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All Journal Sistemasi: Jurnal Sistem Informasi Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Generic Jurnal Abdimas Maduma
Gumay, Naretha Kawadha Pasemah
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Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering

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Perancangan Sistem Informasi Monitoring Dosen Pembimbing Mahasiswa Kerja Praktek (KP) Willy, Willy; Firnando, Ricy; Gumay, Naretha Kawadha Pasemah; Marjusalinah, Anna Dwi; Ariani, Ardina; Febriady, Mukhlis
Generic Vol 16 No 1 (2024): Vol 16, No 1 (2024)
Publisher : Fakultas Ilmu Komputer, Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18495/generic.v16i1.179

Abstract

Ilmu Pengetahuan dan Teknologi saat ini begitu pesat dalam perkembangannya, tidak terkecuali dalam bidang dunia digital, dalam hal ini ketua jurusan dan Koordinator program studi bahkan wakil dekan bidang akademik sangat kesulitan untuk memonitoring mahasiswa yang melakukan bimbingan akademik dan konsultasi kerja praktek. Bahkan sangat banyak kasus tidak mengetahui perkembangan dan keaktifan mahasiswa terhadap dosen pembimbing dan juga kurangnya informasi berapa sering mahasiswa tersebut melakukan mimbingan terhadap dosen pembimbing akademik sampai mahasiswa tersebut melakukan kerja praktek, sehingga dibutuhkan sebuah sistem informasi untuk memonitoring antara dosen pembimbing akademik terhadap mahasiswa dengan menggunakan metode agile, sehingga informasi tersebut dapat menjadi acuan oleh para pimpinan. Hasil penelitian akan menjadi acuan untuk membangun sistem informasi yang diharapkan dapat membantu proses monitoring antara dosen pembimbing dan mahasiswa.
A Comparative Study of Deep Learning’s Performance Methods for News Article using Word Representations Azhar, Iman Saladin B.; Sari, Winda Kurnia; Gumay, Naretha Kawadha Pasemah
SISTEMASI Vol 14, No 2 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i2.5090

Abstract

In natural language processing (NLP), text classification is a crucial task that involves analyzing textual data, which often has high dimensionality. A good word representation is essential to address this challenge, and the word representation using GloVe is one of the popular methods that provides pre-trained word representations in high-dimensional vectors. This research evaluates the effectiveness of three deep learning techniques Convolutional Neural Network (CNN), Deep Neural Network (DNN), and Long Short-Term Memory (LSTM) for online news classification using 300-dimensional GloVe word representations. The CNN model utilizes convolutional and pooling layers to extract local features, the DNN relies on dense layers to learn abstract representations, while the LSTM excels at capturing long-term dependencies between words. The results show that the LSTM model achieved the best accuracy at 93.45%, followed by CNN at 91.24%, and DNN at 90.67%. The superiority of LSTM is attributed to its ability to effectively capture temporal relationships and context, while CNN offers efficiency with faster training times. Although DNN produced solid performance, it is less optimal in understanding word sequences. These findings indicate that LSTM outperforms the other models in online news text classification tasks.
Analysis of Service Quality Factors in the Grab Application on User Satisfaction using the Service Quality (SERVQUAL) Method Yanto, Dimas Hadi; Indah, Dwi Rosa; Novianti, Hardini; Sanjaya, M. Rudi; Gumay, Naretha Kawadha Pasemah
SISTEMASI Vol 14, No 2 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i2.5043

Abstract

The development of information technology in the digital era has had a significant impact, including on online transportation services such as Grab. However, Grab users frequently complain about slow response times from customer support when handling complaints, as well as recurring issues with the balance feature, as reflected in complaints like "saldo" (balance) and "please fix this". This study aims to identify the factors influencing the service quality of the Grab application on user satisfaction in Palembang using the Service Quality (SERVQUAL) approach. A quantitative research method was employed, involving 106 respondents who are Grab users. Data were collected through questionnaires and analyzed using Partial Least Squares-Structural Equation Modeling (PLS-SEM) with SmartPLS 4 to measure the impact of five SERVQUAL dimensions: responsiveness, reliability, tangibles, empathy, and assurance. The findings indicate that these five dimensions collectively have a highly significant effect on service quality (F = 41.92). Individually, the tangibles dimension has the most dominant impact (t = 4.473, p < 0.05), followed by empathy, which also shows a significant influence (t = 2.248, p < 0.05). However, reliability, responsiveness, and assurance do not exhibit significant effects. These results highlight the need for service quality improvements, particularly in the dimensions that were found to be less significant, to enhance the Grab application’s user experience in Palembang.
Pelatihan Pemahaman Literasi Digital Bersama Apparat Desa Sungai Pinang Berbasis Teknologi Informasi Ibrahim, Ali; Ermatita, Ermatita; Oklilas, Ahmad Fali; Farissi, Al; Ruskan, Endang Lestari; Sari, Purwita; Gumay, Naretha Kawadha Pasemah
JURNAL ABDIMAS MADUMA Vol. 4 No. 1 (2025): April, 2025
Publisher : English Lecturers and Teachers Association (ELTA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52622/jam.v4i1.413

Abstract

Pelatihan pemahaman literasi digital berbasis teknologi informasi di Desa Sungai Pinang, Kecamatan Rambutan, Kabupaten Banyuasin, Sumatera Selatan, merupakan langkah strategis untuk meningkatkan kualitas sumber daya manusia di era digital. Kegiatan ini berfokus pada pemberdayaan masyarakat umum dan aparat desa melalui pemanfaatan teknologi informasi sebagai alat untuk mendukung transparansi administrasi, efisiensi pelayanan publik, dan penguatan ekonomi lokal. Pelatihan ini dirancang untuk meningkatkan pengetahuan dan keterampilan dasar dalam menggunakan perangkat teknologi, aplikasi digital, serta memanfaatkan media daring untuk aktivitas sehari-hari dan pengelolaan administrasi desa. Pendekatan kegiatan dilakukan dengan partisipatif, interaktif, dan berkelanjutan. Aparat desa dibekali kemampuan khusus dalam pengelolaan data, administrasi digital, serta strategi komunikasi yang efektif melalui platform digital. Khalayak yang ikut dalam kegiatan berjumlah 25 orang. Kegiatan pengabdian Masyarakat dilaksanakan di balai desa. Hasil dari pelatihan ini diharapkan dapat menciptakan masyarakat yang lebih melek teknologi dan meningkatkan kapasitas aparat desa dalam memberikan layanan yang lebih cepat, tepat, dan transparan. Selain itu, kegiatan ini mendukung transformasi digital di tingkat pedesaan sebagai bagian dari agenda pembangunan berkelanjutan Kata Kunci : literasi digital; teknologi informasi; pemberdayaan masyarakat; transformasi digital.
The Effect of Chatbot Usage on Customer Satisfaction: A Quantitative Study of Shopee, Tokopedia, and Lazada Using SmartPLS Afrina, Mira; Gumay, Naretha Kawadha Pasemah; Ariani, Ardina; Febriady, Mukhlis
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 14 No. 1 (2025): JANUARY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v14i1.2312

Abstract

With the increasing growth of e-commerce, it is important to identify the features available in e-commerce applications that can provide customer satisfaction. One of the features in e-commerce is the chatbot. Chatbots in e-commerce can provide various services to users, such as assistance in product search, ordering, product information, payment processing, customer support, and more. This research aims to analyze and understand how the response quality of each chatbot in e- commerce platforms such as Shopee, Tokopedia, and Lazada affects e-commerce user satisfaction. This study employs a quantitative methodology, integrating data analysis conducted through the SmartPLS 4.1 software. The research results show that the chatbot in Shopee platform has a impact on customer satisfaction. The same goes for chatbot in Tokopedia platform, but there are two variables that do not have a direct impact, there are information quality and waiting time. Meanwhile, chatbot in Lazada platform does not affect customer satisfaction. The findings of this research should reveal new strategies for leveraging chatbot technology to better satisfy customers in e- commerce environments, as well as lay the groundwork for further research on how artificial intelligence can shape customer experiences in the future.
Co-Authors Ahmad Fali Oklilas Al Farissi Ali Ibrahim Ariani, Ardina Dwi Rosa Indah Endang Lestari Ruskan Ermatita - Febriady, Mukhlis Hardini Novianti Iman Saladin B. Azhar Marjusalinah, Anna Dwi Mira Afrina Purwita Sari, Purwita Ricy Firnando Sanjaya, M. Rudi Willy, Willy Winda Kurnia Sari Yanto, Dimas Hadi