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All Journal JURNAL PENDIDIKAN TAMBUSAI Eksakta : Berkala Ilmiah Bidang MIPA Jurnal Teknologi Informasi dan Pendidikan Jurnal Talenta Sipil Abdimas Indonesian Journal Jurnal Kependudukan dan Pembangunan Lingkungan (JKPL)
Syafrijon, Syafrijon
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Religion Agriculture, Biological Sciences & Forestry Astronomy 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 Economics, Econometrics & Finance Education Energy Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Public Health Social Sciences

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Implementasi ESA Pada Pengamatan Lapangan di Kabupaten Pasaman Barat Bismihayati, Bismihayati; Agustanto, Dedy; Azriadi, Emon; Fatmawati, Fatmawati; Warmansyah, Frinsis; Nata, Lismomon; Wirman, Rahmi Putri; Joni, Riri Rahmawati; Sari, Mila; Gusfira, Mona; Sari, Serly Mutia; Wardeni, Siska; Syafrijon, Syafrijon
Jurnal Kependudukan dan Pembangunan Lingkungan Vol 4 No 1 (2023): Jurnal Kependudukan dan Pembangunan Lingkungan (JKPL)
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jkpl.v4i1.184

Abstract

Indonesia memiliki banyak wilayah dengan potensi pertambangan yang besar, diantaranya Nagari Muaro Kiawai, Kecamatan Gunung Tuleh, Kabupaten Pasaman Barat. Namun, dengan melakukan operasi penambangan skala kecil di daerah dekat sungai dan di tengah hutan yang berdampak negatif terhadap ekosistem, kegiatan penambangan emas ilegal telah menjadi sumber pendapatan bagi masyarakat di Nagari Muaro Kiawai. Tujuan dari survei lapangan ini adalah untuk mengetahui seberapa besar kerusakan ekosistem dan kehidupan nelayan di Nagari Muaro Kiawai yang terus menerus dirusak oleh penambangan emas. Dari hasil temuan diketahui bahwa kegiatan PETI berpengaruh nyata terhadap kualitas lingkungan di hilir dan kelestarian lingkungan serta degradasi lingkungan berdampak nyata terhadap hasil tangkapan ikan bagi nelayan, sehingga mempengaruhi pendapatan/pendapatan, sehingga ada ada beberapa rekomendasi yang dihasilkan dari kegiatan ini antara lain mentaati prinsip-prinsip mengenai pengelolaan lingkungan hidup dan adanya sanksi yang tegas terhadap pelaku perusakan lingkungan hidup, diperlukan gugus tugas yang melibatkan semua pihak untuk menindak tegas para perusak lingkungan hidup.
Proses Transformasi: Tinjauan Literatur pada Kawasan Industri Konvensional Menuju Kawasan Industri Berbasis Eco-Smart Syafrijon, Syafrijon
Jurnal Talenta Sipil Vol 7, No 2 (2024): Agustus
Publisher : Universitas Batanghari Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33087/talentasipil.v7i2.519

Abstract

Industrial estates contribute to the economy, but conventional estates can damage the environment. Green technology innovation, especially bio-based and renewable energy, is the solution. Investments in green technology support both the environment and the economy. And the 4th industrial revolution emphasizes sustainable manufacturing. So Eco-Smart based industrial estates with a focus on sustainability are the transformation solution. To knowing the framework for the transformation of conventional industrial estates to eco-smart based industrial estates and its impact on the industrial estate. This study used a literature review method that involved surveying various sources such as journals, books, documentation, internet, and literature relevant to the object of research. PICOT framework was used to search for international online journals with the keywords “Transformation Process, Conventional Industrial Estates, Eco-Smart Industrial Estates. The findings reveal that transforming industrial areas into eco-smart ones requires leadership, community participation and government financial support. Successful initiatives such as the Border Area Development Program in Saboo village, India, and China's progressive policies reflect a commitment to sustainable urbanization. The transformation process involves zone selection, context analysis, community participation, and optimization of Industrial Ecology (IE) and Industrial Symbiosis (IS). By reducing pollutant emissions, improving environmental quality, and contributing to urban green space construction, this transformation brings positive impacts in green innovation, industrial structure optimization, and environmental regulation strengthening, especially in eastern and northern cities with abundant human and financial resources.The transformation of conventional industrial estates to eco-smart industrial estates has resulted in positive impacts in innovation, improved environmental quality, and contributions to urban green spaces as well as financial improvements for the region. Top of Form
Design of a Sky Camera-Based Cloud Monitoring Camera at the Agam Space and Atmospheric Observation Station, Bukit Kototabang Syafrijon, Syafrijon; Fahmi Rahmatia; Ridho Pratama; Teguh Nugraha Pratama; Ednofri; Muzirwan; Ismail, Ainaa Maya Munira binti Ismail
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 24 No. 03 (2023): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/eksakta/vol23-iss03/426

Abstract

Indonesia is a center of convection and acts as a driving force for global atmospheric circulation due to its geographical position. Moreover, Kototabang Hill is one of the national strategic areas in the equatorial atmospheric observation room with limited cloud cover data so that tools and development are needed to meet these data needs. Sky Camera for the purpose of observing clouds (Cloud Camera) is urgently needed to complement the need for cloud cover data to support observation and research activities in the field of the atmosphere. The Cloud Camera design is done by modifying the CCD Camera with several supporting devices including fish eye, solar tracker, sun filter and dome. Evaluation of the urgency of these enhancements is discussed in this paper. Among the four combinations of using supporting instruments (dome and sun filter) for the Cloud Camera device, the best image obtained is the device that uses a sun filter and without a dome. Among the four combinations of using supporting instruments (dome and sun filter) for the Cloud Camera device, the best image obtained is the device that uses a sun filter and without a dome.
Penerapan Data Mining Untuk Klasifikasi Calon Siswa Penerima Program Indonesia Pintar (PIP) Menggunakan Algoritma Naive Bayes Suciko, Adelina; Hendriyani, Yeka; Budayawan, Khairi; Syafrijon, Syafrijon
Jurnal Pendidikan Tambusai Vol. 9 No. 2 (2025): Agustus
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai, Riau, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Program Indonesia Pintar (PIP) merupakan bantuan pendidikan yang ditujuakan bagi siswa dari keluarga kurang mampu. Namun, proses penentuan kelayakan penerima di sekolah masih dilakukan secara manual sehingga rawan ketidaktepatan sasaran. Penelitian ini bertujuan untuk membangun model klasifikasi kelayakan penerima PIP menggunakan algoritma Naive Bayes. Data yang digunakan mencakup 379 siswa dengan atribut penghasilan ayah, penghasilan ibu, jumlah saudara kandung, penerima KIP, penerima KPS serta status layak PIP. Tahapan klasifikasi dilakukan menggunakan perangkat lunak Orange dan hasilnya divisualisasikan melalui Tableau. Model dievaluasi dengan metrik akurasi, precision, recall dan AUC. Hasil menunjukkan bahwa model memiliki akurasi 85,9%, precision 86,3%, recall 85,9% dan AUC 0,973. Visualisasi membantu memperjelas distribusi dan kelayakan PIP. Model ini dapat mendukung keputusan yang lebih objektif dalam penyaluran bantuan PIP.
Implementasi Model Yolov8 untuk Deteksi Jenis Sampah Organik dan Anorganik Berbasis Android Ridha, Muhammad Rasyid; Syafrijon, Syafrijon; Hendriyani, Yeka; Hadi, Ahmaddul
Abdimas Indonesian Journal Vol. 5 No. 1 (2025)
Publisher : Civiliza Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59525/aij.v5i1.655

Abstract

The mismanagement of waste poses serious environmental and public health issues in Indonesia, exacerbated by the increasing volume of waste due to population growth. To address this problem, this research develops a mobile application based on Flutter, utilizing YOLOv8 object detection technology to classify organic and inorganic waste. The application aims to simplify household waste sorting, raise public awareness, and support better and more sustainable waste management. The research methodology involves using a dataset of waste images trained with the YOLOv8 algorithm via google colab. The dataset is divided into training (70%), testing (20%), and validation (10%) portions. The model training process is conducted over 25 and 50 epochs, showing improved accuracy with more epochs. At the 50th epoch, the model achieved a precision of 0.81 and a recall of 0.61, demonstrating good performance in detecting and classifying waste. The implementation of this application is expected to facilitate waste sorting, reduce environmental pollution, and improve public health. Recommendations for further development include enhancing detection accuracy, expanding the range of detectable waste types, and optimizing application performance to ensure a better user experience.
Optimalisasi Klasifikasi Warna Badan Air Dengan Convolutional Neural Network Melalui Reduksi Kelas Skala Forel-Ule Prasetyo, Budi; Novaliendry, Dony; Sriwahyuni, Titi; Syafrijon, Syafrijon
Jurnal Teknologi Informasi dan Pendidikan Vol. 18 No. 1 (2025): Jurnal Teknologi Informasi dan Pendidikan
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jtip.v18i1.970

Abstract

This study presents a method to optimize water color classification based on the Forel-Ule scale using a Convolutional Neural Network (CNN). The original 21-class system presents challenges such as high computational complexity, overlapping spectral characteristics, and class imbalance. A class reduction approach is proposed to group similar spectral categories into three ecologically meaningful classes: oligotrophic (clear blue), mesotrophic (greenish), and eutrophic (brownish). Using a dataset of 3,018 labeled water body images from EyeOnWater and implementing a CNN architecture trained on both the original and the reduced class schemes, the experimental results show that the reduced 3-class model achieved significantly higher accuracy (94.0%) compared to the original 21-class model (44.3%). These findings demonstrate that class reduction improves classification robustness, simplifies interpretation, and enhances practicality for real-world environmental monitoring.
Deteksi Anomali menggunakan Isolation Forest pada Permintaan Kebutuhan Farmasi Pasien di Rumah Sakit Mitra Sejati Medan Novaldi, Farhan; Syafrijon, Syafrijon; Hendriyani, Yeka; Anwar, Muhammad
Jurnal Pendidikan Tambusai Vol. 9 No. 2 (2025): Agustus
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai, Riau, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Rumah Sakit Mitra Sejati Medan menghadapi tantangan dalam mengelola volume permintaan farmasi yang tinggi, menyebabkan proses verifikasi manual menjadi tidak efisien dan berisiko. Penelitian ini bertujuan merancang dan mengimplementasikan sistem deteksi anomali untuk meningkatkan efektivitas pengelolaan permintaan. Metode yang digunakan adalah algoritma Isolation Forest dengan menerapkan metodologi Cross-Industry Standard Process for Data Mining. Data historis permintaan obat, barang medis habis pakai, dan alat kesehatan diolah menggunakan Python untuk melatih model secara kontekstual. Hasil penelitian menunjukkan dari 2.167.942 transaksi, model berhasil mengidentifikasi 13.503 (0,62%) permintaan sebagai anomali statistik. Sistem yang dikembangkan melalui aplikasi web ini terbukti berhasil menjadi alat bantu keputusan berbasis data untuk meningkatkan efisiensi operasional, akurasi stok, dan memberikan peringatan dini.
Co-Authors Agustanto, Dedy Ahmaddul Hadi, Ahmaddul Bismihayati, Bismihayati Budayawan, Khairi Budi Prasetyo Dony Novaliendry Ednofri Emon Azriadi Fahmi Rahmatia Fatmawati Fatmawati Gusfira, Mona Ismail, Ainaa Maya Munira binti Ismail Joni, Riri Rahmawati Muhammad Anwar Muhammad Rasyid Ridha Muzirwan Nata, Lismomon Novaldi, Farhan Rahmi Putri Wirman Ridho Pratama Sari, Mila Sari, Serly Mutia Suciko, Adelina Teguh Nugraha Pratama Titin Sriwahyuni Wardeni, Siska Warmansyah, Frinsis Yeka Hendriyani