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All Journal Journal of Computer Science and Informatics Engineering (J-Cosine) Dielektrika : Jurnal Ilmiah Kajian Teori dan Aplikasi Teknik Elektro Jurnal Begawe Teknologi Informasi
Ida Bagus Ketut Widiartha
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Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering

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Sistem Informasi Pengarsipan Surat Berbasis Website Pada CV Hybrid Master Business Fathony Arroisy Muhammad; Nadiyasari Agitha; Mustiari; Ida Bagus Ketut Widiartha; I Wayan Agus Arimbawa
Jurnal Begawe Teknologi Informasi (JBegaTI) Vol. 4 No. 1 (2023): JBegaTI
Publisher : Program Studi Teknik Informatika, Fakultas Teknik Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jbegati.v4i1.918

Abstract

CV Hybrid Master Business adalah instansi yang terletak di Kota Mataram. NTB. Sebagai instansi perusahaan tidak lepas dari surat menyurat dan pengarsipan. Pengarsipan surat pada CV HMB masih dilakukan dengan sistem manual yaitu masih dengan mencatat semua surat yang masuk serta surat yang keluar di berkas pencatatan data, kondisi itu menyebabkan tidak efektif dalam melakukan pengolahan data karena diperlukan waktu yang banyak, dan dapat mengakibatkan penumpukan dokumen-dokumen serta dapat mengakibatkan terjadinya kehilangan dokumen-dokumen penting apabila terjadi bencana, seperti banjir, tanah longsor, dan kebakaran. Jadi, pengolahan data yang bernilai informasi perlu dilakukan untuk meningkatkan produktivitas pekerjaan, meningkatkan efisiensi serta efektivitas dari CV HMB dalam pengelolaan arsip surat. Maka dari itu, program Praktik Kerja Lapangan yang dilaksanakan berupa membangun sebuah “sistem informasi pengarsipan surat masuk dan surat keluar berbasis web” sebagai sarana pengarsipan surat dan mempermudah pengarsipan, pengelolaan dan penyimpanan surat-surat yang ada. Kegiatan PKL tersebut berhasil dikerjakan berdasarkan dari hasil observasi serta metode perancangan sistem yang telah ditentukan. Keywords: CV Hybrid Master Business, Arsip, Sistem Informasi, Web, PHP.
Sentiment Analysis on the Impelementation of the 2024 Presidential Election on X Application Using Naive Bayes and Support Vector Machine (SVM) Methods Dewa, I Dewa Made Aditya Prasantasya; Ida Bagus Ketut Widiartha; Santi Ika Murpratiwi
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 8 No 1 (2024): Juni 2024
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v8i1.597

Abstract

This article discusses sentiment analysis of the 2024 Presidential Election through data collected from platform X, this research aims to identify and classify positive, negative, and neutral sentiments in X related to the election. This research uses scoring and textblob methods. Where the scoring method is the process of deeply analyzing sentiment and then giving the sentiment value of each data comment and accumulating it. While the textblob method is a tool used specifically for text processing that can provide sentiment for each comment. The results of the analysis provide in-depth understanding of the responses and views of the community manifested in digital space. Sentiment analysis can serve as a guide to understanding the dynamics of public opinion during the election process and its potential to influence public participation and trust in the democratic system. The practical implications of this research include the development of more effective political communication strategies based on an understanding of the sentiments that develop on X.
Boosting Time Efficiency in Helmeted Face Recognition with Transfer Learning and k-NN Dena Indiarto Permadi; Ida Bagus Ketut Widiartha; Santi Ika Murpratiwi; Tran Thi Thanh Thuy
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 8 No 2 (2024): Desember 2024
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v8i2.616

Abstract

This research aims to optimize the retraining process of face recognition systems for motor vehicle parking areas using Transfer Learning and k-nearest Neighbors (k-NN). The system enhances efficiency by retraining only on new classes, identified by checking the encoding file, allowing it to skip pre-existing classes, thus significantly improving retraining speed. Face data from 100 individuals (2725 images) was collected and augmented, with the VGG16 architecture used to generate face embeddings through Transfer Learning. Achieving 95.62% accuracy, with a precision, recall, and F1-score of 0.96 at k=1, the system demonstrates high accuracy and speed in identifying registered faces while effectively rejecting unknown ones. These optimizations greatly increase the feasibility of face recognition in parking security systems, making them more responsive to new data. Future research should focus on increasing dataset diversity and exploring more complex conditions, such as varied lighting, to enhance system performance and robustness further.
Prototype Early Warning System Tanah Longsor Menggunakan Fuzzy Logic Berbasis Google Maps Novalia Dwirohmatun Sugianti; Ida Bagus Ketut Widiartha; Ario Yudo Husodo
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 3 No 2 (2019): December 2019
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1108.717 KB) | DOI: 10.29303/jcosine.v3i2.273

Abstract

Landslide is one of frequent natural disaster in Indonesia that can cause many casualties, damage the buildings, loss of livelihoods, deteriorating sanitation, and the emergence of many diseases. To minimize this, prevention is needed by mapping the landslide prone areas and provided the early warning. This research will test in six areas in Lombok there are Batulayar, Bayan, Tanjung, Gangga, Sambelia, and Sembalun. The variable used are ground height, slope, rainfall, soil type, and land cover. There is a lot of method that can use to mapping such as fuzzy logic. Fuzzy logic is one of method that can mapping the input into the output space. By using fuzzy logic produces a level of accuracy for determining landslide prone areas is 83,3% and for the warning is 91,67%. So that, fuzzy logic can be used to mapping the landslide prone areas and make the early warning sytem.
Co-Authors Agitha, Nadiyasari Andy Hidayat Jatmika Ario Yudo Husodo Ariyan Zubaidi Dena Indiarto Permadi Dewa, I Dewa Made Aditya Prasantasya Fathony Arroisy Muhammad Fitri Bimantoro husnul khotimah I Gede Pasek Suta Wijaya I Made Budi Suksmadana I Wayan Agus Arimbawa Irwan Hadi Julianto Eko Prasetyo Moh. Ali Albar Muamar Ikhsan Mustiari Ni Wayan Eka Widiyani Novalia Dwirohmatun Sugianti qori amalia fitrasani Riris Parahita Robert Silas Kabanga Santi Ika Murpratiwi Siryantini Nurul Adnin Siti Faria Astari Sri Endang Anjarwani Sri Endang Arjarwani Tran Thi Thanh Thuy Tri Yulianto