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Nurmalasari, Dini
Politeknik Caltex Riau
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Implementasi Ekstraksi Fitur untuk Pengelompokan Dokumen Proposal Menggunakan Algoritma Naïve Bayes Dini Nurmalasari; Heri Ribut Yuliantoro
Jurnal Komputer Terapan Vol. 8 No. 1 (2022): Jurnal Komputer Terapan
Publisher : Politeknik Caltex Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (375.908 KB) | DOI: 10.35143/jkt.v8i1.5351

Abstract

Text mining is the process of discovering new, previously unknown information from several text documents. Text mining can be applied to the fields of information extraction, topic tracking, document summarization, document categorization or grouping, concept linking or question answering systems. One thing that is often done in implementing text mining is information extraction. Information extraction aims to extract information from unstructured documents into structured data, with the aim of making it easier to analyze the data. In this study, feature extraction will be used to extract features from the Community Service document, using the Frequent Itemset Mining (FIM) algorithm. The features taken are PKM Title, Abstract, Year of Service, Location, and research topic. After obtaining the features, the service topics will be grouped using the Naive Bayes algorithm. The results of this study were tested using a confusion matrix, with an accuracy of 70%. Factors that affect the accuracy results include the amount of training data, the distribution of training data, and the optimization of the algorithm used
Implementasi Fun Learning Dengan Hour of Code Untuk Meningkatkan Minat Belajar Coding Pada Siswa Mardhiah Fadhli; Yuli Fitrisia; Dini Nurmalasari; Sugeng Purwantoro; Memen Akbar
Literasi: Jurnal Pengabdian Masyarakat dan Inovasi Vol 3 No 1 (2023)
Publisher : Pengelola Jurnal Politeknik Negeri Ketapang

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Abstract

The importance of studying computer programming for students is that students will gain the ability to think computationally systematically, which includes a more robust way of thinking (robust) in looking at a problem. However, learning computer programming is often considered complicated and requires regular practice. The current condition of the partner, namely SMKN 1 Dumai, is the lack of student interest in learning, curiosity, and the joy of learning coding. This is caused by many factors, one of which is the assumption that students learn coding is something that is complicated and boring. In addition, it is also caused by the learning strategies and methods applied by the teacher are not sufficiently capable of arousing students' curiosity about the lesson. The learning process which is not conducive and the low interest in student learning can be handled by the teacher by providing material in a fun way (fun learning). One way to learn basic coding in a fun way is to learn with hours of code in the game Minecraft. This community service activity was carried out on September 6, 2022, with a total of 22 participants. The results of this activity were in the form of an evaluation of activities through a questionnaire and the result was that 89,90% of the training participants understood the material and were able to practice the Minecraft game project themselves. In addition, the participants were very enthusiastic about participating in the activity because it was presented with fun activities, such as playing games. Based on the results of the questionnaire, training recommendations were also obtained for the next activity in the form of training in implementing the Internet of Things (IoT) project.
IMPLEMENTASI DASHBOARD BUSINESS INTELLIGENCE UNTUK VISUALISASI DATA DONATUR (STUDI KASUS: HUMAN INITIATIVE RIAU) Uun Patrio; Dini Nurmalasari
ABEC Indonesia Vol. 9 (2021): 9th Applied Business and Engineering Conference
Publisher : Politeknik Caltex Riau

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Abstract

Human Initiative Riau is one of the humanitarian institutions located in Pekanbaru City which focuses on four areas of work, namely economy, health, education and emergency response. Based on interviews with the Human Initiative, information was obtained that there were several obstacles faced in supporting the activities and programs that were being carried out. The data currently held is still managed conventionally by each division head so that the human initiative is constrained to ascertain whether the program is being implemented according to the target or not. Therefore, a solution is needed that can be used by human initiatives to see the development of donors, donors, beneficiaries and marketers which will later be used as material for evaluating marketer performance and determining future strategies that can improve the performance of human initiatives. This system was built by implementing business intelligence technology with visualization in the form of column-charts and graphs. designed using the codeigniter framework, the programming language PHP and MySQL as its DBMS. This system is tested using testing data transformations, user acceptance test (UAT) and efficiency so that users can find out what improvements they want. Based on the user acceptance test (UAT) that has been carried out, it shows that 96,76% of the systems that have been built are acceptable to users and can help human initiatives in making decisions.
RANCANG BANGUN DASHBOARD BUSINESS INTELLIGENCE UNTUK VISUALISASI DATA PASIEN (STUDI KASUS: PUSKESMAS PAKAN KAMIS) Nazifa Hayati; Dini Nurmalasari
ABEC Indonesia Vol. 9 (2021): 9th Applied Business and Engineering Conference
Publisher : Politeknik Caltex Riau

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Abstract

The Public Health Center (Puskesmas) is a technical implementation unit of the district / city office which is responsible for carrying out health development in a work area. One of the existing community health centers is the Pakan Kamis puskesmas. Based on the interviews conducted, the puskesmas still experienced difficulties in seeing the pattern of disease spread, drug use patterns and patient development, because the process of recapping and calculating data was still done manually. This causes the puskesmas management to have difficulty in analyzing data and obtaining information for decision making. Therefore, a web-based business intelligence dashboard was created that can visualize patient data related to these problems. This Business Intelligence dashboard is built using the PHP programming language and MySQL database. From the results of user satisfaction testing, it was found that 97% of the business intelligence system dashboard for visualizing patient data was in accordance with the needs and could assist the health center in monitoring the pattern of disease spread, patient usage and development, as well as assisting the health center in analyzing data to make appropriate decisions. and efficient. Keywords: Puskesmas Pakan Kamis, Patient Data, Visualization, Dashboard, Business Intelligence
IMPLEMENTASI DASHBOARD BUSINESS INTELLIGENCE UNTUK VISUALISASI DATA PINJAMAN DANA BERGULIR (STUDI KASUS : UPTD FASILITASI PEMBIAYAAN KOTA PAYAKUMBUH) Fathu Rahmi; Dini Nurmalasari
ABEC Indonesia Vol. 9 (2021): 9th Applied Business and Engineering Conference
Publisher : Politeknik Caltex Riau

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Abstract

UPTD Payakumbuh City Financing Facilitation is a Micro Finance Institution that provides and manages assistance in the form of revolving fund loans to strengthen business capital for micro-entrepreneurs such as livestock, trade, agriculture and industry. Based on information obtained through interviews with the UPTD, there were difficulties in obtaining information related to micro-businesses and monitoring customer commitment. Where the data currently owned is still managed conventionally so that the UPTD is difficult to obtain information. Therefore, a system was Dashboard Business Intelligencecreated that could assist the UPTD in managing data and providing information related to micro-businesses to maximize loan funds so that loans can help improve the community's economy. This system is built using the Codeigniter Framework, the programming language PHP and MySQL as the DBMS. This system is tested using blackbox testing and user acceptance test (UAT). Based on the blackbox testing that has been done, the system functionality is in accordance with user expectations. Meanwhile, based on the user acceptance test (UAT) that has been carried out, it shows that 91% of the system that has been built has been accepted by the user and can help the UPTD in making decisions
Penggunaan Metode FIFO pada Real-Time Monitoring Antrian Pendaftaran Pasien Puskesmas Berbasis Web mardhiah fadhli; Dini Nurmalasari; Memen Akbar
Jurnal Komputer Terapan Vol. 9 No. 1 (2023): Jurnal Komputer Terapan
Publisher : Politeknik Caltex Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35143/jkt.v9i1.5915

Abstract

Antrian adalah suatu keadaan di mana seseorang harus menunggu gilirannya untuk mendapatkan pelayanan, yang terjadi akibat oleh sekelompok orang yang membutuhkan jasa pelayanan pada waktu yang bersamaan. Salah satu aktivitas mengantri terjadi pada saat melakukan pendaftaran pasien pada suatu Puskesmas. Di masa setelah pandemi, kita sebagai masyarakat di anjurkan untuk tetap melaksanakan protokol kesehatan, salah satunya adalah menjaga jarak (physical distancing) atau menghindari kerumunan. Namun, di beberapa tempat yang harus didatangi oleh masyarakat, seperti klinik atau puskesmas, kerumunan tidak bisa dihindari karena banyak masyarakat yang sakit dan harus mengantri untuk mendapatkan pelayanan kesehatan. Disamping itu pelayanan yang cepat dan baik juga merupakan salah satu target layanan dari setiap tempat pelayanan publik termasuk puskesmas. Berdasarkan data dari Dinas Kesehatan Pekanbaru, Puskesmas Rumbai merupakan tempat pelayanan kesehatan di wilayah Pekanbaru yang menangani 6 Kelurahan dengan jumlah penduduk kurang lebih 83 ribu jiwa. Setiap harinya rata-rata kunjungan ke puskesmas Rumbai adalah 35 - 60 pasien. Dalam upaya meningkatkan pelayanan kepada masyarakat maka dibangun sistem antrian online berbasis web dengan menggunakan bahasa pemrograman PHP dan My SQL sebagai databasenya. Aplikasi ini dengan menerapkan metode FIFO (First In First Out) yang berfungsi sebagai pendaftaran online sehingga setiap pasien untuk mendapatkan informasi nomor antrian dan perkiraan waktu pelayanan sehingga tidak perlu menunggu langsung di Puskesmas dalam waktu yang cukup lama. Aplikasi antrian yang dibuat dilengkapi dengan fitur monitoring laju antrian yang sedang berjalan yang dapat diakses secara real-time. Informasi nomor antrian diimplementasikan menggunakan SMS Gateway sebagai notifikasi setelah pengambilan antrian berhasil dilakukan. Hasil pengujian dari aplikasi ini berhasil dilakukan dengan 100% fitur berjalan sesuai dengan kebutuhan pengguna. Seluruh fungsi dalam aplikasi memiliki respond time yang baik, dengan pengujian yang dilakukan terhadap 10 user dengan masing-masing request sebanyak 10 dalam waktu 1 detik.
Ekstraksi Data pada Tabel dari Halaman Web Menggunakan Pohon Document Object Model Memen Akbar; Cici Patmala; Dini Nurmalasari
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 5 No 4: November 2016
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (925.883 KB)

Abstract

Data on the web page can be available in various formats, such as table. With the growing of web pages, the need to extract data from tables is increasing. Results of the extraction can be used for integration with other web tables or stored in a database. This study discusses the extraction of data from a table on a web page using a Document Object Model (DOM) tree. The initial step of this extraction process is to transform the HTML document into a DOM tree. Then, by applying search methods Depth First Search (DFS), part of the data in the table is extracted and stored in a CSV file. An engine has been developed using Visual Basic. The results show that the engine can automatically extract data from the table that has the following characteristics: the number of rows and columns are not limited, able to handle all of the table orientation layout, and able to handle tables that are merged cells.
Penggunaan Algoritma Naïve Bayes pada Klasifikasi Judul Proyek Akhir Berdasarkan Kelompok Bidang Kompetensi (KBK) Dini Nurmalasari; Heri Yuliantoro; Saleha Indri Yanti
Media Informatika Vol 22 No 2 (2023)
Publisher : P3M STMIK LIKMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37595/mediainfo.v22i2.174

Abstract

The Final Project is one of the graduation requirements that must be met by Caltex Riau Polytechnic students. The title of the final project is submitted by students through the SIAK system. Currently, students who submit titles will choose their own type of KBK from the inputted title. So that a problem arises where the title of the final project does not match the KBK it should or the KBK is wrong. This is due to the ignorance of students in analyzing the title data of the final project that will be submitted. For this reason, a system is needed to classify Final Project titles based on CBC automatically. The system created is a system that can classify KBK automatically based on the description of the title of the Final Project by using text mining methods and nave Bayes algorithms. The system can also detect the percentage of similarity of the entered title with the existing title in the system database. The algorithm used to generate the percentage of title similarity is cosine similarity with text mining method.
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

Abstract

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

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.
Co-Authors Akbar, Memen Akbar, Memen Alfani, Yessi Alim Syahbana, Yoanda Chairani, Nessa Cici Patmala Dini Hidayatul Qudsi Emansa Hasri Putra Erwin Setyo Nugroho Fadhly, Mardhiah Fathu Rahmi Heri Ribut Yuliantoro, Heri Ribut Heri Yuliantoro Hidayat, Muhammad Taufiq Kartina Diah K. W. Mardhiah Fadhli Mardhiah Fadhli, Mardhiah Mardhian Fadhly memen akbar mutia sari zulvi Mutia Sari Zulvi Nabilah Nasution Nazifa Hayati Neni Febriani Nurzikriah Nurzikriah Palapa, Yusmar Patmala, Cici Puja Hanifah Purwantoro E.S.G.S, Sugeng Putri Radha Retro Tri Wahyuni Saleha Indri Yanti Sugeng Purwantoro Sugeng Purwantoro E.S.G.S Tinambunan, Theresia Elfina Tri Wahyuni, Retro Uun Patrio Warnia Nengsih Wenda Novayani Wenda Novayanti Yoanda Alim Syahbana Yuli Fitrisia Yuli Fitrisia Yuli Fitrisia, Yuli Fitrisia Yuliantoro, Heri R Yusmar Palapa Zusanti Syahrial