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All Journal LEX CRIMEN ZOO INDONESIA Technomedia Journal ULIN: Jurnal Hutan Tropis Zoo Indonesia Dynamic Management Journal 12 Waiheru Jurnal Ilmiah MEA (Manajemen, Ekonomi, dan Akuntansi) Jurnal Indonesia Sosial Teknologi Prosiding Seminar Informasi Kesehatan Nasional Journal of Geographical Sciences and Education Jurnal Teknik Indonesia INSTALL: Information System and Technology Journal
Muhamad Kurniawan, Muhamad
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Religion Agriculture, Biological Sciences & Forestry Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Nursing Public Health Social Sciences Transportation Other

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Effect of Mileage Variation on Learning Outcomes of SMKN Students in Tangerang City, Banten Province Kurniawan, Muhamad; Ira Megawati Gunawan Putri
12 Waiheru Vol. 9 No. 2 (2023): 12 Waiheru
Publisher : Balai Diklat Keagamaan Ambon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47655/12waiheru.v9i2.171

Abstract

This study aims to describe the spatial patterns of variations in students' distance to school and to understand the effect of students' distance to school on student learning outcomes using quantitative descriptive research methods with a spatial approach. Based on the results of the study on variations in the distance traveled by students who fall within the range of 1,000 – 5,000 meters, only 57.82% of the total 11th-grade students are sampled. These results show that 42.18% of students cover a distance of more than 5,000 meters to reach schools from the data processing of the distance to school correlation test with the results of learning vocational subjects in class 11 odd semesters, it was found that the results of the linearity test had a Sig value. 0.04 or Sig. < 0.05, the relationship between the variables in this analysis is negative, the closer the distance students travel, the learning outcomes will have a high value.
PERENCANAAN BANGUNAN GEDUNG SUPERMARKET KABUPATEN BOYOLALI Kurniawan, Muhamad; Sasi, Windu; Hartopo, Hartopo; Apriyanto, Totok
Jurnal Teknik Indonesia Vol 4, No 2 (2023): JTI (Jurnal Teknik Indonesia)
Publisher : Universitas Darul Ulum Islamic Centre Sudirman GUPPI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61689/jti.v4i2.488

Abstract

Boyolali is a developing district in Central Java Province. Therefore, many people from outside the area come to Boyolali to do business or develop their businesses. In order for the activities carried out to run well, adequate and supportive facilities are needed, so the construction of a Supermarket Building is planned. The structural planning for the Boyolali district supermarket building is in Siswodipuran, Boyolali District, Boyolali Regency, Central Java. This supermarket building was built to improve MSMEs for people in Boyolali.This building planning was carried out using primary data, such as soil survey data, and supplemented with other secondary data. This structural planning analysis is assisted by the SAP2000 software application for structural modeling and calculating internal forces. The analysis carried out includes: calculation of the roof structure, beams, columns and foundations.From the analysis results, it was obtained that the roof rafter beam was IWF 300.150.6,5.9, CNP purlins 150.50.20.2.3, steel columns IWF 300.150.6,9.9. Block sizes vary from 40x80 cm, 35x70, 30x60, 25x50, blocks measuring 25x40 and 20x30. Column sizes 80x80 cm, 70x70 cm, 60x60 cm. The foundation uses bored piles F2: 1.20x2.20x1.10 m with 2 bored piles measuring 60x60 cm, depth 5.5 m, F4: 2.20x2.20x1.40 m with 4 bored piles measuring 60x60 cm, depth 5.5 m, F6: 2.20x3.20x1.55 m with 6 bored piles measuring 60x60 cm, depth 5.5 m, F8: 2.20x4.20x2.00 m with 8 bored piles measuring 60x60 cm, depth 5.5 m. From the results, each structural element of the building can be categorized as safe.
Application of Data Mining for Prediction of High School Student Graduation Rates Kurniawan, Muhamad; Isa, Sani Muhamad
Jurnal Indonesia Sosial Teknologi Vol. 5 No. 11 (2024): Jurnal Indonesia Sosial Teknologi
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jist.v5i11.7047

Abstract

The implementation of Data Mining in the education sector aims to develop methods that are able to discover valuable knowledge from data generated in the educational environment. This can be used to increase learning efficiency by paying more attention to students who are predicted to have low grades. However, in its application, each algorithm shows different performance depending on the attributes and dataset used. In this study, a dataset of semester grades and final school exam scores was used. Some of the prediction techniques used are decision trees, support vector machines, and neural networks. Of the four scenarios for the science major at SMAN 2 and SMAN 3 Pangkalpinang with 3 different models, the Mean Squared Error value shows that the test results are in accordance with the testing dataset and can be used as predictions of students' final grades, namely the decision tree model and support vector machine. For the Social Sciences major at SMAN 2 and SMAN 3 Pangkalpinang with 3 different models, the Mean Squared Error value shows that the test results are in accordance with the testing dataset and can be used as a prediction of students' final grades, namely the support vector machine model.
Co-Authors Abdul Latif Agus Priyono Kartono Diah Mukminatul Hasimi Frayoga, Yunus Arif Hartopo, Hartopo Ira Megawati Gunawan Putri Julistia, Ira Lindawati, Ratna Lopa, Nazar Nauval Barra Marni Marni, Marni Maulina, Riska Mirza Dikari Kusrini Mulyati Mulyati Nasril Sany Perwithasari, Resy Ramadhan, Aditya Rawana, Rawana Sabrila, Trifebi Shina Sabrina, Nabila Khalilah Sani Muhamad Isa, Sani Muhamad Sasi, Windu Totok Apriyanto, Totok Witriyani, Witriyani Yuslinawari, Yuslinawari