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All Journal Jurnal Matematika: MANTIK Information System for Educators and Professionals : Journal of Information System Pendas : Jurnah Ilmiah Pendidikan Dasar INFORMATION SYSTEM FOR EDUCATORS AND PROFESSIONALS : Journal of Information System
Sri Harini
UIN Maulana Malik Ibrahim Malang
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering Mathematics Other

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Identification COVID-19 Cases in Indonesia with The Double Exponential Smoothing Method Sri Harini
Jurnal Matematika MANTIK Vol. 6 No. 1 (2020): Mathematics and Applied Mathematics
Publisher : Mathematics Department, Faculty of Science and Technology, UIN Sunan Ampel Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (370.476 KB) | DOI: 10.15642/mantik.2020.6.1.66-75

Abstract

The time-series approach is a method used to analyze a series of data in a time sequence to estimate the value of a series in the future. This article will identification the COVID-19 case model in Indonesia using the Double Exponential Smoothing Method. The Double Exponential Smoothing method is one method that can be used to optimize the estimation of the ARIMA model with smoothing parameters α. The data used is sourced from the National Disaster Management Agency which was released starting March 2, 2020. Based on the results of PACF, ACF, and estimated parameters of the ARIMA model in the Covid-19 case in Indonesia following the ARIMA model (0,1,1).
Komparasi Algoritma Naïve Bayes dan k-Nearest Neighbor Pada Klasifikasi Kontribusi Tokoh Politik Moh Ainur Rohman; Sri Harini
INFORMATION SYSTEM FOR EDUCATORS AND PROFESSIONALS : Journal of Information System Vol 7 No 1 (2022): INFORMATION SYSTEM FOR EDUCATORS AND PROFESSIONALS (Desember 2022)
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat Universitas Bina Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (421.192 KB) | DOI: 10.51211/isbi.v7i1.1857

Abstract

Dalam berita politik, banyak sekali informasi tokoh-tokoh politik dalam mendongkrak elektabilitasnya. Berbagai kontribusi mereka lakukan seperti bidang pendidikan, infrastruktur, UMKM, kesehatan, teknologi, dan pelayanan publik. Namun, untuk mengetahui berbagai kontribusi apa saja yang dilakukan mereka, masyarakat masih sulit menilai. Untuk mengatasi masalah tersebut, dibutuhkan sistem yang dapat mengkategorikan kontribusi-kontribusi para tokoh politik. Pada penelitian ini menggunakan dua algoritma untuk mengkomparasi algoritma mana yang terbaik untuk membangun sistem. Penelitian dilakukan menggunakan berbagai variasi jumlah dataset, dan tiga kali pengujian, untuk KNN dilakukan dengan 4 nilai k yaitu k=7, k=9, k=11, dan k=13. Hasilnya, algoritma KNN dengan k=7 yang terbaik dengan nilai precision sebesar 71.5%, nilai recall sebesar 22%, dan nilai f-measure sebesar 19.2%. Abstract: In political news, there is a lot of information about political figures in boosting their electability. They made various contributions such as education, infrastructure, MSMEs, health, technology, and public services. Therefore, it is necessary to classify news into several, in order for the public to know how big the contribution category of political figures is. To overcome this problem, a system is needed that can categorize the contributions of political figures. In this study, two algorithms are used to compare which algorithm is the best to build the system. The study was conducted using various variations in the number of datasets, and three times of testing, for KNN carried out with 4 values of k, namely k=7, k=9, k=11. As a result, the KNN algorithm with k=7 is the best with a precision value of 71.5%, the recall value is 22%, and the f-measure value is 19.2%.
Komparasi Algoritma Naïve Bayes dan k-Nearest Neighbor Pada Klasifikasi Kontribusi Tokoh Politik Moh Ainur Rohman; Sri Harini
INFORMATION SYSTEM FOR EDUCATORS AND PROFESSIONALS : Journal of Information System Vol 7 No 1 (2022): INFORMATION SYSTEM FOR EDUCATORS AND PROFESSIONALS (Desember 2022)
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat Universitas Bina Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51211/isbi.v7i1.1857

Abstract

Dalam berita politik, banyak sekali informasi tokoh-tokoh politik dalam mendongkrak elektabilitasnya. Berbagai kontribusi mereka lakukan seperti bidang pendidikan, infrastruktur, UMKM, kesehatan, teknologi, dan pelayanan publik. Namun, untuk mengetahui berbagai kontribusi apa saja yang dilakukan mereka, masyarakat masih sulit menilai. Untuk mengatasi masalah tersebut, dibutuhkan sistem yang dapat mengkategorikan kontribusi-kontribusi para tokoh politik. Pada penelitian ini menggunakan dua algoritma untuk mengkomparasi algoritma mana yang terbaik untuk membangun sistem. Penelitian dilakukan menggunakan berbagai variasi jumlah dataset, dan tiga kali pengujian, untuk KNN dilakukan dengan 4 nilai k yaitu k=7, k=9, k=11, dan k=13. Hasilnya, algoritma KNN dengan k=7 yang terbaik dengan nilai precision sebesar 71.5%, nilai recall sebesar 22%, dan nilai f-measure sebesar 19.2%. Abstract: In political news, there is a lot of information about political figures in boosting their electability. They made various contributions such as education, infrastructure, MSMEs, health, technology, and public services. Therefore, it is necessary to classify news into several, in order for the public to know how big the contribution category of political figures is. To overcome this problem, a system is needed that can categorize the contributions of political figures. In this study, two algorithms are used to compare which algorithm is the best to build the system. The study was conducted using various variations in the number of datasets, and three times of testing, for KNN carried out with 4 values of k, namely k=7, k=9, k=11. As a result, the KNN algorithm with k=7 is the best with a precision value of 71.5%, the recall value is 22%, and the f-measure value is 19.2%.
PENGARUH PENDIDIKAN , MOTIVASI, DAN LINGKUNGAN KELUARGA TERHADAP MINAT BERWIRAUSAHA PESERTA DIDIK JURUSAN KULINER (TATA BOGA) DI SMK MUHAMMADIYAH 3 SINGOSARI Nur Azizah; Sri Murni Indriani; Nurwarda Irmadani; Sri Harini
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 8 No. 1 (2023): Volume 08, Nomor 01, Juni 2023
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v8i1.9800

Abstract

The large number of unemployed is due to the fact that the number of Indonesian people is not proportional to the supply of jobs. Here SMK is expected to be able to answer all these challenges by fostering students' interest in entrepreneurship. One of them is in the culinary department (catering) with an analysis of several factors, it is expected to be able to answer all these challenges. This type of research uses logistic regression model test, model goodness test, model significance test, wald parameter test and determination. Based on the results of an analysis of the implementation of entrepreneurship education at SMK Muhammadiyah 3 Singosari using discovery learning and project based learning models. The research model that is suitable for use is using the logit regression equation. The results of the Wald test show that there is only 1 variable that has a significant effect on the interest in entrepreneurship of students majoring in culinary (cooking) at SMK Muhammadiyah 3 Singosari, namely X2 = motivation
Co-Authors Moh Ainur Rohman Nur Azizah Nurwarda Irmadani Sri Murni Indriani