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Analisis Efektivitas Layanan M-Paspor Berdasarkan ITIL V3 pada Kantor Imigrasi Kelas I TPI Cirebon Putri Ajeng Larasmanah; Marsani Asfi; Agus
Teknik: Jurnal Ilmu Teknik dan Informatika Vol. 5 No. 2 (2025): Oktober : Teknik: Jurnal Ilmu Teknik dan Informatika
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi - Studi Ekonomi Modern

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/teknik.v5i2.910

Abstract

This study evaluates the effectiveness of M-Passport service management at the Immigration Office Class I TPI Cirebon using the ITIL V3 framework, focusing on Service Strategy and Service Operation. A quantitative approach was applied through observation, structured interviews, and questionnaires distributed to applicants and staff. Data were analyzed using Maturity Level assessment and GAP Analysis. The findings indicate that the M-Passport service has reached Level 4 (Managed) with an average score of 3.77, showing that processes are measurable, controlled, and consistently implemented. However, Incident Management remains at Level 3 (Defined) with the largest deviation from the expected level, while Problem Management, Request Fulfillment, and Business Relationship Management also show minor gaps. The study recommends strengthening incident handling procedures, enhancing communication strategies, improving applicants’ digital literacy, and increasing staff competencies. These improvements are expected to optimize ITIL V3 implementation and enhance technology-based public service delivery.
MODEL HOT (HUMAN, ORGANIZATION, TECHNOLOGY) FIT UNTUK EVALUASI PENERAPAN APLIKASI SIPANDAI UNTUK PENGGUNA DOSEN (STUDI KASUS : UNIVERSITAS CATUR INSAN CENDEKIA KOTA CIREBON) Devi, Silviana; Marsani Asfi; Mesi Febima
METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Vol. 10 No. 2 (2024): Volume 10 Nomor 2
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/mtk.v10i2.3268

Abstract

Universitas Catur Insan Cendekia telah menerapkan e-learning melalui Sistem Informasi Pembelajaran dan Administrasi Terintegrasi (SIPANDAI). Namun, terdapat beberapa permasalahan dalam aplikasi SIPANDAI yaitu adanya perbedaan penguasaan komputer dan kurangnya feedback dalam sosialisasi, kurang sistematis saat terjadi kesalahan data dan perlu adanya pengembangan beberapa fitur seperti pada fitur kelola pertemuan, fitur generate absen dan fitur cancel. Adapun tujuan penelitian ini adalah mengevaluasi aplikasi SIPANDAI untuk menilai sejauh mana kelayakan dan kesuksesan penerapan aplikasi SIPANDAI di Universitas Catur Insan Cendekia. Metode yang digunakan dalam penelitian ini adalah Model HOT (Human, Organization, Technology) FIT. Model ini melibatkan 3 aspek utama yaitu Human, Organization, Technology yang memiliki beberapa variabel seperti Pengguna Sistem, Kepuasan Pengguna, Stuktur Organisasi, Lingkungan Oragnisasi, Kualitas Sistem, Kualitas Informasi, Kualitas Layanan dan Manfat Bersih. Hasil penelitian ini, variabel yang berpengaruh kuat pada keberhasilan penerapan aplikasi SIPANDAI adalah variabel Kualitas Informasi terhadap Pengguna Sistem dengan nilai 0,743. Dan variabel yang berpengaruh lemah adalah variabel Struktur Organisasi terhadap Manfaat Bersih dengan nilai 0,421. Oleh karena itu, diperoleh rekomendasi yang dapat diberikan ke bagian pusdatin untuk melakukan perbaikan dan pengembangan pada fitur aplikasi SIPANDAI. Kata Kunci : E-Learning, UCIC, Model HOT Fit, Evaluasi, SIPANDAI
IMPLEMENTASI K-MEANS RFM DAN HOLT-WINTERS EXPONENTIAL SMOOTHING ADDITIVE DALAM SISTEM BUSINESS INTELLIGENCE UNTUK STRATEGI PENGELOLAAN PELANGGAN PADA PERUSAHAAN TRANSPORTASI Belfania Priandini; Marsani Asfi; Lena Magdalena
METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Vol. 11 No. 2 (2025): Volume 11 Nomor 2 Tahun 2025
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The growth of customer data in the transportation industry drives the need for analytical systems capable of segmenting customers objectively and strategically. This study aims to apply the K-Means Clustering method based on the Recency, Frequency, and Monetary (RFM) model for customer segmentation and utilize the Holt-Winters Exponential Smoothing Additive method to forecast passenger numbers. The dataset comprises 10,440 customer transactions from PT XYZ during the 2022–2024 period. RFM values were calculated, normalized, and processed using the K-Means algorithm to produce three customer clusters: Loyal, Regular, and Passive. Subsequently, the Holt-Winters method was employed to forecast passenger numbers, achieving the smallest Mean Absolute Percentage Error (MAPE) of 6.88%, indicating a high level of accuracy. The results were visualized through an interactive dashboard using Tableau, enabling management to make data-driven decisions. This research demonstrates that integrating segmentation and forecasting methods into a Business Intelligence system can enhance the effectiveness of marketing strategies and the operational efficiency of the company.