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All Journal Lontar Komputer: Jurnal Ilmiah Teknologi Informasi IJEMS (Indonesian Journal of Environmental Management and Sustainability)
Azhar Kholiq Affandi
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Energy Environmental Science Public Health

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Study of Chemical Characteristics of The Lambidaro River for Sustainable Environment Hisni Rahmi; Restu Juniah; Azhar Kholiq Affandi
Indonesian Journal of Environmental Management and Sustainability Vol. 1 No. 1 (2017): December
Publisher : Research Centre of Inorganic Materials and Complexs

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (455.494 KB) | DOI: 10.26554/ijems.2017.1.1.23-26

Abstract

Residents who live along the Lambidaro watershed, generally use river water to meet their daily needs such as bathing, washing and latrines. Around of Lambidaro is a residential and industrial group such as rubber industry, workshop, home industry, and mining. The activities contained along the watershed can lead to an increase in river water pollution load which can be seen from chemical characteristics. Increased pollution loads can cause the river environment to be unsustainable for the community. Sustainable environment means that the environment as a provider of resources for human life is able to maintain its carrying capacity. The purpose of study is to determine the chemical characteristics of river due to sand mining activities for the environment sustainable. This research is using pollution index method with parameter of chemical characteristics measured that is pH, DO, COD, BOD5, Fe, Mn, NH4, Nitrate, and Nitrite. The results of analysis of water chemical characteristics of the river indicate that the part close to estuary of the river is in good condition indicating that the location is environmentally sustainable. Meanwhile, the upstream to the middle river body is in mild contamination condition which means that the river environment has been contaminated.
Implementation of Sample Sample Bootstrapping for Resampling Pap Smear Single Cell Dataset Anita Desiani; Azhar Kholiq Affandi; Shania Putri Andhini; Sugandi Yahdin; Yuli Andirani; Muhammad Arhami
Lontar Komputer : Jurnal Ilmiah Teknologi Informasi Vol 13 No 2 (2022): Vol. 13, No. 2 August 2022
Publisher : Institute for Research and Community Services, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/LKJITI.2022.v13.i02.p01

Abstract

The purpose of this study was to determine how the effect of using Bootstrapping Samples for resampling the Harlev dataset in improving the performance of single-cell pap smear classification by dealing with the data imbalance problem. The Harlev dataset used in this study consists of 917 data with 20 attributes. The number of classes on the label had data imbalance in the dataset that affected single-cell pap smear classification performance. The data imbalance in the classification causes machine learning algorithms to produce poor performance in the minority class because they were overwhelmed by the majority class. To overcome it, The resampling data could be used with Sample Bootstrapping. The results of the Sample Bootstrapping were evaluated using the Artificial Neural Network and K-Nearest Neighbors classification methods. The classification used was seven classes and two classes. The classification results using these two methods showed an increase in accuracy, precision, and recall values. The performance improvement reached 10.82% for the two classes classification and 35% for the seven classes classification. It was concluded that Sample Boostrapping was good and robust in improving the classification method.
Co-Authors Anita Desiani Arhami, Muhammad Hisni Rahmi Restu Juniah Shania Putri Andhini Sugandi Yahdin Yuli Andirani