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All Journal METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Madaniya Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI)
I Putu Astya Prayudha
Politeknik Negeri Bali
Religion Humanities Computer Science & IT Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science

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Pengembangan Sistem Informasi Desa Wisata di Desa Wongaya Gede, Kecamatan Penebel, Kabupaten Tabanan Bebasis Web Made Pasek Agus Ariawan; Gde Brahupadhya Subiksa; Ida Bagus Adisimakrisna Peling; Ni Ketut Pradani Gayatri Sarja; Luh Gede Putri Suardani; I Nyoman Harini Puspita; Made Pradnyana Ambara; I Putu Oka Wisnawa; I Putu Astya Prayudha
Madaniya Vol. 4 No. 4 (2023)
Publisher : Pusat Studi Bahasa dan Publikasi Ilmiah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53696/27214834.600

Abstract

Pengabdian kepada masyarakat yang akan dilaksanakan oleh Politeknik Negeri Bali khususnya Program Studi Teknologi Rekayasa Perangkat Lunak Jurusan Teknik Elektro ditujukan bagi warga Desa Wongaya Gede. Adapun tujuan implementasi web desa wisata adalah untuk mempromosikan desa wisata kepada wisatawan yang potensial, sehingga dapat meningkatkan jumlah kunjungan wisata ke desa tersebut. Selain itu, web desa wisata juga bertujuan untuk memberikan informasi yang lengkap dan akurat kepada wisatawan mengenai berbagai fasilitas dan atraksi wisata yang tersedia di desa tersebut, serta menawarkan berbagai paket wisata yang menarik. Dengan adanya web desa wisata, wisatawan dapat dengan mudah mencari informasi mengenai desa wisata yang ingin dikunjungi, seperti lokasi, aksesibilitas, penginapan, tempat makan, dan kegiatan wisata yang dapat dilakukan di desa tersebut. Hal ini dapat membantu wisatawan dalam merencanakan perjalanan wisata mereka dengan lebih efektif dan efisien. Selain itu, implementasi web desa wisata juga dapat membantu masyarakat setempat dalam meningkatkan perekonomian desa melalui industri pariwisata. Dengan mempromosikan desa wisata melalui web, masyarakat dapat menjangkau calon wisatawan yang lebih luas dan meningkatkan potensi penghasilan dari sektor pariwisata. Dengan demikian, implementasi web desa wisata sangat penting untuk meningkatkan potensi pariwisata di desa, membantu wisatawan dalam merencanakan perjalanan mereka, serta meningkatkan perekonomian masyarakat setempat.
Perancangan Sistem Peringatan Dini Bencana Berbasis Website Terintegrasi BMKG dan Notifikasi Whatsapp I Wayan Nuarta; I Putu Astya Prayudha; Ni Gusti Ayu Putu Harry Saptarini; Gde Brahupadhya Subiksa
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 10 No. 1 (2026): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol10No1.pp7-17

Abstract

Indonesia has a high level of disaster risk due to its geological conditions. Although the BMKG has provided early warning information, its dissemination has not been fully received by the public in a timely manner. Meanwhile, the widespread use of WhatsApp in Indonesia offers an opportunity to utilize it as a medium for delivering disaster-related information. This study aims to design a website-based disaster early warning system integrated with BMKG data and WhatsApp notifications based on provincial regions. The system was developed using the Waterfall method with PHP, MySQL, and a WhatsApp gateway service, utilizing earthquake and weather data that are updated automatically. The results indicate that the system operates according to functional requirements. WhatsApp notifications were successfully delivered with a 95% success rate and an average delivery time of 2.6 seconds. Black box testing showed 100% valid results, while the System Usability Scale evaluation achieved a score of 82.5, indicating a very good level of usability.
Evaluasi Model Convolutional Neural Network (CNN) dalam Klasifikasi Penyakit Daun Jagung Berbasis Web Menggunakan Citra Digital I Gusti Ngurah Arya Santika; Ni Gusti Ayu Putu Harry Saptarini; I Putu Astya Prayudha; Gde Brahupadhya Subiksa
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 10 No. 1 (2026): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol10No1.pp98-106

Abstract

Corn leaf diseases such as blight and rust can reduce crop yields if they are not detected at an early stage. In Penatahan Village, the process of identifying these diseases is still carried out manually through visual observation, which may lead to misidentification due to the similarity of symptoms between different diseases. Therefore, a technology-based system is needed to assist the identification process in a more objective and efficient manner. This study aims to classify corn leaf diseases using the Convolutional Neural Network (CNN) method based on digital leaf images. The dataset used consists of 319 images categorized into three classes: healthy, blight, and rust, with 80% of the data used for training and 20% for validation. The model was developed using a transfer learning approach with the MobileNetV2 architecture and evaluated using a confusion matrix. The experimental results indicate that the model achieved an accuracy of 92.19%, indicating that the CNN method is capable of effectively classifying corn leaf diseases. The developed system can be utilized as a tool to assist in the rapid and objective identification of corn leaf diseases.
Pengembangan Aplikasi Virtual Tour Kampus Berbasis XR Menggunakan Unity untuk Meta Quest 2 Dengan Chatbot AI LLaMA Farhan Maulana; Ni G. A. P. Harry Saptarini; I Putu Astya Prayudha; Gde Brahupadhya Subiksa
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 10 No. 1 (2026): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol10No1.pp260-268

Abstract

The development of Extended Reality (XR) technology creates new opportunities in delivering more immersive and interactive digital information, particularly in higher education environments. However, current campus promotion media are still dominated by static visual presentations and have not been able to provide natural two-way interaction for users. This study aims to develop an XR-based campus virtual tour application using Unity for the Meta Quest 2 device integrated with an Artificial Intelligence chatbot based on the Large Language Model (LLaMA). The application enables users to explore the campus environment in a three-dimensional virtual space, interact with campus objects, and ask questions through voice input to obtain real-time responses. The research method used is Research and Development (R&D) with an experimental software engineering approach and Agile iterative incremental development model. System development includes XR environment implementation, speech-to-text integration, prompt delivery to the LLaMA model through REST API using LM Studio as a self-hosted AI server, and text-to-speech response generation. System evaluation was conducted using black box testing, performance testing on AI response latency and frame rate stability, and usability evaluation using the User Acceptance Testing (UAT). The expected result of this research is an interactive, stable, and responsive campus virtual tour application capable of providing a more immersive information experience while functioning as an independent digital promotion medium without dependence on cloud-based AI services.
Aplikasi Klasifikasi Penyakit Kentang Menggunakan Algoritma Convolution Neural Network (CNN) I Putu Astya Prayudha; Gde Brahupadhya Subiksa; Putu Satya Saputra; I Nyoman Rai Widartha Kesuma Kesuma; Vianne Clarinta Putri Gurning
Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Vol. 7 No. 02 (2026): Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI)
Publisher : Program Studi Teknik Informatika, FTIK, Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/jrami.v7i02.849

Abstract

Potatoes are an important horticultural commodity that is susceptible to various diseases such as black scurf, blackleg, common scab, dry rot, and pink rot. Early disease detection is crucial for reducing losses and increasing productivity. This study aims to develop an image-based potato disease classification model using the Convolutional Neural Network method. The dataset consists of 1,760 images divided into eight classes, with a data split of 70% training data, 20% validation data, and 10% test data. The data processing involves preprocessing and augmentation to improve the model’s generalisation. The convolutional neural network architecture used consists of four convolutional layers combined with batch normalisation, max pooling, dropout, and fully connected layers. The model was trained using the Adam optimiser with a learning rate of 0.0003 and a batch size of 32. Testing results show that the model achieved an accuracy of 86%, with an average precision of 0.87, a recall of 0.86, and an F1-score of 0.86. The evaluation results indicate that the model is capable of recognising most classes well, although errors still occur in those with high visual similarity. This study demonstrates that the CNN method is effective for classifying potato diseases based on digital images and has the potential for further development on larger datasets.  
Software Quality Tourism Industry: Analisis Aplikasi Mobile Nusatrip dengan Metode System Usability Scale (SUS) Gde Brahupadhya Subiksa; I Putu Astya Prayudha; Ni Gusti Ayu Putu Harry Saptarini; I Putu Bagus Arya Pradnyana
Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Vol. 7 No. 02 (2026): Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI)
Publisher : Program Studi Teknik Informatika, FTIK, Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/jrami.v7i02.874

Abstract

Industry using the System Usability Scale. SUS, or the System Usability Scale, was chosen because of its ease in providing a quantitative picture of an application's usability. This study includes the OVO, Spotify, and Mysurabaya applications to explore user perceptions of the interface and functionality of the applications. The research method uses a descriptive quantitative approach with the SUS questionnaire distributed to 42 active user respondents. The SUS score is calculated by summing the scores of each question item and multiplying it by a factor of 2.5. The Cronbach’s alpha test results show excellent internal consistency (0.793). The results indicate that the tested applications received an average SUS score that demonstrates excellent usability, such as NusaTrip with a score of 72.14, above the global average of 68. However, there is variation in user experience that indicates some aspects of the application need improvement. High-scoring items indicate an intuitive interface and well-integrated features, but low-scoring items emphasize the need to reduce the learning curve for new users. The research recommends adding tutorials or a help system to enhance the user experience.
Co-Authors Farhan Maulana Gde Brahupadhya Subiksa I Gusti Ngurah Arya Santika I Nyoman Harini Puspita I Nyoman Rai Widartha Kesuma Kesuma I Putu Bagus Arya Pradnyana I Putu Gede Abdi Sudiatmika I Putu Oka Wisnawa I Wayan Nuarta Ida Bagus Adisimakrisna Peling Luh Gede Putri Suardani Made Pasek Agus Ariawan Made Pradnyana Ambara, Made Pradnyana Ni G. A. P. Harry Saptarini Ni Gusti Ayu Putu Harry Saptarini Ni Ketut Pradani Gayatri Sarja Putu Satya Saputra Vianne Clarinta Putri Gurning