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PEMANFAATAN TEKNOLOGI INFORMASI DALAM PENGUATAN ADMINISTRASI DESA ADAT Ni Ketut Sudianing; Gede Sandiasa; Ketut Agus Seputra
Jnana Karya Vol 3, No 1 (2022)
Publisher : Universitas Panji Sakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (511.179 KB)

Abstract

Desa menurut UU No. 6 tahun 2014, tentang Desa, terdiri dari Desa Dinas dan Desa Adat atau sebutan lainnya. Dengan demikian kedua desa ini berperan sangat penting dalam pembangunan dan pelayanan masyarakat desa, menuju pencapaian keejahteraan masyarakat. Meskipun keberadaan desa adat lebih dahulu ada, dan diperkuat keberadaannya dengan UU maupun peraturan daerah dalam upaya perlindungan terhadap budaya, adat istiadat dan pola kehidupan masyarakat tradisional. Namun demikian masih terdapat kelemahan dan hambatan dalam mengelola desa adat. Disisi lain desa adat diharapkan mampu menghadapi dan memanfaatkan peluang di era modernisasi  dan dapat mengikuti era keterbukaan dan demokrasi, serta dapat melindungi hak ulayat,  adat istiadat dan pola kehidupan masyarakat adatnya. Tim Fakultas Ilmu Administrasi Universitas Panji Sakti bekerjasama Jurusan Teknik Informatika Fakultas Teknik dan Kejuruan Undhiksa melaksanakan kegiatan pengabdian kepada masyarakat dalam  rangka memberi solusi terhadap permasalahan Desa Adat, khususnya Desa Adat yang berada diwilayah Kecamatan Sukasada, yang dikoordinir oleh Majelis Desa Adat Kecamatan Sukasada. Kegiatan pengabdian kepada masyarakat dilaksanakan dengan  metode ceramah dan fokus group diskusi (FGD). Hasil pengabdian dapat memberikan manfaat antara lain: 1) peningkatan pengetahuan masyarakat tentang administrasi berbasis IT; 2) penguatan administrasi desa adat berbasis elektronik dan 3) meningkatkan upaya kerjasama antara perguruan tinggi dengan pihak-pihak lain serta lembaga kemasyarakatan.
INTEGRASI TEKNOLOGI PENGINDERAAN JAUH DAN MACHINE LEARNING PADA WEB GIS UNTUK PEMETAAN POTENSI BANJIR Ony Andewi, Putu; Seputra, Ketut Agus; Aryanto, Kadek Yota Ernanda; Dewi, Luh Joni Erawati
Jurnal Pendidikan Teknologi dan Kejuruan Vol. 22 No. 1 (2025): Edisi Januari 2025
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jptkundiksha.v22i1.87455

Abstract

Flooding is a natural phenomenon that has frequently posed significant challenges in various regions of Indonesia, driven by factors such as rainfall, river conditions, upstream landscapes, land use patterns, and sea-level rise. These events often lead to severe consequences, including the spread of waterborne diseases, destruction of infrastructure, depletion of natural resources, and economic disruption. One proactive measure to mitigate such impacts is mapping potential flood risk areas. This study utilized Landsat 8 satellite imagery Level 2, Collection 2, Tier 1 processed on the Google Earth Engine (GEE) platform to derive indices such as the Digital Elevation Model (DEM), Topographic Position Index (TPI), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Water Index (NDWI). These indices served as input variables for a Random Forest model, classifying areas into high, medium, and low flood risk categories. The developed model achieved 86% accuracy when evaluated using a confusion matrix, with precision, recall, and F1-score metrics validating its performance. The integration of this model into a WebGIS service was implemented through Flask, offering an API that supports real-time flood risk data retrieval by third-party applications. The front-end interface, built using LeafletJS, provides an interactive and user-friendly map visualization of flood risk levels. The results demonstrate that the Random Forest model effectively classifies flood risk, while the WebGIS service offers a practical tool for visualizing and disseminating flood risk information. This service has the potential to support disaster management efforts and enhance community preparedness against flooding.
A Middleware Applications Design for Health Information Sharing Seputra, Ketut Agus; Paramartha, A.A. Gede Yudhi; Pradnyana, Gede Aditra; Aryanto, Kadek Yota Ernanda
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 3 (2024): June 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i3.5707

Abstract

The interoperability between electronic health records (EHR) and electronic medical records (EMR) from various healthcare facilities for comprehensive patient care is important. However, integrating such systems, including the need for interoperability standards, data privacy, and security, is a highly challenging task, especially since patient rights in data access must be considered. The primary problem addressed is the challenge of integrating electronic health records (EHR) and electronic medical records (EMR) within various healthcare facilities to ensure comprehensive patient care while maintaining data privacy, security, and adherence to patient rights. This work presents an innovative application for consolidating patient health records from various medical facilities. Facilitates seamless data access, improving the efficiency of healthcare care delivery. The GGD approach was used in developing the prototype to ensure that the delivered product was able to meet the user requirements. Four phases are divided into six stages used in this method: research, modeling, requirements definition, framework definition, refinement, and support. The evaluation involved two phases, back-end and front-end testing, using white-box and black-box testing. White-box testing delivers an average frame-rendering rate of up to 56 fps, and black-box testing has shown 100% successful results in the given task. In conclusion, the Med-OID prototype was successfully developed. Integrates and securely transmits medical records across various healthcare services, demonstrating significant potential to enhance personalized medicine and healthcare coordination. The evaluations underscored the robustness of the prototype and its ability to improve interoperability and data sharing in healthcare systems.
FINE TUNNING MODEL INDOBERT UNTUK ANALISIS SENTIMEN BERITA PARIWISATA INDONESIA Wijaya, Wahyu; Seputra, Ketut Agus; Dewi, Ni Putu Novita Puspa
Jurnal Pendidikan Teknologi dan Kejuruan Vol. 22 No. 2 (2025): Edisi Juli 2025
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jptk-undiksha.v22i2.104056

Abstract

Perkembangan kecerdasan buatan pada ranah NLP dewasa ini sangat pesat. Beberapa teknologi kecerdasan buatan pada text-based teknologi seperti ChatGPT, Gemini, LLaMA, dan lain-lain telah dimanfaatkan dalam ranah riset ataupun industry. Dalam analisis sentimen, yang menjadi komponen utama adalah representasi teks. Teknik representasi teks yang menonjol pada akhir-akhir ini adalah bidirectional encoder representation from transformer(BERT). Sesuai dengan permasalahan yang disebutkan sebelumnya, analisis sentimen ini dapat dilakukan untuk berita pariwisata. Namun untuk meningkatkan akurasi dapat dilakukan fine tunning pada metode BERT. Berdasarkan permasalahan tersebut, dalam penelitian ini akan dilakukan analisis sentiment dengan menggunakan metode IndoBERT. Akan dilakukan fine tuning untuk fokus ranah pariwisata. Berdasarkan hasil pengujian yang telah dilakukan didapatkan tangkat akurasi sebesar 77%. Model dapat melakukan klasifikasi sentiment negative dengan baik, namun masih perlu ditingkatkan pada sentiment positif dan netral.  
UNDIKSHA VIRTUAL ASSISTANT (SHAVIRA): INTEGRATION FREQUENCY ASKED QUESTION WITH RASA FRAMEWORK Resika Arthana, I Ketut; Dewi, Luh Joni Erawati; Seputra, Ketut Agus; Marti, Ni Wayan
JST (Jurnal Sains dan Teknologi) Vol. 10 No. 2 (2021)
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1084.369 KB) | DOI: 10.23887/jstundiksha.v10i2.39863

Abstract

Nowadays, the implementation of chatbots in information systems is getting popular to increase user experience. In our previous research, we developed Undiksha Virtual Assistant (Shavira). Shavira is a knowledge management system (KMS) as Frequency Asked Question (FAQ) system to facilitate users to get an answer about their questions. The challenge on the existing Shavira system is that the users must open a website and type queries to get a list of answers. The text query must match with the keyword in systems. To address this problem and to avoid cognitive load, in this research we implemented a chatbot in Shavira. The purpose of the chatbot implementation in Shavira is to make information easier to be accessed and to increase user experience. The users can ask a question in natural language and get an answer immediately on their chat application such as: Telegram, Facebook, or Messenger. We used Rasa Framework as a chatbot engine in Shavira. Rasa Framework is an open-source virtual assistant engine based on artificial intelligence. The challenge in conducting this research is in integrating the existing FAQ system with Rasa Framework. This research consists of four phases, they are: adaptation data structure in the existing FAQ with data structure requested by Rasa framework, data integration and mapper, and evaluation. The result of this research is a new Shavira that is integrated with a chatbot and can be accessed from chat applications such as Telegram.  We evaluated the accuracy of Shavira powered by Rasa Framework with ten topics about academic information. The results showed that the accuracy of Shavira is 90%. We also evaluated the usability of Shavira with Software Usability Scale (SUS) Questionnaire. The usability evaluation showed that Shavira satisfied users with value  81 (threshold 68) and categorized Excellent, Acceptable and Prometer.
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.
Penerapan Algoritma Pillar Untuk Inisialisasi Titik Pusat K-Means Klaster Dinamis Seputra, Ketut Agus; Wijaya, I Nyoman Saputra Wahyu
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7 No 6: Desember 2020
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2020762538

Abstract

K-Means merupakan algoritma yang digunakan untuk melakukan pengklasteran data. Namun, k-means memilikimasalah dalam sensitivitas penentuan partisi awal jumlah klaster. Penelitian terkait menyatakan algoritma k-means tergantung pada penentuan titik pusat klaster awal. Pemilihan pusat klaster awal secara acak cenderung menghasilkan klaster yang berbeda. Sehingga untuk menentukan klaster terbaik harus dilakukan dengan memperhatikan nilai Sum Sequare Error yang terkecil. Untuk mengatasi permasalahan tersebut, penentuan klaster dilakukan dengan menggunakan algoritma pillar. Algoritma pillar menentukan titik pusat klaster dengan memilih data dengan nilai euclidean paling jauh dari titik pusat klaster. Namun pemilihan titik klaster tetap memperhatikan kemungkinan data outlier. Pengujian dilakukan dengan menetapkan satu buah klaster awal sebagai inisialisasi skaligus sebagai klaster pembanding untuk menentukan kualitas klaster berikutnya. Penelitian ini menggunakan data set ruspini dan iris. Untuk data ruspini terdiri dari 76 data set, sedangkan data iris terdiri dari 150 data set. Klaster Pillar memiliki nilai Sum Sequere Error, Variance Cluster, dan Davies yang lebih kecil dibandingkan klaster dinamis pada data set ruspini. Nilai tersebut secara berurutan untuk algoritma pillar adalah 0.28, 0.11, 7.30, 5.88. Untuk data set iris nilai Sum Square Error lebih tinggi dibandingkan dengan klaster dinamis yaitu 0.34. Sedangkan algoritma klaster dinamis memiliki nilai 0.32. Hal tersebut disebahkan penentuan data outlier pada iris data set yang tidak akurat. Ketidakakurantan tersebut berasal dari data yang bersifat multivariat, sehingga memungkinkan data outlier menjadi centroid awal klaster. Sehingga jika dilihat dari nilai validitas SSE, algoritma pillar k-means klaster dinamis masih kurang bekerja optimal dibandingkan dengan algoritma k-means klaster dinamis.
Implementasi Metode Item-Based Collaborative Filtering dalam Rekomendasi Barang pada Aplikasi Mobile Go-BUMDes Arditya, I Putu Dion; Permana, Agus Aan Jiwa; Seputra, Ketut Agus
MASALIQ Vol 5 No 4 (2025): JULI
Publisher : Lembaga Yasin AlSys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/masaliq.v5i4.6569

Abstract

This study is motivated by the low public interest in shopping at BUMDes (village-owned enterprises), primarily due to geographical constraints, highlighting the need for digital innovation to improve service accessibility. The objective of this research is to develop the GO-BUMDes mobile application as a platform for product ordering and recommendation in Cau Belayu Village. The application employs an Item-Based Collaborative Filtering method to provide product recommendations based on item similarity. The development process followed the prototype methodology, while system testing involved white box and black box techniques, accuracy evaluation using MAE (Mean Absolute Error), and user experience assessment through UMUX (Usability Metric for User Experience). Test results showed an MAE value of 0.258, indicating a relatively high prediction accuracy, and a UMUX score of 85.78, reflecting excellent user comfort and satisfaction. The study concludes that GO-BUMDes has the potential to enhance access and facilitate digital transactions at BUMDes, while encouraging community participation in a technology-driven village economy. The practical implications of this research contribute to strengthening digital transformation in the local economic sector, particularly in rural areas.