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All Journal JOURNAL OF SCIENCE AND SOCIAL RESEARCH International Journal of Management Science and Information Technology (IJMSIT) Journal Of Indonesian Social Society
Adi Prijuna Lubis
Universitas Royal
Religion Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Implementation of the Apriori Algorithm for Product Recommendation Analysis at Asyifa Serba 35.000 Retail Store in Kisaran Ardiansyah Putra Tambunan; Adi Prijuna Lubis; Parini Parini
International Journal of Management Science and Information Technology Vol. 6 No. 1 (2026): January - June 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i1.7289

Abstract

This study aims to implement the Apriori algorithm to analyze sales transaction data and generate product recommendations at Toko Asyifa Serba 35.000. The research addresses the problem of underutilized transaction data, where sales records are only used for administrative purposes without further analysis to support marketing strategies and decision-making. The significance of this study lies in its contribution to enhancing data-driven decision-making in retail businesses, particularly in improving product promotion strategies, inventory management, and customer satisfaction. The research adopts an applied quantitative approach with an experimental design. Data were collected through observations, interviews, and documentation of sales transactions, and analyzed using data mining techniques, specifically the Apriori algorithm, to identify frequent itemsets and association rules based on support and confidence values. The results indicate that the implementation of the Apriori algorithm successfully uncovers patterns of consumer purchasing behavior, revealing combinations of products frequently bought together. The generated recommendations provide practical benefits for retail management, including more effective product bundling strategies, optimized shelf arrangement, targeted promotional campaigns, and improved inventory planning. These improvements can contribute to increased sales opportunities and better customer shopping experiences. These findings enable the development of a recommendation system that provides accurate and relevant product suggestions. The study concludes that the application of Apriori-based recommendation systems improves sales effectiveness, optimizes product placement, and enhances customer satisfaction. It is recommended that retail businesses adopt data mining techniques to maximize the value of transaction data and further develop integrated recommendation systems for better decision support.
Menuju Desa Modern Administrasi Digital Dan Manajemen Efektif Nofriadi; Adi Prijuna Lubis; Indra Ramadhona Harahap
Journal Of Indonesian Social Society (JISS) Vol. 4 No. 2 (2026): JISS - Juni
Publisher : PT. Padang Tekno Corp

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59435/jiss.v4i2.670

Abstract

Desa sebagai unit pemerintahan dasar memiliki peran strategis dalam pembangunan dan pelayanan publik, namun masih menghadapi berbagai kendala dalam administrasi dan manajemen. Pengelolaan yang masih manual menyebabkan pelayanan lambat, rawan kesalahan, serta rendahnya transparansi dan akuntabilitas. Selain itu, keterbatasan kompetensi aparatur desa dalam teknologi dan manajemen modern menghambat efektivitas perencanaan, pelaksanaan, serta evaluasi program pembangunan. Kondisi ini berdampak pada rendahnya kualitas layanan publik dan partisipasi masyarakat. Oleh karena itu, transformasi digital dan penguatan manajemen pemerintahan desa menjadi kebutuhan mendesak. Kegiatan Pengabdian kepada Masyarakat bertajuk “Menuju Desa Modern: Administrasi Digital dan Manajemen Efektif” dirancang untuk meningkatkan kapasitas aparatur desa melalui pelatihan dan pendampingan. Program ini bertujuan mengimplementasikan sistem administrasi digital yang terintegrasi serta manajemen pemerintahan yang efektif, guna meningkatkan efisiensi pelayanan, transparansi, dan kualitas tata kelola desa secara berkelanjutan Villages, as the lowest level of government, play a strategic role in development and public service delivery; however, they still face various challenges in administration and management. Manual administrative processes lead to slow services, a high risk of errors, and low levels of transparency and accountability. In addition, the limited competence of village officials in technology and modern management hinders the effectiveness of planning, implementation, and evaluation of development programs. This condition impacts the quality of public services and reduces community participation. Therefore, digital transformation and the strengthening of village governance management have become urgent necessities. A Community Service program entitled “Towards a Modern Village: Digital Administration and Effective Management” is designed to enhance the capacity of village officials through training and mentoring. This program aims to implement an integrated digital administrative system and effective governance management in order to improve service efficiency, transparency, and the overall quality of sustainable village governance
INTRUSION DETECTION SYSTEM BERBASIS DEEP LEARNING UNTUK PENINGKATAN MITIGASI SQL INJECTION DAN SYN FLOOD ATTACK Sahren Sahren; Adi Prijuna Lubis
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 7 No. 4 (2024): November 2024
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v7i4.2340

Abstract

Intrusion Detection System (IDS) tradisional seringkali tidak mampu mengikuti kecepatan perkembangan serangan, sehingga meninggalkan celah yang dapat dimanfaatkan oleh penyerang. Penelitian ini bertujuan untuk melindungi infrastruktur jaringan dari ancaman keamanan yang semakin kompleks. Dalam penelitian ini, penulis mengusulkan penggunaan model Deep Learning arsitektur CNN VGG-16 pada Intrusion Detection System untuk mitigasi serangan SqL Injection dan Syn Flood dengan proses yang lebih mendalam yaitu dengan penerapan normalisasi data diawal dan teknik augmentation sebagai cara meningkatkan variasi data pelatihan dan mengurangi overfitting. Public dataset yang digunakan CICDDoS2019 dan CSE-CIC-IDS2018. Dengan memanfaatkan kekuatan model Deep Learning dalam mengenali pola serangan yang kompleks dan berubah-ubah, serta teknik augmentation data untuk dapat memberikan tingakat Accuracy yang lebih baik.. Hasil Percobaan menujukkan hasil CNN dengan Arsitektur VGG 16 memiliki Accuracy 99.9261%, loss 0,018590 untuk serangan Syn Flood dan Accuracy 99.9983%, loss 0.001294 untuk Sql Injection. Resnet 50 dengan Accuracy 99.9263% , loss 0.024910 untuk syn flood, Accuracy 99.9962%, loss 0.001749 untuk Sql Injection. InceptionV3 dengan Accuracy 99.7784%, loss 0.015571 untuk serangan syn flood, sedangkan untuk sql injection dengan nilai Accuracy 99.9872% dan loss 0.000392.
Co-Authors Ardiansyah Putra Tambunan Indra Ramadhona Harahap Nofriadi Parini Parini sahren, sahren