Article Per Year (5 Year)
p-Index From 2021 - 2026
0.61
P-Index
This Author published in this journals
All Journal PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Jurnal Ilmiah FIFO
Fandi Ali Mustika
Universitas Mercu Buana
Computer Science & IT Decision Sciences, Operations Research & Management

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Analisa Algoritma K-Means untuk Segmentasi Pelanggan Berbasis Data Transaksi dalam Sistem Insight Dashboard E-Commerce Muhammad Hilmy Setiawanto; Fandi Ali Mustika
Jurnal Ilmiah FIFO Vol. 18 No. 1 (2026)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/fifo.2026.v18i1.004

Abstract

Peningkatan volume dan kompleksitas data transaksi pada e-commerce berbasis Print-on-Demand menimbulkan tantangan dalam mengekstraksi insight pelanggan yang dapat ditindaklanjuti menggunakan pendekatan analitik konvensional. Meskipun algoritma K-Means telah banyak digunakan untuk segmentasi pelanggan, sebagian besar penelitian sebelumnya masih memiliki keterbatasan pada aspek validasi multi-metrik yang komprehensif serta minimnya integrasi dengan sistem pendukung keputusan yang aplikatif. Untuk mengatasi kesenjangan tersebut, penelitian ini mengusulkan kerangka segmentasi pelanggan berbasis K-Means yang dilengkapi dengan validasi cluster multi-metrik dan integrasi visualisasi analitik. Penentuan jumlah cluster optimal dilakukan melalui kombinasi metode Elbow dan metrik evaluasi internal, yaitu Silhouette Score, Calinski-Harabasz Index, dan Davies-Bouldin Index, guna memastikan keseimbangan antara ketahanan statistik dan interpretabilitas hasil. Hasil penelitian menunjukkan bahwa konfigurasi tiga cluster memberikan struktur segmentasi yang paling seimbang, serta mengungkap adanya ketimpangan signifikan dalam distribusi nilai pelanggan, di mana sebagian kecil pelanggan memberikan kontribusi dominan terhadap profit perusahaan. Untuk mengevaluasi aspek aplikatif, hasil clustering diimplementasikan ke dalam sistem Insight Dashboard dan dibandingkan dengan metode analisis manual berbasis spreadsheet menggunakan indikator kinerja efisiensi. Hasil evaluasi menunjukkan adanya peningkatan efisiensi analisis yang signifikan serta percepatan dalam identifikasi pelanggan bernilai tinggi. Kontribusi utama penelitian ini terletak pada integrasi validasi multi-metrik dalam penentuan cluster yang robust serta operasionalisasi hasil clustering ke dalam sistem dashboard sebagai pendukung pengambilan keputusan berbasis data pada lingkungan e-commerce Print-on-Demand.
Implementation of Proxy at XYZ Inc. Study: Experiment on Network Performance Optimization Fandi Ali Mustika; Muhammad Rifqi; Yuwan Jumaryadi; Febryo Ponco Sulistyo; Indah Ramadhani; Eko Prasetyo Pratomo
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 13 No. 2 (2025): September 2025
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v13i2.11535

Abstract

The rapid development of information technology demands companies to have a network infrastructure that is not only fast but also secure and efficient. PT. XYZ, as a company engaged in distribution and customer service, faces challenges in managing increasing data traffic while maintaining the stability and security of its internal network. One strategic solution to address this issue is the implementation of a proxy server. A proxy server functions as an intermediary between users and the internet, enabling it to filter data requests, store cache, and restrict access to unwanted content. Thus, the implementation of a proxy server can improve bandwidth efficiency, accelerate access to frequently used websites, and strengthen network security systems through traffic monitoring and restriction. This research aims to implement and evaluate the effectiveness of using a proxy server within PT. XYZ’s environment. The evaluation results show that the use of a proxy server can enhance network efficiency and provide better protection against cyber threats. With a more controlled and secure system, the company can run its operations more optimally and sustainably.
Energy-Aware Multi-Objective Deployment Optimization of Wireless Sensor Networks Using Direct Radio Graph Medium (DRGM) Modelling Fandi Ali Mustika; Ali Herdian; Prastika Indriyanti; Muhammad Rifqi
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 14 No. 1 (2026): March 2026
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v14i1.12233

Abstract

Wireless Sensor Networks (WSNs) are widely deployed for large-scale environmental monitoring applications, particularly in remote and maritime areas where manual surveillance is costly and impractical. One of the major challenges in WSN deployment is achieving full sensing coverage and network connectivity while minimizing energy consumption and deployment density. This paper proposes an energy-aware multi-objective deployment optimization model based on Direct Radio Graph Medium (DRGM) modeling. The deployment problem is formulated as a multi-objective optimization task aiming to minimize the number of active sensor nodes while maintaining communication connectivity under predefined sensing and transmission constraints. A genetic algorithm–based optimization mechanism is employed to generate Pareto-optimal deployment solutions. The proposed model is evaluated using NS-2 simulations under various node densities and traffic rates. Simulation results show that the DRGM-based deployment achieves full coverage using only 10 sensor nodes, compared to 50–100 nodes in random deployment, corresponding to a node reduction of up to 90%. Furthermore, the proposed approach significantly reduces network power consumption and radio duty cycles, demonstrating its effectiveness for energy-efficient and scalable WSN deployment in large monitoring areas.
Co-Authors Ali Herdian Eko Prasetyo Pratomo Indah Ramadhani Jumaryadi, Yuwan Muhammad Hilmy Setiawanto Muhammad Rifqi Ponco Sulistyo, Febryo Ponco Sulistyo Prastika Indriyanti