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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Seminar Nasional Teknologi Informasi Komunikasi dan Industri Computer Based Information System Journal JURNAL TEKNOLOGI DAN OPEN SOURCE REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Journal of Computer Networks, Architecture and High Performance Computing JPM: JURNAL PENGABDIAN MASYARAKAT Journal of Computer Scine and Information Technology Jurnal IPTEK Bagi Masyarakat Jurnal Ipteks Terapan : research of applied science and education pendidikan, science, teknologi, dan ekonomi Jurnal Sains Informatika Terapan (JSIT) Jurnal Komtekinfo Sistem Pendukung Keputusan dengan Aplikasi The Indonesian Journal of Computer Science Jurnal Pustaka Robot Sister Mandala Bakti
Pradani Ayu Widya Purnama
Universitas Putra Indonesia YPTK Padang
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Determining Marketing Strategy to Support Customer Relationship Management with the Apriori Algorithm Dheatri Agrema; Febri Hadi; Pradani Ayu Widya Purnama
Journal of Computer Scine and Information Technology Volume 9 Issue 2 (2023): JCSITech
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/jcsitech.v9i2.70

Abstract

Business competition has forced companies to be more selective in implementing their marketing strategies. This increasingly rapid technological development is an aspect that can be utilized in achieving ease of doing everything. The development of this technology can have a good impact on business people, Customer Relationship Management (CRM) is one of the business strategies to meet the goals of the store. To fulfill these objectives, the authors conducted an analysis of sales transaction data using assistive devices such as data mining. Data mining is part of analytical Customer Relationship Management (CRM) which is used to find patterns in data. By applying the Apriori Algorithm or Association Rule to achieve this business strategy. The Apriori algorithm is a method for finding relationship patterns between one or more items in a dataset. By using sales transaction data at the Rahmat Elektronik Store, it is possible to find out which products are in great demand by customers every time they shop at the Rahmat Elektronik Store. The results of applying the Apriori Algorithm or Association Rule use Minimum Support 5% and Minimum Confidance 50%
Klasifikasi Penjualan Produk Menggunakan Algoritma Naive Bayes pada Konter HP Bayu Cell Purnama, Pradani Ayu Widya; Putra, Teri Ade
REMIK: Riset dan E-Jurnal Manajemen Informatika Komputer Vol. 8 No. 1 (2024): Call for Paper: Volume 8 Nomor 1 Januari 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/remik.v8i1.13207

Abstract

Data Mining merupakan proses iteratif dan interaktif untuk menemukan pola atau model baru yang dapat digeneralisasi untuk masa yang akan datang, bermanfaat dan dapat dimengerti dalam suatu database yang sangat besar (massive database). Pada Konter HP Bayu Cell mempunyai masalah dalam menentukan produk yang laris atau tidak laris terjual pada konter tersebut. Dengan demikian untuk adanya suatu sistem yang dapat menunjang Konter HP Bayu Cell dalam mengambil keputusan secara cepat dan tepat agar tidak terjadinya penumpukan produk. Untuk itu pada penelitian ini penulis menggunakan Algoritma Data Mining Metode Algoritma Naïve Bayes, Pada metode Naive Bayes untuk ukuran peluang suatu peristiwa yang terjadi berdasarkan peristiwa lain yang telah (dengan asumsi, praduga, pernyataan, atau terbukti) terjadi. Pada data training yang dilakukan dengan produk handphone REDMI NOTE 9 menggunakan algoritma Naive Bayes dimana menghasilkan klasifikasi masuk ke kategori “Laris” dengan nilai 0,005211. Oleh karena itu pada konter HP Bayu sudah dapat menghasilkan hasil yang diharapkan dan dapat membantu dalam mengetahui mana saja produk handphone yang termasuk kategori laris dan tidak laris.
Naive Bayes Algorithm Classification for Predicting Graduation Rate Pradani Ayu Widya Purnama; Nurmaliana Pohan
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 7 No. 2 (2024): Jurnal Teknologi dan Open Source, December 2024
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v7i2.3866

Abstract

Classification refers to the process of identifying a model or function that clarifies or differentiates concepts or categories of data, with the goal of predicting the class of an object. Naïve Bayes is a machine learning technique that employs probability computations. In this case study, various algorithms are used for modeling classification, and the naïve bayes algorithm is applied to examine the graduation rate. By utilizing this method, accuracy is assessed, which allows for an analysis based on criteria such as School Major, First Choice of College, Second Choice of College, Average Graduation Value, and Graduation Information. The outcome of the computation utilizing the Naïve Bayes Algorithm (Information Systems | Option 1) > (Information Engineering | Option 2) is 53.32% > 0%, which allows us to infer that the First Option of Information Systems and the Second Option of Informatics Engineering yield an Average Score of 75.00, resulting in a Graduation Information status of PASS, thus, Information Pass (Option 1-Information Systems).
ALGORITMA K-MEANS CLUSTER UNTUK SEGMENTASI PELANGGAN Fazri, Ahmad Harya; Muhammad, Abulwafa; Purnama, Pradani Ayu Widya
Computer Based Information System Journal Vol. 11 No. 2 (2023): CBIS Journal
Publisher : Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/cbis.v11i2.7156

Abstract

Consumer data for business transactions in retail agricultural products has not been managed digitally. This can be seen from consumer data which is still stored manually, some customer data is stored only based on purchase receipts and others have logbooks so that consumer data can be lost at any time. To improve service to consumers, sales analysis is carried out using the k-means algorithm. The aim is to be able to group consumers based on the number of transactions, the number of products purchased, and the frequency of transactions made. The data processed was 127 transaction data and grouped by name of the consumer, 116 consumers made transactions in the last 1 months. From this data, 5 clusters were determined including: Superstar, Golden, Typical, Occasional, Everyday. Of the 5 clusters, there were 4 consumers including Superstar, 12 Golden consumers, 34 Typical consumers, 29 Occasional consumers and 37 Everiday consumers.
SMART Method to Choose The Best Smartphone Purnama, Pradani Ayu Widya; Armonitha, Shary; Rahmi, Nadya Alinda; Pohan, Nurmaliana
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4101

Abstract

Smartphones are important devices for many people and are considered a necessity in today's industrial age 4.0. This is the beginning of the advancement of digital technology and the internet, where information can be easily accessed in various places. Therefore, people started buying smartphones. With this, people can utilise the Decision Support System. used to determine the data criteria needed to select a smartphone. With these criteria, users can accurately and quickly determine their choice. Where in the research in choosing a smartphone according to the needs of the community using 9 criteria that are often taken into consideration including Brand, Price, Processor Specifications, RAM Specifications, Model, Battery Capacity, Camera Resolution, Internal Capacity, Screen size which will be processed using the SMART method. Where the weight for each criterion has a value range of 0-100 depending on the priority given to each criterion. Based on calculations using the SMART method, the Iphone 11 Pro smartphone ranks highest with a final score of 8.3.
Pengenalan Aplikasi Teknologi Komputer untuk Edukasi Islami bagi Anak-anak TPQ Nurul Huda Gunung Pangilun, Kota Padang Pohan, Nurmaliana; Widya Purnama , Pradani Ayu; Kurnia AR, Harlan
Mandala Bakti (Jurnal Pengabdian kepada Masyarakat) Vol. 1 No. 3 (2025): MANDALA BAKTI (Jurnal Pengabdian kepada Masyarakat) September 2025
Publisher : Yasin Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65359/mandala_bakti.v1i3.56

Abstract

Perkembangan teknologi komputer yang pesat telah merambah ke berbagai bidang kehidupan, termasuk dalam dunia pendidikan, begitu juga dalam pembelajaran agama Islam. Kegiatan pengabdian masyarakat ini bertujuan untuk memperkenalkan dan melatih santri TPQ Nurul Huda dalam memanfaatkan aplikasi komputer edukatif bernuansa Islami sebagai sarana belajar yang menyenangkan. Beberapa aplikasi yang digunakan meliputi game edukasi do’a sehari-hari, aplikasi tajwid interaktif, kuis Islami berbasis komputer, serta aplikasi murattal Al-Qur'an dengan animasi visual. Kegiatan ini dirancang dengan pendekatan pembelajaran yang partisipatif dan berorientasi pada eksplorasi langsung oleh anak-anak, sehingga mereka dapat belajar dengan cara bermain sambil tetap mendapatkan pemahaman keislaman yang bermakna. Metode pelaksanaan kegiatan pengabdian ini dimulai dengan melakukan observasi lapangan, wawancara dengan guru TPQ, serta eksperimen langsung dengan siswa menggunakan berbagai aplikasi Islami yang dirancang khusus untuk anak-anak. Dalam konteks ini, pengenalan aplikasi edukasi Islami berbasis komputer menjadi langkah strategis untuk memperkaya metode pembelajaran Islam yang lebih interaktif, menyenangkan, dan sesuai dengan perkembangan zaman, khususnya bagi anak-anak usia 7 hingga 12 tahun. Hasil yang diharapkan dari kegiatan ini adalah meningkatnya antusiasme belajar anak-anak TPQ terhadap materi-materi keislaman, tumbuhnya pemahaman dasar mengenai penggunaan komputer sebagai media pembelajaran, serta meningkatnya keterampilan dasar digital yang dapat berguna di masa depan. Selain itu, kegiatan ini juga bertujuan untuk membantu guru TPQ dan orang tua dalam mengakses serta menggunakan sumber belajar Islami berbasis teknologi yang berkualitas dan ramah anak. Kegiatan ini juga merekomendasikan agar lembaga pendidikan Islam lainnya turut memanfaatkan teknologi sebagai alat bantu pembelajaran guna menciptakan generasi Muslim yang cakap, cerdas, dan berakhlak mulia.
Naive Bayes Algorithm Classification for Predicting Graduation Rate Purnama, Pradani Ayu Widya; Pohan, Nurmaliana; Adiddo Restiady
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 7 No. 2 (2024): Jurnal Teknologi dan Open Source, December 2024
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v7i2.3866

Abstract

Classification refers to the process of identifying a model or function that clarifies or differentiates concepts or categories of data, with the goal of predicting the class of an object. Naïve Bayes is a machine learning technique that employs probability computations. In this case study, various algorithms are used for modeling classification, and the naïve bayes algorithm is applied to examine the graduation rate. By utilizing this method, accuracy is assessed, which allows for an analysis based on criteria such as School Major, First Choice of College, Second Choice of College, Average Graduation Value, and Graduation Information. The outcome of the computation utilizing the Naïve Bayes Algorithm (Information Systems | Option 1) > (Information Engineering | Option 2) is 53.32% > 0%, which allows us to infer that the First Option of Information Systems and the Second Option of Informatics Engineering yield an Average Score of 75.00, resulting in a Graduation Information status of PASS, thus, Information Pass (Option 1-Information Systems).
Predicting New Student Admissions with the SVM Regression Model in Data Mining Purnama, Pradani Ayu Widya; Pohan, Nurmaliana; Adiddo Restiady
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 8 No. 2 (2025): Jurnal Teknologi dan Open Source, December 2025
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v8i2.5035

Abstract

Prediction is an action to predict future conditions based on past data. One method for making predictions that can be used is the linear regression method. The linear regression method itself consists of two types, simple linear regression and multiple linear regression. One method that uses past data to make predictions is the linear regression method. Regression is a statistical calculation to test how closely the relationship between variables. The simplest and most frequently used regression analysis is simple linear regression. In regression analysis, there is one dependent variable usually written with the symbol Y and one or more independent variables usually written with the symbol X. The relationship between the two variables has a linear nature according to its name. The SVM method was chosen for data mining analysis in this study. There are two parameters used: Exam Scores and Admission Status. This research uses recapitulation data on the acceptance of new students at Play Group & Kindergarten Rahmah Abadi with a total of 50 people. Based on the analysis results, an accuracy rate of 91%.
Optimalisasi Pengenalan Dasar Coding Berbasis Visual untuk Meningkatkan Literasi Digital Siswa Sekolah Menengah Pohan, Nurmaliana; Kurnia AR, Harlan; Purnama, Pradani Ayu Widya
JPM: Jurnal Pengabdian Masyarakat Vol. 6 No. 3 (2026): January 2026
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jpm.v6i3.2782

Abstract

This activity was motivated by the low level of digital literacy and the limited implementation of programming education in secondary schools, which have resulted in students’ lack of understanding of computational thinking from an early age. In fact, this ability is essential for developing critical and creative thinking skills to face the challenges of the Industrial Revolution 4.0 and Society 5.0. This condition highlights the need for educational interventions that introduce the concept of coding starting from the high school level. The workshop aimed to introduce the fundamentals of programming to students of SMA INS Kayutanam through an interactive visual approach using the Scratch platform. This platform was chosen because it is beginner-friendly, featuring a block-based interface that is easy to understand without requiring complex syntax. Through this activity, students learned programming logic, algorithmic thinking, and problem-solving skills in a fun and practical way. The implementation used a project-based learning approach that combined short lectures, demonstrations, hands-on practice, and group discussions. The activity was carried out over two days in the school’s computer laboratory, involving 20 students and two accompanying teachers. Each session focused on introducing programming logic, creating mini projects using Scratch, and evaluating learning outcomes through pre-tests and post-tests. The results showed a significant improvement in students’ understanding, with the average pre-test score increasing from 43 to 82 in the post-test. A total of 90% of participants expressed satisfaction with the activity, and 85% were interested in continuing to learn programming afterward. The visual-based workshop model proved effective in enhancing students’ motivation, confidence, and understanding of technology. This activity not only developed students’ cognitive abilities but also encouraged them to experiment, collaborate, and create through simple projects such as animations or interactive games. The program has the potential to serve as a sustainable community engagement model that integrates educational, technological, and social aspects in supporting the digital transformation of education in Indonesia.
Fluensi Digital untuk Siswa SD dalam Kompetensi Komputer di SD N 02 Lubuk Buaya Kota Padang Harlan Kurnia AR; Nurmaliana Pohan; Pradani Ayu Widya Purnama
Jurnal IPTEK Bagi Masyarakat Vol 4 No 1 (2024)
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/jibm.v4i1.882

Abstract

Siswa SD saat ini sudah memanfaatkan teknologi digital dalam pembelajaran di sekolahnya, bahkan dalam kehidupan sehari-hari. Tapi masih banyak siswa SD yang belum memahami bagaimana seharusnya memanfaatkan teknologi digital ini dengan baik dan benar, juga agar lebih efisien dan etis. Teknologi digital yang biasa siswa SD gunakan saat ini adalah komputer maupun turunannya. Agar siswa SD dapat mengambil hal positif dari penggunaan teknologi ini, maka kami tim pengabdi perlu melakukan kegiatan pengabdian kepada masyarakat. Kegiatan pengabdian kepada masyarakat ini lebih dikhususkan kepada fluensi digital, yang bertujuan untuk meningkatkan fluensi digital siswa SD kelas V di SD N 02 Lubuk Buaya, Kota Padang. Kemampuan dalam menggunakan komputer menjadi penting bagi siswa untuk menghadapi era globalisasi. Sebelum melaksanakan kegiatan, tim pengabdi telah melakukan pretest terhadap siswa dengan cara tanyajawab langsung. Kemudian mensosialisasikan fluensi digital dan memberikan pelatihan yang berkaitan dengan fluensi digital. Kegiatan ini melibatkan metode pembelajaran interaktif yang mencakup permainan edukatif, proyek kelompok, dan simulasi. Setelah kegiatan selesai dilaksanakan, tim pengabdi kembali melaksanakan posttest terhadap siswa dengan tanyajawab langsung dan menggunakan aplikasi yang berkaitan dengan fluensi digital. Hasil kegiatan menunjukkan peningkatan signifikan dalam keterampilan komputer siswa. Kegiatan ini juga mendapatkan tanggapan positif dari siswa dan guru, menunjukkan bahwa pendekatan interaktif, informatif dan inovatif efektif dalam meningkatkan motivasi dan partisipasi siswa SD kelas V SD N 02 Lubuk Buaya, Kota Padang.
Co-Authors Adiddo Restiady Adiddo Restiady Alfin Andika Putra Ariandi, Vicky Aulia Fitrul Hadi Ayu Mahessya, Raja Dari, Rahmatia Wulan Desi Ardila Dheatri Agrema Elvira Sawitri Fazri, Ahmad Harya Febri Hadi Hadi, Aulia Fitrul Hana Afifah Harlan Kurnia AR Ilmawati Ilmawati Rahmi Indra Irawan Kaila Azahra Kurnia AR, Harlan Lusinia, Shary Armonitha Muhammad, Abulwafa Mutiara Sakinah Nadya Alinda Rahmi Nurfa Rahma Julita Ondra Eka Putra Pohan, Nurmaliana Rahman, Sepsa Nur Rahmi, Nadya Alinda Reza Suriadinata Riandana Afira Sopi Sapriadi Teri Ade Putra Wijaya, Romi Yesri Elva