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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Teknoin Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Ilmiah Informatika Komputer Jurnal Ilmiah Teknologi dan Rekayasa Prosiding KOMMIT TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnas Nasional Teknologi dan Sistem Informasi InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) J-SAKTI (Jurnal Sains Komputer dan Informatika) Journal of Information Systems and Informatics International Journal of Engineering, Science and Information Technology J-SAKTI (Jurnal Sains Komputer dan Informatika) International Journal of Engineering Continuity
Emy Haryatmi
Universitas Gunadarma
Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation

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Journal : Journal of Information Systems and Informatics

 1 
Analisis Kepuasan Pengguna Aplikasi Daily Apps Berbasis Web Di Internal Divisi Digital Marketing PT. Transcosmos Indonesia dengan Metode End-User Computing Satisfaction (EUCS) Arini Islahul Nimah; Emy Haryatmi
Journal of Information System and Informatics Vol 3 No 4 (2021): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v3i4.186

Abstract

Website saat ini dimanfaatkan untuk hal manajemen internal, maupun untuk promosi ke pihak eksternal perusahaan, baik untuk mengumpulkan ataupun membagikan informasi kepada pengguna. Daily Apps adalah suatu aplikasi yang digunakan oleh karyawan Divisi Digital Marketing PT. Transcosmos Indonesia dengan tujuan merekam Daily Data, Project List, hingga menampilkan Individual Rates maupun Team / Group Rates. Masalahnya Daily Apps yang digunakan di internal divisi Digital Marketing belum pernah diulas sama sekali sehingga belum dapat diketahui kepuasan penggunanya. Tujuan penelitian ini adalah Menganalisis kuisioner kepuasan pengguna aplikasi Daily Apps menggunakan metode End User Computing Satisfaction (EUCS). Penelitian ini menggunakan metode kuantitatif, sedangkan teknik pengumpulan data menggunakan kuesioner dengan mengaplikasikan model End User Computing Satisfaction (EUCS), yang dianalisis menggunakan analisis factor. Kemudian disebarkan kepada 71 responden yang merupakan karyawan Divisi Digital Marketing PT. Transcosmos Indonesia. Hasil dari penelitian menunjukkan bahwa kepuasan pengguna berdasarkan analisis faktor yaitu pada Indikator content mempunyai pengaruh terbesar terhadap kepuasan pengguna Daily Apps di Divisi Digital Marketing PT. TCID, dengan nilai sebesar 2,908 atau > 1 maka menjadi faktor pertama, sedangkan pada indikator accuracy, timeliness,format, dan ease of use, didapatkan nilai < 1 maka dianggap faktor yang tidak mempengaruhi kepuasan pengguna.
Classification of Tomato Ripeness Based on Convolutional Neural Network Methods Ayunda, Nur Azizah; Haryatmi, Emy; Riyadi, Tri Agus
Journal of Information System and Informatics Vol 5 No 4 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i4.613

Abstract

Sorting system for tomato is one of the important things to deploy to achieve better quality of tomato. Nowadays, many sorting system is done manually and this could spend a lot of time and become inefficient. One method can be implemented in the sorting system by using Convolutional Neural Network (CNN) method to classify the ripeness of tomatoes. The objective of this research is to classify the ripeness of tomatoes based on the color of tomatoes. There are three categories of color level such as green for raw tomato, turning for half-ripe tomato and red for ripe tomato. Research methodology of this research is data collection, data pre-processing and image maintenance, CNN model, and training data. The image used in this research are 1148 images. These images were taken manually using smartphone camera in outdoor environment. These images were used to build CNN model. The results of this research show that by testing 10 images of tomatoes achieved raw tomatoes close to 90%, ripe tomatoes close to 90% and half-ripe tomatoes close to 80%. Based on the results, CNN can be used as a good alternative in image classification tasks.
Co-Authors A. Benny Mutiara Abdul Rachman Rasyid Andhika Alif Arsadi Annisya Arini Islahul Nimah Arum TiaraSari Ary Bima Kurniawan Ayunda, Nur Azizah Bagaskoro Bagaskoro Bima Kurniawan, Ary Budi Prasojo Budi Prasojo, Budi Busono Soerowirdjo Busono Soerowirdjo Busono Soerowirdjo Dzulfikar, Laksamana Akbar E. Susy Suhendra Fathimah Nur Afifah Fauzi, Alfharizky Febrin Ludia Ramadini Hanum, Fatmi Aulia Haryadi, Deni Ilham Wijaya Murniyati, Murniyati Musa, Purnawarman Randy Rahmanto Rio Setiawan Riyadi, Tri Agus Riza Adrianti Supono, Riza Adrianti Robbani, Fatih Dien Rosdiana Rosdiana Sheila Pramita Hervianti Teddy Oswari Teddy Oswari Tubagus Maulana Kusuma Yuhani, Ahmad Yunus Bakhtiar Arafat