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All Journal Jurnal Sistem Komputer dan Informatika (JSON) Jurnal Pendidikan dan Ilmu Sosial Jurnal Ilmiah Research Student
Inneke Putri
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Religion Arts Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology

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IMPLEMENTASI APLIKASI STOK BARANG PERANGKAT JARINGAN BERBASIS WEB DI PT ZATHCO Inneke putri; Dwi prapita sari; Mhd ikhsan rifki
JURNAL ILMIAH RESEARCH STUDENT Vol. 1 No. 3 (2024): Januari
Publisher : CV. KAMPUS AKADEMIK PUBLISING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61722/jirs.v1i3.835

Abstract

The system currently used experiences problems in handling recipient and delivery data, customer data, and inventory data which are recorded on paper and only copied by the admin to the company computer. These problems can result in product calculation errors, problems in recording and reporting product recipients and deliveries, and in several months the product in and out can reach the target. There are often differences in inventory. This is caused by a helper or admin error. The warehouse department is recording, receiving and sending products. In addition, the accumulation of large numbers of files can make it difficult to find the product data you need, and searching files can take time and interfere with other tasks. The aim of this research is to develop an inventory management application that can manage recipient or delivery data, inventory data, and delivery data using visual modeling used in building object-oriented systems and waterfall system development methods. This is about developing a website that is created to simplify incoming goods data and outgoing goods data so that it can help business processes in the company.
Penerapan Deep Learning dalam Analisis Citra Gigi Supiyandi Supiyandi; Wahyu Eka Judistira; Sepriana Nurliani; Rondi Sahputra Darmono; Inneke Putri
JURNAL PENDIDIKAN DAN ILMU SOSIAL (JUPENDIS) Vol. 2 No. 4 (2024): Oktober : JURNAL PENDIDIKAN DAN ILMU SOSIAL
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jupendis.v2i4.2165

Abstract

Testing in dental medical recognition and recording is still done manually, causing it to take a long time. In this study, an object detection method was applied to assist doctors in identifying patient conditions. Convolutional Neural Network (CNN) method was trained with an intraoral image dataset that includes five categories of tooth conditions: normal, filling, caries, and residual roots. CNN performance evaluation was conducted using evaluation metrics, and the results showed that the best CNN model achieved an mAP of 84% and a testing accuracy of 82%. This research successfully achieved its main goal, which is to build a reliable deep learning model for dental disease detection and recognition in humans.
Penerapan Metode Collaborative Filtering untuk Rekomendasi Pemilihan Bibit Herbal Temulawak Inneke Putri; M. Fakhriza
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 7 No. 2 (2025): Desember 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v7i2.9352

Abstract

Budidaya tanaman obat di Indonesia menunjukkan perkembangan signifikan seiring meningkatnya industri obat tradisional dan tren masyarakat terhadap gaya hidup alami. Temulawak (Curcuma xanthorrhiza) merupakan salah satu tanaman herbal unggulan yang memiliki nilai ekonomi tinggi serta manfaat kesehatan karena kandungan kurkuminoid, minyak atsiri, dan senyawa bioaktif lainnya. Namun, pemilihan bibit temulawak berkualitas masih sering dilakukan berdasarkan pengalaman subjektif petani, sehingga berpotensi menghasilkan ketidaktepatan dalam budidaya. Penelitian ini bertujuan menentukan bibit temulawak terbaik dengan menerapkan metode Collaborative Filtering sebagai sistem rekomendasi berbasis preferensi pengguna. Metode yang digunakan adalah pendekatan kuantitatif dengan model pengembangan sistem Rapid Application Development (RAD). Data diperoleh melalui observasi, wawancara, studi pustaka, serta pengumpulan rating bibit dari petani di Desa Pulo Bandring, Kabupaten Asahan. Proses perhitungan rekomendasi dilakukan menggunakan Item-Based Collaborative Filtering yang menghasilkan skor prediksi untuk setiap alternatif bibit. Hasil penelitian menunjukkan bahwa metode Collaborative Filtering mampu memberikan rekomendasi bibit secara lebih objektif. Bibit dengan nilai rekomendasi tertinggi diperoleh oleh Bibit 1 (C1) dengan skor 4,349, sedangkan nilai terendah diperoleh oleh Bibit 4 (C4) dengan skor 1,533. Sistem rekomendasi yang dibangun dapat membantu petani memilih bibit temulawak terbaik secara terukur dan efektif, serta berpotensi meningkatkan hasil panen dan pendapatan.
Co-Authors Dwi Prapita Sari M. Fakhriza Mhd Ikhsan Rifki Rondi Sahputra Darmono Sepriana Nurliani Supiyandi Supiyandi Wahyu Eka Judistira