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All Journal Informasi Interaktif EDUMATIC: Jurnal Pendidikan Informatika Jurnal Pengabdian kepada Masyarakat Nusantara SmartComp
Sri Rahayu
Program Studi Informatika Fakultas Teknik Universitas Janabadra
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Social Sciences

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Journal : Informasi Interaktif

 1 
PERBANDINGAN ANALISIS DATA FITUR NOMINAL MULTI-KATEGORI MENGGUNAKAN METODE ADAPTIVE SYNTHETIC NOMINAL (ADASYN-N) SERTA ADAPTIVE SYNTHETIC-KNN (ADASYN-KNN) Putra, Jeffry Andhika; Rahayu, Sri
Informasi Interaktif Vol 6, No 2 (2021): Jurnal Informasi Interaktif
Publisher : Universitas Janabadra

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Abstract

Growing need for efficient algorithms for data manipulation, analysis, and intelligent use has been a very active research area in machine learning field. However, some research areas still not fully developed, especially when unbalanced data classification is needed. Datasets with this class imbalance occur because of an unbalanced ratio between one case and another. This class imbalance will be detrimental to data mining because machine learning in data mining has difficulty in classifying minority classes (small instances) correctly. There are several approaches to handling imbalances, one of which is by using the original data sampling method. The first sampling method approach to overcome class imbalance is undersampling which is a method to balance classes by randomly reducing the majority class instances. Over-sampling is a method of balancing class distribution by randomly replicating instances in minority classes.This study presents comparison of over-sampling techniques to overcome problem of class imbalances in datasets with nominal-multi categories features between Adaptive Synthetic-Nominal (ADASYN-N) and Adaptive Synthetic-kNN (ADASYN-KNN) methods. There are seven datasets with nominal-multi categories features which have an unbalanced class distribution. Then the dataset that has been over-sampled with both methods is classified using the Random Forest method. Furthermore, a comparison of the accuracy of the original dataset and the dataset of the ADASYN-N and ADASYN-KNN over-sampling techniques was carried out.  Keywords: ADASYN-KNN, ADASYN-N, class imbalance, nominal, multi-category, over-sampling. 
Pra-rancangan Sistem Pengelolaan Arsip Surat Berbasis Website (Kasus: Kapanewon Mlati, Sleman, Yogyakarta) Jeffry Andhika Putra; Sri Rahayu
Informasi Interaktif Vol 7, No 2 (2022): Jurnal Informasi Interaktif
Publisher : Universitas Janabadra

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Abstract

The purpose of this study was to design a mail archive management system at Kapanewon Mlati to archive government letter data (data of incoming letters, outgoing letters, incoming invitations, and outgoing invitations). With the design of this system, it is hoped that it can be implemented into a storage and archive management system in accordance with their respective fields into the system. The facts of this study indicate that the management of the Kapanewon Mlati archives has not been carried out optimally. This can be seen from the use of agenda books that are not accompanied by disposition sheets, archive storage systems that are still combined, controls that do not use form cards and the existence of damaged and dirty archives. The development of technology is currently becoming information as an important pillar with the operational activities of an institution to achieve goals that are beneficial to the institution. One technology that is currently very useful and is often used is the world wide web or known as the website. Even now the web has penetrated every agency, one of which is government agencies.
PERBANDINGAN ANALISIS DATA FITUR NOMINAL MULTI-KATEGORI MENGGUNAKAN METODE ADAPTIVE SYNTHETIC NOMINAL (ADASYN-N) SERTA ADAPTIVE SYNTHETIC-KNN (ADASYN-KNN) Jeffry Andhika Putra; Sri Rahayu
Informasi Interaktif Vol 6, No 2 (2021): Jurnal Informasi Interaktif
Publisher : Universitas Janabadra

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

ABSTRACTGrowing need for efficient algorithms for data manipulation, analysis, and intelligent use has been a very active research area in machine learning field. However, some research areas still not fully developed, especially when unbalanced data classification is needed. Datasets with this class imbalance occur because of an unbalanced ratio between one case and another. This class imbalance will be detrimental to data mining because machine learning in data mining has difficulty in classifying minority classes (small instances) correctly. There are several approaches to handling imbalances, one of which is by using the original data sampling method. The first sampling method approach to overcome class imbalance is undersampling which is a method to balance classes by randomly reducing the majority class instances. Over-sampling is a method of balancing class distribution by randomly replicating instances in minority classes.This study presents comparison of over-sampling techniques to overcome problem of class imbalances in datasets with nominal-multi categories features between Adaptive Synthetic-Nominal (ADASYN-N) and Adaptive Synthetic-kNN (ADASYN-KNN) methods. There are seven datasets with nominal-multi categories features which have an unbalanced class distribution. Then the dataset that has been over-sampled with both methods is classified using the Random Forest method. Furthermore, a comparison of the accuracy of the original dataset and the dataset of the ADASYN-N and ADASYN-KNN over-sampling techniques was carried out.Keywords: ADASYN-KNN, ADASYN-N, class imbalance, nominal, multi-category, over-sampling
PRA-RANCANGAN SISTEM PENGELOLAAN ARSIP SURAT BERBASIS WEBSITE (KASUS: KAPANEWON MLATI, SLEMAN, YOGYAKARTA) Jeffry Andhika Putra; Sri Rahayu
Informasi Interaktif Vol 7, No 2 (2022): Jurnal Informasi Interaktif
Publisher : Universitas Janabadra

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

ABSTRACTThe purpose of this study was to design a mail archive management system at Kapanewon Mlati to archive government letter data (data of incoming letters, outgoing letters, incoming invitations, and outgoing invitations). With the design of this system, it is hoped that it can be implemented into a storage and archive management system in accordance with their respective fields into the system.The facts of this study indicate that the management of the Kapanewon Mlati archives has not been carried out optimally. This can be seen from the use of agenda books that are not accompanied by disposition sheets, archive storage systems that are still combined, controls that do not use form cards and the existence of damaged and dirty archives.The development of technology is currently becoming information as an important pillar with the operational activities of an institution to achieve goals that are beneficial to the institution. One technology that is currently very useful and is often used is the world wide web or known as the website. Even now the web has penetrated every agency, one of which is government agencies. Keywords: Archive, Website, Kapanewon, Data Flow Diagram, MySQL
Co-Authors Bororing, Jemmy Edwin Fenthy Faharani Jeffry Andhika F Jeffry Andhika Putra Larasati Rahmat Hadiyat Tan Anugrah Ramadhani Yumarlin MZ