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All Journal Jurnal Pengabdian Masyarakat Nusantara Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI)
Regizka Ayu Mega Saputri
Universitas Muria Kudus
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Engineering Social Sciences

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Implementasi Sistem Informasi Perekrutan Karyawan Berbasis Web pada PT Citra Wahana Nusantara Unit Dua Kelinci Regizka Ayu Mega Saputri; Eko Darmanto
Jurnal Pengabdian Masyarakat Nusantara (JPMN) Vol. 6 No. 1 (2026): Februari - Juli 2026
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) - Lembaga KITA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jpmn.v6i1.7138

Abstract

PT Citra Wahana Nusantara Unit Dua Kelinci is a labor outsourcing company recruits an average of 40 employees per day. The recruitment process is still conducted using conventional methods, including manual registration, the management of applicant data that is not yet integrated, and the delivery of information via messaging applications such as WhatsApp. This makes the selection process less efficient, prone to registration errors, and difficult to monitor the status of applications in real time. This study aims to design and build a web-based Employee Recruitment Information System, equipped with online registration, test scheduling, application tracking, and Fixed-Term Employment Contract (FTE) management, to improve the efficiency of human resource management. This study employs an applied research approach using the waterfall (a sequential software development lifecycle model) system development method, which includes the stages of needs analysis, system design, implementation, testing, and maintenance. Data collection was carried out through direct observation, interviews with the Human Resources Department, and literature reviews. The system was developed using the PHP programming language with a MySQL database. The study results demonstrate that the developed system integrates the entire recruitment process onto a single digital platform, from online registration, document verification, and test scheduling, to real-time tracking of application status and the management of employment contracts. This study recommends implementing an integrated information system as a solution for digitizing human resource management, especially in outsourcing companies with high recruitment volumes.
Analisis Segmentasi dan Prediksi Pola Pembelian IC Label Gamis Menggunakan Hybrid K-Means Random Forest Chandra Ayu Fatikasari; Alifa Marsha Rahmania; Lu’lu’il Laili; Regizka Ayu Mega Saputri; Muhammad Arifin
Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Vol. 5 No. 1 (2026): Juni 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juktisi.v5i1.1007

Abstract

Industri fashion muslim, khususnya busana gamis, menghadapi tantangan dalam memahami pola pembelian konsumen yang bersifat fluktuatif, sehingga kerap menimbulkan permasalahan overstock dan stockout. Penelitian ini bertujuan untuk menganalisis segmentasi pelanggan dan memprediksi pola pembelian gamis pada toko IC Label melalui pendekatan hibrida yang mengintegrasikan algoritma K-Means Clustering dan Random Forest Classification. Data yang digunakan merupakan 1.000 transaksi penjualan dari platform e-commerce Shopee pada periode Januari 2025 hingga Maret 2026. Metodologi penelitian mengacu pada kerangka kerja CRISP-DM, yang meliputi eksplorasi data, preprocessing, ekstraksi fitur RFM, pemodelan, serta evaluasi. Hasil penerapan K-Means dengan K=4 menghasilkan empat segmen pelanggan yang terdistribusi secara merata, yaitu: Pembeli Premium Wilayah Jawa (26,1%), Pembeli Sumatera Sensitif Diskon (24,9%), Pembeli Digital Wilayah Kepulauan (23,3%), dan Pembeli Mitra Wilayah Sumatera Bagian Selatan (25,7%). Label klaster hasil segmentasi selanjutnya digunakan sebagai variabel target pada model Random Forest, yang menghasilkan akurasi 96,38% pada data latih dan 68,00% pada data uji dengan konsistensi cross-validation 5-fold sebesar 68,70% (±3,50%). Analisis feature importance mengidentifikasi variabel provinsi (40,5%) dan jasa pengiriman (26,8%) sebagai faktor paling dominan dalam menentukan segmen pembeli. Simulasi prediksi pada pembeli baru membuktikan kemampuan model dalam mengklasifikasikan segmen secara real-time. Penelitian ini berkontribusi secara praktis dalam mendukung strategi pemasaran tersegmentasi, optimasi manajemen inventori, dan penguatan loyalitas pelanggan berbasis data pada industri fashion muslim
Co-Authors Alifa Marsha Rahmania Chandra Ayu Fatikasari Eko Darmanto Lu’lu’il Laili Muhammad Arifin