Garuda - Garba Rujukan Digital

Penerapan Computational Thinking Melalui Media Permainan Robot Untuk Melatih Kemampuan Critical Thinking Siswa SMK Taruna Persada Dumai Novayani, Wenda; Akbar, Memen; Fitrisia, Yuli; Nurmalasari, Dini; Syahbana, Yoanda Alim
JITER-PM (Jurnal Inovasi Terapan - Pengabdian Masyarakat) Vol. 1 No. 2 (2023): JITER-PM
Publisher : Politeknik Caltex Riau

Computational thinking (CT) is the ability to think in formulating problems and solutions by thinking logically step by step to be able to determine an effective decision. CT can be embedded in all subjects, one of which is Science, Technology, Engineering, and Mathematics (STEM). Not all teachers are competent, and not all students are interested in it. This PkM applies computational thinking in STEM classes by providing realistic views of the STEM field to students through an educational robot game called Robot Edison. This workshop uses the pre-test and post-test methods to measure the increase in students' knowledge. Students do the pre-test questions, and after being given CT material and robot games, students work on the post-test questions. The number of students who took this test amounted to 16 people. Students experienced an increase in post-test scores for SMA-level questions by 66.7%. All students strongly agree (100%) that the material provided can improve their insights and abilities as vocational students. When playing with the Robot, the students looked enthusiastic and happy and were starting to think critically when making decisions on a problem effectively, and one group successfully completed the robot challenge in about 30 minutes

Pemanfaatan Media Digital Sebagai Penunjang Pembelajaran di SMA IT Al-Ittihad Pekanbaru Fitrisia, Yuli; Nurmalasari, Dini; Fadhli, Mardhiah; Novayani, Wenda; Alim Syahbana , Yoanda; Akbar, Memen; Purwantoro, Sugeng
JITER-PM (Jurnal Inovasi Terapan - Pengabdian Masyarakat) Vol. 1 No. 4 (2023): JITER-PM
Publisher : Politeknik Caltex Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35143/jiter-pm.v1i4.6105

Media pembelajaran adalah alat atau sarana yang digunakan untuk menyampaikan informasi untuk memfasilitasi proses pembelajaran. Adapun tujuan penggunaan media pembelajaran diharapkan dapat meningkatkan pemahaman dan meningkatkan kreatifitas siswa. Berdasarkan hasil wawancara yang telah dilakukan dengan calon Mitra yaitu SMA IT Al-Ittihad Pekanbaru, dalam proses belajar mengajar penggunaan media pembelajaran digital telah dilakukan seperti pembuatan slide interaktif, pembuatan video pembelajaran, penggunaan aplikasi quizizz dan sebagainya. Namun dalam pembuatan media digital tersebut, guru-guru masih mengalami kesulitan dalam hal penggunaan aplikasi khususnya untuk pembuatan video pembelajaran. Seluruh guru belum memiliki kompetensi yang sama, sehingga terdapat beberapa video pembelajaran yang dihasilkan kurang menarik, jarangnya dilaksanakan pelatihan yang mendukung dalam menerapkan media video pembelajaran, kurangnya waktu untuk belajar otodidak dalam membuat media video pembelajaran itu sendiri yang efektif dan menarik untuk diterapkan pada saat pembelajaran. Berdasarkan permasalahan tersebut, diusulkanlah Kegiatan Pengabdian kepada Masyarakat mengenai Pemanfaatan Media Digital sebagai Penunjang Pembelajaran di SMA IT Al-Ittihad Pekanbaru. Dengan dilaksanakan kegiatan ini, dapat membantu mitra memiliki pemahaman dasar dan keterampilan dalam menggunakan aplikasi pembuatan video pembelajaran interaktif. Selain itu dapat membantu mitra agar memiliki kompetensi yang sama, sehingga video pembelajaran yang dihasilkan menarik untuk digunakan pada saat pembelajaran.

Analisis Sentimen dari Perspektif Peserta Implementasi Computational Thinking Dengan Block-Based Programming Dan Permainan Robot Nurmalasari, Dini; Novayani, Wenda; Fadhli, Mardhiah; Fitrisia, Yuli; Akbar, Memen; Purwantoro, Sugeng; Syahbana, Yoanda Alim
JITER-PM (Jurnal Inovasi Terapan - Pengabdian Masyarakat) Vol. 2 No. 3 (2024): JITER-PM
Publisher : Politeknik Caltex Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35143/jiter-pm.v2i2.6224

Computational Thinking (CT) is the ability to solve complex problems by analyzing, understanding issues, and logically developing appropriate solutions. Possessing CT skills enables individuals to think in a structured manner when faced with complex problems, making it easier to adapt and compete in the future. This ability is highly valuable for anyone, including students from elementary to high school. Enrichment material on logical thinking skills for high school students is currently provided as an extracurricular activity integrated into Information and Computer Technology (ICT) subjects. The ICT curriculum includes office administration, graphic design, and programming. However, programming material often cannot be effectively delivered to students due to the limited expertise of teachers in this field. Unfortunately, this situation is regrettable because programming is not solely about technical programming skills but primarily about CT and problem-solving abilities. In this Community Service activity, workshops will be conducted on the implementation of CT for high school students and several High School (SMA) teachers, utilizing two approaches: block-based programming and robot gaming. Block-based programming involves implementing CT using blocks of code arranged to produce a function. On the other hand, the CT approach using robot gaming will involve utilizing Edison robots, which can be implemented in Science, Technology, Engineering, and Mathematics (STEM) subjects. Results from satisfaction surveys conducted among participants in the implementation activities of block-based programming and robot gaming indicate that they perceived significant benefits in enhancing computational thinking among high school students, thus preparing them better for global competition in the future. Meanwhile, from the processed feedback data using sentiment analysis, it was found that 83.3% provided positive feedback, 16.7% were neutral, and there were no negative comments.

Penguatan Kompetensi Jaringan Komputer Berbasis Hardware Cisco bagi Siswa Jurusan Teknik Komputer Jaringan SMK Taruna Persada Dumai Purwantoro E.S.G.S, Sugeng; Novayani, Wenda; Fitrisia, Yuli; Akbar, Memen; Fadli, Mardhiah; Nurmalasari, Dini; Alim Syahbana, Yoada
JITER-PM (Jurnal Inovasi Terapan - Pengabdian Masyarakat) Vol. 2 No. 1 (2024): JITER-PM
Publisher : Politeknik Caltex Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35143/jiter-pm.v2i1.6228

Cisco menjadi standar utama pada dunia jaringan professional dam dunia industri yang secara core bisnisnya kearah IT atau bahkan non-IT. Kebutuhan Kompetensi Jaringan ini juga bukan hanya dirasakan untuk kebutuhan perusahaan atau industri yang bergerak di bidang IT tapi juga non-IT seperti Perbankan, Kesehatan, Entertainment, Military dan masih banyak lagi tersebut dalamnya dunia pendidikan. Pada Sekolah Menengah Kejuruan, khususnya yang memiliki jurusan Teknik Jaringan Komputer (TKJ), kurikulum Cisco sudah menjadi standar acuan yang banyak diadopsi pada kurikulum jurusan TKJ. Bahkan sudah masuk kedalam kurikulum yang wajib dikuasai siswa SMK bidang TJK. Pada Uji Kompetensi (UK) yang harus dijalani siswa pada akhir semester, bahkan perangkat cisco router secara hardware menjadi salah satu bahan uji. Sehingga siswa dan guru SMK saat ini harus bisa menggunakan perangkat Cisco secara hardware. Namun masih banyak Sekolah yang belum memberikan penguasan Hardware kepada siswanya dikarenakan keterbatasan dana untuk mempersiapkan perangkat Hardware. Oleh karena ini kegiatan PkM ini diselenggarakan oleh Program Studi Teknologi Rekayasa Komputer PCR bermitra dengan SMK Taruna Persada Dumai dalam rangka untuk memberikan pemahaman dan pengalaman kepada siswa untuk dapat menggunakan hardware Cisco dari pengenalan secara bentuk fisik perangkat, cara installasi dan konfigurasi pada perangkat sampai verifikasi keterhubungan jaringan komputer dengan perangkat Cisco.

Improving Panic Disorder Classification Using SMOTE and Random Forest Nurmalasari, Dini; Yuliantoro, Heri R; Qudsi, Dini Hidayatul
Journal of Applied Informatics and Computing Vol. 8 No. 2 (2024): December 2024
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v8i2.8315

Panic disorder is a serious anxiety disorder that can significantly impact an individual's mental health. If left undetected, this disorder can disrupt daily life, social relationships, and overall quality of life. Early detection and intervention are crucial for managing panic disorder and improving the well-being of those affected. Technology plays a pivotal role in facilitating early detection through data-driven approaches that employ algorithms to identify patterns of behavior or symptoms associated with panic disorder. Accurate classification of panic disorder is crucial for effective diagnosis and treatment. However, machine learning models trained on imbalanced datasets, such as those containing panic disorder patients, are prone to overfitting, leading to poor generalization performance. This study investigates the effectiveness of the Synthetic Minority Oversampling Technique (SMOTE) in addressing overfitting in panic disorder dataset classification using the Random Forest algorithm. The results demonstrate that SMOTE significantly improves the classification performance of Random Forest. By mitigating overfitting and improving generalization to unseen data, SMOTE increases accuracy by 15 percentage points. Before using SMOTE, the accuracy was 82%, and after using SMOTE it is 97%. The findings underscore the promise of SMOTE as a tool for boosting the performance of machine learning algorithms in classifying panic disorder from imbalanced data.

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

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.

Implementasi dan Workshop Penggunaan Aplikasi Penerimaan Peserta Dididk Baru (PPDB) Sekolah bagi Guru dan Operator fadhli, mardhiah; Nurmalasari, Dini; Fitrisia, Yuli; Novayani, Wenda; Akbar, Memen; Purwantoro, Sugeng; Alim Syahbana , Yoanda
JITER-PM (Jurnal Inovasi Terapan - Pengabdian Masyarakat) Vol. 2 No. 4 (2024): JITER-PM
Publisher : Politeknik Caltex Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35143/jiter-pm.v2i4.6233

Penerimaan Peserta Didik Baru (PPDB) merupakan kegiatan rutin sekolah setiap tahunnya yang dilakukan untuk mendapatkan calon peserta didik baru. Sekolah memerlukan media promosi dan informasi yang tepat agar informasi penerimaan calon peserta didik baru dapat di terima oleh masyarakat banyak. Salah satu bentuk teknologi informasi yang banyak digunakan untuk berbagi informasi adalah aplikasi berbasis website. Proses penerimaan peserta didik baru (PPDB) yang dilakukan MI Muhammadiyah 01 Pekanbaru saat ini masih dilakukan secara manual, masih menggunakan formulir sehingga sering terjadi berbagai masalah dari penginputan data yang lambat, berkas pendaftaran yang tidak tersusun rapih, antrian pendaftaran dan calon peserta didik terkadang kesulitan mendapatkan informasi tentang sekolah tersebut dan proses pendaftarannya. Untuk itu perlu dibangun aplikasi PPDB Online yang mampu mengelola pelaksanaan penerimaan peserta didik baru dengan lebih efektif dan efisien. Aplikasi PPDB sudah selesai dibangun dan dilakukan sosialisasi penggunaan aplikasi dalam bentuk kegiatan workshop. Dalam kegiatan ini dihadiri oleh 6 orang peserta yang terdiri dari kepala sekolah, panitia PPDB dan bendahara sekolah. Hasil evaluasi kegiatan menyatakan 98,67% dari peserta merasakan bahwa kegiatan ini sangat bermanfaat dan sangat sesuai dengan harapan mereka

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

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

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

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.

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