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All Journal JUSIFO : Jurnal Sistem Informasi Jurnal Ilmiah Rekayasa dan Manajemen Sistem Informasi Sistemasi: Jurnal Sistem Informasi Briliant: Jurnal Riset dan Konseptual Jurnal CoreIT JURNAL MEDIA INFORMATIKA BUDIDARMA INOVTEK Polbeng - Seri Informatika Jurnal Teknologi Sistem Informasi dan Aplikasi Jurnal Sistem Cerdas JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) JOISIE (Journal Of Information Systems And Informatics Engineering) Building of Informatics, Technology and Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Jurnal Teknik Informatika (JUTIF) Jurnal Pendidikan dan Teknologi Indonesia Indonesian Journal of Informatic Research and Software Engineering Malcom: Indonesian Journal of Machine Learning and Computer Science CONSEN: Indonesian Journal of Community Services and Engagement METRIK SERIAL TEKNOLOGI DAN SAINS
Zarnelly Zarnelly
Jurusan Sistem Informasi Universitas Islam Negeri Sultan Syarif Kasim Riau
Religion Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Physics Social Sciences Other

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Penerapan Algoritma K-Means Menggunakan Model LRFM Dalam Klasterisasi Nilai Hidup Pelanggan Afifah, Tiara Afrah; Novita, Rice; Ahsyar, Tengku Khairil; Zarnelly, Zarnelly
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 8, No 2 (2024): April 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v8i2.7605

Abstract

In implementing customer relationship management, there are still many companies that have not utilized CRM optimally as part of their business strategy. As is the case with UD Sandeni. UD Sandeni still has problems in managing its relationships with customers because UD Sandeni does not fully understand the difference between customer information that is profitable and unprofitable for the company's sustainability. UD Sandeni has used a system to manage customer transaction data. However, this system is only used to calculate profits and create bookkeeping for registered agents so that UD Sandeni does not have an in-depth understanding of the characteristics of its customers. To overcome this problem, the solution that can be applied is to use customer grouping techniques, such as clustering. Customer transaction data is processed using a clustering process with K-Means and LRFM. Test the validity of cluster results using DBI and calculate CLV values using AHP weights to produce cluster rankings. The results of this research obtained customer clustering which consists of 2 segments, namely cluster 1 which has the highest CLV value of 0.3171156 with a total of 298 customers and includes the High Value Loyal Customers segmentation, and cluster 2 with a CLV value of 0.1434054 with a total of 72 customers. which is included in the segmentation of uncertain new customers (uncertain lost customers).
Penerapan Algoritma Artificial Neural Network dan Economic Order Quantity dalam Memprediksi Persediaan Pengendalian BBM Ula, Walid Alma; Afdal, M; Zarnelly, Zarnelly; Permana, Inggih
Journal of Computer System and Informatics (JoSYC) Vol 5 No 2 (2024): February 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i2.4916

Abstract

Motor vehicle production in Indonesia increases every year along with increasing demand for fuel as a raw material. Generally, gas stations carry out the process of ordering fuel from Dempo on an irregular basis, the frequency of orders does not have a certain time, orders depend on sales transactions and the amount of fuel inventory available depends on the fuel in storage. Regarding prediction and control of fuel supplies, the risk at gas stations is that the volume of fuel received is different from that ordered. It is suspected that tank trucks carrying fuel during delivery from the depot to gas stations tend to experience evaporation in the tank (loses), so that the fuel quantity decreases. Requests for fuel filling are only based on monitoring without any special calculations resulting in stock being maintained and not covering consumer demand. This research is to analyze the Artificial Neural Network algorithm in predicting fuel, and determine inventory control using Economic Order Quantity. The research was conducted using data from November 2020 - October 2023. The data was processed using the ANN algorithm using Google Colab, and continued with EOQ using Microsoft Excel. The ANN parameters are 1 hidden layer with 100 units, Adam optimizer, learning rate 0.001, batch size 8 and epoch 200. Pertalite ANN test results are MSE 248852593.81 and MAE 12749.45, while Pertamax Turbo MSE 803842.94 and MAE 672, 74 provides predictions for November and December of 11,1436.82 L and 11,1960.83 L and Pertamax Turbo of 3,782.46 L and 3,660.70 L. Furthermore, in 2023 the fuel EOQ of Pertalite and Pertamax Turbo will be 8,445 L and 5,261 L, Safety Stock 3,516 L and 1,064 L, Maximum Inventory 6,042 L and 5,153 L, Re order point 2,403 L and 108 L, Order frequency 149 times and 6 times with Total Inventory Cost Rp. 178,830,302 and Rp. 7,700,459.
The Implementation of Internet of Things (IOT) for Aquaponic Cultivation Zuriati, Zuriati; Widyawati, Dewi Kania; Dulbari, Dulbari; Zarnelly, Zarnelly
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 10, No 2 (2024): December 2024
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/coreit.v10i2.29541

Abstract

Aquaponic is a plant cultivation technique that is widely used by farmers and today’s communities due to its efficiency and ability to increase the agricultural productivity. The aquaponic cultivation in general still uses simple systems, such as manually feeding the fish by spreading the feed at predetermined times, monitoring water pH using a pH meter and monitoring water height or level through measurements, requiring farmers to spend time and special labor to care for and maintain plants and fish. Therefore, a solution is needed in the form of a system that can monitor and control plants and fish conditions automatically and continuously for 24 hours. The system should have the ability to control and monitor feeding activities, water pH, water and environmental temperature, water level and environmental humidity. The system in question is the internet of things (IoT) system that can be used as a tool for automatic control and monitoring through an application. The IoT system consists of several sensors that are connected to a microcontroller which can measure water pH, temperature, water level and environmental humidity. The data obtained by the sensor will be sent to a server via Wi-Fi protocol and stored in a database. The system is equipped with a web application that can be accessed through a computer device. The application provides a visual display of data: time, water pH, temperature, water level and environmental humidity, making it easier for farmers to monitor aquaponic conditions from a distance without having to come to the land. Through the implementation of IoT in aquaponic cultivation, farmers can increase efficiency and agricultural productivity by reducing the time, labor and costs required for control and monitoring.
Customer Satisfaction Analysis of ShopeeFood Service Quality using E-Servqual Method and Importance-Performance Analysis Yanti, Rahma; Megawati, Megawati; Zarnelly, Zarnelly; Saputra, Eki; Marsal, Arif
Sistemasi: Jurnal Sistem Informasi Vol 14, No 1 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i1.4785

Abstract

ShopeeFood was launched in April 2020. However, since its initial release, traffic to ShopeeFood services did not immediately perform well, as the platform had to compete with major players like GoFood and GrabFood, which are already well-known among the public. Numerous negative customer reviews about ShopeeFood indicate that customer satisfaction with the company's performance remains low. To measure the level of customer satisfaction, this study employed the E-Service Quality (E-Servqual) and Importance-Performance Analysis (IPA) methods. The results of the study show that, on average, the seven dimensions of E-Servqual measured exhibit a gap, with the average gap being negative. The highest gap was found in the "Responsiveness" dimension (-0.32), while the lowest gap was in the "Efficiency" dimension (-0.01). These findings indicate a discrepancy between customer expectations and satisfaction, suggesting that ShopeeFood's services are perceived as less satisfactory by its users. Data analysis revealed that the Importance-Performance Analysis (IPA) matrix for ShopeeFood's service quality highlights several attributes as top priorities for improvement. These attributes, identified through the Cartesian diagram of the Importance-Performance Analysis, fall under Quadrant I, specifically R11, RE16, and C19.
Analysis of User Satisfaction Levels for X Mobile Application in Pekanbaru using End-User Computing Satisfaction (EUCS) and Technology Acceptance Model (TAM) Methods Butar Butar, Febiola Siska; Zarnelly, Zarnelly; Jazman, Muhammad; Novita, Rice; Marsal, Arif
Sistemasi: Jurnal Sistem Informasi Vol 14, No 1 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i1.4851

Abstract

Mobile X is a digital innovation in banking transactions, combining mobile banking, internet banking, and e-money functions into a single platform. However, Mobile X faces several usage challenges that lead to user dissatisfaction. Therefore, an analysis of user satisfaction is essential to improve customer loyalty. The End-User Computing Satisfaction (EUCS) and Technology Acceptance Model (TAM) methods are evaluation tools used to measure user satisfaction with an application system. This study employed a quantitative approach by distributing questionnaires to 100 respondents, determined using the Lameshow equation. The research model was analyzed through demographic analysis and model analysis using PLS-SEM, resulting in both internal and external models. The findings revealed that three hypotheses were accepted: the content variable (p-value = 0.495), the perceived usefulness variable (p-value = 0.007), and the timeliness variable (p-value = 0.001). Meanwhile, three hypotheses were rejected: the accuracy variable (p-value = 0.734), the content variable (p-value = 0.495), and the format variable (p-value = 0.184). Additionally, three user satisfaction factors were found to be significant for the accepted variables, indicating that meeting user expectations, perceived usefulness, information quality, and timeliness positively contribute to user satisfaction. This demonstrates that these factors effectively address user needs and enhance overall satisfaction with the Mobile X application.
Penerapan Algoritma Fuzzy C-Means untuk Klasterisasi Customer Lifetime Value menggunakan Model LRFMD Ramadhani, Indah; Afdal, M; Mustakim, Mustakim; Zarnelly, Zarnelly
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 8, No 3 (2024): Juli 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v8i3.7613

Abstract

PT X is a retail company engaged in printing. The company has not differentiated between information about profitable and unprofitable customers for the company. Transaction data is only used as profit and loss information so they do not know the characteristics of the customers they have. In addition, the lack of extensive services in the merchandise category is one of the reasons the company's revenue has not reached the predetermined target. Currently, the company has opened additional services in the merchandise field. This research aims to identify customer segmentation as well as analyze the characteristics and provide a strategy proposal that will be submitted to PT. X. Customer loyalty and characteristics have a significant impact on a company. To identify customers who show loyalty to the company, the Fuzzy C-Means algorithm is used to perform clustering, using the Davies Bouldin Index (DBI) to evaluate the clustering results. The model used is in accordance with the principles of Length, Recency, Frequency, Monetary and Diversity (LRFMD) to categorize purchasing patterns. By analyzing LRFMD variables, it is possible to identify customers who are loyal to the company and those who are not. This research produces 6 clusters with the best cluster or supestar customer in cluster 6, the second best value customer or golden customer is cluster 2, the average value customer or typical customer is cluster 4 and 5 and the lowest cluster or dormant customer is in cluster 3.
Analisa Kualitas Website Lancangkuning.Com Menggunakan Metode Webqual 4.0 dan Importance Performance Analysis Nazaf, Latiful; Saputra, Eki; Megawati, Megawati; Zarnelly, Zarnelly; Marsal, Arif
Jurnal Pendidikan dan Teknologi Indonesia Vol 5 No 2 (2025): JPTI - Februari 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.484

Abstract

Website portal berita Lancangkuning.com dalam penerapannya masih terdapat permasalahan, seperti iklan yang besar yang mengganggu tampilan, navigasi yang kurang responsif, serta informasi yang jarang diperbarui. Sehingga penelitian ini berfokus pada dua hal utama yaitu pengukuran kualitas website Lancangkuning.com dan menganalisis apakah kualitas website memiliki pengaruh kepada kepuasan pengguna. Untuk mengukur kualitas website maka digunakan WebQual 4.0 yang selanjutnya hasilnya akan dipetakan pada kuadran Importance-Performance Analysis. Penelitian ini menggunakan 3 variabel independen yaitu dimensi pada WebQual seperti usability, information quality, dan service interaction quality. Selain variabel independen, terdapat variabel dependen yaitu customer satisfaction. Hasil pengukuran dari 100 responden penelitian menunjukkan bahwa sebanyak 2 atribut pernyataan berada pada kuadran I IPA dan 5 atribut pernyataan berada pada kuadran III IPA. Hasil uji t-statistic dan p-value menunjukkan bahwa seluruh dimensi pada WebQual mempengaruhi secara bersamaan. Dari hasil analisis pengaruh tersebut dapat disimpulkan bahwa perbaikan untuk kuadran I IPA dan kuadran III IPA harus berdasarkan prioritasi yaitu nilai kesenjangan dan dimensinya secara urut yaitu usability, information quality, dan service interaction quality.
Klasifikasi Penerima Bantuan Program Indonesia Pintar (PIP) Pada Siswa SMK Menggunakan Algoritma KNN, NBC dan C4.5 Putra, Tandra Adiyatma; Permana, Inggih; Zarnelly, Zarnelly; Megawati, Megawati
Building of Informatics, Technology and Science (BITS) Vol 6 No 4 (2025): March 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i4.6395

Abstract

The Indonesia Smart Program (PIP) is a government initiative aimed at providing educational assistance to students from underprivileged families. This research was conducted at SMKN 4 Pekanbaru to enhance the accuracy of distributing PIP aid using data mining methods. Three classification algorithms were used to identify students eligible for assistance: K-Nearest Neighbor (KNN), Naive Bayes Classifier (NBC), and C4.5. The data used in this study included attributes such as parental occupation, income, and the type of transportation used. The data processing involved cleaning, normalization, and splitting into test and training sets. The results showed that the KNN algorithm performed best with an accuracy of 84.20%, precision of 89.83%, and recall of 99.18%. The C4.5 algorithm excelled in model simplicity, while NBC showed less optimal results compared to KNN.
Evaluasi User Experience Pada Aplikasi Maxim Mobile Menggunakan User Experience Questionnaire Permana, Jeki Harya; Megawati, Megawati; Saputra, Eki; Zarnelly, Zarnelly
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 2 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i2.6192

Abstract

Studi ini bertujuan untuk mengukur tingkat kepuasan pengguna aplikasi Maxim Ojek dan Transportasi serta memberikan rekomendasi untuk meningkatkan pengalaman pengguna. Penelitian ini bertujuan untuk mengevaluasi pengalaman pengguna aplikasi Maxim menggunakan metode User Experience Questionnaire (UEQ). Penelitian ini menggunakan pendekatan kuantitatif dengan metode survei menggunakan kuesioner UEQ. Subjek penelitian adalah mahasiswa pengguna aplikasi Maxim di Pekanbaru dengan rentang usia 20-23 tahun. Karena populasi pengguna tidak diketahui, penentuan sampel menggunakan rumus Lemeshow. Data dikumpulkan melalui kuesioner yang dibagikan kepada 100 responden dan dianalisis menggunakan alat analisis data UEQ. Hasil penelitian menunjukkan bahwa pengguna memberikan nilai positif untuk sebagian besar variabel, seperti daya tarik (1.34), kejelasan (1.18), efisiensi (0.97), dan ketepatan (1.19). Namun, variabel kebaruan menerima skor yang lebih rendah dengan nilai 0.43. Diperlukan perbaikan pada aspek kebaruan dan akurasi lokasi untuk meningkatkan pengalaman pengguna aplikasi Maxim. Studi ini memberikan wawasan tentang kepuasan pengguna dan menawarkan ide untuk mengoptimalkan aplikasi.
Analysis of Facebook Pro User Satisfaction Using the PIECES Method 'alimah, Muta; Megawati, Megawati; Angraini, Angraini; Fronita, Mona; Zarnelly, Zarnelly
Sistemasi: Jurnal Sistem Informasi Vol 14, No 4 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i4.5121

Abstract

Facebook Pro is a feature developed by Meta to provide a professional experience for users in managing content and interactions on the Facebook platform. However, user satisfaction with this feature has not been extensively studied, particularly in the city of Pekanbaru. This study aims to analyze the level of user satisfaction with Facebook Pro in Pekanbaru using the PIECES framework, which consists of six key variables: Performance, Information and Data, Economy, Control and Security, Efficiency, and Service. The research findings indicate that the satisfaction scores for each variable are as follows: Performance (3.70), Information and Data (3.84), Economy (3.37), Control and Security (3.48), Efficiency (3.58), and Service (3.70). Most of these fall under the “satisfied” category, with the exception of Economy, which is rated as “moderately satisfied.” Overall, the average satisfaction score was 3.61, placing user satisfaction within the “satisfied” category. These results suggest that most users feel comfortable and supported by the features and services provided by Facebook Pro. However, the relatively lower scores in the Economy and Control and Security dimensions highlight areas where users are experiencing challenges, indicating a need for improvement in those aspects.
Co-Authors 'alimah, Muta Afifah, Afifah Pendri Afifah, Tiara Afrah Ahsyar, Tengku Khairil Akhiril Anwar Harahap Al-Qadr, Nola Ardelia Al-Yasir, Al-Yasir Alfian, Zhevin Anahyu, Yelfi Dwi Angraini Angraini Anjani, Yulia Merry Anofrizen Anofrizen Ariansah, Rizky Arif Marsal Aulia Rahman, Hafiz Butar Butar, Febiola Siska Dulbari, Dulbari Eki Saputra fitriano, ernesto Hamzah, Muhammad Luthfi Harmutika, Della Inggih Permana Irwanda, Mahyuda Jazman, Muhammad M. Afdal Megawati , Megawati Megawati - Mona Fronita, Mona Munandar, Darwin Munzir, Medyantiwi Rahmawita Mustakim Mustakim Muttakin, Fitriani Nazaf, Latiful Nurfadilla, Nadia Permana, Jeki Harya Pratama, Arya Yendri Priady, Muhamad Ilham Pristiawati, Andani Putri Putra, Ahdika Sawiyya Putra, Tandra Adiyatma Rahman, Eman Rahmawita, Medyantiwi Ramadhani, Indah Razmi, Fikri Rice Novita Rozanda, Nesdi Evrilyan S. Nagalay, Fitra Salam Siti Monalisa Sri Lestari Sriyanto Sriyanto Suwito, Bagus Anjari Syaifuddin, Aditya tri utami, septiana Ula, Walid Alma Widi Nugroho, Handoyo Widyawati, Dewi Kania Wulandari, Suri Yanti, Rahma Zulkarnain Zulkarnain Zuriati, Zuriati