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All Journal Indonesian Journal of Electrical Engineering and Computer Science Journal of Business Application MAREN: Jurnal Pengabdian dan Pemberdayaan Masyarakat
Tuhuteru, Joselina
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Religion Humanities Economics, Econometrics & Finance Education Engineering Health Professions Social Sciences

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GENERASI MILENIAL BEBAS FINANCIAL Tuhuteru, Joselina; Ririmasse, Olyvia
MAREN: Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol 4, No 1 (2023): Maret
Publisher : Lembaga Pengabdian kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69765/mjppm.v4i1.1013

Abstract

Berdasarkan argumen dan kesimpulan kegiatan sebelumnya, maka kegiatan PkM ini menyasar mitra yaitu kaum milenial yang tergabung dalam persekutuan Angkatan Muda Gereja Protestan Maluku (AMGPM) Cabang Zebaoth di Kota Masohi dengan foksu permasalahan yang disepakati dengan mitra antara lain (1) Kurangnya pemahaman mitra tentang pengelolaan keuangan pribadi, meliputi perencanaan, penganggaran, pengelolaan, evaluasi dan pengendalian; (2) Kurangnya pemahaman mitra tentang pengelolaan perilaku konsumtif menyikapi perkembangan e commerce dengan kemudahan penawaran dari market place dan (3) Kurangnya pemahaman mitra tentang investasi di pasar modal yang lebih menguntungkan dari sekedar menabung. Solusi yang ditawarkan untuk menyelesaikan permasalahan mitra antara lain (1) Pelatihan pengelolaan keuangan pribadi (2) Sosialisasi Perilaku Hidup Konsumtif dan (3) Sosialisasi investasi di pasar modal. Metode pelaksanaan PkM ini dilakukan dengan empat tahapan antara lain tahap persiapan, tahap pelaksanaan, tahap evaluasi dan tahap tindak lanjut. Pelatihan pengelolaan keuangan dilakukan dengan metode coaching clinic sedangkan kegiatan sosialisasi perilaku hidup konsumtif dan investasi di pasar modal. Target luaran kegiatan yang akan dicapai dalam pelaksanaan PkM ini antara lain (1) Meningkatnya keterampilan mitra dalam pengelolaan keuangan pribadi sebesar 80% (2) Meningkatnya pemahaman mitra tentang perilaku hidup konsumtif sebesar 85% dan (3) Meningkatnya pemahaman mitra tentang pasar modal sebesar 85%.
Altman Z-Score dan Grover G-Score Dalam Analisis Kebangkrutan PT. Sepatu Bata Tbk Periode Tahun 2014 - 2020 Tuhuteru, Joselina
Journal of Business Application Vol. 1 No. 1 (2022): Journal of Business Application
Publisher : Program Studi Administrasi Niaga STIA Said Perintah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55098/jba.v1.i1.p19-26

Abstract

During the COVID-19 pandemic in Indonesia, PT. Sepatu Bata Tbk recorded a net loss in 2020 of IDR 177,761,030,000 down 858% from the previous year. The company’s financial statements reflect the company’s performance. If there is a continuous decline in profits, it is possible that the company will go bankrupt. The purpose of this study was to predict the risk of corporate bankruptcy at PT. Sepatu Bata, Tbk so that companies can anticipate, prevent and reduce the risk of bankruptcy. This study uses the Altman Z-Score and Grover G-Score methods as a company bankruptcy tool analysis with indicators for the company’s financial statements for the period of 2014 to 2020. Based on the results of the analysis using the Altman and Grover Methods, in 2020 PT. Sepatu Bata Tbk is estimated to go bankrupt with a Z-Score 0f 0,000 < 1,080 and a G-Score of -0,669 ≤ -0,02
Comparative analysis of linear regression, random forest, and LightGBM for hepatitis disease prediction Tuhuteru, Hennie; Nivaan, Goldy Valendria; Rijoly, Marvelous Marvel; Tuhuteru, Joselina
Indonesian Journal of Electrical Engineering and Computer Science Vol 41, No 1: January 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v41.i1.pp430-438

Abstract

In bioinformatics research, computational pattern-analysis techniques are frequently employed to assist in disease prediction and diagnostic modeling, including applications for hepatitis prognosis. Hepatitis is a type of serious disease with various types that have the potential to threaten the life of the sufferer without showing significant symptoms and signs, so many sufferers do not realize that they are affected by the disease. Various methods are used to predict diseases in the hope of providing the best results from the learning model used. The objective of this study is to implement linear regression, random forest, and light gradient boosting machine (LightGBM) to estimate mortality risk among hepatitis patients. In addition, a performance comparison of the results of hepatitis disease prediction using the three algorithms was also carried out to find out which model gave the most accurate and optimal results. The results of this study show that the application of learning models from the linear regression, random forest and Light-GBM algorithms has been successfully carried out to predict the survival status of patients with hepatitis. The findings reveal that random forest achieved the highest predictive performance with an accuracy of 84%, followed by LightGBM at 77% and linear regression at 32%.
Co-Authors Hennie Tuhuteru Nivaan, Goldy Valendria Rijoly, Marvelous Marvel Ririmasse, Olyvia