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All Journal Jurnal Teknologi dan Manajemen Informatika SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JATI (Jurnal Mahasiswa Teknik Informatika) Abdimas Galuh : Jurnal Pengabdian Kepada Masyarakat IJIIS: International Journal of Informatics and Information Systems JPMB: Jurnal Pemberdayaan Masyarakat Berkarakter Jurnal Teknologi Informasi dan Komunikasi Journal of Applied Data Sciences Nusantara Hasana Journal International Journal for Applied Information Management Naratif : Jurnal Nasional Riset, Aplikasi dan Teknik Informatika Jurnal Rekayasa Informasi Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Saturnus: Jurnal Teknologi dan Sistem Informasi International Journal of Information Engineering and Science
Bangkit, Jeffri Prayitno
Universitas AMIKOM Purwokerto
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Journal : Journal of Applied Data Sciences

 1 
Market Basket Analysis Using FP-Growth Algorithm to Design Marketing Strategy by Determining Consumer Purchasing Patterns Saputra, Jeffri Prayitno Bangkit; Rahayu, Silvia Anggun; Hariguna, Taqwa
Journal of Applied Data Sciences Vol 4, No 1: JANUARY 2023
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v4i1.83

Abstract

The development and competition that exists in the business world today leads every manager or company to be more dexterous in making marketing strategies to increase sales. Various things are done to keep up with existing market competition, such as analyzing customer purchase transaction data to serve as a policy determination and decision-making system in making marketing strategies. In determining marketing strategies, it can be done by taking transaction data to see existing purchase or transaction patterns. Market Basket Analysis is part of a data mining method that uses the FP-Growth algorithm technique to find out associated products. This research uses data taken from sales transaction data archives as much as 150 sales transaction data and 26 product data. In this study, it is determined that the minimum support value is 50% and the minimum confidence is ≥ 0.75 From the test results, 9 products have superior support values and meet the minimum value. From the test results, a rule with a confidence value of 0.870 was obtained: D → W (if consumers buy Wardah Lightening Gentle Wash, then buy Azarine Sunscreen SPF50), and 0.808: A → E → O (if consumers buy Emina Face Wash, then buy Azarine Night Moisturizer and Himalaya Neem Mask).
Data Mining Implementation with Algorithm C4.5 for Predicting Graduation Rate College Student Saputra, Jeffri Prayitno Bangkit; Waluyo, Retno
Journal of Applied Data Sciences Vol 2, No 3: SEPTEMBER 2021
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v2i3.37

Abstract

Academic evaluation and graduation of students are critical components of an academic information system's (AIS) effectiveness since they allow for the measurement of student learning progress. Additionally, the assessment stating whether the student passed or failed would benefit both the student and teacher by acting as a reference point for future performance suggestions and evaluations. Using Decision Tree C4.5, a comprehensive analysis of the student academic evaluation approach was conducted. Age, gender, public or private high school status, high school department, organization activity, age at high school admission, progress GPA (pGPA), and total GPA (tGPA) were all documented and evaluated from semester 1–4 utilizing three times the graduation criterion periods. The article's scope is confined to undergraduate programs. An accuracy algorithm (AC) with a performance accuracy of 79.60 percent, a true positive rate (TP) of 77.70 percent, and 91 percent quality training data achieved the highest performance accuracy value.
Development of Gamification-Based Learning Management System (LMS) with Agile Approach and Personalization of FSLSM Learning Style to Improve Learning Effectiveness Saputra, Jeffri Prayitno Bangkit; Prabowo, Harjanto; Gaol, Ford Lumban; Hertono, Gatot Fatwanto
Journal of Applied Data Sciences Vol 6, No 1: JANUARY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i1.486

Abstract

This research focuses on designing a Learning Management System (LMS) that incorporates gamification elements while addressing student learning styles based on the Felder-Silverman Learning Style Model (FSLSM). Using Agile methodology in the development process, the LMS is designed to deliver a more personalized learning experience, with features tailored to students' unique learning style preferences. The research process began with a comprehensive user needs analysis, followed by iterative design and development in accordance with Agile principles. System evaluation involved user feedback and performance analysis, revealing that the developed LMS increased student engagement by 25% and improved learning motivation by 30% compared to the previous system. Furthermore, 88% of users reported a positive experience with the personalized features, and the system achieved an overall satisfaction score of 85% in usability testing. These results demonstrate that the LMS effectively enhances student motivation and engagement in the learning process while providing a more individualized learning experience. This research contributes to the advancement of adaptive and responsive learning systems that better meet the diverse needs of students.
Co-Authors Andri Laksono Arifah Budi Hidayah Bernarte, Racidon P Dede Ari Putragani Dendi Putra Prakoso Diksi Metris Diya Ulhaq Jauhari Budiarto Dominic Dinand Aristo Dwi Puji Lestari, Dwi Puji El Syafangatun Aulia Difa Esti Nur Wakhidah Fadil Tazakka Pribadi Farah Setyaningsih Fariz Nur Fikri Zaki Fiby Nur Afiana Ford Lumban Gaol, Ford Lumban Hani, Nurul Harjanto Prabowo Hertono, Gatot Fatwanto Hidayat, Muhammad Taufik Nur Ika Romadoni Yunita Ito Setiawan Iwan Haryatno Khalidy, Shodiq Kusuma, Rahayu Linda Lestari, Putri Vidia M Afrian Maulana Muhamad Awiet Wiedanto Prasetyo Muhammad Taufik Hidayat Nurhidayah, Isnaeni Nurul Afifah Priambodo, Aji Putri Awaliatuz Zahra Rahayu, Silvia Anggun Ramadhani, Sekar Ajeng Retno Waluyo Riyan Dwi Yulian Prakoso Riyanto Riyanto Satria Dwi Nurwicaksana Setyaningsih, Gustin Sigit Setoyoko Taqwa Hariguna Tarwoto, Tarwoto Toni Anwar Trias Bratakusuma Ummul Hidayah, Debby Vidia Alma Cyrilla Wahyu Latifatun Waluyo, Retno Wisnu Muamar Zamora, Hanenda Putri Zanuar Rifai Zulfa Aulia2