Article Per Year (5 Year)
p-Index From 2020 - 2025
0.408
P-Index
This Author published in this journals
All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Statistika Universitas Muhammadiyah Semarang SEEIJ (Social Economics and Ecology International Journal) Engineering, Mathematics and Computer Science Journal (EMACS)
Syarifah Diana Permai
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering Mathematics Social Sciences Other

Published : 4 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search

 1 
UNTUKMU.COM : THE CROWDSOURCING APPLICATION TO LEVERAGING THE USED OF SECONDHAND GOODS Arifin, Yulyani; Permai, Syarifah Diana; Pudjihastuti, Herena; Dwiputra, Kristian; Faisal, Fiandra Rheza; Marcellino, Marcellino
Social Economics and Ecology International Journal Vol 2, No 2 (2018): October
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/seeij.v2i2.5635

Abstract

Information technology can be used in profit or non-profit activities. The concept of crowdsourcing has been widely used in fundraising in the form of money, better known as crowdfunding. In general, most people has secondhand items that are still good to use by others. On the other hand, there are also many people who need those items but cannot afford to buy them. A Website application with the Crowdsourcing concept can be used to bring together donors with recipients of donations in the form of goods.This study conducted data collection to assess the needs of application through questionnaires and analyzed the data using descriptive statistical analysis and Chi Square independence tests, and then developed a website-based application untukmu.com.  This study examined the relationship between age, type of work and intention to donate and the type of goods needed. The Chi Square independence test showed that there is no relationship between age and type of work to the intention to donate.  The descriptive statistics analysis showed that the majority (82%) of the types of goods usually donated by the donors are clothing. The results of the analysis provides input for the development of the application Untukmu.com. In the last stage, the study evaluated the level of satisfaction of the users (i.e. the donors) based on the level of ease of using the application and the time needed to master the application. The analysis showed that there is no relationship between the ease of use of the application and the donors satisfaction,  but there is relationship between time needed to master the application to the user satisfaction. Untukmu.com application has a good usability level since users have no difficulty in using this application and are satisfied with the features available in the application.
PEMODELAN KECEPATAN ANGIN RATA-RATA DI SUMENEP MENGGUNAKAN MIXTURE OF ANFIS Syarifah Diana Permai; Nur Iriawan; - Irhamah
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 1, No 2 (2013): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (713.947 KB) | DOI: 10.26714/jsunimus.1.2.2013.%p

Abstract

Angin memiliki dampak positif dan dampak negatif. Dampak positif dari angin yaitu memperlancar aktivitas pelayaran, membantu irigasi menggunakan kincir angin,pembangkit tenaga listrik dan lain sebagainya. Namun perubahan cuaca yang ekstrim akhir-akhir ini dapat menimbulkan angin kencang serta gelombang laut yang tinggi, sehingga menghambat pelayaran. Salah satu kabupaten yang mengalami dampak negatif ini adalah Sumenep, daerah pesisir di Pulau Madura. Oleh karena itu diperlukan pemodelan kecepatan angin rata-rata di Sumenep yang akurat. Dua metode yang diterapkan adalah Adaptive Neuro Fuzzy Inference System (ANFIS) dan Mixture of ANFIS. Mixture of ANFIS dilakukan melalui beberapa pembagian kelompok, yaitu dua, tiga, empat, lima dan enam kelompok. Evaluasi perbandingan kebaikan model dilakukan berdasarkan kriteria Root Mean Square Error (RMSE). Hasil evaluasi menunjukkan bahwa pemodelan kecepatan angin rata-rata menggunakan mixture of ANFIS dengan enam kelompok memiliki RMSE in sample dan out-sample lebih kecil daripada jumlah kelompok yang lain. Mixture of ANFIS memodelkan kecepatan angin rata-rata di Sumenep lebih baik dari ANFIS karena menghasilkan RMSE in dan out sample yang lebih kecil dari ANFIS. Kata kunci : Kecepatan Angin, ANFIS, Mixture of ANFIS
Sampling methods in handling imbalanced data for Indonesia health insurance dataset Kurniadi, Felix Indra; Purwandari, Kartika; Wulandari, Ajeng; Permai, Syarifah Diana
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i1.pp348-357

Abstract

Health insurance fraud is one of the most frequently occurring fraudulent acts and has become a concern for every insurance. According to data from The Indonesian General Insurance Association or Asosiasi Asuransi Umum Indonesia (AAUI), the private insurance industry suffered losses up to billions rupiah throughout 2018 due to the fraudulent acts commited by the perpetrators. The problem in with the number of frauds in Indonesia is that the current system is highly vulnerable and they is still done manually. The other problem from this detection is imbalance data which often occurs in fraudulent cases. In this research, we used a sampling methods using several machine learning as the baseline. The result shows that the instance hardness thresholding algorithm and extreme gradient boosting gives the best performance for all the case. It shows the method can reduced the bias and can achieve better generalization.
Forecasting Poverty Ratios in Indonesia: A Time Series Modeling Approach Hidayat, Muhammad Fadlan; Henryka, Diva Nabila; Citra, Lovina Anabelle; Permai, Syarifah Diana
Engineering, MAthematics and Computer Science Journal (EMACS) Vol. 6 No. 3 (2024): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v6i3.11968

Abstract

Poverty is one of the main problems still faced by Indonesia today. To help find the right solution, an annual prediction of the poverty rate in Indonesia is needed. This study uses data on the 'Ratio of the Number of Poor People in Indonesia per year from 1998 to 2023' obtained from data.worldbank.org. The prediction methods used in this study include the Naïve Model, Double Moving Average, Double Exponential Smoothing, ARIMA, Time Series Regression, and Neural Network, with a total of 26 models. Of the 26 models, only 19 models passed the model comparison stage. Based on the evaluation results using the RMSE, MAE, MAPE, and MDAE metrics, it was concluded that the NNETAR Neural Network model showed the best performance among the six methods used to predict the poverty ratio in Indonesia.
Co-Authors Ajeng Wulandari Arifin, Yulyani Citra, Lovina Anabelle Dwiputra, Kristian Faisal, Fiandra Rheza Henryka, Diva Nabila Hidayat, Muhammad Fadlan Irhamah - Kurniadi, Felix Indra Marcellino, Marcellino Nur Iriawan Pudjihastuti, Herena Purwandari, Kartika