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Sistem Informasi Perpustakaan Berbasis Website Menggunakan Repository Pattern Agung Stiven Cahyati Angely; Lapatta, Nouval Trezandy; Syahrullah; Andi Hendra; Ryfial Azhar
The Indonesian Journal of Computer Science Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i5.4332

Abstract

Pengembangan Sistem Informasi Perpustakaan Sekolah menggunakan Metode Repository Pattern bertujuan meningkatkan efisiensi dan efektivitas pengelolaan perpustakaan yang sebelumnya dilakukan secara konvensional. Sistem informasi berbasis web ini mempermudah pencatatan peminjaman, pengembalian buku, dan pengelolaan data lainnya. Hasil penelitian menunjukkan peningkatan kualitas pengelolaan perpustakaan, dengan akses informasi yang lebih cepat dan akurat. Mayoritas pengguna menyatakan puas dengan antarmuka sistem yang intuitif dan user-friendly. Sistem ini juga memudahkan pustakawan dan admin dalam mengelola data, mencatat peminjaman dan pengembalian buku, serta mengorganisasikan kategori buku. Kesimpulannya, penerapan sistem informasi perpustakaan berbasis web dengan metode Repository Pattern di SMK Negeri 3 Palu berhasil meningkatkan efektivitas dan efisiensi pengelolaan perpustakaan, serta memberikan kemudahan akses bagi pengguna.
Artikel Analisis Sentimen terhadap Resolusi Genjatan Senjata PBB 2023: Studi pada 10 Negara Penolak Resolusi Konflik Israel-Palestina Qofifa, Sitti Nurlaili; Ardiansyah, Rizka; Joefrie, Yuri Yudhaswana; Wirdayanti; Lapatta, Nouval Trezandy
The Indonesian Journal of Computer Science Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i5.4405

Abstract

The Israeli-Palestinian conflict is the longest conflict that still has not found a bright spot. In December 2023 the UN again gave the latest resolution with the title “Armistice” this resolution received pros and cons from UN member states. The number of pro countries is 150 countries, contra as many as 10 countries and 23 countries abstain. This study aims to investigate whether the 10 countries that voted against the UN resolution represent the interests of their people or only represent the interests of their country. This research approach uses sentiment analysis on platform X with the Support Vector Machine method. Data was taken from March 2024 to the latest data, 137,447 data were obtained with 5 countries using non-English languages and 4 countries using English. Each data from these countries was successfully classified into positive and negative classes. The survey was conducted on 9 countries with an average positive sentiment of 34.82% and an average negative sentiment of 77.41%. The results of this research show that the decisions made by the 10 countries that rejected the resolution represent the voice of their people.
Implementation of QR Code in A Student Attendance Information Based On WhatsApp Gateway Karnita Sumbaluwu, Harlin Feby; Angreni, Dwi Shinta; Pusadan, Mohammad Yazdi; Lamasitudju, Chairunnisa; Lapatta, Nouval Trezandy
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 2 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i2.6308

Abstract

The attendance information system at Senior High School 7 Sigi, still uses a manual attendance system, namely writing on paper sheets. The problem that often occurs is the loss of student attendance books which causes the school to have difficulty in recapitulating attendance and also reporting attendance to parents. Another problem that occurs due to manual attendance is that parents cannot directly monitor their children's attendance at school which causes some students to skip school. The recommended solution is to use an attendance information system by utilizing QR Code technology so that student attendance is more practical and also the data storage is much safer. WhatsApp Gateway is used as a monitoring medium for parents because this system will send notifications via the WhatsApp application every time the lesson starts, effectively and in real-time. This attendance system uses the Waterfall method which starts from the planning, analysis, design and implementation stages
Optimization of Inventory Management with QR Code Integration and Sequential Search Algorithm: A Case Study in a Regional Revenue Office Fajar, Moh; Azhar, Ryfial; Anshori, Yusuf; Laila, Rahma; ., Rinianty; Lapatta, Nouval Trezandy
Journal of Applied Informatics and Computing Vol. 9 No. 2 (2025): April 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i2.8919

Abstract

Inventory management at a government office was previously conducted manually, leading to issues such as data inaccuracies, delays in item searches, and low work efficiency. This study develops a web-based inventory management system integrated with QR Code technology and a sequential search algorithm to address these challenges. The system was developed using the prototyping method, with iterative design based on user feedback until the final version met the office's operational needs. Key features of the system include digital inventory recording, item tracking using QR Codes, and real-time information access through a web-based interface. The system was tested in two stages: simulation and direct implementation in a real-world environment, involving 10 respondents to evaluate effectiveness and usability. The test results showed a 95% improvement in data recording accuracy, a 60% reduction in item search time, and an average user satisfaction score of 77.25 based on the System Usability Scale (SUS). This research successfully improved inventory management efficiency and demonstrated the system’s potential for adoption by other similar organizations, with modular adjustments tailored to their needs.
Comparative Performance Analysis of GRPC and Rest API Under Various Traffic Conditions and Data Sizes Using a Quantitative Approach Ain, Moch. Zukhruf; Rizka Ardiansyah; Septiano Anggun Pratama; Muhammad Akbar; Nouval Trezandy Lapatta
Journal of Applied Informatics and Computing Vol. 9 No. 2 (2025): April 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i2.9276

Abstract

Web 3.0 presents challenges in efficient data exchange, especially in decentralized systems. REST API (HTTP/1.1) remains widely used due to its broad compatibility but has communication inefficiencies, while gRPC (HTTP/2) offers better performance with multiplexing and Protocol Buffers. This study compares REST API and gRPC under various traffic conditions and data sizes using Apache JMeter and Wireshark, measuring throughput, response time, latency, and data transfer efficiency. Results show that REST API has higher throughput in low-traffic scenarios (995 vs. 29.5 req/min) and faster GET response time (3 ms vs. 20 ms), while gRPC excels in large data transfers (276.34 KB/s vs. 134.1 KB/s) and stable latency (0.147 ms). However, ANOVA analysis (p > 0.05) indicates no statistically significant difference. REST API is ideal for standard web applications, while gRPC is suited for microservices and real-time systems.
Digitalization of Legal Information Management in Primary Schools Based on the JDIH Application: Digitalisasi Manajemen Informasi Hukum Sekolah Dasar Berbasis Aplikasi JDIH Saada, Rahmadian A.; Lapatta, Nouval Trezandy
Technomedia Journal Vol 10 No 1 (2025): June
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v10i1.2269

Abstract

The rapid development of science and technology in the education sector has prompted institutions like the elementary school to improve the efficiency and effectiveness of information and legal management. This study aims to develop a Legal Documentation and Information Network (JDIH) application to facilitate the publication of school regulations. The primary objective of this research is to create an application that simplifies the management of student and school information, ensuring compliance with educational laws, and fostering an adaptive educational environment. The research used the System Development Life Cycle (SDLC) methodology, utilizing the Waterfall Model approach, which includes planning, analysis, design, implementation, testing, and maintenance. Data was gathered through observation, interviews, and literature studies, ensuring comprehensive insights into the existing regulatory management practices at the school. The JDIH application was successfully developed and implemented at the elementary school. It improved the accessibility of school regulations, ensuring better legal compliance and enhancing transparency. Positive feedback was received from respondents, with an average satisfaction level of 83.3%. This study demonstrates the effectiveness of the JDIH application in streamlining regulatory management. It is expected that the application will be expanded to other schools, further improving the management of legal information and promoting a more transparent and efficient educational environment.
Implementation of Brute Force Algorithm for Digital Land Mapping Information System: Implementasi Algoritma Brute Force untuk Sistem Informasi Pemetaan Tanah Digital Irfan, Mohamad; Ngemba, Hajra Rasmita; Hendra, Syaiful; Syahrullah, Syahrullah; Lapatta, Nouval Trezand; Hamid, Odai Amer
Technomedia Journal Vol 10 No 1 (2025): June
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v10i1.2271

Abstract

The Land Asset Mapping Information System of the Palu City Local Government was developed to streamline digital land record management and enhance public service delivery. However, users experience substantial delays averaging 3-5 minutes per query during manual data searches. This study aims to optimize search efficiency by implementing the Brute force string-matching algorithm, allowing users to retrieve precise land records through direct pattern input. A waterfall system development methodology was systematically applied across five phases: requirements analysis, system design, PHP/JavaScript implementation, White Box testing, and maintenance. The research team collaborated closely with 12 technical officers from the City Spatial Planning and Land Office to validate system requirements and evaluate real-world performance. The implementation of the Brute force algorithm reduced average search times by 68\% (from 185s to 59s) while maintaining 100\% accuracy in test datasets containing 5,000+ land records. Rigorous testing confirmed the algorithm's reliability across various edge cases, including partial matches and special character inputs. The application of the Brute force method has transformed the system's search functionality, particularly for frequent queries involving land parcel IDs and owner names. These improvements have increased daily processing capacity by 40\%, significantly benefiting urban planning and dispute resolution workflows. While demonstrating excellent performance for medium-sized datasets, the solution presents opportunities for future enhancement through hybrid approaches combining Brute force with indexing techniques for large-scale deployments beyond 50,000 records.
Land Cover Analysis with Fully Convolutional Network Ihwan, Abib Raifmuaffah; Lapatta, Nouval Trezandy; Joefrie, Yuri Yudhaswana; Anshori, Yusuf; Syahrullah, Syahrullah
Jurnal Sistem Cerdas Vol. 8 No. 1 (2025)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v8i1.496

Abstract

This study analyses land cover in Morowali Regency using Sentinel-2 satellite imagery and the Fully Convolutional Network (FCN) algorithm. Land cover analysis in this area is crucial for monitoring rapid industrialization, especially in the mining sector. The methodology includes retrieving image data from Google Earth Engine, image processing to eliminate cloud influences, and model training using the European Space Agency (ESA) datasets. The results of the analysis show that 50% of the Morowali Regency area has the potential to be planted with trees, followed by 20% for water areas, and the rest for bushes, development land, and empty land. This study proves that FCN can be relied on to predict land potential with high accuracy with a loss value of 1.3001.
Utilization of EfficientNet-B0 to Identify Oncomelania Hupensis Lindoensis as a Schistosomiasis Host Lamadjido, Moh. Raihan Dirga Putra; Laila, Rahmah; Pusadan, Mohammad Yazdi; Yudhaswana, Yuri; Lapatta, Nouval Trezandy; Ngemba, Hajra Rasmita
Journal of Applied Informatics and Computing Vol. 9 No. 3 (2025): June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i3.9058

Abstract

Schistosomiasis caused by the Schistosoma japonicum worm is a significant health problem in Indonesia, especially in endemic areas such as the Napu Plateau and Bada Plateau. The main problem in controlling this disease is the difficulty in rapid and accurate identification of Oncomelania hupensis lindoensis snails as intermediate hosts of the parasite. This research aims to develop an artificial intelligence-based system that can efficiently identify the snail species. The stages of this research include collecting snail image data from the Central Sulawesi Provincial Health Office, consisting of 2100 images covering seven snail species, then processed through preprocessing and augmentation stages. The model applied was EfficientNet-B0. The results showed that the EfficientNet-B0 model achieved 98.80% training accuracy and 98.33% validation accuracy. Confusion matrix testing showed good performance, with an accuracy of 98% and for the species Oncomelania hupensis lindoensis had a recall of 93%, precision of 100%, F1-score of 97%, and the resulting AUC value of 99.7%. This research successfully developed an efficient identification system, which is expected to help health surveillance personnel in accelerating the identification process of schistosomiasis intermediate hosts.
CNN Algorithm for Herbal Leaf Classification Using MobileNetV2 and ResNet50V2 Pagiu, Harry T.; Kasim, Anita Ahmad; Lapatta, Nouval Trezandy; Pratama, Septiano Anggun; Laila, Rahma
CCIT (Creative Communication and Innovative Technology) Journal Vol 18 No 2 (2025): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/ccit.v18i2.3776

Abstract

Indonesia is home to over 30,000 types of herbal plants, with approximately 1,200 species utilized as raw materials for alternative and traditional medicine. Leaves play a crucial role in herbal medicine preparation. However, many people struggle to identify different herbal leaves due to their similar appearances, making classification difficult. Each leaf possesses unique characteristics such as shape, size, midrib, stalk, blade, and type, which can be used for differentiation. To assist in identifying herbal leaves, a classification system based on image recognition is essential. Convolutional Neural Networks (CNN) are deep learning algorithms designed for processing two-dimensional image data. Model performance can be enhanced through transfer learning, with MobileNetV2 and ResNet50V2 being widely used architectures. These pretrained models have been trained to recognize images with high accuracy. This study focuses on classifying herbal plants based on leaf shape using CNN architectures from MobileNetV2 and ResNet50V2. The evaluation results show that the MobileNetV2 architecture, with a 90%:10% data split, achieved an accuracy of 98.51%, precision of 98.92%, recall of 98.51%, and an F1-score of 98.56%. These findings indicate that CNN with transfer learning can effectively classify herbal leaves with high accuracy.
Co-Authors ., Rezki Abdillah Sani, Ilham Abdul Mahatir Najar Abdullah Abdullah Adhira Putri, Dhivanny Agung Stiven Cahyati Angely Ain, Moch. Zukhruf Amriana Amriana Andhyka, Andhyka Andi Hendra Andi Hendra Angraeni, Dwi Shinta Anita Ahmad Kasim Anita, Ayu Arsita, Tiara Juli Asriani Asriani, Asriani Ayu Hernita Bakri Chairunnisa Ar. Lamasitudju Chandra, Ferri Rama Darojah, Murtafiatun Delia, Fenita Deni Luvi Jayanto Deny Wiria Nugraha Djohari, Riyandi Dwitama Dwi Shinta Angreni Dwimanhendra, Muhammad Rifaldi Fahlevi, Mohammad Fazrin Fajar, Moh Fajriyah, Nurul Faldiansyah, Faldiansyah Firzatullah, Raden Muhamad Hajra Rasmita Ngemba Hamid, Odai Amer Hanama, Ikhsan Wahyudin Ihalauw, Sahron Angelina Ihwan, Abib Raifmuaffah Karnita Sumbaluwu, Harlin Feby Kartika, Rina Laila, Rahma Lamadjido, Moh. Raihan Dirga Putra Lamasitudju, Chairunnisa Mandra Maulana, Muhammad Syahputra Mohamad Irfan, Mohamad Mohammad Yazdi Pusadan Muhammad Akbar Muhammad Akbar Mutiara Sari Ngemba, Hajra Ningsih, Alief Surya Noviantika, Noviantika Pagiu, Harry T. Priska, Salsa Dilah Qofifa, Sitti Nurlaili Rahmah Laila Rasmita Ngemba, Hajra Rasmita, Hajra Rinianty, Rinianty Rizka Ardiansyah Rizky, Moh Taufiq Ryfial Azhar Ryfial Azhar, Ryfial Saada, Rahmadian A. Sabarudin Saputra Septiano Anggun Pratama Setiawan, Dita Widayanti Siti Rahmawati Sri Khaerawati Nur Sukirman Sukirman Syahrullah Syahrullah Syahrullah Syaiful Hendra Wirdayanti Wiria Nugraha, Denny Wongkar, Noel Marcell Jonathan Yanti, Wirda Yudhaswana, Yuri Yuri Yudhaswana Joefrie Yusuf Anshori Zulkifli Zulkifli