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All Journal Jurnal Informatika dan Teknik Elektro Terapan Jurnal Pilar Nusa Mandiri JITK (Jurnal Ilmu Pengetahuan dan Komputer) INTI Nusa Mandiri BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer IPSIKOM Innotech Journal of Informatics and Advanced Computing Journal of Applied Research In Computer Science and Information Systems
Hesananda, Rizki
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Industrial & Manufacturing Engineering

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Journal : Journal of Informatics and Advanced Computing

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Rancang Bangun Aplikasi Pengajuan dan Perhitungan Lembur Pekerja untuk Meningkatkan Efisiensi SDM di BRI Cabang Veteran Hesananda, Rizki; Surya Kencana, Nurrahman Putra
Journal of Informatics and Advanced Computing (JIAC) Vol 5 No 2 (2024): Journal of Informatics and Advanced Computing
Publisher : Universitas Pancasila

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35814/jiac.v5i2.7766

Abstract

Pengelolaan perhitungan lembur secara manual pada bagian Penunjang Operasional Layanan SDM PT. Bank Rakyat Indonesia (Persero), Tbk Kantor Cabang Jakarta Veteran sering kali memakan waktu dan tidak efisien. Proses ini melibatkan pengumpulan dokumen lembur fisik, yang menyebabkan keterlambatan dan potensi kesalahan dalam penginputan data. Penelitian ini bertujuan untuk merancang dan membangun sistem informasi perhitungan lembur berbasis web menggunakan PHP dan MySQL guna meningkatkan efektivitas proses pengajuan lembur. Metode pengembangan yang digunakan adalah Waterfall Model, dimulai dari analisis kebutuhan melalui observasi lapangan, perancangan sistem dengan UML dan High Fidelity Mockup, implementasi menggunakan PHP dan HTML, serta pengujian dengan metode Black Box Testing. Hasil evaluasi menunjukkan bahwa rata-rata waktu pengerjaan lembur oleh petugas SDM tanpa sistem adalah 186 menit, sedangkan dengan sistem informasi perhitungan lembur menjadi 33 menit. Dengan demikian, sistem yang dikembangkan mampu menghemat waktu pengerjaan hingga 153 menit atau sekitar 82,3%. Kesimpulannya, sistem informasi yang diusulkan dapat meningkatkan efektivitas dan efisiensi dalam proses pengajuan lembur serta meminimalkan kesalahan penginputan data. Sistem ini diharapkan dapat diintegrasikan dengan aplikasi web BRI Human Capital (BRIHC) untuk mendukung pengolahan data yang lebih lanjut.
Penerapan Klasterisasi K-Means terhadap Produktivitas Padi di Pulau Sumatera sebagai Strategi Pendukung Ketahanan Pangan Hesananda, Rizki
Journal of Informatics and Advanced Computing (JIAC) Vol 6 No 1 (2025): Journal of Informatics and Advanced Computing
Publisher : Universitas Pancasila

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35814/ve9jhz24

Abstract

Rice production is a crucial aspect of national food security, particularly in the Sumatra region, which plays a strategic role as Indonesia's food barn. This study was conducted to identify rice production patterns based on the characteristics of harvested area and annual production yields in order to produce a more informative segmentation of productivity areas. The main objective of this study is to segment rice production data using a clustering method, and evaluate the clustering results using statistical metrics and data mining visualization. The methodology used follows the CRISP-DM approach, with stages of data exploration, visualization, modeling, and evaluation. The algorithm used is K-Means Clustering with a total of three clusters. Data were obtained from Kaggle and BMKG, covering 8 provinces in Sumatra Island between 1995 and 2020, with a total of 208 annual observation data entries. The results show that the clustering model built has very good quality with a Silhouette Score of 0.7147 and a Davies-Bouldin Index (DBI) of 0.3752. The scatterplot visualization shows clear segmentation between clusters based on harvested area and production. In conclusion, the clustering approach is effective in classifying regions based on rice production characteristics. The implications of this research support the optimization of data-driven agricultural land management policies. For industry stakeholders and decision-makers, the results can provide a basis for prioritizing interventions, channeling agricultural assistance, and planning for sustainable food security at the regional level.
Co-Authors Agus Trihandoyo Apriliga, Patri Faizal Racma, Dhany Firmansyah, Vian Issa Wirakusumah, Raden Mochamad Mulyawan, Yudhi Natasya, Desima Noviani, Irma Ayu Prianggara, Erdham Hestiadhi Rahmawati, Nidya Sari Surya Kencana, Nurrahman Putra Tiara, Beby Widiyaningrum, Diyah Kiki Wiliani, Ninuk Zulfariansyah, Muhammad