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Peningkatan Performa Analisis Sentimen Ulasan Pelanggan terhadap Layanan Pengiriman Menggunakan Model Naïve Bayes yang Dioptimalkan dengan PSO Yuda Septiawan; Aglasia, Adimas; Muktiawan, Danang Ade
ROUTERS: Jurnal Sistem dan Teknologi Informasi Vol. 3 No. 1, Februari 2025
Publisher : Program Studi Teknologi Rekayasa Internet, Politeknik Negeri Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25181/rt.v3i1.4001

Abstract

This research is motivated by the rapid growth of the delivery service industry and the importance of customer feedback in competition, especially for ID Express which has a mobile application. The main issue raised is how to analyse the sentiment of customer reviews on the ID Express app on the Google Play Store to improve service quality. User reviews, although rich in information, have not been optimally utilised, making it difficult for companies to understand user perceptions. In this study, we develop a new method to analyse the sentiment of ID Express app user reviews. This method integrates Naïve Bayes algorithm with Particle Swarm Optimisation (PSO)-based feature selection optimisation technique to produce more accurate analysis. The method used includes collecting user review data from the Google Play Store (2020-2023), preprocessing the data, implementing the Naïve Bayes algorithm, and applying PSO for feature selection. Model performance was tested with accuracy and F-measure metrics using 90:10 and 80:20 data sharing ratios. The results showed that the Naïve Bayes algorithm with PSO produced 52% accuracy at 90:10 ratio and 63% at 80:20 ratio, with F-measure values of 43% and 55% respectively. In conclusion, the use of PSO as feature selection improves the accuracy and F-measure of sentiment analysis using Naïve Bayes, especially at a data sharing ratio of 80:20.
PENGENALAN SAINS DATA UNTUK MENINGKATKAN LITERASI DATA DAN KESIAPAN KARIER DIGITAL SISWA SEKOLAH MENENGAH ATAS Karnila, Sri; Kurniawan, Hendra; Irianto, Suhendro Yusuf; Muktiawan, Danang Ade; Septiawan, Yuda; Safitri, Egi; Nurjoko, Nurjoko
JMM (Jurnal Masyarakat Mandiri) Vol 9, No 4 (2025): Agustus
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jmm.v9i4.31940

Abstract

Abstrak: Pengenalan sains data di tingkat sekolah menengah memiliki peran penting dalam membekali siswa menghadapi era digital yang kian berkembang. Kegiatan pengabdian ini dirancang untuk menumbuhkan pemahaman siswa terhadap konsep dasar sains data sekaligus mendorong kesiapan mereka dalam meniti karier di bidang digital. Pelatihan dilangsungkan secara tatap muka di Institut Informatika dan Bisnis Darmajaya dan melibatkan 26 siswa dari empat sekolah di Bandar Lampung. Materi pelatihan meliputi pengantar teori sains data, praktik pengolahan dan visualisasi data serta pengantar bahasa pemrograman Python, hingga pengenalan awal pembelajaran mesin. Sebagai bentuk evaluasi, peserta mengikuti pre-test dan post-test dengan menjawab soal pilihan ganda sebanyak 25 soal. Hasil penilaian menunjukkan bahwa mayoritas siswa mengalami peningkatan kemampuan setelah pelatihan yang diberikan. Persentase peningkatan pengetahuan diperoleh melalui analisis hasil melalui pre-test dan post-test. Peningkatan diperoleh, dimana 18 dari 26 siswa menjawab benar soal atau persentase sebesar 69,23%, meningkat 30,73% dari nilai sebelumnya sebesar 38,5%. Hal ini mencerminkan respon yang sangat positif terhadap isi materi dan fasilitas pendukung yang tersedia. Secara keseluruhan, kegiatan ini memberikan pengalaman belajar yang membekas dan bermanfaat, serta dapat dijadikan model untuk pelatihan serupa di masa mendatang.Abstract: The introduction of data science at the high school level has an important role in equipping students to face the growing digital era. This service activity is designed to foster students' understanding of the basic concepts of data science while encouraging their readiness to pursue careers in the digital field. The training was held face-to-face at Darmajaya Informatics and Business Institute and involved 26 students from four schools in Bandar Lampung. The training materials included an introduction to data science theory, data processing and visualization practices and an introduction to the Python programming language, to an early introduction to machine learning. As a form of evaluation, participants took a pre-test and post-test by answering 25 multiple choice questions. The assessment results showed that the majority of students experienced an increase in ability after the training provided. The percentage of knowledge improvement was obtained through analysis of results through pre-test and post-test. An increase was obtained, where 18 out of 26 students answered the questions correctly or a percentage of 69.23%, an increase of 30.73% from the previous value of 38.5%. This reflects a very positive response to the material content and supporting facilities available. Overall, this activity provided a memorable and useful learning experience, and can be used as a model for similar training in the future.
PENGENALAN WAJAH PELAKU KRIMINAL BERBASIS SKETSA DENGAN METODE SEGMENTASI DAN CONTENT BASED IMAGE RETRIEVAL Aglasia, Adimas; Ramaputra, Muhammad Galih; Muktiawan, Danang Ade; Septiawan, Yuda
Jurnal Informatika dan Teknik Elektro Terapan Vol. 13 No. 3S1 (2025)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v13i3S1.8091

Abstract

Penelitian ini mengusulkan sistem pengenalan wajah pelaku kriminal berbasis sketsa yang menggabungkan segmentasi citra dan Content-Based Image Retrieval (CBIR). Alur kerja dimulai dari pra-proses (penyetaraan resolusi 1800×2400, grayscaling) dan ekstraksi koefisien DC pada blok 8×8 untuk menonjolkan energi citra, dilanjutkan segmentasi Multi-Otsu Thresholding guna menghasilkan representasi vektor tiga wilayah sebagai data training basis data wajah. Tahap penelusuran menggunakan CBIR dengan ukuran kemiripan Euclidean Distance antara sketsa kueri dan fitur citra tersegmentasi pada basis data. Evaluasi dilakukan pada kumpulan data berukuran 1.080 citra yang merepresentasikan ±50 identitas (≈20 citra/identitas) dengan skenario kueri berulang; metrik yang dilaporkan meliputi presisi dan waktu proses. Hasil menunjukkan presisi rata-rata 82% dengan waktu proses rata-rata 11,51 detik per kueri, serta variasi presisi 60%–100% pada berbagai identitas. Integrasi segmentasi Multi-Otsu pada tahap indeksasi terbukti membantu memisahkan objek–latar dan menstabilkan pencocokan berbasis sketsa. Temuan ini menegaskan bahwa kombinasi ekstraksi DC + segmentasi berbasis ambang multi-kelas + CBIR efektif untuk skenario sketch-to-photo forensik, dengan potensi penguatan di pekerjaan lanjut melalui modifikasi segmentasi dan skema pembelajaran metrik
Design of A Laboratory Assistant Presence System Using Rfid Sensor and Web Based Esp8266 Microcontroller Juniasyah, Deki; Sudibyo, Novi Herawadi; Muktiawan, Danang Ade
Prosiding International conference on Information Technology and Business (ICITB) 2023: INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND BUSINESS (ICITB) 9
Publisher : Proceeding International Conference on Information Technology and Business

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

A computer laboratory is a facility that provides space and hardware (computers, printers, monitors and other equipment) as well as software for teaching, researc and development purposes in the field of information and computer technology. The computer laboratory has assistants whose job is to assist lecturers in implementing practical learning. Laboratory assistants accompany lecturers in  practical courses based on a predetermined schedule. Apart from that, there is a picket schedule that must be carried out regularly to prepare replacement assistants if an assistant is unable to attend. After completing the practical lecture, the laboratory assistant writes the summary results on a sheet of paper. This causes a lack of efficiency in monitoring picket schedules and assistance carried out by laboratory assistants. There are several innovations carried out, such as research conducted by [1] regarding the use of radio frequency identification (RFID) technology for employee attendance systems. Researchers use RFID as a sensor to perform employee attendance, nodemcu esp8266 as a microcontroller and the data obtained is displayed on the web. Based on the background of existing problems, in order to improve monitoring of laboratory assistant attendance, the author built a laboratory assistant attendance system with RFID sensors using Web-based ESP8266. From the system that has been created, monitoring of laboratory assistance and picket activities can be monitored by the laboratory coordinator via the website in real time so that it is easier and faster. Apart from that, it becomes easier for laboratory coordinators to discipline assistants who are often late for attendance. Keywords— Presence, RFID, Esp8266, Laboratory, WebÂ