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All Journal Antivirus : Jurnal Ilmiah Teknik Informatika bit-Tech SinarFe7 Literasi: Jurnal Pengabdian Masyarakat dan Inovasi
Asrofi Buntoro, Ghulam
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Other

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Sistem Prediksi Jalur Karier Siswa SMK Menggunakan Metode Naïve Bayes Berbasis Web Permatasari, Dian Wahyu; Asrofi Buntoro, Ghulam; Mustikasari, Dyah
SinarFe7 Vol. 7 No. 1 (2025): SinarFe7-7 2025
Publisher : FORTEI Regional VII Jawa Timur

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Penelitian ini mengembangkan sistem prediksi berbasis web untuk mengklasifikasikan kecenderungan minat siswa kelas XII SMK Negeri 2 Ponorogo dalam memilih melanjutkan pendidikan ke perguruan tinggi atau langsung bekerja. Metode Naïve Bayes digunakan sebagai algoritma utama karena kemampuannya mengolah data secara probabilistik dengan tingkat akurasi yang baik dan implementasi yang sederhana. Atribut data yang digunakan meliputi jenis kelamin, jurusan, nilai rapor, minat siswa, dan pekerjaan orang tua. Perancangan sistem bertujuan untuk menyediakan alat bantu objektif berbasis data bagi guru Bimbingan Konseling dan wali kelas dalam memberikan bimbingan karier. Sistem dibangun dengan antarmuka web yang mudah diakses, memiliki dua peran pengguna (admin dan pengguna biasa), dan tidak memerlukan registrasi berbasis email. Hasil implementasi menunjukkan bahwa sistem mampu menghasilkan prediksi yang akurat dan mudah dipahami oleh pengguna non-teknis. Sistem ini memberikan manfaat signifikan bagi sekolah dalam mengoptimalkan pembimbingan karier, membantu siswa memahami kecenderungan pilihan pasca kelulusan, serta menjadi referensi bagi penelitian lanjutan di bidang sistem prediksi pendidikan.
SISTEM MONITORING ASET DENGAN ALGORITMA APRIORI BERBASIS WEB DI KAMPUS POLITEKNIK PERKERETAAPIAN INDONESIA MADIUN Wicaksono, Agung; Asrofi Buntoro, Ghulam; Rahmatika Az-Zahra, Rifqi
SinarFe7 Vol. 7 No. 1 (2025): SinarFe7-7 2025
Publisher : FORTEI Regional VII Jawa Timur

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Good asset management is one of the key factors in supporting the operational effectiveness of educational institutions, including at the Indonesian Railway Polytechnic (PPI) Madiun. However, manual asset management often leads to problems such as reporting delays, data discrepancies, and a lack of information patterns that can be utilized for decision-making. This research aims to develop a web-based asset monitoring system equipped with the Apriori algorithm to analyze the correlation patterns among asset data. The Apriori algorithm was chosen for its ability to extract association rules from large historical datasets, thereby supporting the asset evaluation and planning process. The research involves the stages of asset data collection and preprocessing, application of the Apriori algorithm to generate association rules with a minimum support value of 0.1 and a confidence value of 0.7. The system design is capable of providing accurate information on asset correlations and supports a more systematic monitoring process. This system is not only beneficial for operational management but also directly contributes as supporting data for LAMTEKNIK program study accreditation, particularly in the aspects of facilities-infrastructure and asset governance. In addition, this system can serve as part of the Internal Quality Audit (AMI) instruments, strengthening evidence of administrative orderliness and data-driven decision-making in quality assurance at PPI Madiun. Keywords: Apriori, Asset Monitoring, Data Mining, Web Information System, LAMTEKNIK, Internal Quality Audit Manajemen aset yang baik merupakan salah satu faktor kunci dalam mendukung efektivitas operasional institusi pendidikan, termasuk di lingkungan Politeknik Perkeretaapian Indonesia (PPI) Madiun. Namun, pengelolaan aset secara manual sering menimbulkan masalah seperti keterlambatan pelaporan, ketidaksesuaian data, dan kurangnya pola informasi yang dapat digunakan untuk pengambilan keputusan. Penelitian ini bertujuan untuk mengembangkan sistem monitoring aset berbasis web yang dilengkapi dengan algoritma Apriori untuk menganalisis pola keterkaitan antar data aset. Algoritma Apriori dipilih karena kemampuannya dalam mengekstraksi aturan asosiasi dari kumpulan data historis yang besar, sehingga mendukung proses evaluasi dan perencanaan aset. Penelitian ini menggunakan tahapan pengumpulan dan preprocessing data aset, penerapan Apriori untuk menghasilkan aturan asosiasi dengan nilai minimum support 0.1 dan confidence 0.7,. Perancangan sistem mampu memberikan informasi keterkaitan antar aset secara akurat dan mendukung kegiatan monitoring secara lebih sistematis. Sistem ini tidak hanya bermanfaat bagi pengelolaan operasional, tetapi juga berkontribusi langsung sebagai data dukung akreditasi program studi LAMTEKNIK, khususnya pada aspek sarana-prasarana dan tata kelola aset. Selain itu, sistem ini dapat menjadi bagian dari instrumen Audit Mutu Internal (AMI) yang memperkuat bukti tertib administrasi dan pengambilan keputusan berbasis data dalam penjaminan mutu di PPI Madiun. Kata Kunci: Apriori, Monitoring Aset, Data Mining, Sistem Informasi Web, LAMTEKNIK, Audit Mutu Internal
Implementasi Perancangan Automatic Watering And Nutrition Plant Berbasis Cam IoT Sebagai Monitoring Smart Farming Dinda Annura Sukmawati; Asrofi Buntoro, Ghulam; Intan Vidyastari, Rhesma
SinarFe7 Vol. 7 No. 1 (2025): SinarFe7-7 2025
Publisher : FORTEI Regional VII Jawa Timur

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Abstract

Agricultural development and food security still face various challenges, one of which is climate change. Extremely hot environmental temperatures in a region impact plant growth, which ultimately has the potential to reduce agricultural productivity. Therefore, an automated system is needed that allows timely watering control to support optimal plant growth. This study aims to design a Cam IoT-based smart farming monitoring system capable of monitoring plant conditions in real-time and remotely. The system is designed using an Arduino Mega microcontroller, an ESP32-CAM camera as an image capture device, and a soil moisture sensor to detect the condition of the growing medium. The obtained data is sent automatically via Telegram as a communication medium between the system and the user. The results of the study showed that the automatic watering pump is only active when the sensor value of the soil condition is dry (value > 750). The system successfully maintains the pH of the growing medium within the ideal range (6.0–7.0) for spinach plant growth. The integration of motion sensors and servos showed 100% success in detecting and responding to pest movements in the agricultural area. In 25 observations, there were 13 motion detections, and all were successfully responded to by moving the servo to a 90° angle. The conclusion of this study is that the IoT Cam-based monitoring system can perform key functions such as monitoring soil moisture and pH, visualizing the planting area, and automatically removing animals. This demonstrates the potential for IoT technology to be applied in smart farming practices, particularly to improve efficiency, productivity, and crop safety in the field.
Co-Authors Abdurrozzaq Zulkarnain, Ismail Agung Wicaksono Desriyanti, Desriyanti Dinda Annura Sukmawati Dwi, Dwi Prasetia Dwiyono Ariyadi, Dwiyono Dyah Mustikasari Ekatama, Hafidz Roja ihsan firdaus, muhammad bayu Intan Vidyastari, Rhesma Irfansyah, Muhammad Karaman, Jamilah Kuncoro, Fakih Moh iqbal bisri mustofa Permadi, Dimas Agus Permatasari, Dian Wahyu Puji Astuti, Indah Rahmatika Az-Zahra, Rifqi Ramadhan, Ardi Sugianti Sulthon Habiby, Jawwad Yoga, Robis Fahma Yovi Litanianda, Yovi