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Siti Monalisa
Jurusan Sistem Informasi Fakultas Sains dan Teknologi UIN Suska Riau
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Penerapan Algoritma K-Means Dan Metode Marketing Mix dalam Segmentasi Mahasiswa dan Strategi Pemasaran Monalisa, Siti; Nurainun, Tengku; Hartati, Misra
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 8 No 1: Februari 2021
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.0811939

Abstract

Idealnya, semakin tinggi jumlah pendaftar di suatu institusi pendidikan, semakin tinggi kualitas dari mahasiswa yang diterima. Akan tetapi, kondisi ideal ini tidak dicapai oleh Fakultas Sains dan Teknologi (FST) UIN Suska Riau disebabkan karena sedikitnya jumlah mahasiswa yang berasal dari sekolah menengah unggul yang mendaftar sebagai mahasiswa di FST UIN Suska Riau. Berdasarkan survey terhadap dosen di FST UIN Suska, masih terdapat kendala yang cukup besar dalam proses transfer ilmu kepada mahasiswa terutama dalam hal daya tangkap dan pemahaman mahasiswa terhadap materi ajar. Oleh karena itu, analisis lebih lanjut mengenai mahasiswa saat ini diperlukan untuk merancang sebuah strategi bagaimana menarik minat siswa yang berasal dari sekolah menengah unggul untuk mendaftar sebagai mahasiswa di FST UIN Suska Riau. Metodologi yang digunakan dalam penelitian ini adalah segmentasi mahasiswa menggunakan algoritma K-Means dan teknik kluster menggunakan algoritma Dunn Index. Pengumpulan data dilakukan sebanyak 614 mahasiswa FST tahun ajaran 2015 sampai 2017. Output dari segmentasi mahasiswa digunakan untuk menentukan target dari Marketing Mix 7P. Penelitian ini menghasilkan 2 kluster mahasiswa dengan nilai Dunn Index 1,99. Kuesioner disebarkan kepada mahasiswa dari dua kluster yang berbeda tersebut dan hasilnya menunjukkan bahwa terdapat tiga variabel Marketing Mix yang berpotensi untuk meningkatkan target pasar yaitu people, product, dan place. AbstractIdeally, the higher number of registrant in an educational institution, the higher quality of the accepted students. But, this ideal condition was not achieved by Faculty of Science dan Technology UIN Suska Riau due to the minimum number of students from top ranking senior high school who registered as student in FST UIN Suska Riau. Based on a survey of lecturers at FST UIN Suska, there are still significant limitations in the process of transferring knowledge to students, especially in terms of catching dan understdaning students towards teaching materials. Therefore, further analysis of current input of students is needed to design a strategy how to attract the high quality of high school students to register as student in FST UIN Suska Riau. The methodology in this research are student segmentations using K-Means Algorithm dan Clustering with Dunn Index Algorithm. The data collection derived from 614 students of FST in academic year 2015 until 2017. The output of student segmentations were used to determine the target using Marketing Mix 7P.  This research yield two clusters of students with Dunn Index Value was 1.99. The questionnaire were spreaded to students from the two different clusters dan the results showed that there are three variables of Marketing Mix that potentially increase the market target that is people, product, dan place.
Segmentasi Pelanggan B2B Berdasarkan Perilaku Pembelian dan Firmografi pada PT. Sukses Riau Permata (SRP) monalisa, Siti; Nurahmah, Novia
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 11 No 1: Februari 2024
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.20241116487

Abstract

Aset yang memberi pengaruh besar pada proses bisnis perusahaan retail adalah pelanggan. PT. Sukses Riau Permata (SRP) adalah badan usaha yang bergerak dalam bidang distribusi barang konsumsi yang pelanggannya banyak berjenis Business to Business (B2B). Permasalahan yang muncul pada PT. SRP ini adalah menurunnya jumlah konsumen sebanyak 27% yang terjadi pada 6 bulan terakhir Tahun 2021 dikarenakan strategi bisnis perusahaan belum mengaplikasikan Customer Relationship Management (CRM). PT. SRP belum mengidentifikasi pelanggan mana yang berkontribusi dan mana yang tidak memberikan keuntungan pada perusahaan akibatnya program pemasaran masih diberlakukan seragam kepada semua pelanggan. Maka dari itu pada penelitian ini dilakukan pengelompokan pelanggan berdasar kepada perilaku pembelian dan firmografi dengan algoritma Fuzzy C-Means. Indeks Davies Bouldin (DBI) digunakan untuk memverifikasi validitas hasil klasterisasi. Dari proses klasterisasi pelanggan dihasilkan 6 klaster yang dianalisis sesuai karakteristik segmen dengan segmen pelanggan terbaik yaitu cluster 4 (Superstar Segment) yang memiliki 383 pelanggan. Sedangkan segmen pelanggan terparah, yaitu cluster 6 (New Dormant Segment) yang memiliki 298 pelanggan. Adapun di akhir penelitian didapatkan hasil yaitu usulan strategi penjualan terbaik yang sesuai dengan deskripsi karakteristik dan kebutuhan segmen pelanggan. 
Segmentasi Pelanggan B2B dengan Model LRFM Menggunakan Algoritma Fuzzy C-Means pada Rotte Bakery Ananda, Dea Putri; Monalisa, Siti
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 10 No 5: Oktober 2023
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2023106569

Abstract

Pelanggan B2B (Business to Business) merupakan pelanggan yang membeli produk dari suatu perusahaan dengan tujuan menjualnya kembali kepada konsumen akhir. Oleh karena itu, pengelolaan pelanggan B2B dengan strategi yang baik dan tepat sangatlah penting. Setiap pelanggan memiliki karakteristik yang berbeda, termasuk perilaku pembelian, demografi, dan geografi. Oleh karena itu, segmentasi pelanggan perlu dilakukan untuk mengelompokkan pelanggan dengan karakteristik serupa. Dengan demikian, perusahaan dapat menerapkan strategi pemasaran yang lebih efektif dan sesuai dengan kebutuhan setiap segmen pelanggan. Dalam penelitian ini, kami menggunakan model LRFM (Length, Recency, Frequency, dan Monetary) dengan Algoritma Fuzzy C-Means untuk melakukan segmentasi pelanggan. Metode validasi Davies Bouldien-Index digunakan untuk menentukan jumlah cluster yang optimal. Hasilnya menunjukkan bahwa terdapat lima cluster yang optimal untuk pelanggan agen dengan nilai DBI sebesar 0,57, sedangkan pelanggan outlet memiliki empat cluster dengan nilai DBI sebesar 0,49. Karakteristik yang dihasilkan untuk pelanggan agen adalah Average Value Segment, New Low Value Customer, New Dormant Segment, Golden Segment, dan Superstar Segment. Sementara itu, pelanggan outlet terbagi menjadi Golden Segment, Superstar Segment, New Low Value Customer, dan Dormant Segment. Berdasarkan temuan tersebut, kami memberikan usulan strategi pemasaran yang sesuai dengan karakteristik masing-masing segmen pelanggan B2B. Usulan ini relevan baik bagi akademisi, praktisi, maupun peneliti dalam bidang pemasaran.   Abstract B2B customers (Business to Business) are customers who purchase products from a company with the intention of reselling them to end consumers. Therefore, managing B2B customers with effective and appropriate strategies is crucial. Each customer has different characteristics, including purchasing behavior, demographics, and geography. Therefore, customer segmentation is necessary to group customers with similar characteristics. This enables companies to implement more effective and targeted marketing strategies tailored to the needs of each customer segment. In this study, we employed the LRFM model (Length, Recency, Frequency, and Monetary) with the Fuzzy C-Means algorithm for customer segmentation. The Davies Bouldien-Index validation method was used to determine the optimal number of clusters. The results revealed that there are five optimal clusters for agent customers with a DBI value of 0.57, while outlet customers have four clusters with a DBI value of 0.49. The resulting characteristics for agent customers are the Average Value Segment, New Low Value Customer, New Dormant Segment, Golden Segment, and Superstar Segment. Meanwhile, outlet customers are divided into the Golden Segment, Superstar Segment, New Low Value Customer, and Dormant Segment. Based on these findings, we propose marketing strategies that align with the characteristics of each B2B customer segment. These proposals are relevant to academics, practitioners, and researchers in the field of marketing.
Dampak E-Service Quality terhadap Customer Satisfaction dan Customer Loyality Website Blibli Fadli, Muhammad; Monalisa, Siti; Muttakin, Fitriani
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 7 No. 3 (2024): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jtsi.v7i3.40325

Abstract

Blibli.com is one of the most popular web-based e-commerce in Indonesia that continues to provide the best service to create customer satisfaction and lead them to make repeat purchases. The relationship between e-service quality to customer satisfaction and customer loyalty on the Blibli.com website needs to be measured to determine its effect, so this is the background of this research. This research uses quantitative methods with nonprobability sampling techniques and purposive sampling for sample collection. Data were collected through questionnaires from 100 respondents who use Blibli.com in the UIN SUSKA RIAU environment. Data analysis was carried out using Structural Equation Modeling (SEM) and SMARTPLS 4 software. The results showed that customer satisfaction has a significant influence on customer loyalty with a path coefficient value of 0.414, a P-value of 0.003, and a T value of 2.952 (> 1.96). In addition, e-service quality also has a significant influence on customer loyalty with a path coefficient value of 0.462, a P-value of 0.001, and a T value of 3.362 (> 1.96).
Analisa Studi Kelayakan Sistem Informasi Penjualan pada CV. Mitra Restu Jaya Menggunakan Metode TELOS Afilla, Dini; Saputra, Eki; Monalisa, Siti; Ahsyar, Tengku Khairil
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 7 No. 3 (2024): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jtsi.v7i3.41323

Abstract

Manual recording of sales systems using books faces various problems that affect business efficiency and accuracy. Problems that arise include the risk of errors in recording and the difficulty of accessing data quickly and precisely. In addition, manual recording is prone to data loss or damage due to human error and physical damage to books. Therefore, the implementation of a computerized recording system is proposed. This study aims to evaluate the feasibility of implementing an information system in CV. Mitra Restu Jaya consists of four stages, namely planning, data collection, data analysis, and closing. The research consists of four stages: planning, data collection, data analysis, and conclusion. A feasibility study is used to assess whether to proceed with or halt the development of a system project, typically covering technical, economic, legal, operational, and schedule feasibility. The assessment is conducted through TELOS feasibility worksheets, containing research questions and corresponding answers rated on a scale of 6-10. Cost-benefit analysis of the information system is conducted to consider cost components and benefit components to determine project feasibility, including the calculation of the payback period (PP) and Return on Investment (ROI). The results of this study show that the TELOS method can be applied to assess the feasibility of the sales information system at CV. Mitra Restu Jaya. The assessment results for each TELOS method are 8.50 for technical feasibility, 7.50 for economic feasibility, 8.50 for legal feasibility, 7.50 for operational feasibility, and 8.50 for schedule feasibility, with an average TELOS eligibility score of about 8.10. According to the payback period calculation, the funds invested by CV. Mitra Restu Jaya can be recovered approximately 6 months after operationalization, and the sales information system is feasible because the Return-on-Investment value is around 3.33, which is greater than 1. This is supported by PIECES-framed operational feasibility proving that the system to be developed can operate effectively and efficiently in the context of a retail company. The conclusion of this research is that the sales information system is feasible to be developed at CV. Mitra Restu Jaya.
THE INFLUENCE OF STUDENST PERCEPTION OF DATA SECURITY AND PRIVACY ON TRANSACTION TRUST IN THE TOKOPEDIA APPLICATION Wiranti, Ririn; Angraini, Angraini; Fronita, Mona; Monalisa, Siti; Munzir, Medyantiwi Rahmawita
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 10 No. 3 (2024): Juni 2024
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v10i3.3179

Abstract

Abstract: The current development of technology has successfully met various societal needs, one of which is the buying and selling activities. This development has led people to engage in online transactions, where buyers do not necessarily have to meet sellers in person. Tokopedia is one of the most popular e-commerce platforms used in Indonesia. Security issues arose when in 2020 Tokopedia experienced a breach, with data from around 91 million accounts being compromised by hackers. Consequently, Tokopedia needed to establish a Data Protection and Privacy Office (DPPO) to protect and safeguard user data privacy.This research addresses how perceptions of security and privacy can influence users' trust in transacting on Tokopedia. Using multiple linear regression analysis, the study evaluates the relationship between perceptions of data security and privacy with trust in transacting on Tokopedia. Based on the calculations of the multiple linear regression model using previously collected respondent data, it was found that perceptions of data security do not directly affect trust in transactions. However, perceptions of privacy are considered to have a significant influence and can increase trust in transactions among students in Pekanbaru. Keywords: data security; e-commerce; tokopedia; transaction trust; user perceptions Abstrak: Perkembangan teknologi saat ini telah sukses mencapai berbagai kebutuhan masayarakat salah satunya kegiatan jual beli, perkembangan ini membawa manusia untuk dapat melakukan jual beli secara online dimana tidak mengharuskan pembeli bertemu penjual secara langsung. Tokopedia menjadi salah satu platform e-commerce yang sangat popular digunkanan diindonesia. Masalah keamaan terjadi dimana pada tahun 2020 tokopedia mengalami peretasan dengan sekitar 91 juta akun berhasil diperoleh datanya oleh peretas, sehingga Tokopedia perlu membentuk data protection and privacy office (DPPO) guna melindungi dan menjaga privasi data pengguna Tokopedia.terkait hal tersebut penelitian ini mengangkat bagaimana persepsi keamanan dan privasi dapat mempengaruhi kepercayaan pengguna dalam bertransaksi ditokopedia. Dengan menggunakan metode regresi linear berganda, evaluasi dilakukan untuk menjelaskan hubungan antara persepi keamanan data dan privasi terhadap kepercayaan bertransaksi ditokopedia. Berdasarkan perhitungan model regresi linear berganda menggunakan data responden yang telah dilakukan sebelumnya didapat persepsi keamanan data terhadap kepercayaan bertransaksi tidak berpengaruh secara langsung. Namun pada persepsi privasi terhadap kepercayaan bertransaksi dinilai sangat berpengaruh dan dapat meningkatkan kepercayaan bertransaksi di kalangan mahasiswa di pekanbaru. Kata kunci: e-commerce; keamanan data; kepercayaan transaksi; persepsi pengguna; tokopedia  
Co-Authors Afilla, Dini Ahsyar, Tengku Khairil Ananda, Dea Putri Andriyani, Dwi Ratna Angraini Angraini Ardiansah, Yoga Bacin, Jukhri Syahputra Eki Saputra Fitri Amillia fitriano, ernesto Hartati, Misra M. Afdal MaySarah, M Megawati - Mona Fronita, Mona Muhammad Fadli Munzir, Medyantiwi Rahmawita Muttakin, Fitriani Nurahmah, Novia Rachmawati, Dyana Sarbaini Sarbaini Tengku Nurainun Wilrose, Anandeanivha Wiranti, Ririn Zarnelly Zarnelly