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All Journal International Journal of Advances in Applied Sciences IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Pendidikan Fisika Undiksha Jurnal Pendidikan Teknologi dan Kejuruan Prosiding Seminar Nasional MIPA Wahana Matematika dan Sains Jurnal Sains dan Teknologi Jurnal Simetris Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Sistem dan Informatika Mimbar Pendidikan: Jurnal Indonesia untuk Kajian Pendidikan KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Sistemasi: Jurnal Sistem Informasi Sinkron : Jurnal dan Penelitian Teknik Informatika JUTIK : Jurnal Teknologi Informasi dan Komputer JITK (Jurnal Ilmu Pengetahuan dan Komputer) JOURNAL OF APPLIED INFORMATICS AND COMPUTING PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer SINTECH (Science and Information Technology) Journal Jurnal Teknik Informatika UNIKA Santo Thomas Jurnal Serambi Engineering Jurnal RESISTOR (Rekayasa Sistem Komputer) International Journal of Community Service Learning Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Riset Informatika Jurnal Ilmiah Sinus EDUMATIC: Jurnal Pendidikan Informatika Jurnal Teknologi Informasi dan Pendidikan Jurnal Mantik Jurnal Teknologi Informasi dan Terapan (J-TIT) JURNAL ILMU KOMPUTER INDONESIA Jurnal Teknologi Informasi dan Multimedia Bali Medika Jurnal Indonesian Journal of Electrical Engineering and Computer Science INFOKUM Didaktik : Jurnal Ilmiah PGSD STKIP Subang Journal of Computer Networks, Architecture and High Performance Computing Jurnal Teknik Informatika (JUTIF) Journal of System and Computer Engineering J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Info Sains : Informatika dan Sains Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Jurnal Locus Penelitian dan Pengabdian Malcom: Indonesian Journal of Machine Learning and Computer Science Bulletin of Network Engineer and Informatics (BUFNETS) INOVTEK Polbeng - Seri Informatika
I Gede Aris Gunadi
Universitas Pendidikan Ganesha
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Nursing Physics Public Health Social Sciences Other

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Analisis Gerakan Mata Terhadap Tingkat Kecemasan Mahasiswa Dengan Metode Fuzzy Inference System David Juli Ariyadi; I Gede Aris Gunadi; Dewa Gede Hendra Divayana
Jurnal Teknologi Informasi dan Terapan Vol 10 No 1 (2023)
Publisher : Jurusan Teknologi Informasi Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/jtit.v10i1.304

Abstract

Penelitian ini bertujuan mengetahui bagaimana metode Fuzzy Inference System (FIS) mampu menilai tingkat kecemasan seseorang melalui gerakan mata. Gerakan mata mengandung banyak informasi yang menggambarkan kondisi fisik dan psikis. Gerakan mata direkam menggunakan Tobii Eye Tracker, data disimpan dan diproses dengan FIS karena sifat variabelnya yang tidak tegas. Penelitian ini bekerja sama bersama pakar dengan observasi dan wawancara bersama responden dan memberikan keputusan secara profesional tentang tingkat kecemasan yang dialami di akhir sesi observasi. Dalam penelitian ini diperbandingkan FIS metode Tsukamoto dan Mamdani yang paling tepat atau direkomendasikan untuk menentukan tingkat kecemasan seseorang secara umum. Penentuan rekomendasi ini berdasarkan jumlah pandangan responden terhadap layar monitor yang dibagi menjadi lima area bagian. Pengujian performa setiap metode menggunakan confusion matrix. Berdasarkan tingkat akurasinya (accuracy), FIS metode mamdani memiliki nilai yang lebih baik sebesar 81,25% daripada FIS Tsukamoto yang sebesar 79,69%. Dengan demikian secara umum, FIS metode Mamdani lebih baik daripada FIS metode Tsukamoto dengan selisih sebesar 1,56%. Ke depan diharapkan penelitian ini memberikan informasi lebih awal kepada seseorang untuk mengetahui tingkat kecemasannya.
COMBINATION OF THE PROFILE MATCHING AND TOPSIS METHOD IN DECISION SUPPORT SYSTEM OF LECTURER PERFORMANCE ASSESSMENT I Putu Dody Suarnatha; I Gede Aris Gunadi
Jurnal Riset Informatika Vol. 3 No. 3 (2021): June 2021 Edition
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v3i3.87

Abstract

An information system is a system within an organization that collects data management needs, supports operations, has important management and strategy in organizational or institutional activities, and provides reports to certain parties by using computers as a means to access the internet. To be able to manage data in the form of a database, it is necessary to develop a web-based information system. For that we need an information system that can facilitate the sale of a sales transaction and as a promotional event, so that it is expected to improve the company and compete with other companies. Public relations can be interpreted as relations between publics, indicating that there are many publics who have to do these relationships, and because there are many publics, it means that there are many relationships. The purpose of making this web program is to facilitate service sales transactions so that they are more efficient, fast and easy without the need to be hindered by distance and time.
Analisis Kesuksesan Sistem Informasi Online (SION) Menggunakan Metode Delone and Mclean: Analysis of Online Information System (SION) Success Using the Delone and Mclean Method I Putu Putra Damana; I Made Candiasa; I Gede Aris Gunadi
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 3 No. 2 (2023): MALCOM October 2023
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v3i2.958

Abstract

SION adalah sebuah sistem  informasi yang memudahkan mahasiswa STIKOM Bali untuk mendapatkan informasi terkait kegiatan akademik dan kemahasiswaan, seperti perkuliahan, TA/ Skripsi, profil mahasiswa, dan kegiatan lainnya. Dengan adanya sistem informasi online ini semua mahasiswa bisa mendapatkan informasi dan pengumuman tanpa harus datang ke kampus karena sistem ini berbasis web. Penelitian ini dimaksudkan untuk untuk mengukur tingkat keberhasilan penerapan SION menggunakan model kesuksesan DeLone dan McLean. Model kesuksesan DeLone dan McLean ini memiliki enam variabel sebagai pengukurannya yaitu: kualitas sistem, kualitas informasi, kualitas pelayanan, minat penggunaan, kepuasan pengguna dan netbenefit.  Akan tetapi, penelitian ini hanya melibatkan empat variabel, yaitu kualitas system, kepuasan pengguna, minat pengguna, dan minat pengguna  Alasannya sesuai dengan rumusan masalah penelitian ini. Berdasarkan hasil pengujian hipotesis diperoleh temuan sebagai berikut pengaruh kualitas sistem terhadap kepuasan pengguna bernilai positif sebesar 0,341. Pengaruh kualitas informasi terhadap kepuasan pengguna bernilai positif sebesar 0,530. Pengaruh kepuasan pengguna terhadap minat pengguna bernilai positif sebesar 0,409. Pengaruh kualitas sistem terhadap minat pengguna bernilai positif sebesar 0,285. Pengaruh kualitas informasi terhadap minat pengguna bernilai positif sebesar 0,173. Dengan demikian dapat disimpulkan bahwa pengaruh seluruh variabel penelitian adalah signifikan.
Batch size and learning rate effect in covid-19 classification using CNN Ni Komang Rai Mirayanti; Sariyasa Sariyasa; I Gede Aris Gunadi
Jurnal Mantik Vol. 7 No. 3 (2023): November: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v7i3.4177

Abstract

This study evaluated the performance of a Convolutional Neural Network (CNN) model in classifying CT-Chest images of COVID-19 and non-COVID patients. The primary focus was to determine the influence of learning rate and batch size on the model's effectiveness. This research used 698 datas from Covid-19 and NonCovid-19 CT-Chest Image. Those dataset was obtained from medRxiv dan bioRxiv and has been approved by radiology expert in Tongji Hospital, China. In this research, COVID-16 dataset was classified by CNN with different batch sizes and learning rates for each iteration. Batch size used in this study were 1, 2, 4, 8, 16, 32, 64, and 128 with learning rates 0,00001; 0,0001; 0,001; 0,01; 0,1 and 1. This study found that this study showed that batch size and learning rate have a positive effect on CNN performance. The lower the learning rate, the lower the batch size will allow the network in the CNN model to perform better in classifying COVID-19 CT-Chest. In Addition, the best batch size for the classification is 64 with learning rate 0,01. These findings provided important insights into how parameters such as learning rate and batch size impacted the performance of the CNN model in classifying COVID-19 CT-Chest
Analysis of User Satisfaction with E-Learning Services During the Covid-19 Pandemic Using the PIECES Framework I Putu Agus Eka Yatna Cipta; Made Windu Antara Kesiman; I Gede Aris Gunadi
Journal of Computer Networks, Architecture and High Performance Computing Vol. 5 No. 2 (2023): Article Research Volume 5 Issue 2, July 2023
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v5i2.2557

Abstract

During the Covid-19 pandemic, the education sector has been able to provide assistance for the continuation of the learning process through e-Learning services. E-Learning is an online-based learning and teaching process that utilizes information technology services. E-Learning is specially designed by the institution and integrated with academic progress data to offer the best support to students who have become increasingly familiar with information technology during the pandemic, addressing its limitations. The objective of this research is to measure user satisfaction with the e-Learning service using the PIECES framework. The PIECES framework consists of Performance, Information/data, Control/security, Efficiency, and Service categories. The PIECES framework is employed for analyzing the information system and consists of six variables: performance, information, economic, control, efficiency, and services. Data was collected through questionnaires distributed to 368 students from different graduation years, spanning from 2018 to 2021, who are users of the e-Learning service. Based on the gathered data analysis, the average satisfaction levels for each variable are as follows: performance scored 3.75, information scored 3.82, economic scored 3.84, control scored 3.74, efficiency scored 3.7, and services scored 3.84. Combining these values and referencing Kaplan and Norton, it can be concluded that the overall user satisfaction level with e-Learning falls into the satisfied category
Prediksi Jumlah Penumpang Bus Trans Metro Dewata Pada PT. Satria Trans Jaya Menggunakan Double Exponential Smoothing dan Weighted Moving Average N Dinda Maharani; I Gede Aris Gunadi; Komang Setemen
Jurnal Serambi Engineering Vol 8, No 2 (2023): April 2023
Publisher : Fakultas Teknik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jse.v8i2.5686

Abstract

Peramalan merupakan teknik atau proses untuk melakukan prediksi suatu kejadian di masa depan dengan menggunakan data histori sebelumnya. Transportasi umum merupakan layanan jasa untuk mengangkut orang atau barang dari satu tempat ke tujuan tempat lainnya. Tujuan penelitian ini untuk memprediksi jumlah penumpang transportasi umum yaitu bus Trans Metro Dewata pada setiap koridor di masa mendatang dengan metode peramalan yang tepat. Metode peramalan yang di gunakan adalah Double Exponential Smoothing dan Weighted Moving Average. Pada penelitian ini menggunakan Mean Absolut Precentage Error (MAPE) sebagai nilai uji akurasi error. Hasil peramalan berdasarkan nilai MAPE bahwa Double Exponential Smoothing lebih tepat digunakan dibandingkan Weighted Moving Average karena nilai error yang di hasilkan lebih kecil, yaitu koridor I sebesar 7,41%, koridor II sebesar 7,05%, koridor III sebesar 9,83%, koridor IV sebesar 6,37% dan hasil peramalan 48 periode mendatang menghasilkan tren meningkat lurus.
KLASIFIKASI KUALITAS BIJI KOPI ROBUSTA DENGAN METODE NAIVE BAYES Putra, I Kadek Nurcahyo; Gunadi, I Gede Aris; Sunarya, I Made Gede
KLIK- KUMPULAN JURNAL ILMU KOMPUTER Vol 10, No 3 (2023)
Publisher : Lambung Mangkurat University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/klik.v10i3.565

Abstract

Sortasi Kualitas biji kopi merupakan proses yang sangat penting untuk menjaga serta meningkatkan kualitas produksi, melihat kopi sebagai salah satu komoditas paling penting yang diperjual belikan. Penulis ingin meminimalisir kesalahan klasifikasi oleh manusia yang subjektif dengan mengimplementasi metode Naive Bayes untuk melakukan klasifikasi kualitas biji kopi secara objektif. Biji kopi difoto sehingga menghasilkan citra biji kopi, ruang warna HSV digunakan untuk melakukan ekstraksi ciri warna biji, tekstur biji kopi diekstrak dengan metode GLCM, dan ukuran biji kopi dihitung dengan mengakumulasi nilai piksel pada objek citra biner. Pengujian terhadap model klasifikasi yang dibangun dengan 480 data latih menghasilkan akurasi 90.8% berdasarkan 120 data uji. Hasil akurasi menunjukkan ketika ada 120 data uji maka 11 data salah diklasifikasi atau ketika ada 200 data uji maka 19 hingga 20 biji akan salah diklasifikasi oleh model. Penelitian selanjutnya disarankan untuk melakukan pengamatan yang lebih dalam untuk mendapatkan fitur ciri yang dapat merepresentasikan perbedaan kualitas biji dengan lebih representative, serta membandingkan metode klasifikasi Naive Bayes dengan metode klasifikasi lain untuk mendapatkan model klasifikasi yang lebih baik di masa depan
UX Evaluation Using Firstclick, Performance Measurement, RTA, And Questionnaire On E-Commerce Website Candiasa, I Made; Gunadi, I Gede Aris; Putra, I Nyoman Wahyu Semeru
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 1 (2023): Articles Research Volume 7 Issue 1, 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i1.12037

Abstract

E-commerce has made transactions easier for several persons. SKI (Semadi Kwazay Indoland), a company in the real estate market, is one of the numerous organizations that develop e-commerce websites. The company wants the e-commerce website to attract a wider audience. Therefore, an evaluation is necessary to measure the usefulness of the website. Twenty responses were divided into two groups of ten: the advanced group and the novice group. The selected assessment approaches are performance measurement to evaluate the system's efficiency and error rate, first-click usability testing to evaluate the system's effectiveness, and RTA and the SUS questionnaire to evaluate user happiness. The following are the study's findings: This e-commerce website is quite efficient, as there is no significant difference in the time necessary to complete the 10 activities between the two groups of respondents. The mean participant questionnaire score for the e-commerce website was 49.75, which was much lower than the average SUS score of 68. The e-commerce website page is highly effective, as the performance measurement test results suggest a comparatively low error rate across both novice and advanced respondent groups.
Development of a Web-Based Dashboard System for Monitoring Study Programme Accreditation Instruments Gunawan, Agus; Gunadi, I Gede Aris; Dewi, Luh Joni Erawati
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 3 (2023): Article Research Volume 7 Issue 3, July 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.12799

Abstract

Accreditation is a form of assessment or evaluation of the quality of education, both at the level of study programme and higher education institutions, conducted by independent organizations or bodies external to the universities. BAN-PT is one such external agency responsible for accrediting higher education institutions in Indonesia. However, many universities encounter challenges during the accreditation process, such as the absence of a monitoring system and data integration in the preparation of some documents, which are essential for accreditation. To address this issue, researchers have recognized the need to design and build a system that can aid in the preparation and monitoring of accreditation forms. The system was developed using the Extreme Programming model, which adopts the agile concept as the core of application development. The Extreme Programming model consists of four key activities, namely system planning, system design, code writing, and system testing. Based on the black box testing results, the developed system was found to operate as intended. Based on the benchmark results for each aspect of the UEQ, Attractiveness has a value of 1.69 with the good category, Perspicuity has a value of 1.57 with the above average category, Efficiency has a value of 2.11 with the excellent category, Dependability has a value of 1.68 with the good category, Stimulation has a value of 1.29 with the above average category, and Novelty has a value of 0.86 with the above average category.
Analisis Hyperparameter Pada Klasifikasi Jenis Daging Menggunakan Algoritma Convolutional Neural Network Dinata, I Made Anom Mahartha; Gunadi, I Gede Aris; Sunarya, I Made Gede
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 8, No 1 (2024): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v8i1.763

Abstract

In the context of food and economy, meat plays a vital role in fulfilling the nutritional needs of society and serves as a strategic economic commodity. However, the difficulty in distinguishing between beef and pork often leads to fraud by meat traders. Particularly in Indonesia, where the consumption of beef and pork is high, this confusion raises significant concerns, especially since pork is prohibited in the Islamic religion. This research aims to address this issue by applying Artificial Intelligence technology, specifically the Convolutional Neural Network (CNN) deep learning method in classifying images of beef, pork, and mixed meat. The study utilizes a dataset of 410 samples, with 70% used for training and 30% for testing. Testing is conducted using a basic CNN model with hyperparameter analysis such as image size, number of epochs, and batch size. Additionally, the dataset is tested using a comparative architecture, namely the ResNet-50 architecture. The best accuracy rate of the CNN model is 82.20%, achieved with an image size of 75 x 75 pixels, 100 epochs, and a batch size of 64. Testing with the ResNet-50 architecture yields the highest accuracy of 76.14%. Evaluation is performed using a confusion matrix with four categories: Accuracy, Precision, Recall, and F1 Score.
Co-Authors ., Ketut Suma ., Putu Sonia Virgawati Pratiwi Adi Sista, Dewa Nyoman Agus Ariwanta, I Putu Yesha Agus Gunawan Agus Harjoko Agus Harjoko Agus Harjoko Ahmad Asroni Ahmad Asroni, Ahmad Anandita, Ida Bagus Gede Andiny T T Arditaloka, I Wayan Angga Ariasa, Komang Artama, Made Bella Eka Wahyuningtias Cipta, I Putu Agus Eka Yatna Cokorda Oka Birawidya David Juli Ariyadi Dewa Gede Hendra Divayana, Dewa Gede Hendra Dewi Oktofa Rachmawati Dharmana, I Wayan Dinata, I Made Anom Mahartha Erlangga, Anak Agung Gde Wahyu Sukma Fauzi, Muhammad Rizki Galih Cahyaningsih, Agung Ukki Gede Indrawan Gede Rasben Dantes Hajrin, M. Heryanto, I Wayan Agus I Gede Andika Diana Putra I Gusti Agung Putu Mahendra I Ketut Agus Indra Diatmika I Ketut Paramarta I Komang Adyanata I Made Arya Adinata Dwija Putra I Made Candiasa I Made Gede Sunarya I Made Gede Sunarya I Made Pradipta I Nyoman Sukajaya I Nyoman Wahyu Semeru Putra I Putu Agus Eka Yatna Cipta I Putu Aris Sanjaya I Putu Aris Sanjaya, I Putu Aris I Putu Arya Putra I Putu Dody Suarnatha I Putu Putra Damana I Wayan Agus Heryanto I Wayan Gede Suweca Antara I Wayan Pio Pratama I Wayan Rosiana I Wayan Sadia I Wayan Santyasa I Wayan Sukra Ida Ayu Mirah Cahya Dewi Ida Bagus Satriya Satriya Wibawa Jana Satvika, Gd. Aditya Kadek Kusuma Wardana Kadek Yota Ernanda Aryanto Ketut Suma Ketut Suma . Ketut Suma . Komang Ariasa Komang Setemen Lika Hanifah Luh Joni Erawati Dewi Luh Putu Budi Yasmini Luh Putu Budi Yasmini Luh Putu Risma Noviana Risma Luh Rumni Oktaria M. Hajrin M.Cs S.Kom I Made Agus Wirawan . Made Artama Made Junindra Maha Arta Sang Made Wahyu Aditya Arta Made Windu Antara Kesiman Made Windu Segara Matius Ivan Bimasena Mimin Yeli Sholekah Moh. Heri Setiawan MS Prof. Dr. Ketut Suma . N Dinda Maharani Ni Kadek Erna Supriathi Ni ketut Lisa Maheni Ni Komang Rai Mirayanti NI LUH PUTU MANIK WIDIYANTI Ni Made Dwi Andayani Ni Made Yeni Dwi Rahayu Ni Putu Eka Apriyanthi Nugraha, I Gede Pradipta Adi Nugraha, I Gusti Agung Satria Oktaria, Luh Rumni Pathni, Ida Ayu Wisma Anggaritha pramana, i gede pramana ade saputra Prof. Dr. Ketut Suma, MS . Putra, I Kadek Nurcahyo Putra, I Nyoman Wahyu Semeru Putra, I Putu Arya Putu Eka Parianthana Putu Sonia Virgawati Pratiwi . Putu Wendy Ariyani Rai Sujanem Risha, Nurfa Sandhiyasa, I Made Subrata Saputri, Ni Kadek Tesya Ari Sariyasa Sariyasa Sariyasa Sariyasa Sawitri D U Segara, Made Windu Sidik, Purnama Sisilia Fhelly Djun Sonia Dewi Parna.T Sri Hartati Suputra, I Putu Arsana Suryawan, I Made Yuda Sutarno, Erwan Sutarno, Erwan Suweca Antara, I Wayan Gede T, Andiny T U, Sawitri D Wardana, I Komang Tri Edi Wayan Eka Ariawan Yogi Duwi Antara