Water quality mapping in Pontianak City using multiple discriminant analysis

Kusnandar, Dadan; Debataraja, Naomi Nessyana; Rizki, Setyo Wira; Saputri, Ernita

doi:10.1063/5.0016809

Cited by 2 publications

(3 citation statements)

References 2 publications

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“…Apparent Error Rate (APER) is used to express the value of the proportion of samples that are misclassified in the classification process [15]. Calculation of classification accuracy to calculate the value of 1-APER will result in a small chance of misclassification.…”

Section: Classification Accuracymentioning

confidence: 99%

Application of Bagging Cart in the Classification of on-Time Graduation of Students in the Statistics Study Program of Tanjungpura University

Imtiyaz,

Satyahadewi,

Perdana

2023

BAREKENG: J. Math. & App.

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The timeliness of graduation is used as the success of students in pursuing education which can be seen from the time taken and measured by the predicate of graduation obtained. The characteristics of students who tend to graduate not or on time can be analyzed using classification techniques. Classification and Regression Tree (CART) is one of the classification tree methods. There is a weakness in CART, which is less stable in predicting a single classification tree. The weaknesses in CART can be improved by using Ensemble methods, one of which is Bootstrap Aggregating (Bagging) which can reduce classification errors and increase accuracy in a single classification model. This study aims to classify and determine the accuracy of Bagging CART in the case of the accuracy of student graduation classification. The number of samples used is 140 data on the graduation status of Untan Statistics Study Program students from Period I of the 2017/2018 academic year to Period II of the 2022/2023 academic year. The variables used are the timeliness of graduation which is categorized into two namely Not and On Time, Gender, Semester 1 GPA, Semester 2 GPA, Semester 3 GPA, Semester 4 GPA, Region of Origin Domicile, High School Accreditation, Entry Path, Scholarship, and first TUTEP. A good classification can be seen from the accuracy value. The CART method obtained an accuracy value of 70%. While using the CART Bagging method obtained an accuracy value of 85.71%. Based on the accuracy value obtained, the application of the CART Bagging method can increase accuracy and correct classification errors on a single CART classification tree by 15.71% by resampling 25 times.

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Section: Classification Accuracymentioning

confidence: 99%

Application of Bagging Cart in the Classification of on-Time Graduation of Students in the Statistics Study Program of Tanjungpura University

Imtiyaz,

Satyahadewi,

Perdana

2023

BAREKENG: J. Math. & App.

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“…Keberadaannya dibutuhkan dalam hampir semua kegiatan manusia sehari-hari, baik untuk rumah tangga, pertanian atau industri. Akan tetapi, kegiatan tersebut umumnya menghasilkan limbah yang dapat menurunkan kualitas air dan menimbulkan polusi [1]. Beberapa jenis limbah bahkan berbahaya bagi kehidupan manusia.…”

Section: Pendahuluanunclassified

“…Beberapa jenis limbah bahkan berbahaya bagi kehidupan manusia. Analisis klasifikasi kualitas air di Kota Pontianak telah dilakukan dengan menggunakan teknik analisis multivariat [1]- [3]. Dalam penelitian ini digunakan perluasan analisis multivariat dengan mempertimbangkan model regresi spasial.…”

Section: Pendahuluanunclassified

Pemodelan Tingkat Kualitas Air Di Kota Pontianak Dengan Menggunakan Multivariate Geographically Weighted Regression

Kusnandar

Debataraja

Utari

2021

BAREKENG: J. Il. Mat. & Ter.

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Ketersediaan air bersih dan sanitasi yang layak merupakan salah satu tujuan dalam Sustainable Development Goals. Kualitas air cenderung mengalami penurunan terutama di daerah permukiman akibat tercemar limbah dari hasil kegiatan manusia. Penyebab pencemaran air bisa jadi berbeda-beda di setiap lokasi pengamatan, sehingga faktor letak geografis perlu dipertimbangkan pada proses pengambilan keputusan. Multivariat Geographically Weighted Regression digunakan untuk mengatasi adanya pengaruh heterogenitas spasial dalam data yang disebabkan oleh perbedaan kondisi lokasi yang satu dengan lokasi lain. Tujuan dari penelitian ini adalah menentukan model dan faktor-faktor apa saja yang berpengaruh terhadap kualitas air di Kota Pontianak. Data yang digunakan pada penelitian ini adalah data kualitas air di Kota Pontianak sebanyak 42 titik sampel lokasi. Variabel responnya terdiri dari Y1 (COD) dan Y2 (TDS), sedangkan untuk variabel prediktor terdiri dari X1 (warna), X2 (pH), X3 (kandungan zat besi), dan X4 (kesadahan). Hasil penelitian menunjukkan bahwa variabel yang mempengaruhi COD adalah warna, sedangkan variabel TDS dipengaruhi oleh warna dan kesadahan.

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Water quality mapping in Pontianak City using multiple discriminant analysis

Cited by 2 publications

References 2 publications

Application of Bagging Cart in the Classification of on-Time Graduation of Students in the Statistics Study Program of Tanjungpura University

Application of Bagging Cart in the Classification of on-Time Graduation of Students in the Statistics Study Program of Tanjungpura University

Pemodelan Tingkat Kualitas Air Di Kota Pontianak Dengan Menggunakan Multivariate Geographically Weighted Regression

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