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All Journal Jurnal Ekonomi Pembangunan DERIVATIF Media Mahardhika JAST : Jurnal Aplikasi Sains dan Teknologi JURNAL PENELITIAN EKONOMI DAN AKUNTANSI (JPENSI) TRIDARMA: Pengabdian Kepada Masyarakat (PkM) Jurnal Berdaya Mandiri Enrichment : Journal of Management Jurnal Scientia Jurnal Ekonomi Jurnal Abdimas Terapan
Erna Hayati
Faculty Of Economics, Universitas Islam Lamongan
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ANALISIS DISKRIMINAN DAN MULTIVARIATE ADAPTIVE REGRESSION SPLINE (MARS) UNTUK MEMPREDIKSI FINANCIAL DISTRESS PADA PERUSAHAAN MANUFAKTUR DI BEI Erna Hayati; Diah Ayu Novitasari; Rosdiyati Rosdiyati
Media Mahardhika Vol. 17 No. 1 (2018): September 2018
Publisher : STIE Mahardhika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29062/mahardika.v17i1.55

Abstract

Business competition that is very tight in the current era of globalization, requires companies to be able to maintain their performance. Companies that are not able to compete are feared to experience financial distress until it leads to bankruptcy. Considering the importance of predicting financial distress for company managers, investors, creditors and decision-making institutions, it is necessary to make a prediction model for financial distress. Financial distress prediction model that was first developed by Altman, using the statistical method, Discriminant Analysis. In its use, Discriminant Analysis has the disadvantage of having to fulfill certain assumptions related to the predictor measurement scale, the relationship between predictors and distribution along with predictors. In this research a prediction model of financial distress will be made using a new method, Multivariate Adaptive Regression Spline (MARS). MARS was chosen because this method was developed using a nonparametric approach, so it does not require certain assumptions and is more flexible. The MARS method and Discriminant Analysis will be used to make predictive models of financial distress in manufacturing companies listed on the Indonesia Stock Exchange. The modeling resulting from the MARS and Discriminant Analysis methods will then be compared to the accuracy of the predictions. The results of this study indicate that the MARS model has a smaller classification error and is statistically consistent than the Discriminant Analysis method.
DETEKSI DEPRESI PADA SISWA BERBASIS WEB (STUDI KASUS: MTs TERPADU RAUDLATUL QUR’AN LAMONGAN) Miftahus Sholihin; Dinar Mahdalena Leksana; Erna Hayati; Abdul Kholiq; M. Rosidi Zamroni; M. Khairul Anam; Akhmad Nurali Sulaiman; Moch. Zuhrul Umam; M. Miftah Fatkhul U; Diko Prastowo
Jurnal Abdimas Terapan Vol. 3 No. 2 (2024): JURNAL ABDIMAS TERAPAN (MEI)
Publisher : Program Vokasi Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56190/jat.v3i2.58

Abstract

This Students' mental health in the school environment is becoming increasingly important. Depression, as a severe mental health disorder, can have a negative impact on students' well-being and academic achievement if it is not detected and treated appropriately and quickly. This service program aims to detect depression in MTs Roudlatul Qur'an students as early as possible to reduce the risk of ongoing depression. This can be done by building a website-based system that students can use to detect depression independently. This system was created to make it easier for students to recognize the early symptoms of depression by selecting the symptoms according to what they are experiencing. With this system, it is hoped that it can prevent depression as early as possible for students and teachers quickly and more efficiently, thereby reducing students who are at risk of experiencing depression. Apart from that, the system provides valuable information for students and teachers to understand depression more deeply and find ways to overcome it. Through this program, it is hoped that awareness of the importance of mental health in the school environment can increase and create a healthier and more supportive learning environment for all students.
Co-Authors Abdul Kholiq Abdul Kholiq Akhmad Nurali Sulaiman Chodariyanti, Laily Diah Ayu Novitasari Diah Ayu Novitasari Diko Prastowo Dinar Mahdalena Leksana 1 Khoirul Bariroh KIKI SEPTARIA M. Khairul; Anam M. Miftah Fatkhul U M. Rosidi Zamroni Miftahus Sholihin Miftahus Sholihin Moch. Zuhrul Umam Muhtarom, Abid Nanda Ary Chandra W Novitasari, Diah Ayu Rivatul Ridho Elvierayani Rosdiyati Rosdiyati Rosdiyati Shania Dwi Krispriandini Syafik, Mohammad Tarisa Ayu Firnanda Vanesta Ikhsana Putri Maulana Zulyanti, Noer Rafikah