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All Journal Jurnal AKSI (Akuntansi dan Sistem Informasi) jurnal teknik informatika dan sistem informasi
Nurdian, Risky Agung
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Computer Science & IT Economics, Econometrics & Finance

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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.
Komparasi Metode SMOTE dan ADASYN dalam Meningkatkan Performa Klasifikasi Herregistrasi Mahasiswa Baru Nurdian, Risky Agung; Mujib Ridwan; Ahmad Yusuf
Jurnal Teknik Informatika dan Sistem Informasi Vol 8 No 1 (2022): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v8i1.4004

Abstract

Universities annually accept new students at the beginning of the new school year. In the acceptance of prospective students on the Seleksi Prestasi Akademik Nasional Perguruan Tinggi Keagamaan Islam Negeri (SPAN PTKIN) di State Islamic University Of Sunan Ampel Surabaya, many prospective students who do not register will have an impact on income of the State Islamic University Of Sunan Ampel Surabaya institution. If the institution can find out early on the probability of a prospective student who will resign, then the management can take action to retain the prospective student. To overcome this, data mining classification can be carried out. The methods used in this classification are decision trees and naïve bayes. The number of students who did not re register compared to reregister resulted in the data being imbalanced. Data imbalances can affect the accuracy of the classification results. The imbalance of the data used can result in an unsuitable model. The solution to handle the data imbalance is to use the SMOTE and ADASYN oversampling methods. The purpose of this study was to compare performance of the SMOTE and ADASYN methods. The results show that the SMOTE method can balance the data in a balanced way compared to ADASYN. From the test results, the SMOTE method is more suitable to use than the ADASYN method because the ROCAUC SMOTE value is higher than ADASYN.  
Co-Authors Ahmad Yusuf Mujib Ridwan Yusuf Amrozi Zamakhsyari, Fardan