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All Journal Journal of Informatics Management and Information Technology Media Riset Akuntansi Auditing & Informasi JPNM : Jurnal Pustaka Nusantara Multidisiplin
Dwi Asih Haryanti
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Religion Humanities Computer Science & IT Economics, Econometrics & Finance Education Social Sciences

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Perbandingan Metode Simple Additive Weighting (SAW) Dan Weighted Product (WP) Dalam Pemilihan Aplikasi Belanja Sayur Online Nisrina Nur Puspanegara; Dwi Asih Haryanti
Journal of Informatics Management and Information Technology Vol. 5 No. 2 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jimat.v5i2.471

Abstract

The selection of the right online vegetable shopping application is becoming increasingly important as public awareness of a healthy lifestyle grows. The aim of this study is to develop a Decision Support System (DSS) that can help consumers choose the best online vegetable shopping application. This research contributes to the development of a decision support system for selecting an online vegetable shopping application by comparing the performance of two multi-criteria methods: Simple Additive Weighting (SAW) and Weighted Product (WP). A case study was conducted on three applications HappyFresh, Segari, and Sayurbox considering criteria such as price, product quality, application convenience, and promotions. This research is quantitative in nature, aiming to test predetermined hypotheses. The data sources used in this study include both primary and secondary data. The sampling technique applied was purposive random sampling, involving 100 respondents. The selected respondents were users of HappyFresh, Sayurbox, and Segari applications residing in the Jabodetabek area. The analysis results show that both methods produced consistent rankings, with the HappyFresh application consistently ranking first. This indicates that HappyFresh has the best performance in meeting user expectations based on the established criteria. Based on calculations using the SAW and WP methods, HappyFresh obtained the highest score in both methods, with a score of 1 using SAW and 0.3341 using WP. This suggests that HappyFresh is the most recommended application among HappyFresh, Sayurbox, and Segari..
Faktor yang Mempengaruhi Pengungkapan Emisi Gas Rumah Kaca dari Perspektif Green Accounting pada Perusahaan Industri Dasar dan Kimia di Indonesia Fara Putri Syakira; Dwi Asih Haryanti
JPNM Jurnal Pustaka Nusantara Multidisiplin Vol. 3 No. 3 (2025): October : Jurnal Pustaka Nusantara Multidisiplin
Publisher : SM Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59945/jpnm.v3i3.654

Abstract

Pengungkapan emisi gas rumah kaca (greenhouse gas disclosure) menjadi isu penting di era keberlanjutan, namun di Indonesia penerapannya masih bersifat sukarela sehingga belum merata. Penelitian ini bertujuan menganalisis pengaruh kinerja lingkungan, ukuran perusahaan, profitabilitas, dan leverage terhadap pengungkapan emisi gas rumah kaca pada perusahaan sektor Industri Dasar dan Kimia yang terdaftar di Bursa Efek Indonesia periode 2020–2024. Penelitian menggunakan metode kuantitatif dengan data sekunder berupa laporan tahunan dan keberlanjutan, serta dianalisis menggunakan regresi linier berganda. Hasil penelitian menunjukkan bahwa ukuran perusahaan, kinerja lingkungan dan leverage berpengaruh signifikan terhadap pengungkapan emisi, sedangkan profitabilitas tidak berpengaruh signifikan. Temuan ini mengindikasikan bahwa faktor skala perusahaan, finansial dan lingkungan lebih dominan meskipun skala profit perusahaan tidak berpengaruh dalam mendorong keterbukaan emisi. Kesimpulannya, pengungkapan emisi gas rumah kaca di Indonesia lebih dipengaruhi oleh karakteristik perusahaan dibandingkan faktor keuangan, sehingga diperlukan regulasi yang lebih tegas untuk meningkatkan transparansi lingkungan.
ZAKAT APPLICATION TO ESTIMATE ZAKAT REVENUE BY IMPLEMENTING STOCHASTIC DYNAMICAL SYSTEM METHOD Dwi Asih Haryanti; Feni Andriani; Dewi Putrie Lestari; Beny Susanti; Nurma Nugraha
Media Riset Akuntansi, Auditing & Informasi Vol. 25 No. 2 (2025): September
Publisher : LEMBAGA PENERBIT FAKULTAS EKONOMI DAN BISNIS UNIVERSITAS TRISAKTI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/mraai.v25i2.23068

Abstract

Zakat is an obligation to spend part of the assets we own in accordance with applicable conditions. In the context of a modern state, zakat plays a significant role in ensuring equitable economic distribution for the welfare of society. In Indonesia, the collection, management, and distribution of zakat are facilitated by the National Zakat Agency (Baznas) at the national level, Regional Zakat Agencies (Bazda) at the local level, and non-governmental Zakat Institutions (Laznas/Lazda). One effort to address poverty issues is through the optimization of zakat implementation, including its distribution and management. This study employs the Stochastic Dynamical System method using the Kalman Filter algorithm to estimate zakat revenue, aiming for optimal distribution and management of zakat. The research involves four stages: Data Analysis and Collection, Application Design, Data Analysis and Collection. Zakat revenue prediction using the Kalman Filter algorithm is conducted by calculating the Mean Absolute Error (MAE), achieving an accuracy rate of 89.6%.
Co-Authors Beny Susanti Dewi Putrie Lestari Fara Putri Syakira Feni Andriani Nisrina Nur Puspanegara Nurma Nugraha