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SISTEM EVALUASI MODEL GREEN SUPPLY CHAIN MANAGEMENT UNTUK MENINGKATKAN KINERJA KEUANGAN UMKM TEPUNG TAPIOKA KABUPATEN PATI Puryono, Daniel Alfa; Sudiati, Listiarini Edy
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol 10, No 1 (2019): JURNAL SIMETRIS VOLUME 10 NO 1 TAHUN 2019
Publisher : Fakultas Teknik Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (407.47 KB) | DOI: 10.24176/simet.v10i1.2608

Abstract

Sistem evaluasi yang digunakan untuk mengatasi permasalahan pada studi kasus ini mengunakan model Green Supply Chain Management (GSCM). Model GSCM adalah solusi yang dapat menilai, mengevalusi dan mengembangkan masalah industri, lingkungan sosial dan ekomoni. GSCM digunakan untuk hubungan timbal balik antar praktik rantai pasok yang ramah linkungan. Sedangkan metode Analytical Hierarchy Process (AHP) untuk pengambilan keputusan agar lebih terukur dan konsisten. Selain itu juga mengunakan metode analisis Du pont untuk menilai dan mengevaluasi tingkat kinerja keuangan pada Usaha Mikro Kecil dan Menegah (UMKM). Kombinasi dari metode yang digunakan dapat membantu para pengambil keputusan serta dapat mengevaluasi progam yang komplek menjadi lebih efesien, sehingga akan tercapai pembangunan yang berkesinambungan. Hasil penelitan ini juga dapat memberikan petunjuk dan pedoman bagi para analisis dan pengambil keputusan, serta dapat menjadi masukan yang berdampak pada peningkatan kinerja dan keuangan UMKM tepung tapioka. Studi lapangan, penyebaran kuesioner dan wawancara dilakukan untuk menggambarkan metodologi yang digunakan.
PENERAPAN MODEL INTEGRATIF SCRUM DENGAN UX DESIGN DALAM PENGEMBANGAN WEBSITE E-COMMERCE YANG EFISIEN DAN USER-CENTERED Prastichia, Vistalia Putri; Priyanto, Adhi; Puryono, Daniel Alfa
SOSCIED Vol 8 No 1 (2025): SOSCIED - Juli 2025
Publisher : LPPM Politeknik Saint Paul Sorong

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32531/jsoscied.v8i1.954

Abstract

The rapid development of e-commerce demands a system that is not only functional but also provides an optimal user experience. This research aims to apply an integrative model between SCRUM and UX Design methods in the process of developing EXO Thrifting Pati's e-commerce website. The approach method used in this research is DSRM, which includes the stages of problem identification, model design, implementation, and evaluation. The results of this study show that the integration between SCRUM and UX Design can improve the efficiency of the development process and the quality of user experience. Usability test results produce a very good level of user satisfaction, with an interface that is easy to use, attractive, and according to user needs. This integrative model was effective and can be a reference for the development of other user-oriented digital systems.
Implementasi Algoritma Deep Learning untuk Analisis Sentimen Pengguna Platform Pendidikan Nugroho, Anjis Sapto; Prasetyo, Eko; Priyanto, Adhi; Puryono, Daniel Alfa
SOSCIED Vol 8 No 2 (2025): SOSCIED - November 2025
Publisher : LPPM Politeknik Saint Paul Sorong

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32531/jsoscied.v8i2.999

Abstract

More than 3.5 million Indonesian educators had used the Merdeka Mengajar Platform by 2024. Comparing this figure to the 3.37 million from the previous academic year, there has been an increase of almost 3.85%. However, an investigation is required to determine the reasons why the application's use has not yet achieved the anticipated goal number of users. This study does sentiment analysis on evaluations of the Merdeka Mengajar platform using Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM). The benefits of RNN and LSTM in processing sequential data, especially in text processing for sentiment analysis, led to their selection. The purpose of this study is to solve the difficulties in determining if users' sentiments on the platform are favorable or negative. Important steps in the research technique include preprocessing, data cleaning, and employing FastText embedding to convert text into numerical vectors. Then, using patterns in the text data, RNN and LSTM models are used to forecast sentiment. The study's findings demonstrate that the LSTM model can, with an estimated accuracy of 93.58%, identify long-term associations in sequential data. The RNN model, on the other hand, produces a lesser accuracy of 91.70%. Particularly in text data with intricate temporal circumstances, the LSTM model performs better at accurately classifying sentiment. By better understanding customer opinions and input on the Merdeka Mengajar platform, this study helps platform developers improve the quality of their services.