Article Per Year (5 Year)
p-Index From 2020 - 2025
5.836
P-Index
This Author published in this journals
All Journal (JELIKU) Jurnal Elektronik Ilmu Komputer Udayana JOIV : International Journal on Informatics Visualization JUTIK : Jurnal Teknologi Informasi dan Komputer Jurnal Pengabdian Informatika (JUPITA) Jurnal Nasional Teknologi Informasi dan Aplikasinya
Luh Gede Astuti
Unknown Affiliation
Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Engineering Social Sciences Other

Published : 43 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 43 Documents
Search

 1   2   3   4   5 
Analisa Usability User Interface Sistem SIMAK Universitas Udayana Adiartika, Made Harry Dananjaya; Astuti, Luh Gede
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 8 No 4 (2020): JELIKU Volume 8 No 4, Mei 2020
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JLK.2020.v08.i04.p15

Abstract

With the increasingly high level of exchange of information at this time, the demand for a system capable of managing all of that information is getting higher, where one of these systems is the Udayana University Student Management Information System (SIMAK) which has a vital role in the academic administration of Udayana University, which of course requires an interface that is easy to use so that it can speed up the process of academic administration, where it is one of the things that is often taken into consideration when designing an interface that is easy to use or user-friendly, to find out whether an interface from a user-friendly system can be done by testing the usability aspects of the system. Usability is one of the important aspects that must be fulfilled for a system where to find out whether the Usability aspect of a system is fulfilled, it can be tested using the Usability Testing method with questionnaire media, this study aims to examine the Usability aspects of the SIMAK system at Udayana University using the Usability method Testing with questionnaire media, where the results of this study indicate that the SIMAK system as a whole has met the Usability component with an average value of 3, which means that the SIMAK system of Udayana University already has a good Usability aspect value.
Analisis Pengaruh Unit Hidden Layer terhadap Prediksi Jantung Koroner Menggunakan Algoritma Radial Basis Functions Semara Wijaya, I Gede Bagus; Astuti, Luh Gede
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 9 No 2 (2020): JELIKU Volume 9 No 2, November 2020
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JLK.2020.v09.i02.p17

Abstract

Heart disease is a disease that occurs due to disturbances in the heart, especially when pumping blood so that it can cause death. Nearly half of deaths in the United States and other developed countries are caused by heart disease. Therefore, an early prognosis of heart disease is needed to prevent the risk of coronary heart disease. One thing that can be done is to predict coronary heart disease sufferers using the neural network method. This study conducted an analysis of the effect of hidden layer units on the neural network radial basis functions algorithm to predict coronary heart disease sufferers. This study obtained the highest accuracy at 10 hidden layers, namely 85.08%.
Design and Development of Poultry Disease Classification with Certainty Factor Method Panji Palguna, I Gusti Agung Ngurah; Astuti, Luh Gede
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 8 No 3 (2020): JELIKU Volume 8 No 3, February 2020
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JLK.2020.v08.i03.p13

Abstract

Expert systems in organizations aimed at adding value, increasing productivity and managerial areas that can draw conclusions quickly. Like with organizations that conduct livestock business that are very promising but necessary high vigilance against disease as well as highly poultry susceptible to various types of diseases caused by viruses or bacteria. To know the disease quickly made a system that is useful for detecting, so breeders can check their poultry without seeing a veterinarian for early detection. Permanent Veterinarian required for further treatment.
PENERAPAN METODE CERTINTY FACTOR(CF) DALAM PEMBUATAN SISTEM PAKAR DIAGNOSIS PENYAKIT TUMOR OTAK Prebiana, Kiki Dwi; Astuti, Luh Gede
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 8 No 3 (2020): JELIKU Volume 8 No 3, February 2020
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JLK.2020.v08.i03.p14

Abstract

Diagnosis adalah klasifikasi seseorang berdasarkan suatu penyakit atau abnormalitas yang diidapnya. Salah satu jenis penyakit yang memerlukan diagnosis adalah penyakit tumor otak. Akan tetapi dalam proses pemeriksaannya tentu memerlukan sautu biaya yang cukup mahal. Oleh sebab itu diperlukan suatu sistem yang dapat bertindak layaknya serang pakar untuk mengetahui gejala- gejala yang timbul akibat penyakit tumor otak. Salah satu metode yang dapat diterapkan dalam pembuatan sistem pakar adalah metode Certinty Factor(CF). Metode ini dapat digunakan untuk mengatasi permasalahan berkaitan dengan ketidakpastian dalam menyelesaikan atau menentukan suatu solusi. Hasil dari penelitian ini adalah prosantase kemungkinan pasien terhadap keempat jenis penyakit tumor otak yang ada.
Implementasi Learning Vector Quantization(LVQ) untuk KLasifikasi Penyakit Ginjal Kronis Pramana, I Gst Bgs Bayu Adi; Widiartha, I Made; Astuti, Luh Gede
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 9 No 2 (2020): JELIKU Volume 9 No 2, November 2020
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JLK.2020.v09.i02.p11

Abstract

Chronic kidney disease is a disruption in the function of the kidney organs. When the kidneys are no longer fully functioning, the body is filled with water and a waste product called uremia. As a result, the body or legs will experience swelling and feel tired quickly because the body needs clean blood. Therefore, impaired kidney function should not be underestimated because it can be fatal. Researchers have conducted research related to the classification of kidney disease to find out what symptoms can cause kidney disease. One method that can be used for classification is the Learning Vector Quantization (LVQ) method. In this study, the LVQ algorithm was applied to classify chronic kidney disease. From the research results, the highest accuracy is 81.667% with the optimal learning rate is 0.002.
Sistem Pakar Untuk Diagnosis Fobia Menggunakan Metode Certainty Factor (CF) Bimantara, I Made Satria; Astuti, Luh Gede
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 10 No 1 (2021): JELIKU Volume 10 No 1, Agustus 2021
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JLK.2021.v10.i01.p16

Abstract

A phobia is an excessive fear of a certain situation or object that can hinder the life of the sufferer. Phobias that are not immediately treated in individuals can lead to a state of frustration and even depression and the worst situation is the feeling of wanting to commit suicide. The earlier it is known that a person's phobic disorder is experienced, the faster treatment can be done by an expert. Expert systems can be used to diagnose a person's phobia and replace the role of an expert through a computer program. The expert system developed can diagnose nine phobias using 84 symptoms which are divided into three types of symptoms. Knowledge about phobias was obtained from a health online site in partnership with the Ministry of Health of the Republic of Indonesia. Certainty Factor (CF) method is used to overcome uncertainty in determining a disease based on its symptoms that usually occur in expert systems. The expert system is implemented based on a website using the PHP programming language and MySQL database. The CF method can be used to determine the percentage of a person's phobia based on symptoms by taking into account the weights of experts and users. System testing using Blackbox Testing shows that all the features that have been implemented in the expert system can function properly.
Implementasi Metode Gaussian dan Median Filtering dalam Penghilangan Noise pada Citra Satya, I Dewa Gede Rama; Widiartha, I Made; Atmaja Darmawan, I Dewa Made Bayu; Ari Mogi, I Komang; Astuti, Luh Gede; Santiyasa, I Wayan
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 10 No 2 (2021): JELIKU Volume 10 No 2, November 2021
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JLK.2021.v10.i02.p01

Abstract

Meningkatnya angka kriminalitas menjadikan salah satu faktor dipasangnya CCTV pada beberapa sudut area oleh beberapa lembaga sebagai bentuk pengawasan, salah satunya yang telah dilakukan oleh Kementerian Perhubungan Republik Indonesia. Pengawasan melalui CCTV sering kali menghadapi gangguan, seperti hasil citra ber-noise yang menghambat proses pengidentifikasian suatu objek yang tertangkap CCTV. Oleh karena itu, penulis mencoba untuk melakukan implementasi metode Gaussian Filtering dan Median Filtering sebagai upaya dalam menghilangkan noise pada citra yang dihasilkan oleh CCTV. Implementasi yang akan dilakukan pada penelitian ini diawali dengan melakukan input data yang berupa citra hasil screen capture CCTV, kemudan dilakukan konversi dari citra berwarna menjadi citra greyscale. Tahap selanjutnya adalah melakukan penghilangan noise menggunakan metode Gaussian Filtering dan Median Filtering. Mean Square Error (MSE) dan Peak Signal to Noise Ratio (PSNR) digunakan dalam pengujian. Dapat disimpulkan dari penelitian ini, Median Filtering lebih efektif dalam melakukan penghilangan noise dari pada Gaussian Filtering. Hal ini dibuktikan dari 20 percobaan penghilangan noise menggunakan Median Filtering, 80% citra yang diproses menghasilkan nilai PSNR yang lebih besar daripada nilai PSNR citra dengan noise dan mengartikan jika citra yang diproses mendekati citra asli (citra tanpa noise). Sedangkan dari dari 20 percobaan penghilangan noise menggunakan Gaussian Filtering hanya 50% citra yang diproses menghasilkan nilai PSNR yang lebih besar daripada nilai PSNR citra dengan noise. Selanjutnya, untuk nilai standar deviasi terbaik penghilangan noise pada citra adalah ketika ada pada nilai 2 dengan rerata persentase penurunan noise sebesar 1,73%. Kata Kunci: CCTV, Citra, Pengolahan Citra, Noise, Gaussian Filtering, Median Filtering.
IMPLEMENTASI K-NEAREST NEIGHBOR PADA PENENTUAN KELUARGA MISKIN BAGI DINAS SOSIAL KABUPATEN TABANAN I Wayan Supriana; Luh Gede Astuti
Jurnal Teknologi Informasi dan Komputer Vol 5, No 1 (2019): Jurnal Teknologi Informasi dan Komputer
Publisher : LPPM Universitas Dhyana Pura

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

ABSTRACT Poverty is one of the problems prioritized for completion by the central government or the regions. This condition seems to have no limits because every year the problem of poverty is an issue that has always been a discussion of the government. As in Bali, even though the tourism industry is growing very rapidly, until now the problem of poverty is still a fundamental problem that needs to be resolved. Based on data from the Central Statistics Agency in 2016 the poverty rate of the province of Bali is 4.25% and one of the districts that has a higher poverty rate than the province is Tabanan Regency [1]. Various poverty alleviation programs have been implemented to break the cycle of poverty. However, poverty alleviation programs that have been implemented by the Tabanan regional government are still not optimal. In overcoming these problems, this study has the aim of creating an application system that can identify the conditions of households in Tabanan regency. The system built will identify a family based on 5 welfare categories so that it will provide an easy assessment for the poverty program survey officers. The system development model uses the K-Nearest Nighbor algorithm in modeling and classifying households. The results showed the system had an assessment accuracy rate of 83% Keywords: Poverty, Poor Households, K-Nearest Neighbor ABSTRAK Kemiskinan menjadi salah satu permsalahan yang diprioritaskan untuk di selesaikan oleh pemerintah pusat maupu daerah. Kondisi ini seakan tidak ada batasnya karena setiap tahun permasalahan kemiskinan merupakan isu yang selalu menjadi pembahasan pemerintah. Seperti halnya di provinsi bali, meskipun industri pariwisata berkembang sangat pesat namu sampai saat ini permasalahan kemiskinan masih menjadi permasalahan mendasar yang perlu diselesaikan. Berdasarkan data Badan Pusat Statistik tahun 2016 tingkat kemiskinan provinsi bali sebesar 4,25% dan salah satu kabupaten yang memiliki tingkat kemiskinan lebih tinggi dari provinsi adalah Kabupaten Tabanan [1]. Berbagai program pengentasan kemiskinan sudah dilaksanakan untuk memutus siklus kemiskinan yang terjadi. Namun program-program pengentasan kemiskinan yang sudah dilaksanakan pemerintah daerah Tabanan masih belum optimal. Dalam mengatasi permasalahan tersebut, pada penelitian ini memiliki tujuan untuk membuat sistem aplikasi yang dapat mengidentifikasi kondisi rumah tangga yang ada di kabupaten Tabanan. Sistem yang dibangun akan mengidentifikasi sebuah keluarga berdasarkan 5 katagori kesejahteraan sehingga akan memberikan kemudahan penilaian untuk petugas pendata program kemiskinan. Model pengembangan sistem menggunakan algoritma K-Nearest Nighbor dalam memodelkan dan mengklasifikasi rumah tangga. Hasil penelitian menunjukkan sistem memiliki tingkat akurasi penilaian sebesar 83% Kata Kunci : Kemiskinan, Rumah Tangga Miskin, K-Nearest Neighbor
Rancang Model Ontologi untuk Representasi Pengetahuan Rumah Tradisional di Indonesia Kadek Diah Pramesti; Luh Gede Astuti
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 12 No 3 (2024): JELIKU Volume 12 No 3, February 2024
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JLK.2023.v12.i03.p03

Abstract

Indonesia is famous for its diversity from ethnicity, religion, culture, customs, to traditional buildings or commonly called traditional houses. There are many traditional houses in Indonesia. Each region or place has its own traditional house or building. To preserve this traditional house, a model such as Ontology is needed. The ontology knowledge base is an appropriate method used to represent information. In this project, the ontology model was built using the Protégé ontology development tool. We use the method of METHONTOLOGY in the development of the ontology model where this method describes each step-in detail. The ontology model built has 9 classes, 4 object properties, 1 data properties, and 80 individuals. The testing process in the development of the ontology model by performing SPARQL queries.
Pengembangan Sistem Informasi Digital Zoonosis Melalui Pendekatan Web Semantik Komang Kartika Noviyanti; Luh Gede Astuti; I Gede Surya Rahayuda; Agus Muliantara
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 12 No 4 (2024): JELIKU Volume 12 No 4, May 2024
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JLK.2024.v12.i04.p17

Abstract

Bali Province with a population of 44,426,000 in 2023, faces challenges in ensuring sufficient food supply. Zoonotic diseases, which can be transmitted from animals to humans, pose a serious and underreported threat, affecting both animal production and human health. To address these challenges, the web-based application Healthy Zoonosis was developed, providing comprehensive digital information on animal diseases, including zoonoses and non-zoonoses, in Bali from 2015 to 2022. The application features browsing, search, and a dashboard for viewing overall disease data. The research utilized Design Science Research Methodology (DSRM) and Mentontology for ontology modeling, with Prototyping for application design. Evaluation involved 17 Participants for ontology validation, yielding a 100% valid result, and 50 Participants for usability testing, scoring 87.3 on the System Usability Scale (SUS). The app not only demonstrates accuracy and validity but also signifies a shift in animal disease prevention paradigms. It is hoped that this application will enhance public understanding of animal health and support proactive government measures in addressing animal disease challenges.
Co-Authors Adiartika, Made Harry Dananjaya Agus Muliantara Amanda, Naurah Adinda Putrie Anak Agung Istri Ngurah Eka Karyawati Ari Mogi, I Komang Awidya, Duta Bhisma Satwika Ari Priandana Cokorda Rai Adi Pramartha Culio, Shelomita Putrinda Dewa Made Wiharta Farin Istighfarizky Frady Cakra Negara, Anak Agung Ngurah Gede Dikka Widya Prana Gunawan, I Made Suma I Dewa Made Bayu Atmaja Darmawan, I Dewa Made Bayu I Gede Arta Wibawa I Gede Surya Rahayuda I Gede Tendi Ariyanto I Gusti Agung Gede Arya Kadyanan I Gusti Made Sinta Widya Ningrat I Gusti Ngurah Anom Cahyadi Putra I Ketut Gede Suhartana I Ketut Santa Wijaya I Komang Ari Mogi I Made Krisna Dwipa Jaya I Made Satria Bimantara I Made Suma Gunawan I Made Widhi Wirawan I Made Widiartha I Made Widiartha I Putu Gede Hendra Suputra I WAYAN SANTIYASA I Wayan Supriana Ida Ayu Gde Suwiprabayanti Putra Ida Bagus Ari Widhiana Kadek Diah Pramesti Karlina Surya Witanto Komang Kartika Noviyanti Krisnayana, Nyoman Kusuma, Ni Made Rika Padeswari Lie, Gary Melvin Luh Arida Ayu Rahning Putri Mahagangga, Made Dhandy Satria Mardana, I Dewa Made Michael Tanaya Ngurah Agus Sanjaya ER Ni Made Rika Padeswari Kusuma Ni Wayan Anti Andari Nyoman Putra Sastra Panji Palguna, I Gusti Agung Ngurah Pasaribu, Theresia Angel Oktarina Pramana, I Gst Bgs Bayu Adi Prebiana, Kiki Dwi Rukmi Sari Hartati Sandhiprasta, I Putu Riyan Satria Mahagangga, Made Dhandy Satya, I Dewa Gede Rama Semara Wijaya, I Gede Bagus Triana, Ni Putu Ayu Widhiana, Ida Bagus Ari Widya Prana, Gede Dikka Wirapati, Satya