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All Journal TEKNOLOGI INFORMASI Jurnal EECCIS JURNAL PASTI (PENELITIAN DAN APLIKASI SISTEM DAN TEKNIK INDUSTRI) Jurnal Ilmiah Rekayasa dan Manajemen Sistem Informasi Indonesian Journal of Applied Informatics Antivirus : Jurnal Ilmiah Teknik Informatika Industri Inovatif : Jurnal Teknik Industri Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika Jurnal Mnemonic JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Bumigora Information Technology (BITe) SKANIKA: Sistem Komputer dan Teknik Informatika Darmabakti : Junal Pengabdian dan Pemberdayaan Masyarakat Jurnal Informatika Teknologi dan Sains (Jinteks) JASTEN (Jurnal Aplikasi Sains Teknologi Nasional
Suryo Adi Wibowo
Institut Teknologi Nasional Malang
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Physics Transportation Other

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Sistem Pakar Diagnosa Kerusakan Laptop Berbasis Forward Chaining Dan Certainty Factor Yogi Ainur Rofiq Anggara; Suryo Adi Wibowo; Yosep Agus Pranoto
IJAI (Indonesian Journal of Applied Informatics) Vol 9, No 2 (2025)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijai.v9i2.95556

Abstract

Abstrak : Penelitian ini bertujuan mendiagnosa kerusakan laptop dengan menggunakan sistem pakar berbasis web yang menggabungkan metode Forward Chaining dan Certainty Factor. Ketika laptop mengalami kerusakan perangkat keras, laptop sering kali tidak dapat digunakan dan memerlukan perbaikan. Karena proses diagnosis teknisi terkadang membutuhkan waktu yang lama untuk menentukan diagnosis kerusakan, maka diperlukan sebuah sistem yang dapat membantu dalam mendeteksi kerusakan. Teknisi dapat menilai seberapa yakin mereka terhadap temuan diagnosis kerusakan komponen laptop dengan menggunakan metode Forward Chaining untuk memproses diagnosis dan Certainty Factor untuk menghasilkan tingkat kepastian diagnosis. Berdasarkan hasil implementasi dan pengujian, sistem ini memperoleh hasil pengujian metode validasi selisih hasil kurang dari 1% , dapat diartikan sistem aplikasi berhasil menerapkan metode forward chaining dan certainty factor diagnosa kerusakan laptop dengan hasil selisih validasi yang kecil kurang dari 1%. Dengan demikian, sistem pakar ini tidak hanya membantu teknisi mempercepat proses identifikasi kerusakan laptop, tetapi juga memberikan tingkat presentase pada kerusakan yang terdiagnosis.=====================================================Abstract :This research aims to diagnose laptop damage using a web-based expert system that combines the Forward Chaining and Certainty Factor methods. When a laptop experiences hardware damage, it is often unusable and requires repair. Because the technician's diagnosis process sometimes takes a long time to determine the diagnosis of damage, a system is needed that can assist in detecting damage. Technicians can assess how confident they are in the findings of the diagnosis of laptop component damage by using the Forward Chaining method to process the diagnosis and the Certainty Factor to generate the level of certainty of the diagnosis. Based on the results of implementation and testing, this system obtained a validation method test result difference of less than 1%, which means that the application system successfully applies the forward chaining method and certainty factor to diagnose laptop damage with the results of a small validation difference of less than 1%. Thus, this expert system not only helps technicians speed up the process of identifying laptop damage, but also provides a percentage level on diagnosed damage.
Perancangan Prototipe Smart Locker Mahasiswa Berbasis ESP32-CAM Dengan Sistem Keamanan QR Code Authentication Menggunakan Decision Tree Roy Mahendra Pedro Pratama; Joseph Dedy Irawan; Suryo Adi Wibowo
Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika Vol 9, No 1 (2026): Januari
Publisher : Akademi Ilmu Komputer Ternate

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47324/ilkominfo.v9i1.411

Abstract

Abstrak: Perkembangan teknologi Internet of Things (IoT) mendorong terciptanya sistem keamanan yang lebih efisien, termasuk pada fasilitas penyimpanan barang di lingkungan kampus. Meskipun fasilitas loker sudah tersedia, banyak kampus masih menggunakan loker konvensional dengan kunci fisik. Penggunaannya tidak efisien karena mahasiswa harus menemui staf kampus untuk meminjam kunci, serta rawan menimbulkan masalah seperti kehilangan, kerusakan dan duplikasi kunci. Selain itu, sistem keamanannya juga cenderung lemah karena hanya mengandalkan kunci manual atau RFID sederhana. Sistem loker konvensional yang seperti ini tidak lagi memenuhi kebutuhan keamanan dan efisiensi di lingkungan akademik modern. Penelitian ini bertujuan untuk merancang prototipe Smart Locker Mahasiswa berbasis ESP32-CAM dengan sistem autentikasi QR Code menggunakan metode Decision Tree sebagai validasi akses pengguna. Metode penelitian meliputi perancangan perangkat keras, pengembangan perangkat lunak berbasis web untuk pembuatan QR Code, serta pengujian sistem menggunakan Blackbox Testing. Hasil pengujian menunjukkan bahwa proses pembacaan QR Code memiliki waktu rata-rata 0,729 detik, sedangkan respon ESP32 dalam membuka solenoid rata-rata 2,197 detik dengan tingkat keberhasilan 100%. Temuan ini membuktikan bahwa sistem bekerja dengan baik, cepat, dan akurat, serta mampu meningkatkan keamanan penyimpanan barang mahasiswa di lingkungan kampus.Kata kunci: Smart Locker, ESP32-CAM, QR Code, Decision TreeAbstract: The development of Internet of Things (IoT) technology encourages the creation of more efficient security systems, including in storage facilities on campus. Although locker facilities are available, many campuses still use conventional lockers with physical keys. Their use is inefficient because students must meet with campus staff to borrow keys, and they are prone to problems such as loss, damage, and duplication of keys. In addition, the security system also tends to be weak because it only relies on manual keys or simple RFID. Conventional locker systems like this no longer meet the security and efficiency needs in a modern academic environment. This study aims to design a prototype of an ESP32-CAM-based Student Smart Locker with a QR Code authentication system using the Decision Tree method as user access validation. The research methods include hardware design, web-based software development for QR Code generation, and system testing using Blackbox Testing. The test results show that the QR Code reading process has an average time of 0.729 seconds, while the ESP32 response in opening the solenoid takes an average of 2.197 seconds with a 100% success rate. These findings prove that the system works well, quickly and accurately, and is able to increase the security of storing student belongings on campus.Keywords: Smart Locker, ESP32-CAM, QR Code, Decision Tree
SIG DENGAN K-MEANS++ UNTUK KLASTERISASI PENGEMBANGAN UMKM KAIN TENUN (STUDI KASUS: KABUPATEN NAGEKEO) Wulang, Maria Yasinta; Wibowo, Suryo Adi; Susanto, Eko Heri
SKANIKA: Sistem Komputer dan Teknik Informatika Vol 9 No 1 (2026): Jurnal SKANIKA Januari 2026
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/skanika.v9i1.3630

Abstract

The woven cloth Small and Medium Enterprises (SMEs) in Nagekeo Regency possess significant economic and cultural potential; however, the current coaching process is executed uniformly without data-driven analysis, resulting in inefficient allocation of aid. This study aims to map the distribution of woven cloth SMEs, develop a web-based Geographic Information System (GIS) application, and implement the K-Means++ method to cluster the SMEs based on their productivity levels. The system was designed using Laravel and Leaflet.js, incorporating features for data management, interactive maps, and visualization of productivity clusters, which include Medium Productivity (PM), Low Productivity (PR), and Dense/Massive Productivity (PP). The research findings indicate that the system's clustering process achieved 100% accuracy compared to manual calculation using Excel, with a 0% error rate. A lift ratio of 7.69 (>1) signifies a strong relationship between variables and validates the clustering results. The algorithm's computation time was recorded at 0.464 seconds. Black-box and browser compatibility tests confirmed that all features functioned as intended across Chrome, Edge, and Firefox. Furthermore, user testing involving 10 respondents yielded a positive assessment, with percentages of 43% Strongly Agree, 41% Agree, 14.5% Neutral, and 1.5% Disagree. This system is capable of supporting more effective and objective spatial data-driven decision-making
Co-Authors Ababil, Oliver Januardi Abdul Wahid Achmad Fauzi Adi Prasetyo, Guntur Adi Saputra, Yoga Aeni Fahila, Nur Agung Panji Sasmito AHMAD FAISOL Airi Mundzilin, Difania Aktafi, Billah Alfina, Alfina Ali Mahmudi Ali Mahmudi Andriano Frans, Jemmy Anshor Taufikurrahman, Muhammad ARI, DANIEL Ariwibisono, Ariwibisono Ariwibisono, F.X Arjunastya Miftaharif, Rayhan Armedianto Putro, Bima Aulia, Lalu Muhammad Fatwa Ayutantri, Dik Ajeng Benjamin Maahury, David Budi Raharjo, Piter cahya ardi wahana, zakiey Cahya Kusuma, Firdaus Dwi Deddy Rudhistiar Deswandi Yahya, Raflizar Dibrayogasta, Nandaka Dwi Lukas Saputro, Ardana Dwi Sasmita, Sudrajad Dyah Agustin, Praditasari Dzulhijjah, Dwi Ahmad Erwinda, Gesha Warilotte Esa Arya Mahardika Fadly, Erviansyah Fahrudi Setiawan, Ahmad Fahrul Taufiqurrohman, Achmat Farabi Phasa, Fianda Febriana Santi Wahyuni Febrianti, Fitri Fikar Mu'afi, Arya Firdanu, Rizha Garinanto, Budi Guntur Adi Prasetyo Hani Zulfia Zahro Hernoko, Marvelina Gracia Ilham Ali, Muhammad Irma Sari, Ramandani Joas, Kirene Wardaini Joseph Dedy Irawan Joyo Sentoso, Lukas Kalimatullah, Moh. Teguh Karina Auliasari kartiko Kartiko Ardi Widodo Kharisma, Dandy Kurnia Sella, Fernanda Kurniawan, William Lalo Nusa, Faustino M. Julius Maarif, Shohibul Mahdi, Moh Maulidin Mahesa Ramadhan, Deo Manusiwa, Mizaell Mira Orisa Misbachul Munir, Muhammat Moh. Miftakhur Rokhman Moh. Miftakhur Rokhman, Moh. Miftakhur Mucthar, Firmanda Muttakin, Muhammad Yoga Adliyani Nelly Budiharti Nurlaily Vendyansyah Ompusunggu, Andry Pambudi, Yitno Prameswara P., Renaldi Pranata, Krish Prasetiyo, Agung Sugih Prasetyo, Sony Prastya Bayu Pasifik, Rizka Pratama Irianto, Mario Pratama, Irgi Yoga Pratama, Wahyu Tedy Priga Putra, Angga Pratama Primaswara P, Renaldi Primaswara P., Renaldi Putra Snyders, Saveraga Qulub, Hizbul Rachmad Agung Laksono Raden Mohamad Herdian Bhakti Renaldi Primaswara Prasetya Renaldi, Bima Reynaldi Prayoga, Thomas Rismayanti, Sintiya Riyan Wicaksono Riziq Gyfari, Aghisna Rizka Fitriandra, Zeylla Rohman, Moh Miftakhur Roy Mahendra Pedro Pratama Safitra, Wahyu Saiqul Umam, Muhamad Sakrani, Fikriadi Satwikayana, Sujud Sentot Achmadi Setyo Aji, Bayu Sholihin, Mukhlis Sonny Prasetio Sonny Prasetio, Sonny susanto, eko heri Tejasukmana Putra, Rehadian Vito Eka Perdana Putra, Alfonsus Wahyudi, Desvianty Ayu Wijono Wijono Wulang, Maria Yasinta Xaverius Ariwibisono, Franciscus Xaverius Ariwibisono, Fransiscus Yoga Tama, Prastyo Yogi Ainur Rofiq Anggara Yosep Agus Pranoto Yuris Wijayanto, Fajar Zahro, Hani Zulfia Zidan Rusminto, Muhammad Zidan, Rifqi Zulfia Zahro’ , Hani Zulfia Zahro’, Hani