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Komparasi Algoritma SVM dan Random Forest Dalam Sentimen Analisis Review Shopee di Google Play Store Dengan Anova
Eko Susanto
; Sharipuddin Sharipuddin
; Benni Purnama
Prosiding Seminar Nasional Ilmu Teknik
Vol 2
, No 2
(2026)
The rapid growth of e-commerce in Indonesia, particularly the Shopee platform, has generated a large volume of user reviews on the Google Play Store, which can be analyzed to understand consumer sentiment. This study aims to compare the performance of the Support Vector Machine (SVM) and Random Forest (RF) algorithms in binary sentiment classification (positive and negative) on Shopee reviews, as well as to statistically test the significance of their differences using One-Way ANOVA. A total of...
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Analisis Sentimen Publik Terhadap Kebijakan Efisiensi Anggaran Menggunakan Naive Bayes, dan SVM
Elin Tamaya
; Sharipuddin Sharipuddin
; Nurhadi Nurhadi
Prosiding Seminar Nasional Ilmu Teknik
Vol 2
, No 2
(2025)
Budget efficiency is an important issue in state financial management because it is directly related to government spending priorities and their impact on public service programs. Discussions about budget efficiency policies are widespread on social media platform X, generating diverse public responses, thus necessitating an automated approach to understand public opinion trends more quickly and objectively. This research aims to analyze the sentiment of Indonesian people toward budget efficienc...
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Pengembangan Sistem Repositori Karya Ilmiah Berbasis Web di Fakultas Hukum Universitas Jambi
Muhammad Iqram Hidayatullah
; Sharipuddin Sharipuddin
; Fachruddin Fachruddin
Prosiding Seminar Nasional Ilmu Teknik
Vol 2
, No 2
(2025)
The management of scientific works at the Faculty of Law, Universitas Jambi, is still carried out manually through physical archives and simple digital storage without an integrated information system. This condition causes limited access, slow information retrieval, and a high risk of document loss and damage. This study aims to develop a web-based scientific repository system to improve the efficiency, accessibility, and security of managing academic works. The system was developed using the W...
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Penerapan Algoritma K-Means Untuk Klasterisasi Balita Rentan Stunting dan Wasting Berdasarkan Indikator Antropometri
Rizky Khairun’nisa
; Benni Purnama
; Sharipuddin Sharipuddin
Prosiding Seminar Nasional Ilmu Teknik
Vol 2
, No 2
(2025)
Stunting and wasting are nutritional problems in toddlers that remain a double burden of malnutrition in Indonesia and have an impact on the quality of health and future human resource development. Monitoring the nutritional status of toddlers is generally carried out using anthropometric indicators, but the use of this data is still limited to descriptive analysis. This study aims to apply the K-Means algorithm in clustering infants vulnerable to stunting and wasting based on anthropometric ind...
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