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All Journal Journal of Economic, Bussines and Accounting (COSTING) Journal Of Artificial Intelligence And Software Engineering
Angelica Angelica
Universitas Prima Indonesia
Computer Science & IT Economics, Econometrics & Finance

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Pengaruh Net Profit Margin, Return On Assets, Debt To Equity Ratio Dan Ito Pada Perusahaan Manufaktur Yang Terdaftar Di Bursa Efek Indonesia Maya Sabirina Panggabean; Angelica Angelica; Dinny Khairunnisa Aprilia; Edyson Wijaya; Sonia Febriani
Journal of Economic, Bussines and Accounting (COSTING) Vol 5 No 1 (2021): COSTING : Journal of Economic, Bussines and Accounting
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/costing.v5i1.2600

Abstract

The increase in profit obtained by a company within a certain period is the definition of profit growth. The percentage increase in profit can indicate the company's financial position. The purpose of this research is to know how Net Profit Margin, DER, ROA and ITO can impact on profit growth in the company. The type of research used is descriptive quantitative using secondary data, the sample is determined using the purposive sampling method, and the examination method uses multiple linear regression analysis.The population of the company is 139 manufacturing companies listed on the Indonesia Stock Exchange for the period 2016-2019. Based on the research results, it is known that NPM has an effect of 34.38 percent, ROA has an effect of -45.71 percent, DER has an effect of 49.2 percent and ITO has an effect of 0.5 percent on Profit Growth. Simultaneously, NPM, DER, ROA and ITO have a positive and relevant impact. Partially, only NPM and DER have a positive and relevant effect on Profit Growth, while ROA and ITO have no relevant impact on Profit Growth. Keywords: Net Profit Margin, Return On Assets, Debt to Equity Ratio and ITO
Prediction Analysis of KIP Student Placement at Universitas Prima Indonesia Using SVM Hyperparameter Optimization Method and Comparative Study Oloan Sihombing; Calvin Wahyu Febrian Sidabutar; Angelica Angelica; Rico Halim; Daniel Agus Towi Sitompul
Journal of Artificial Intelligence and Software Engineering Vol 6, No 2 (2026): Juni (OnProgress)
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v6i2.9179

Abstract

Penelitian ini bertujuan membangun model prediksi penempatan mahasiswa penerima Kartu Indonesia Pintar (KIP) di Fakultas Sains dan Teknologi Universitas Prima Indonesia menggunakan algoritma Support Vector Machine (SVM) yang dioptimasi hyperparameternya dan dibandingkan dengan K-Nearest Neighbor (KNN). Penelitian menggunakan 269 data mahasiswa yang diperoleh dari instansi akademik dan kuesioner. Tahapan penelitian meliputi pra-pemrosesan data, pembentukan label target, encoding, normalisasi, serta pembagian data 80:20. Optimasi SVM dilakukan menggunakan Grid Search dan 5-fold cross-validation, sedangkan KNN digunakan tanpa optimasi. Hasil penelitian menunjukkan bahwa SVM dengan kernel RBF, parameter C=10 dan gamma=0,1 memperoleh akurasi 88,89%, lebih tinggi dibandingkan KNN sebesar 83,33%. Selain itu, SVM juga menunjukkan performa lebih baik pada metrik precision, recall, dan F1-score, sehingga lebih efektif digunakan untuk mendukung pengambilan keputusan penempatan mahasiswa KIP secara objektif dan tepat sasaran.
Co-Authors Calvin Wahyu Febrian Sidabutar Daniel Agus Towi Sitompul Dinny Khairunnisa Aprilia Edyson Wijaya Oloan Sihombing Panggabean, Maya Sabirina Rico Halim Sonia Febriani