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All Journal JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Jurnal Pustaka AI : Pusat Akses Kajian Teknologi Artificial Intelligence
Ardi Syawaldipa
Politeknik Negeri Padang
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Mathematics

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Perancangan Aplikasi Konversi File Musik Midi Menjadi Notasi Musik Ardi Syawaldipa; Youllia Indrawaty Nurhasanah; Muhammad Ichwan
JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Vol 3 No 3 (2022)
Publisher : SOTVI - Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/jitsi.3.3.92

Abstract

Musical notation is a system of musical works that serves to document a person's musical works, which are generally written using block notation and number notation. The notation standard used by the international community is the block notation. However, for some musicians, reading musical notes is relatively more difficult than reading numerical notes. This causes the conversion that is done manually to be less effective. Therefore, in this study, an application was developed that functions to convert midi music files (file formats containing digital instruments) into notation. With this application, users can create their own sheet music from midi music files automatically, and the conversion results can be played back to find out how the song is playing. The input received by the system is a music file in midi format. While the output produced is musical notes and numeric notes in text format
Sistem Pakar Diagnosa Kerusakan Smartphone Menggunakan Metode Certainty Factor Ilham Agus Pratama; Aldo Erianda; Ardi Syawaldipa
JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Vol 7 No 1 (2026)
Publisher : SOTVI - Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/jitsi.7.1.556

Abstract

Smartphones are multifunctional telecommunication devices that have become an essential part of everyday life. However, with the increasing use of smartphones, damage to these devices often occurs and is difficult for lay users to detect. To assist Pagaruyung Ponsel employees or cashiers in diagnosing smartphone damage without needing to rely on expert technicians, this study developed a computer-based expert system. This system combines the Forward Chaining and Certainty Factor (CF) methods to accurately detect smartphone damage. By utilizing expert knowledge, this system provides appropriate solutions based on detected symptoms. The system's accuracy test results showed a value of 85%, which proves the system's effectiveness in providing accurate diagnoses. It is hoped that this system can facilitate independent smartphone diagnosis and repair anytime and anywhere, through a website-based platform. The implementation of this expert system with the Forward Chaining and Certainty Factor (CF) methods is expected to increase the speed and efficiency in handling smartphone damage problems
Sistem Smart Door Lock Terintegrasi IoT dan Face Recognition Berbasis Edge Computing ardi syawaldipa; Ideva Gaputra; Andre Febrian Kasmar; Dian Eka Putra
Jurnal Pustaka AI (Pusat Akses Kajian Teknologi Artificial Intelligence) Vol 6 No 2 (2026): Pustaka AI (Pusat Akses Kajian Teknologi Artificial Intelligence)
Publisher : Pustaka Galeri Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55382/jurnalpustakaai.v6i2.1930

Abstract

Sistem keamanan pintu pengenalan wajah berbasis IOT saat ini sering mengalami latensi tinggi dan rentan gagal saat koneksi internet tidak stabil akibat pemrosesan data yang terpusat di cloud, sehingga memerlukan pemrosesan lokal (edge computing) agar respons otentikasi dan kendali jarak jauh menjadi lebih cepat dan real-time. Serta Penggunaan kunci Pintu fisik memiliki berbagai kelemahan, yaitu mudah hilang, rusak, atau diduplikasi. Oleh karena itu, Pada penelitian ini membahas rancangan dan implementasi edge computing sistem keamanan pintu dengan face recognition berbasis Internet of Things dengan kendali jarak jauh. Sistem ini menggunakan ESP32-CAM sebagai alat pengambil sampel wajah, NodeMCU ESP32 sebagai alat pengendali akuator, serta solenoid door lock sebagai mekanisme buka dan tutup pintu. Proses verifikasi wajah dilakukan secara lokal pada edge server menggunakan Python dan OpenCV tanpa menggunakan cloud, sehingga meningkatkan kecepatan respon dan keamanan data. Sistem ini juga dilengkapi dengan aplikasi Android sebagai kendali jarak jauh untuk membuka dan menutup pintu. Hasil pengujian menunjukkan sistem mampu mengenali wajah yang terdaftar dengan baik, mengontrol pintu secara otomatis, serta mengakses pintu dari jarak jauh. Sistem ini diharapkan dapat menjadi solusi keamanan pintu rumah yang lebih efektif, efisien dan modern.
Co-Authors Aldo Erianda Andre Febrian Kasmar Eka Putra, Dian Ideva Gaputra Ilham Agus Pratama Muhammad Ichwan Youllia Indrawaty Nurhasanah