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All Journal Sistemasi: Jurnal Sistem Informasi JURNAL MEDIA INFORMATIKA BUDIDARMA INOVTEK Polbeng - Seri Informatika JURTEKSI Building of Informatics, Technology and Science Malcom: Indonesian Journal of Machine Learning and Computer Science
Munzir, Medyantiwi Rahmawita
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Penerapan Algoritma FP-Growth untuk Menentukan Strategi Promosi Berdasarkan Waktu dan Pembelian Produk Wilrose, Anandeanivha; Afdal, M; Monalisa, Siti; Munzir, Medyantiwi Rahmawita
Building of Informatics, Technology and Science (BITS) Vol 5 No 1 (2023): June 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i1.3577

Abstract

Sales is the main activity in every business. In making business decisions, sales patterns can be used to provide useful information such as strategies for promotion. Wandri Mart is a business engaged in the sale of products or goods commonly referred to as minimarkets in the city of Payakumbuh. In conducting promotional strategies, the owner of Wandri Mart does not know when to do promotions and what promotions are needed in order to increase sales. The purpose of this study is to obtain purchasing patterns related to the time of purchase and the type of goods purchased, so that a more effective promotional strategy can be developed. The method used by researchers is data mining techniques with the FP-Growth algorithm. The data used was taken as much as 5471 sales transaction data for 1 year. The results of this study indicate that the FP-Growth algorithm can be used to determine association rules using a minimum support of 1%, 2%, 3% and a minimum confidence of 10%. Experiments using Minimum Support 1% and Minimum Confidence 10% have the highest lift ratio value and produce more rules compared to other experiments so that it is obtained if on Tuesdays in August, customers buy instant noodles and packaged drinks with 6% and 5% support respectively and 50% and 45% confidence respectively with a lift ratio of 1.75 and 1.59 respectively. The lift ratio means that the rules have high association accuracy, and this also has a positive impact on sales and can be used as useful information for Wandri Mart to increase sales
Implementasi The Concurrent Development Model Untuk Membangun Learning Management System Novita, Rice; Munzir, Medyantiwi Rahmawita; Kurniawan, Viki
Jurnal Inovtek Polbeng Seri Informatika Vol 9, No 1 (2024)
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/isi.v9i1.3879

Abstract

Technology plays an important role in the educational process. The weakness of the current educational process is that there is no media that helps store data, share data and monitor data properly. Learning Management System (LMS) is a web-based software program that has five main elements for management, documentation, monitoring, reporting, administration and distribution of educational content. This research aims to develop an LMS that is in accordance with the five main features in the LMS. with software development methods using The Concurrent Development Model. In this model, work activities are carried out simultaneously, each work process has several work triggers for the activity. Triggers can come from the beginning of the work process or from other triggers because each trigger will be interconnected. In system design, the concept of Object-Oriented Analysis Design (OOAD) is used with use case diagrams, activity diagrams and class diagrams.
Peramalan Jumlah Kedatangan Wisatawan Menggunakan Support Vector Regression Berbasis Sliding Window Fitriah, Ma’idatul; Permana, Inggih; Salisah, Febi Nur; Munzir, Medyantiwi Rahmawita; Megawati, Megawati
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.v8i3.7408

Abstract

As a developing city, Pekanbaru has the potential for attractive tourist attractions for tourists. The arrival of tourists has had a big positive impact on the economy of Pekanbaru City. The number of tourist arrivals can experience ups and downs every month, for this reason it is necessary to forecast the number of tourists in the future. This research aims to apply the Orange Data Mining application in predicting the number of tourist arrivals by comparing the kernels in the Support Vector Regression (SVR) method and applying Sliding Window size 3 to window size 13 to transform into time series data. As well as sharing data using the K-Fold Validation method with a value of K-10. Then the performance of the kernels used can be seen using the Test and Score widget which presents the results of Root Mean Absolute Error (MAE), Mean Square Error (MSE), Root Mean Square Error (RMSE), dan R-squared(R2). The results for forecasting the number of tourist arrivals to Pekanbaru City using the SVR method show that the RBF Kernel is the optimal choice compared to the Polinomial and Linear Kernels. The results of the Test and Score widget show that the RBF Kernel with window size 10 has lower MAE, MSE and RMSE values, namely 0.118, 0.022 and 0.147. Apart from that, the comparison of R2 in window size 10 for Kernel RBF shows better performance with a value of 0.519.
Perbandingan Performa Algoritma RNN dan LSTM dalam Prediksi Jumlah Jamaah Umrah pada PT. Hajar Aswad: Comparison of RNN and LSTM Algorithm Performance in Predicting the Number of Umrah Pilgrims at PT. Hajar Aswad Al Kiramy, Razanul; Permana, Inggih; Marsal, Arif; Munzir, Medyantiwi Rahmawita; Megawati, Megawati
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 4 No. 4 (2024): MALCOM October 2024
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v4i4.1373

Abstract

Secara bahasa umrah bermakna ziarah atau berkunjung, sedangkan secara istilah umrah adalah perjalanan ke Baitullah di luar waktu haji dengan tujuan melaksanakan ibadah tertentu dan memenuhi syarat-syarat khusus. PT Hajar Aswad merupakan sebuah perusahaan travel umrah yang beroperasi di Indonesia. PT Hajar Aswad bertanggung jawab untuk mengatur perjalanan, akomodasi, transportasi, dan berbagai keperluan lainnya bagi para jemaah umrah, untuk itu perlu memiliki pemahaman yang baik mengenai pola dan tren jumlah jemaah umrah agar dapat mengoptimalkan operasional dan memberikan pelayanan yang memuaskan kepada jamaah. Oleh karena itu penelitian ini dilakukan untuk memprediksi jumlah jamaah umrah pada PT Hajar Aswad menggunakan algoritma RNN dan LSTM agar PT Hajar Aswad. . Hasil perbandingan kedua algoritma menunjukkan bahwa LSTM mampu memberikan hasil prediksi yang sedikit lebih baik dibandingkan RNN dengan parameter window size 7, optimizer Adam, batch size 8, dan learning rate 0,01. Model ini memiliki nilai RMSE sebesar 0,1758, MAPE sebesar 0,4846, dan R2 sebesar 0,5198.
Peramalan Jumlah Kedatangan Wisatawan Menggunakan Support Vector Regression Berbasis Sliding Window Fitriah, Ma’idatul; Permana, Inggih; Salisah, Febi Nur; Munzir, Medyantiwi Rahmawita; Megawati, Megawati
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.v8i3.7408

Abstract

As a developing city, Pekanbaru has the potential for attractive tourist attractions for tourists. The arrival of tourists has had a big positive impact on the economy of Pekanbaru City. The number of tourist arrivals can experience ups and downs every month, for this reason it is necessary to forecast the number of tourists in the future. This research aims to apply the Orange Data Mining application in predicting the number of tourist arrivals by comparing the kernels in the Support Vector Regression (SVR) method and applying Sliding Window size 3 to window size 13 to transform into time series data. As well as sharing data using the K-Fold Validation method with a value of K-10. Then the performance of the kernels used can be seen using the Test and Score widget which presents the results of Root Mean Absolute Error (MAE), Mean Square Error (MSE), Root Mean Square Error (RMSE), dan R-squared(R2). The results for forecasting the number of tourist arrivals to Pekanbaru City using the SVR method show that the RBF Kernel is the optimal choice compared to the Polinomial and Linear Kernels. The results of the Test and Score widget show that the RBF Kernel with window size 10 has lower MAE, MSE and RMSE values, namely 0.118, 0.022 and 0.147. Apart from that, the comparison of R2 in window size 10 for Kernel RBF shows better performance with a value of 0.519.
Evaluation of the Impact of the Online Game Mobile Legends on Users’ Mental Health using the Fuzzy Logic Method Kurniawansyah, Fito Cahya; Munzir, Medyantiwi Rahmawita; Mustakim, Mustakim; M. Afdal, M. Afdal; Marsal, Arif
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.v14i4.5311

Abstract

One of the benefits of advancing technology is its ability to serve as a medium for entertainment. The online game Mobile Legends has gained widespread popularity and attracts a broad audience, including university students. While playing Mobile Legends can offer cognitive stimulation, enjoyment, and entertainment, it can also lead to excessive addiction, which may negatively affect users’ mental health. This study applies a fuzzy logic approach, which processes input data through fuzzy rules involving fuzzification, fuzzy inference, and defuzzification. Three input variables are used: Playing Time, Emotional Level, and Stress Level, with a single output variable: Health Index, which reflects the user's mental health condition. The purpose of this study is to evaluate the impact of the Mobile Legends online game on users’ mental health using fuzzy logic implemented in MATLAB. Based on the results, the manual Mamdani fuzzy analysis yielded a defuzzification result of 44.75. Meanwhile, using MATLAB Fuzzy Mamdani Toolbox (version 2023b) with input values of Playing Time (69), Emotional Level (68), and Stress Level (65) produced an output of 52.7. Both results fall within the fuzzy domain of “Agree” [40, 60, 80], indicating that prolonged playing time of Mobile Legends can influence players’ mental health.
Influence of User Satisfaction of the Halodoc Mobile Application using the End User Computing Satisfaction (EUCS) and DeLone and McLean methods Wulandari, Suri; Munzir, Medyantiwi Rahmawita; Rozanda, Nesdi Evrilyan; Zarnelly, Zarnelly
Sistemasi: Jurnal Sistem Informasi Vol 13, No 2 (2024): 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.v13i2.4035

Abstract

PT. Media Dokter Investama is one of several technology companies that provides health consultation services in Indonesia through Mobile Health Technology (MHealth Tech) products. Mobile application. It was recorded that in October 2023 the Halodoc application on Playstore received a rating of 4.8 on a scale of 5 with more than 426 thousand reviews from users. The level of use of the Halodoc application is very high, giving rise to several negative ratings. As in the reviews from rating 2 or not liking the application as much as 658 or 5.76%, and rating 1 or really not liking the application as many as 1,577 reviews or 13.78%. From these results it can be seen that there are still some users who are dissatisfied with the Halodoc application. This research was conducted to measure the influence of user satisfaction of the Halodoc application using the End User Computing Satisfaction and DeLone and McLean methods and to provide research recommendations which can be an input for Halodoc application managers to manage and improve the Halodoc application in the future.
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 Al Kiramy, Razanul Angraini Angraini Arif Marsal Febi Nur Salisah, Febi Nur Fitriah, Ma’idatul Fitriah, Ma’idatul Inggih Permana Kurniawan, Viki Kurniawansyah, Fito Cahya M Afdal M. Afdal, M. Afdal Megawati - Mona Fronita, Mona Mustakim Mustakim Rice Novita Rozanda, Nesdi Evrilyan Siti Monalisa Wilrose, Anandeanivha Wiranti, Ririn Wulandari, Suri Zarnelly Zarnelly