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All Journal Jurnal Simetris Speed - Indonesian Journal on Computer Science Seruni - Seminar Riset Unggulan Nasional Inoformatika dan Komputer Speed - Sentra Penelitian Engineering dan Edukasi Jurnal Teknik Informatika (JUTIF) Indonesian Journal of Networking and Security - IJNS
Berliana Kusuma Riasti
Surakarta University
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering

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Pembangunan Sistem Informasi Inventarisasi Sekolah Pada Dinas Pendidikan Kabupaten Rembang Berbasis Web Sholikhin, Akhmad; Riasti, Berliana Kusuma
IJNS - Indonesian Journal on Networking and Security Vol 2, No 2 (2013): IJNS April 2013
Publisher : APMMI - Asosiasi Profesi Multimedia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (976.173 KB)

Abstract

Abstrak:Perkembangan ilmu pengetahuan dan teknologi yang saat ini berkembang dengan begitu pesatnya. Semua itu dikembangkan dengan tujuan untuk memberikan kemudahan bagi manusia dalam melaksanakan tugas dan kepentingannya. Inventarisasi sekolah di lingkungan Dinas Pendidikan Kabupaten Rembang saat ini masih dalam cara konvensional dengan mencatat pada buku inventaris kemudian direkap hasilnya secara manual pula, selain itu untuk penerimaan laporan dari sekolah juga harus melalui beberapa tahapan, yaitu sekolah datang langsung ke kantor dinas untuk mengirimkan berkas data inventaris. Hal ini menyebabkan proses memakan waktu lama dan tidak terkendali dengan baik, selain itu juga tingkat kecepatan akses data (laporannya) jika dibutuhkan sewaktu-waktu jadi terlambat. Inventarisasi sekolah dengan sistem komputerisasi yang diharapkan nantinya dapat mengatasi permasalahan yang telah ada. Metode yang digunakan dalam penelitian ini adalah observasi, wawancara, kepustakaan, analisis, perencanaan, perancangan atau desain, pembangunan, uji coba sistem serta implementasi sistem. Dari penelitian ini dihasilkan sistem yang bisa memberikan kemudahan dalam pelaksanaan kegiatan koordinasi inventarisasi sekolah, serta bisa meningkatkan efektifitas dan efisiensi kerja. Kata Kunci : Inventarisasi, Dinas Pendidikan Kabupaten Rembang   Abstract – Science and technology growth that at this time expand that way fast its. All of that developed as a mean to give amenity for human in its getting tasks done and importance. School’s inventories in environment Educatioan States of Rembang at this time still in conventional way by note at inventories book then summarized the result manually also, in other hand for report acceptance from school also must passed by some steps, that is school comes direct to office on duty to deliver bundle of inventories data. This condition causes process eats old time and not in control properly, in other hand also data access level speed if required at any times become late. School’s inventories with expected computerization system later can overcome problems that already. Method as used in research this is the observation, interview, bibliography, analysis, planning, design or design, development, system test-drive and system implementation. From this research expected in order to give amenity in execution of stocktaking coordination activity school, and can improve efectivity and job efficiency. Keywords: Inventories, Educational State of Rembang
A Hybrid Approach for Recommender Systems Based on Alternating Least Squares and CatBoost Yusfida A'la, Fiddin; Hartatik, Hartatik; Riasti, Berliana Kusuma
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.5002

Abstract

This study aims to improve the accuracy of movie rating predictions by applying and combining collaborative filtering and machine learning techniques in a hybrid recommender system. The research utilizes the MovieLens dataset to implement two distinct approaches: the Alternating Least Squares (ALS) matrix factorization model and the CatBoost gradient boosting model. The ALS model is trained to capture latent user–item interactions, while CatBoost leverages nonlinear relationships using user and item features. A simple hybrid strategy averages the predictions from both models to evaluate potential performance gains. Experimental results show that the hybrid approach achieves lower error metrics compared to either model individually, with Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE) values of 0.828 and 0.666, respectively. This demonstrates that combining latent factor models with tree-based learning can effectively reduce prediction errors by exploiting complementary strengths. The novelty of this research lies in its efficient yet effective hybridization strategy that improves recommendation quality without complex ensembling techniques. The findings suggest that even lightweight model fusion can significantly enhance predictive accuracy in recommender systems and may be adapted for other domains where combining linear and nonlinear modeling is beneficial. This research contributes to the field of Informatics and Computer Science by demonstrating that a lightweight hybridization of latent factor models and tree-based learning can significantly improve recommender system accuracy while offering practical implications for real-world digital applications.
Co-Authors Aditya Prihantara Akhmad Sholikhin Alex Fahrudin Alfian Eko Hery Setyawan Anjar Priyadna ‘Adhim, Ismu Bambang Eka Purnama Budhi Santoso Dafit Nur Hidayanto Eko Wahyudianto Endah Setyorahayu Hartatik Hidayah, Insani Nur Hisyam Wahid Luthfi Ida Asta Rina Ismu ‘Adhim Kaharudin Setiyawan Luky Adrianto Muhammad Khoirul Nur Badri Ongki Risti Pramitha Dita Syilvia Purnama, Bambang Eka Puryanto . Ramadian Agus Triyono Riky Hardianti Rindo, Akhmad Rini Purwanti Rudi Hartono Salsabila, Unik Hanifah Samuri . Sinta Susilowati Sri1 Haryanti Sukadi . Tri Agus Setiawan Tri Irianto TJ Yoni Widhiarso Yusfida A'la, Fiddin