented Microsoft Excel files, causing inefficiencies such as difficulty locating tables, vulnerability to manual entry errors, and the absence of a structured verification pathway before data reaches external users. This study designed and developed SISTADISS (Sistem Pengelolaan Data Statistik Sosial), a web-based application for social statistics data management, using the Kanban agile development method. The system was built using Next.js, Neon PostgreSQL, Prisma ORM, and Tailwind CSS. Authentication is implemented through an SSO integration for internal BPS staff and a bcryptjs-JWT mechanism for external users. Development was conducted across four iterative cycles: user authentication, dynamic statistical table display, data management via a change-request workflow, and a multi-level verification module. All nineteen functional requirements were validated through black-box testing, yielding a 100% pass rate across three user roles: Admin Verifikasi, Petugas, and Pengguna. The system was deployed on Vercel and is accessible at the BPS Jambi Province institutional domain.
Perbandingan Algoritma Apriori dan FP-Growth dalam Menemukan Pola Asosiasi pada Data Penjualan Produk Ritel di Toko IT Amaliyah Dwi Ardiani; Margaretha Pereta Kein; Siti Marfuah; Novita Wanti Hallatu
Jurnal Publikasi Teknik Informatika Vol. 5 No. 2 (2026): Mei: Jurnal Publikasi Teknik Informatika
Publisher : Universitas Sains dan Teknologi Komputer Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupti.v5i2.7173

Abstract

A method known as data mining is used to discover hidden patterns in very large data sets. Shopping cart analysis, also known as "shopping cart analysis," is one of the most common techniques in the retail industry that utilizes association rules. The focus of this study is to discover association patterns between the Apriori Algorithm and FP-Growth on sales transaction data of information technology (IT) products in a retail store. The dataset used consists of 7,496 transactions, with a maximum of 20 items and an average of 3.91 items, respectively. The raw data before analysis contained 137 different product names. After preprocessing and name standardization, 75 products met the minimum support threshold of 1%. They were also tested with a minimum support parameter of 1% and a minimum confidence level of 30%. Both algorithms generated 253 frequently occurring itemsets and 63 association rules. The SanDisk Ultra 64GB and SanDisk Ultra 128GB microSDXC cards had the highest lift score of 3.4225. By requiring only two database scans, FP-Growth excels in computational efficiency. One can use these results to create cross-selling and reordering strategies.
Efektivitas Sistem Informasi Prestasi Mahasiswa (SIPRESMA) dalam Pengelolaan Data Prestasi Mahasiswa UKM Pelita di Universitas Tidar Khorin Noor Latifah; Izzatul Yazidah; Oktavia Ramadhani; Tiara Novita Sari; Ranti Nisrina Mufidah
Jurnal Publikasi Teknik Informatika Vol. 5 No. 2 (2026): Mei: Jurnal Publikasi Teknik Informatika
Publisher : Universitas Sains dan Teknologi Komputer Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupti.v5i2.7229

Abstract

This study aims to analyze the effectiveness of the Student Achievement Information System (SIPRESMA) in managing student achievement data of UKM Pelita at Universitas Tidar. The study employed a quantitative approach with a descriptive research method. The population consisted of 305 members of UKM Pelita, with a sample of 76 respondents determined using the Slovin formula with a 10% margin of error. The sampling technique used was simple random sampling. Data collection was conducted through questionnaires based on the DeLone and McLean Information System Success Model, which includes system quality, information quality, service quality, use, user satisfaction, and net benefits. Data analysis was carried out using validity tests, reliability tests, descriptive analysis, t-tests, and the coefficient of determination (R²) with the assistance of IBM SPSS Statistics. The results showed that all questionnaire items were valid and reliable. The hypothesis testing results indicated a significance value of <0.001, meaning that the effectiveness of SIPRESMA has a positive and significant effect on the management of student achievement data of UKM Pelita at Universitas Tidar. The coefficient of determination (R²) value of 0.660 indicates that the effectiveness of SIPRESMA explains 66% of the variation in student achievement data management, while the remaining 34% is influenced by other factors outside the study. Overall, SIPRESMA is considered capable of facilitating data management, improving work efficiency, accelerating access to information, and providing user satisfaction. However, several issues such as system stability, service responsiveness, and consistency of data updates still need improvement to optimize the effectiveness of the system.
Pengaruh Social Media dan Marketplace Terhadap Minat Beli Produk Sepatu Bola Handin Arif Rahmawati; Budi Hartono; Migunani Migunani
Jurnal Publikasi Teknik Informatika Vol. 5 No. 2 (2026): Mei: Jurnal Publikasi Teknik Informatika
Publisher : Universitas Sains dan Teknologi Komputer Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupti.v5i2.7303

Abstract

This study aims to analyze the influence of social media and marketplaces on consumers' purchase intention toward online football shoes products in Indonesia. The research employed a quantitative approach with a causal descriptive design. The sampling technique used was purposive sampling, resulting in 102 respondents who had searched for or purchased football shoes through social media and marketplace platforms. Data were collected through a Google Form questionnaire and analyzed using multiple linear regression with SPSS version 25. The validity test showed that all 24 questionnaire items had correlation coefficients higher than the critical value (r > 0.361), while the reliability test indicated Cronbach’s Alpha values above 0.70, confirming that the instrument was valid and reliable. The regression equation obtained was Y = 4.614 – 0.045X₁ – 0.096X₂, with a coefficient of determination (R²) of 0.010. The partial t-test results revealed that social media (Sig. = 0.666) and marketplace (Sig. = 0.347) had no significant effect on purchase intention. Likewise, the simultaneous F-test showed that both variables did not significantly affect purchase intention (F = 0.507; Sig. = 0.604). Nevertheless, descriptive analysis indicated high mean scores for social media (4.015), marketplace (3.983), and purchase intention (4.051), suggesting that respondents held highly positive perceptions of digital marketing for football shoes products. The insignificant inferential results were likely influenced by data homogeneity and a ceiling effect, which limited the variability of respondents’ answers.
Analisis Penggunaan Kecerdasan Buatan terhadap Kemampuan Berpikir Kritis Mahasiswa Informatika: Pendekatan MMSLR Louise Gabriella; Usman Arfan; Imanuel Aji Karisteo
Jurnal Publikasi Teknik Informatika Vol. 5 No. 2 (2026): Mei: Jurnal Publikasi Teknik Informatika
Publisher : Universitas Sains dan Teknologi Komputer Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupti.v5i2.7326

Abstract

The rapid development of artificial intelligence (AI) has significantly transformed learning processes in higher education, particularly in Informatics education, where critical thinking skills are essential for solving computational problems. On the one hand, AI offers various advantages in accessing information, supporting problem-solving activities, and improving learning effectiveness. On the other hand, inappropriate use of AI may lead to cognitive dependency that can affect students' critical thinking abilities. This study aims to analyze the relationship between AI usage and the critical thinking skills of Informatics students through a Mixed Method Systematic Literature Review (MMSLR) approach. The study integrates quantitative mapping and qualitative synthesis of 25 selected articles retrieved from several academic databases based on predetermined inclusion criteria. The findings indicate that AI can function as cognitive scaffolding that supports analysis, evaluation, reflection, and problem-solving processes. Furthermore, AI literacy and self-regulated learning were identified as key factors influencing the effectiveness of AI utilization in learning activities. However, passive use of AI without information verification may reduce students' engagement in independent thinking processes. This study highlights the importance of integrating AI literacy and self-regulated learning into AI-based educational strategies to strengthen critical thinking skills in higher education.

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