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All Journal BISE: Jurnal Pendidikan Bisnis dan Ekonomi Teknik: Jurnal Ilmu Teknik dan Informatika Jurnal Ilmiah Research Student
Wahyu Nugraha
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Religion Computer Science & IT Economics, Econometrics & Finance Mathematics Medicine & Pharmacology

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ANALISIS BUTIR SOAL PENILAIAN MATA PELAJARAN EKONOMI DALAM KAITANNYA DENGAN ASPEK KOGNITIF TAXONOMY BLOOM Wahyu Nugraha; Harini Harini; Sudarno Sudarno
BISE: Jurnal Pendidikan Bisnis dan Ekonomi Vol 2, No 2 (2016): Jurnal Pendidikan Bisnis dan Ekonomi
Publisher : Department of Economics Education, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/bise.v2i2.16872

Abstract

This research aims to identify the quality of items about the assessment of subjects Economics class XI in SMA Negeri 4 Surakarta in the academic year  2016/2017 in relation to cognitive aspects Taxonomy Bloom. The subjects chosen are Economics subject teachers and students of XI IPS class in SMA Negeri 4 Surakarta academic year 2016/2017, the subject taking technique in this study using the posposive sampling. Meanwhile, the technique used in sampling the data source is by using snowball sampling technique. This research is a descriptive research with qualitative approach. Data collection was obtained by observation method for test development activity data, interview method for test development data and quality of item and documentation for data item quality. The results showed that: (1) a valid question a total of 11 items (36.7%) while invalid 19 items (63.3%). (2) Based on the reliability, including the matter of which the reliability is very low, -0.057. (3) Based on the level of difficulty, including difficult level items totaled 25 questions (83%), moderate level 2 questions (7%), and an easy level 3 questions (10%). (4) Based on the distinguishing features, items that includes not very good 5 questions (16.7%), there is a good 5 questions (16.7%), 10 items are good enough (33.3%), 8 points are good (26, 7%), and splendidly questions are 2 points (6.67%). (5) Based on the effectiveness of the use of distractors, items which serve very good 3 point (10%), serves as good 8 points (26.7%), and 10 items as enough (33.3%), less 5 questions (16.7%), and serves no good / bad 4 items (13.3%). (5) Based on the analysis validity, level of difficulty, distinguishing, and the effectiveness of the use of distractors there are good-quality questions amount to 2 questions (6.7%), unfavorable 6 matter (20%), and not good or bad 22 questions (73.3%). Based on the cognitive aspects of Taxonomy Bloom, the majority of items are dominated by items with category C1 consisting of 13 items (43.3%), category C2 amounted to 11 items (36.7%), category C3 amounted to 3 items (10%) and the items with category C4 amounted to 3 items (10%). Overall matter of assessment of subjectsEconomics class XI SMA Negeri 4 Surakarta Academic year 2016/2017 in relation to the cognitive aspects of Taxonomy Bloom including the problem that is not good.
ETIKA DALAM KEGIATAN KEMASYARAKATAN: DENGAN KEGIATAN BERBAGI NASI Wahyu Nugraha
JURNAL ILMIAH RESEARCH STUDENT Vol. 1 No. 3 (2024): Januari
Publisher : CV. KAMPUS AKADEMIK PUBLISING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61722/jirs.v1i3.779

Abstract

Business ethics in a societal context refers to a company's moral behavior that takes into account its impact on society as a whole. In the era of globalization and increasingly close connectivity, companies have a responsibility not only to achieve economic profits, but also to pay attention to their contribution to social welfare. This abstract discusses the implications and challenges of business ethics in society, highlighting the role of companies as active members in shaping and supporting the sustainability of society. The implications of business ethics in society include the obligation of companies to ensure that their operational activities comply with moral norms and that their contribution to society is more than just creating financial gain. Society-centered business ethics requires companies to pay attention to their impact on the environment, human rights, and social justice. The challenges facing business ethics in society involve frequent conflicts between corporate profits and the general welfare. Economic globalization can create increasing inequality, and companies are faced with pressure to meet shareholder demands while maintaining ethical integrity. Managing this balance requires business policies and practices that focus on transparency, accountability and sustainable development. Thus, this research underlines the need for a paradigm shift in the view of business, where business ethics is not only understood as a moral obligation, but also as a foundation for growth sustainable and inclusive economy in society.
Evaluasi Performa Algoritma Klasifikasi dalam Prediksi Kekambuhan Kanker Tiroid Pasca Terapi RAI: Studi Kasus Dataset RAI Therapy Wahyu Nugraha; Raja Sabaruddin
Teknik: Jurnal Ilmu Teknik dan Informatika Vol. 5 No. 1 (2025): Mei: Teknik: Jurnal Ilmu Teknik dan Informatika
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi - Studi Ekonomi Modern

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/teknik.v5i1.717

Abstract

Thyroid cancer is the most common endocrine malignancy, with a steadily increasing incidence rate. Although the overall survival rate is relatively high, the risk of recurrence after definitive treatment such as Radioactive Iodine (RAI) therapy remains a significant clinical challenge. Predicting recurrence risk is crucial for optimizing monitoring strategies and interventions. With advances in technology, machine learning (ML) approaches are increasingly utilized to support medical predictions, including the recurrence of thyroid cancer. This study aims to evaluate the performance of four classification algorithms—Logistic Regression, XGBClassifier, Random Forest Classifier, and Voting Classifier—in predicting thyroid cancer recurrence using the Thyroid Cancer Recurrence After RAI Therapy dataset, which consists of 383 patient records and 13 key clinical attributes. The evaluation was conducted using accuracy, precision, recall, F1-score, and area under the curve (AUC) metrics. The results show that the XGBClassifier is the best-performing model with an accuracy of 97.4% and an AUC of 0.95, demonstrating superior performance in handling the minority class. This research is expected to contribute to the development of more effective machine learning–based clinical decision support systems for predicting thyroid cancer recurrence after therapy.
Co-Authors Harini Harini Raja Sabaruddin Sudarno Sudarno