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Pengaruh Motivasi Dan Tingkat Literasi Terhadap Minat Mahasiswa Untuk Memutuskan Berinvestasi Di Pasar Modal Yuliantoro, Heri Ribut; Nurmalasari, Dini; Tinambunan, Theresia Elfina
Jurnal Ilmiah Raflesia Akuntansi Vol 10 No 1 (2024): Jurnal Ilmiah Raflesia Akuntansi
Publisher : Politeknik Raflesia Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53494/jira.v10i1.369

Abstract

This study looked at how students' motivation and literacy levels related to their interest in share investment. All Politeknik Caltex Riau Investment Gallery registered students enrolled in the Accounting Study Program served as the study's subjects; they were chosen from a sample. A total of 100 student data sets were examined based on sample selection. In order to evaluate the data and make conclusions, this research use multiple regression approaches along with conventional assumption testing and hypothesis testing through a data processing tool. The study's findings demonstrate that, among the 100 student data examined, motivation and reading proficiency had a major impact on students' levels of interest. The study's findings revealed that most pupils who were enthusiastic about.
Analisis Faktor-Faktor yang Mempengaruhi Harga Saham pada Perusahaan Sub Sektor Kosmetik dan Barang Keperluan Rumah Tangga dengan Python Yuliantoro, Heri Ribut; Nurmalasari, Dini
Journal of Applied Informatics and Computing Vol. 6 No. 2 (2022): December 2022
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v6i2.4606

Abstract

This study aims to determine the relationship between stock prices of companies listed on the Stock Exchange in the Household Goods and Cosmetics sub-sector with several independent variables, namely quick ratio, current ratio, net profit margin, and return on assets. The analysis carried out is multiple regression analysis, conventional hypothesis testing, and descriptive analysis. The results of this study indicate that the current ratio and return on assets have a large influence on stock prices on the IDX, quick ratios and net profit margins have no significant effect. Return on assets, net profit margin, quick ratio, and current ratio all together have a big influence on stock prices. The results of the analysis of this study can be concluded that stock prices are positively influenced by the variables quick ratio, current ratio, net profit margin, and return on assets of 49.4%, and the remaining 50.6% is influenced by other factors.
Discovering User Sentiment Patterns in Libraries with a Hybrid Machine Learning and Lexicon-Based Approach Nurmalasari, Dini; Qudsi, Dini Hidayatul; Chairani, Nessa; Yuliantoro, Heri R
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 13 No. 3 (2024): NOVEMBER
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v13i3.2217

Abstract

The need to enhance library services is the focus of this study, which relies on user feedback for data-driven decision-making. Text data from library user surveys conducted at Politeknik Caltex Riau (PCR) is analyzed to categorize sentiment and identify areas for improvement. The biannual student and lecturer feedback collected from 2018 to 2023 through the institution's official survey system (survey.pcr.ac.id) is utilized, providing a comprehensive and robust picture of user needs across five years. Sentiment analysis is employed using the VADER method to classify user comments into positive or negative categories. Text preprocessing techniques, such as stemming, tokenizing, and filtering, are performed to ensure robust classification. Machine learning algorithms – Naïve Bayes, Support Vector Machine (SVM), and Random Forest – are then utilized to evaluate sentiment classification accuracy. The study offers significant findings. Both SVM and Random Forest achieve an outstanding accuracy of 99%, indicating highly reliable sentiment categorization. Notably, these algorithms also achieve 100% precision, recall, and F1-score, demonstrating their effectiveness in accurately identifying positive and negative user sentiment. While Naïve Bayes shows slightly lower accuracy at 98%, it maintains a high recall rate (100%), ensuring all negative feedback is captured. This research presents a novel approach combining user sentiment analysis with a comprehensive five-year dataset. This enables a deeper understanding of evolving user needs and priorities. The high accuracy and effectiveness of the employed algorithms highlight the potential of this methodology for libraries. Libraries can leverage user feedback for evidence-based service improvement and increased user satisfaction.
INTEGRASI NAIVE BAYES DAN ITEM-BASED COLLABORATIVE FILTERING DALAM SISTEM PEMETAAN KOMPETENSI MAHASISWA Nurmalasari, Dini; Fadhli, Mardhiah; Yuli Fitrisia, Yuli Fitrisia; Yuliantoro, Heri R
Jurnal Komputer Terapan Vol 11 No 1 (2025): Jurnal Komputer Terapan
Publisher : Politeknik Caltex Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35143/jkt.v11i1.6612

Abstract

Preparing a strong portfolio is a crucial aspect for students in entering the workforce, one of which can be achieved through participation in various competitions. However, selecting competitions that align with student competencies remains a challenge due to the abundance of competition information, diversity in student interests and abilities, and limitations in budget, time, and resources. This study develops a recommendation system based on a Hybrid Recommendation System designed to map student competencies to relevant competition types. The system integrates the Naive Bayes method to classify student competencies and Item-Based Collaborative Filtering to calculate similarities between competition types based on other users’ preferences. The system is developed incrementally using the waterfall approach, including the stages of planning, analysis, design, implementation, and testing. The model follows standard machine learning workflows, comprising data collection, exploration and preprocessing, model building, performance evaluation, and method integration. The research data includes student profiles, competencies, and competition preferences collected through surveys and internal databases. Evaluation results indicate that the system successfully provides relevant competition recommendations with an accuracy rate of 70%. These results demonstrate the system’s contribution in assisting students to select competitions that match their competencies, presented in a user-friendly web-based application.
Analisis Faktor-Faktor Yang Mempengaruhi Minat Mahasiswa Dalam Pemilihan Karir Menjadi Auditor (Studi Empiris Pada Mahasiswa Akuntansi Perpajakan Politeknik Caltex Riau) Yuliantoro, Heri R; Nurmalasari, Dini; Putri Radha
Jurnal Ilmiah Raflesia Akuntansi Vol. 11 No. 2 (2025): Jurnal Ilmiah Raflesia Akuntansi
Publisher : Politeknik Raflesia Press

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The purpose of this study is to ascertain how accounting students' interest in a career as auditors is influenced by societal values, the workplace, financial incentives, job market factors, and personality. The subjects of this study are Caltex Riau Polytechnic students enrolled in the tax accounting study program. 201 Caltex Riau Polytechnic tax accounting study program students made up the research's population. This study's sample consisted of 66 students from tax accounting education programs in their 20th and 21st generations. By using Likert scale-based surveys to gather data, this study employs quantitative approaches. Primary data was employed as the data source for this study. Descriptive statistical analysis, data quality testing, traditional assumption testing, and hypothesis testing are the data analysis methods employed in this study. SPSS 23 is the media or analytical tool utilized in this study. According to the study's findings, the factors of social values, the workplace culture, and financial incentives significantly and negatively affect accounting students' interest in pursuing a career as auditors, whereas personality traits and job market considerations significantly and favorably influence this interest.
Pengujian Kualitas Coding Pada Aplikasi Bank Sampah DLHK Kota Pekanbaru Menggunakan Code Smell Tools fadhli, mardhiah; Yuli Fitrisia; Nurmalasari, Dini
Jurnal Komputer Terapan Vol 10 No 1 (2024): Jurnal Komputer Terapan
Publisher : Politeknik Caltex Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35143/jkt.v10i1.6211

Abstract

Kualitas dari kode program akan mempengaruhi kemampuan perangkat lunak untuk dapat mudah dimodifikasi dan dikembangkan serta dipelihara. Code smells merupakan suatu karakteristik dari perangkat lunak yang mengindikasikan permasalahan pada kode dan desain perangkat lunak yang mengakibatkan perangkat lunak sulit untuk dikembangkan dan dilakukan pemeliharaan. Deteksi code smell perlu dilakukan agar dalam pengembangan kedepannya aplikasi dapat lebih mudah dimodifikasi dan dikembangkan. Deteksi code smell dalam sebuah aplikasi dapat membantu programmer untuk mengidentifikasi adanya rancangan kode program yang dapat menyulitkan kedepannya untuk dilakukan modifikasi dan pengembangan. Pendeteksian Code Smell pada aplikasi Bank Sampah DLHK Kota Pekanbaru dilakukan karena adanya permintaan kebutuhan untuk perbaikan dan penambahan fitur dari Bank Sampah DLHK Kota Pekanbaru. Permintaan perbaikan dan penambahan fitur pada aplikasi Bank Sampah DLHK Kota Pekanbaru dilakukan berdasarkan hasil evaluasi aplikasi sebelumnya yang dilakukan oleh pihak DLHK Kota Pekanbaru kepada 10 Bank Sampah Unit dan 25 Nasabah. Berdasarkan hasil evaluasi dan uji coba aplikasi, maka perlu dilakukan penyesuaian karena adanya ketidaksinkronisasian proses dengan mekanisme yang sedang berjalan dimasyarakat terhadap fitur pada aplikasi tersebut. Untuk memudahkan proses modifikasi program maka pendeteksian code smell pada aplikasi yang sudah ada perlu dilakukan, agar programmer dapat menjaga kualitas kode program menjadi lebih mudah untuk dikembangkan. Deteksi Code Smell dilakukan dengan menggunakan tool SonarQube. Hasil dari pengukuran dari dua aplikasi Bank Sampah adalah, pada aplikasi Basada berbasis mobile terdapat 126 Code smells dengan estimasi waktu perbaikan sekitar 2 jam 34 menit. Sedangkan pada aplikasi Basada berbasis website terdeteksi 25 Code smells dengan estimasi waktu perbaikan sekitar 25 menit.
Analisis Rekomendasi Media Promosi PPDB SMA Nurul Falah Pekanbaru dengan Algoritma K-Means Clustering Hidayat, Muhammad Taufiq; Emansa Hasri Putra; Dini Nurmalasari
Computer Science and Information Technology Vol 6 No 3 (2025): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v6i3.10499

Abstract

The advancement of information technology has significantly transformed how educational institutions conduct promotional activities and student admissions. The shift toward digital behavior among society requires schools to adopt more adaptive and data-driven marketing strategies. SMA Nurul Falah Pekanbaru, as one of the private high schools, has experienced a decrease in student enrollment after the Covid-19 pandemic. Conventional promotional methods such as banners, billboards, and printed brochures have proven less effective in reaching prospective students. This research aims to analyze the effectiveness of promotional media based on student characteristics using the K-Means Clustering algorithm as a segmentation method. The dataset was obtained from three years of PPDB registration records, including demographic, socioeconomic, school origin, and promotion media information. The analysis process involved several stages, namely data preprocessing, exploratory data analysis (EDA), determination of the optimal number of clusters using the Elbow and Silhouette methods, and the development of a web-based recommendation system using Python, PHP, and MySQL. The results indicate that the optimal number of clusters is k=4 with a Silhouette Score of 0.351. The four clusters represent distinct behavioral patterns in accessing educational information, with digital media emerging as the most effective channel. The developed recommendation system provides decision support for the school in designing promotional strategies that are more efficient, measurable, and accurately targeted through data analytics-based insights.
Workshop Pembelajaran Jaringan Komputer Berbasis Physical Mode pada Packet Tracer Sebagai Penguatan Pembelajaran Praktik kepada Siswa-Siswi SMK Taruna Persada Dumai Purwantoro E.S.G.S, Sugeng; Novayani, Wenda; Fitrisia, Yuli; Akbar, Memen; Alim Syahbana, Yoanda; Nurmalasari, Dini; Fadhly, Mardhiah
KAIBON ABHINAYA : JURNAL PENGABDIAN MASYARAKAT Vol. 8 No. 1 (2026)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/385st874

Abstract

Workshop "Pembelajaran Jaringan Komputer Berbasis Physical Mode pada Packet Tracer" bertujuan untuk memperkuat pembelajaran praktik jaringan komputer di SMK Taruna Persada Dumai. Program ini memberikan solusi atas keterbatasan perangkat keras dengan memanfaatkan fitur Physical Mode pada Cisco Packet Tracer, yang memungkinkan siswa belajar secara virtual tetapi dengan pengalaman menyerupai penggunaan perangkat asli. Kegiatan ini melibatkan 41 siswa dan 5 guru pendamping, dengan metode pelatihan berupa teori dan praktik di laboratorium jaringan Politeknik Caltex Riau. Materi yang disampaikan meliputi dasar-dasar jaringan komputer, pengenalan perangkat keras, konfigurasi jaringan, dan pengaplikasian fitur Physical Mode. Hasil evaluasi menunjukkan tingkat kepuasan yang tinggi di kalangan peserta, dengan skor rata-rata di atas 4,5 dari skala 5. Feedback peserta mencatat pengalaman belajar yang interaktif dan relevan untuk mendukung kebutuhan industri. Namun, terdapat ruang untuk perbaikan terkait manajemen waktu dan pelayanan selama pelatihan. Kegiatan ini tidak hanya memberikan pemahaman teknis, tetapi juga mempersiapkan siswa menghadapi tantangan industri dengan pendekatan pembelajaran yang inovatif.
Developing an Educational Software Platform for Stock Learning Using LSTM Forecasting Models Nurmalasari, Dini; Alfani, Yessi; Yuliantoro, Heri R; Fitrisia, Yuli
Journal of Educational Science and Technology (EST) Volume 11 Number 3 December 2025
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26858/est.v11i3.81360

Abstract

This study aims to develop an educational software platform that supports Indonesian students in learning stock market behavior by addressing low financial literacy, limited analytical skills, and emotion-driven investment decisions. The proposed platform integrates historical data from liquid IDX80 stocks with a Long Short-Term Memory (LSTM) forecasting model enhanced by technical indicators and calendar-based market features, and presents predicted price movements and trend classifications through an interactive, user-friendly learning interface. Experimental results show that the model achieved strong predictive performance on most IDX80 stocks, demonstrating its ability to capture temporal price patterns, while the inclusion of technical and calendar-based features improved prediction clarity and trend interpretability for student users. Variations in forecasting accuracy across stocks indicate that liquidity and volatility influence model performance, highlighting the importance of contextual interpretation in learning. In conclusion, the findings indicate that integrating LSTM-based forecasting with instructional design principles can support experiential and data-driven investment learning, and the developed platform demonstrates strong potential as both a forecasting tool and an educational technology medium for supporting financial literacy development. 
PELATIHAN PEMBUATAN PERANGKAT CBT (Computer Based Test) UNTUK MEMPERSIAPKAN SEKOLAH SIAGA BENCANA Dini Nurmalasari; Mardhian Fadhly; Wenda Novayanti; Yuli Fitrisia
Jurnal Pengabdian Masyarakat Multidisiplin Vol 4 No 3 (2021): Juni
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/jpm.v4i3.1787

Abstract

Learning process between students and teachers includes face-to-face activities and evaluation in the form of exams. In certain conditions, such as the natural disasters of haze or disease outbreaks, the teaching and learning process cannot be done directly. One alternative to face-to-face activities in the teaching and learning process is SPADA (Online Learning System), which was inaugurated nationally in 2014. This online system allows students and teachers to be in different places but can carry out online learning. Apart from online learning, exams or evaluations can also be done online. There are many free applications that can be used to create an online exam system, known as CBT. However, not all teachers understand and know how to use and make the CBT application. In this Community Service activity, lecturers in the Computer Engineering Study Program provide training and workshops on how to use and create CBT applications online through the Zoom Cloud streaming application. The workshop which was held for two days was attended by approximately 225 participants from high school and equivalent teachers who came from various cities in Riau and a small part from outside Riau and outside Sumatra.