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All Journal PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Jurnal Khatulistiwa Informatika Techno Nusa Mandiri : Journal of Computing and Information Technology
Jafar Shadiq
Universitas Bina Insani
Computer Science & IT Decision Sciences, Operations Research & Management

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Sistem Pengolahan Data Keluhan Pelanggan Berbasis Web Menggunakan Extreme Programming Method Dwi Ismiyana Putri; Jafar Shadiq; Muhammad Surya Apandi; Muhammad Ari Kuncoro
Jurnal Khatulistiwa Informatika Vol 10, No 2 (2022): Periode Desember 2022
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/jki.v10i2.14371

Abstract

Keluhan pelanggan menjadi langkah yang dapat diambil oleh perusahaan dalam menilai layanan yang diberikan kepada pelanggan, apakah pelanggan merasa puas atau tidak. Seringkali, waktu pelayanan menjadi hambatan dalam mengatasi masalah yang ada. Pertimbangan ini menjadi acuan perusahaan untuk dapat memberikan pelayanan terbaik kepada seluruh pelanggan atas pengaduan yang diberikan dari produk-produk layanan. Ditambah dengan keadaan kritis dikarenakan penyebaran virus covid-19 yang menjadi keterbatasan dalam mengakomondir semua jenis keluhan dari pelanggan. Sehingga diperlukan sebuah sistem keluhan pelanggan yang dapat membantu meningkatkan kinerja customer service. Sistem informasi keluhan pelanggan yang dikembangkan menggunakan Metode Extream Programming berbasis website dengan dibantu implementasi freamwork Laravel 9 dalam proses pengembangannya. Sistem informasi yang telah dikembangkan akan digunakan untuk menjamin tidak terjadi antrian dalam menangani keluhan pelanggan dengan memanfaatkan kinerja teknisi yang terakomondir secara jelas.
THE POWER OF ADAPTABILITY: ACHIEVING AGILITY AND QUALITY IN WEB BASED COMPANY PROFILES THROUGH EXTREME PROGRAMMING Harjunadi Wicaksono; Jafar Shadiq; Dwi Ismiyana Putri; Rina Sayekti
Jurnal Techno Nusa Mandiri Vol 20 No 1 (2023): Techno Nusa Mandiri : Journal of Computing and Information Technology Period of
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v20i1.4219

Abstract

This study explores the utilization of Extreme Programming (XP) methodology, coupled with black box testing, in developing a Web-Based Company Profile as a supportive medium for information and promotional purposes. The objective is to optimize the effectiveness and usability of the company's online profile through an adaptive and collaborative approach. However, successful implementation of XP methodology in developing Web-Based Company Profiles relies not solely on methodological approaches. Effective project management, good team communication, and support from management are equally essential to achieve optimal outcomes. In conclusion, the integration of Extreme Programming methodology, together with black box testing, enables companies to enhance their Web-Based Company Profiles as effective mediums for information and promotional purposes. This study emphasizes the importance of adaptability, collaboration, and quality assurance in achieving successful online profiles
Data-Driven Insights for Higher Education Marketing: Segmenting Applicant Pools Using K-Means Clustering Jafar Shadiq; Harjunadi Wicaksono; Rahmat Budiarto; Raisha Nur Salamah; Zidan Al Buqhori Fakhrudin
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.v13i2.11545

Abstract

This research aims to optimize marketing strategies for new student recruitment at Bina Insani University (BiU), which faces intense competition. The current marketing efforts are generic and inefficient. Utilizing the CRISP-DM framework, this study applies the K-Means clustering data mining method to analyze primary data from applicants from 2021 to 2024. The analysis focuses on the attributes of previous school major, information source, and location. The findings successfully identified four distinct segments of prospective students: the "Proactive Outreach Segment," reached through school presentations; the "Social Network & Affiliation Segment," influenced by friends and relatives; the "Academic Recommendation Segment," who rely on guidance from teachers; and the "Digital & Non-Technical Segment," who actively seek information on social media. Based on the unique profile of each cluster, this study provides recommendations for specific and targeted marketing strategies to improve the effectiveness and efficiency of student recruitment
Co-Authors Dwi Ismiyana Putri Harjunadi Wicaksono Harjunadi Wicaksono Muhammad Ari Kuncoro Muhammad Surya Apandi Rahmat Budiarto Raisha Nur Salamah Rina Sayekti Zidan Al Buqhori Fakhrudin