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IMPLEMENTATION OF SUPPLY CHAIN MANAGEMENT IN MANAGING VEHICLE SPARE PARTS USING CODEIGNITER FRAMEWORK Nurdian, Risky Agung; Zamakhsyari, Fardan; Amrozi, Yusuf
Jurnal AKSI (Akuntansi dan Sistem Informasi) Vol 5, No 1 (2020)
Publisher : Politeknik Negeri Madiun

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (517.562 KB) | DOI: 10.32486/aksi.v5i1.448

Abstract

Company Z is a business entity engaged in the distribution of motorcycle parts in partnership with local shops in the supply chain. The process of recording parts distribution services, service returns and report services is still done manually. So this process is quite vulnerable to data loss that has been recorded. Therefore, a more effective and efficient recording system is needed. The system will be designed using the concept of Supply Chain Management which includes the process of purchasing goods, selling goods, managing suppliers, returning goods and managing reports. In this study the authors used a descriptive qualitative research method with interview, observation and document collection data collection techniques. The system is designed using a codeigniter framework and uses a MySQL database. The system that has been designed can provide solutions in recording the purchase, sales, management, product returns, and report management services that have been carried out based on the website so that it becomes more effective and efficient.
Comparison of KNN and Random Forest Algorithms on E-Commerce Service Chatbot Zamakhsyari, Fardan; Makayasa, Bagas Adi; Hamami, R. Abudullah; Akbar, Muhammad Tulus; Cahyono, Andi; Amirullah, Amirullah; Hisyamuddin, Muhammad Zida; Siregar, Maria Ulfah
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 10 No. 1 (2025): January 2025
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiska.2025.10.1.100-109

Abstract

Technology heavily influences our lives, with the expansion of e-commerce being an important outcome that demands attention. Given the prevalence of smartphones equipped with messaging apps and fast networks, people often utilize these platforms to communicate with sellers, offering a convenient way for sellers to engage efficiently with a diverse customer base. Recognizing this trend, there is a need for digital transformation of services to improve operational efficiency. Thus, this study aimed to compare the efficiency of classification algorithms in e-commerce service chatbots. The researcher used machine learning techniques with KNN and Random Forest algorithms in this case. To assess the feasibility of the application, the chatbot results will be tested using the confusion matrix method to assess accuracy. From this study, it was obtained that the KNN method and calculating word weight using TF-IDF produces an accuracy value of 71.4%, thus confirming its feasibility.