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All Journal Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Academic Journal of Computer Science Research (AJCSR) SOROT: Jurnal Pengabdian Kepada Masyarakat
Haddad Alwi Yafie
School Of Computing - Telkom University
Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering Mechanical Engineering Other

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Corn Seeds Identification Based on Shape and Colour Features Yafie, Haddad Alwi; Rachmawati, Ema; Prakasa, Esa; Nur, Amin
Khazanah Informatika Vol. 6 No. 2 October 2020
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v6i2.10840

Abstract

Corn is one of the agricultural products that are essential as daily food sources or energy sources. Corn selection or sorting is important to produce high-quality seeds before its distribution to areas with varying conditions and agricultural characteristics. Hence, it is necessary to build corn seeds identification. In this paper, we propose a corn seed identification technique that incorporates the advantage of combining shape and colour features. The identification process consists of three main stages, namely, ROI selection, feature extraction, and classification using the Artificial Neural Network (ANN) algorithm. The shape feature originates from the eccentricity value or comparison value between a distance of minor ellipse foci and major ellipse foci of an object. Meanwhile, the color features are extracted based on the HSV (Hue-Saturation-Value) channel. The experimental result shows that the proposed system achieves excellent performance for the identification of poor and good corn quality for BIMA-20 and NASA-29 species. The classification result for BIMA-20 Good vs. BIMA-20 Bad gives an accuracy of 89%, while the classification accuracy of BIMA-20 Good vs. NASA-29 Good is 97%.
Corn Seeds Identification Based on Shape and Colour Features Haddad Alwi Yafie; Ema Rachmawati; Esa Prakasa; Amin Nur
Khazanah Informatika Vol. 6 No. 2 October 2020
Publisher : Department of Informatics, Universitas Muhammadiyah Surakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v6i2.10840

Abstract

Corn is one of the agricultural products that are essential as daily food sources or energy sources. Corn selection or sorting is important to produce high-quality seeds before its distribution to areas with varying conditions and agricultural characteristics. Hence, it is necessary to build corn seeds identification. In this paper, we propose a corn seed identification technique that incorporates the advantage of combining shape and colour features. The identification process consists of three main stages, namely, ROI selection, feature extraction, and classification using the Artificial Neural Network (ANN) algorithm. The shape feature originates from the eccentricity value or comparison value between a distance of minor ellipse foci and major ellipse foci of an object. Meanwhile, the color features are extracted based on the HSV (Hue-Saturation-Value) channel. The experimental result shows that the proposed system achieves excellent performance for the identification of poor and good corn quality for BIMA-20 and NASA-29 species. The classification result for BIMA-20 Good vs. BIMA-20 Bad gives an accuracy of 89%, while the classification accuracy of BIMA-20 Good vs. NASA-29 Good is 97%.
Optimalisasi Penjualan Ritel Furniture melalui Aplikasi Mobile Berbasis Android: Studi Kasus Transformasi Digital pada UMKM Zailani, Achmad Udin; Nurmaningsih, Desi; Putro, Zuki Pristiantoro; Muttaqin, Widang; Yafie, Haddad Alwi
Academic Journal of Computer Science Research Vol 7, No 2 (2025): Academic Journal of Computer Science Research (AJCSR)
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/ajcsr.v7i2.15912

Abstract

Perkembangan pesat teknologi digital mendorong kebutuhan sistem informasi modern dan mudah diakses. Toko Jaya Mandiri Furniture (UMKM furnitur) menghadapi tantangan operasional akibat ketergantungan pada proses manual, promosi terbatas, dan jangkauan pasar sempit. Sistem manual mengakibatkan proses bisnis lambat, kesulitan penyajian informasi produk, serta interaksi daring terbatas. Penelitian ini merancang aplikasi mobile berbasis Android untuk mengoptimalkan penjualan, memperluas pasar, dan meningkatkan efisiensi. Metode PIECES digunakan untuk analisis kebutuhan sistem, menunjukkan performa rendah pada sistem lama. Pemodelan sistem dilakukan dengan UML, sedangkan desain antarmuka menggunakan Figma dengan prinsip user-centered design (UCD). Hasil pengujian prototipe menunjukkan aplikasi efektif menjawab permasalahan toko: mempermudah promosi, pemesanan, manajemen transaksi, dan pelacakan pesanan. Validasi melalui survei 40 responden: kepuasan pengguna mencapai 86% dengan skor rata-rata 4,15 dari 5, dan aspek persepsi visual 4,3 dari 5. Temuan membuktikan aplikasi memberikan pengalaman pengguna positif dan efisien, serta mendukung transformasi digital UMKM furnitur.
Desa Cerdas Cikasungka: Inovasi Pelayanan Administrasi Melalui Sistem Informasi Desa Yafie, Haddad Alwi; Aulia, Indra; Solehuddin, Muhammad; Putro, Zuki Pristiantoro
SOROT : Jurnal Pengabdian Kepada Masyarakat Vol 4 No 2 (2025): Juli
Publisher : Fakultas Teknik dan Ilmu Komputer (FASTIKOM) UNSIQ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32699/sorot.v4i2.9635

Abstract

Program pengabdian masyarakat ini mengembangkan sistem informasi desa berbasis web untuk mendukung transformasi digital di Desa Cikasungka. Menggunakan pendekatan Design Thinking dalam perancangan partisipatif dan metode Scrum dalam implementasi iteratif, sistem ini menghadirkan fitur utama: otomasi pengajuan surat, dashboard kependudukan terintegrasi, dan portal informasi publik. Hasil implementasi menunjukkan peningkatan efisiensi signifikan: waktu layanan administrasi berkurang dari 5.2 hari menjadi 1.5 hari (penurunan 71.2%), kesalahan data menurun 40.9%, dan frekuensi kunjungan kantor desa berkurang 66.7%. Pengujian dengan 100 pengguna mengungkapkan 93% menyelesaikan pengajuan surat dalam <15 menit dan 78% pengguna lansia beroperasi secara mandiri tanpa bantuan. Pelatihan intensif bagi 15 perangkat desa menggunakan modul bilingual (Indonesia-Sunda) menjamin keberlanjutan sistem. Inisiatif ini mendukung pencapaian SDGs Tujuan 9 (Inovasi Infrastruktur) dan Tujuan 16 (Tata Kelola Inklusif) melalui peningkatan transparansi layanan publik.
Co-Authors Achmad Udin Zailani Amin Nur AMIN NUR Ema Rachmawati Esa Prakasa Esa Prakasa, Esa Indra Aulia M. Solehuddin Muttaqin, Widang Nurmaningsih, Desi Syamsul Arifin Zuki Pristiantoro Putro