Article Per Year (5 Year)
p-Index From 2020 - 2025
0.61
P-Index
This Author published in this journals
All Journal Jurnal Sains & Teknologi Fakultas Teknik Universitas Darma Persada
Norman, Suzuki Syofian
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mechanical Engineering

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
ANALISIS SENTIMEN TANGGAPAN PELANGGAN INDIHOME DI PLATFORM SOSIAL MEDIA FACEBOOK DAN TWITTER MENGGUNAKAN SUPPORT VECTOR MESIN DAN PENDEKATAN KLASIFIKASI NAÏVE BAYES (STUDI KASUS: PT. TELKOM INDONESIA) Norman, Suzuki Syofian; Kusuma, Dhino Rahmad; Afifa, Linda Nur
Jurnal Sains & Teknologi Fakultas Teknik Universitas Darma Persada Vol. 13 No. 1 (2023): Jurnal Sains & Teknologi
Publisher : Fakultas Teknik Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70746/jstunsada.v13i1.221

Abstract

In the digital era, the internet has become an inseparable part of everyday life, including the ease of finding information and sharing opinions through social media such as Twitter and Facebook. On these two platforms, users can provide reviews about products, including IndiHome services. The large number of reviews on social media reflects the high level of feelings users have for the service. However, currently PT. Telkom Indonesia does not fully know the opinions and reviews of IndiHome customers on social media, both positive and negative. This study aims to improve understanding of the positive and negative opinions of customers towards IndiHome and to compare the effectiveness of the Support Vector Machine and Naive Bayes algorithms in sentiment analysis. Thus, PT. Telkom Indonesia can take the necessary steps to increase public trust in IndiHome and evaluate the performance of the classification results using the Support Vector Machine and Naïve Bayes methods. The data used in this study amounted to 5000 data, but after the data preparation stage, the remaining 2000 data. From the data that has gone through the preparation stage, there are 638 data with positive sentiment and 1341 data with negative sentiment. The test results on the Support Vector Machine model achieve an accuracy of 91%, while the Naive Bayes model achieves an accuracy of 85%.
ANALISIS SENTIMEN TINGKAT KEPUASAN PELANGGAN TERHADAP LAYANAN KURIR J&T EXPRESS MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (SVM) BERDASARKAN ULASAN PENGGUNA DI GOOGLE PLAYSTORE: ANALISIS SENTIMEN TINGKAT KEPUASAN PELANGGAN TERHADAP LAYANAN KURIR J&T EXPRESS MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (SVM) BERDASARKAN ULASAN PENGGUNA DI GOOGLE PLAYSTORE Norman, Suzuki Syofian; Mahendra, Saddam
Jurnal Sains & Teknologi Fakultas Teknik Universitas Darma Persada Vol. 13 No. 2 (2023): Jurnal Sains & Teknologi
Publisher : Fakultas Teknik Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70746/jstunsada.v13i2.450

Abstract

Courier Service Is One Of The Services That Are Widely Used By The Public, Especially In The Current Digital Era. In This Context, Courier Services Allow Shippers To Deliver Goods Or Documents Without The Need To Be Present Directly To The Destination Location. J & T Express, As One Of The Shipping Expedition Service Providers In Indonesia, Is The First Choice For Many People. Although Technology Continues To Evolve And Competition Is Increasingly Fierce, The Quality Of Courier Services Is A Key Factor That Customers Need To Pay Attention To. However, It Should Be Noted That The J&T Express Application In The Google Play Store Received A Low Rating, And This Is The Background Of This Study. the main focus of this study was to identify the level of customer satisfaction with j&t express courier services through reviews available on the google play store. within the framework of this study, sentiment analysis was conducted using the support vector machine algorithm, by applying crisp-dm methodology. the results showed that from the business understanding stage to the modeling stage, the performance of the support vector machine can be considered good. in addition, this study also resulted in an implementation that can be accessed through a website with the address jnt-sentiment.streamlit.app. hopefully, this research can contribute to j & t express in understanding the views of customers and improving the quality of their services
P PENGEMBANGAN TEKNOLOGI INTERNET OF THINGS PENDETEKSI KEBAKARAN UNTUK RUANG SERVER DILENGKAPI PEMANTAUAN REAL-TIME MELALUI CLOSED CIRCUIT TELEVISION (CCTV) DAN NOTIFIKASI WHATSAPP SERTA MONITORING MENGGUNAKAN GRAFANA: PENGEMBANGAN TEKNOLOGI INTERNET OF THINGS PENDETEKSI KEBAKARAN UNTUK RUANG SERVER DILENGKAPI PEMANTAUAN REAL-TIME MELALUI CLOSED CIRCUIT TELEVISION (CCTV) DAN NOTIFIKASI WHATSAPP SERTA MONITORING MENGGUNAKAN GRAFANA Rikhi, Muhammad; Setiyaningsih, Timor; Norman, Suzuki Syofian
Jurnal Sains & Teknologi Fakultas Teknik Universitas Darma Persada Vol. 14 No. 1 (2024): Jurnal Sains & Teknologi
Publisher : Fakultas Teknik Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70746/jstunsada.v14i1.492

Abstract

PENGEMBANGAN TEKNOLOGI INTERNET OF THINGS PENDETEKSI KEBAKARAN UNTUK RUANG SERVER DILENGKAPI PEMANTAUAN REAL-TIME MELALUI CLOSED CIRCUIT TELEVISION (CCTV) DAN NOTIFIKASI WHATSAPP SERTA MONITORING MENGGUNAKAN GRAFANA. Kebakaran merupakan ancaman serius yang dapat menyebabkan kerugian fisik, ekonomi, dan kehilangan nyawa. Seringkali dipicu oleh faktor manusia, alam, atau peralatan seperti kelistrikan dan Gas LPG, kebakaran membutuhkan deteksi dan respons yang cepat. Teknologi Internet of Things (IoT) menyediakan solusi dengan sensor pintar yang memantau lingkungan secara real-time untuk mendeteksi suhu, asap, atau gas berbahaya. Penelitian ini mengembangkan sistem deteksi kebakaran berbasis IoT untuk ruang server yang mengintegrasikan sensor api, sensor asap MQ-2, sensor suhu DHT-11, CCTV untuk pemantauan visual, dan notifikasi melalui WhatsApp. Platform monitoring Grafana digunakan untuk visualisasi data sensor. Studi kasus dilakukan di PT Askara Internal, dengan tujuan meningkatkan keamanan ruang server dan mengurangi risiko kebakaran, serta meningkatkan ketahanan operasional melalui teknologi inovatif dan efektif. Fires are a serious threat that can cause physical, economic, and life losses. Often triggered by human factors, nature, or equipment such as electrical and LPG gas, fires require rapid detection and response. Internet of Things (IoT) technology provides solutions with smart sensors that monitor the environment in real-time to detect temperature, smoke, or hazardous gases. This research develops an IoT-based fire detection system for server rooms that integrates fire sensors, MQ-2 smoke sensors, DHT-11 temperature sensors, CCTV for visual monitoring, and notifications via WhatsApp. The Grafana monitoring platform is used for sensor data visualization. A case study was conducted at PT Askara Internal, aiming to enhance server room security and reduce fire risk, as well as improve operational resilience through innovative and effective technology.
Co-Authors Afifa, Linda Nur Kusuma, Dhino Rahmad Mahendra, Saddam Rikhi, Muhammad Timor Setiyaningsih, Timor