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All Journal Jupiter Jurnal Pendidikan Matematika RAFA INTECH (Informatika dan Teknologi)
Imelda Saluza
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Industrial & Manufacturing Engineering Library & Information Science Mathematics Social Sciences

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PENGARUH PEMBELAJARAN GEOMETRI ANALITIK MENGGUNAKAN PENDEKATAN PAIKEM Imelda Saluza
Jurnal Pendidikan Matematika RAFA Vol 1 No 1 (2015): JURNAL PENDIDIKAN MATEMATIKA RAFA
Publisher : Program Studi Pendidikan Matematika UIN Raden Fatah Palembang

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

Abstract

Geometri analitik adalah suatu cabang ilmu matematika yang merupakan penggabungan antara aljabar dan geometri. Hal ini berarti untuk dapat memahami aljabar dapat menggunakan gemotri ataupun sebaliknya. Berdasarkan pengamatan peneliti terhadap mahasiswa yang mengambil mata kuliah geometri analitik, mahasiswa sering mengalami kesulitan untuk memahami materi. Penyebab utamanya adalah mahasiswa kurang antusias mengikuti pembelajaran, daya kreativitasnya rendah, dan bersikap acuh tak acuh sedangkan materi geometri analitik mentut keaktifan siswa untuk lebih memahami konsep aljabar secara geometrik. Hal ini menunjukkan bahwa proses pembelajaran secara konvensional yang biasa dilakukan tidak mampu mendorong mahasiswa untuk menggunakan daya pikirnya secara optimal, akibatnya mahasiswa menjadi kurang aktif dan proses pembelajaran menjadi kurang efektif. Untuk meningkatkan kemampuan mahasiswa dalam mengaitkan konsep-konsep aljabar menggunakan geometrik, maka dalam penelitian ini dilakukan pembelajaran dengan menggunakan pendekatan PAIKEM
PENENTUAN TINGKAT KEKUMUHAN PERMUKIMAN KUMUH KOTA PALEMBANG DENGAN METODE ALGORITMA K-MEANS CLUSTERING DAN ALGORITMA ID3 Lastri Widya Astuti; Endah Puspita Sari; Imelda Saluza; Faradillah Faradillah; Rini Yunita
INTECH Vol 2 No 1 (2021): INTECH (Informatika Dan Teknologi)
Publisher : Program Studi Informatika Fakultas Teknik dan Komputer Universitas Baturaja

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (584.102 KB) | DOI: 10.54895/intech.v2i1.869

Abstract

Slum settlers are a condition of uninhabitable settlements. Slums are devided into 4 levels, namely : high slums, medium, light and not slum. To produce these four levels, method is used namely K-Means Clustering Algorithm and the ID3 Algorithm is used to give priority with pre determined attributes then accumulated with the results of clustering classified as slum level. The accuracy test is performe by using the confusion matrix method, where the data results from the K-Means Clustering method compared to the baseline data. The results obtained from the accuracy with confusion matrix is 0,70%, which means the level of truth (accuracy) between the result of the baseline data with research data is 70%.
Ensemble Backpropagation Neural Network Dalam Memprediksi Inflasi Imelda Saluza; Lastri Widya Asuti; Dhamayanti; Evi Yulianti
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 15 No 1d (2023): Jupiter Edisi April 2023
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281./6613/15.jupiter.2023.04

Abstract

Global economic volatility that continues to experience spikes is a particular concern for countries in the world, including Indonesia. This is due to the impact that will occur if it continues to increase which can result in a country's economic recession. A country must pay attention to the pressure on the inflation rate. Unreasonable inflation rate volatility can have a negative impact on economic growth. Therefore, it is very important to accurately predict future inflation rates so that it becomes important information for economic policy makers. Inflation prediction is one of the problems that has been widely researched because the data is non-stationary and non-linear, so an algorithm is needed that can overcome this problem. One of the algorithms that can be used is the Backpropagation Neural Network (BPNN), but the BPNN network in its application has many parameters that must be determined so that it often causes overfitting. For this reason, instead of learning from multiple models, the ensemble method is used. The main benefit of this method is to reduce overfitting and at the same time maintain the accuracy and diversity of the BPNN network.
Penentuan Tingkat Kekumuhan Permukiman Kumuh Kota Palembang Dengan Metode Algoritma K-Means Clustering Dan Algoritma ID3 Lastri Widya Astuti; Endah Puspita Sari; Imelda Saluza; Faradillah Faradillah; Rini Yunita
INTECH (Informatika dan Teknologi) Vol 2 No 1 (2021): INTECH (Informatika Dan Teknologi)
Publisher : Informatics Study Program, Faculty of Engineering and Computers, Baturaja University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54895/intech.v2i1.869

Abstract

Slum settlers are a condition of uninhabitable settlements. Slums are devided into 4 levels, namely : high slums, medium, light and not slum. To produce these four levels, method is used namely K-Means Clustering Algorithm and the ID3 Algorithm is used to give priority with pre determined attributes then accumulated with the results of clustering classified as slum level. The accuracy test is performe by using the confusion matrix method, where the data results from the K-Means Clustering method compared to the baseline data. The results obtained from the accuracy with confusion matrix is 0,70%, which means the level of truth (accuracy) between the result of the baseline data with research data is 70%.
Co-Authors Dhamayanti Endah Puspita Sari Faradillah Faradillah Lastri Widya Astuti Lastri Widya Asuti Rini Yunita Yulianti, Evi