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All Journal Program Kreativitas Mahasiswa - Kewirausahaan Jurnal Pendidikan (Teori dan Praktik) Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Jurnal Penelitian IPTEKS Jurnal Teknologi Informasi dan Terapan (J-TIT) Jurnal Pengabdian Masyarakat IPTEKS JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) Generation Journal Kontribusia : Research Dissemination for Community Development Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Budapest International Research in Exact Sciences (BirEx Journal) Journal of Community Development Journal of Computer Science and Informatics Engineering JP (Jurnal Pendidikan) : Teori dan Praktik Smart Techno (Smart Technology, Informatic and Technopreneurship) Jurnal Aplikasi Sistem Informasi dan Elektronika JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) Computing and Information System Journal
Suharso, Wiwik
Universitas Muhammadiyah Jember
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Nursing Physics Public Health Social Sciences Transportation Other

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SISTEM PENGONTROLAN PERSEDIAAN OBAT BERBASIS WEB DI APOTEK BUANA FARMA JEMBER Permatasari, Arifani Putri; Suharso, Wiwik; Yanuarsa, Eko Fajar
IPTEQ Vol 1, No 1 (2019): JASIE
Publisher : Universitas Muhammadiyah Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32528/jasie.v1i1.2849

Abstract

Pengontrolan persedian obat merupakan aktifitas penting untuk memastikan bahwa obat selalu tersedia dalam kondisi baik atau tidak kadaluarsa. Obat memiliki rentang waktu tertentu untuk dikonsumsi secara aman. Penggunaan obat diluar batas waktu aktif atau expired akan menimbulkan efek berbahaya seperti keracunan, bahkan kematian. Oleh karena itu, setiap apotek harus memperhatikan batas kadaluarsa obat sehingga diperlukan suatu sistem pengontrolan persediaan obat dalam berbagai jenis dan satuan. Kualitas pengontrolan ini akan mempengaruhi kualitas pelayanan kepada para konsumen, perkembangan dan keberlanjutan usaha. Apotek Buana Farma merupakan apotek yang melayani penjualan obat berdasarkan resep dokter dan pembelian obat-obatan kepada para pemasok dari dalam maupun luar kota. Saat ini pengontrolan data obat masih manual, sehingga dibutuhkan suatu sistem pengontrolan otomatis persediaan obat berbasis web agar informasi persediaan obat dan retur obat expired dapat dilakukan setiap saat. Sistem ini dapat mempermudah dan mempercepat karyawan dalam menangani transaksi penjualan, pembelian, pengontrolan persediaan obat dan retur obat expired secara lebih efektif dan efisien.
APLIKASI PENGOLAHAN DATA BARANG CHECKLIST ORDER DAN STOK BERBASIS CLIENT SERVER BUTIK MARDHANI MUNCAR BANYUWANGI Hasanah, Umi Kulsum; Fibriani, Ike; Suharso, Wiwik
IPTEQ Vol 1, No 1 (2019): JASIE
Publisher : Universitas Muhammadiyah Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32528/jasie.v1i1.2851

Abstract

Butik Madhani Muncar Banyuwangi salah satu bisnis yang bergerak dalam bidang jual beli pakaian yang saat ini masih menggunakan sistem pengolahan data barang secara manual pada proses checklist order dan stok sehingga sering terjadi kesalahan. Maka perlu adanya pengolahan data barang checklist order dan stok menjadi terkomputerisasi.Tugas Akhir ini membahas tentang rancangan sistem checklist order dan stok barang berbasis client server di Butik Madhani Muncar Banyuwangi. Rancangan sistem ini akan membantu dalam proses checklist order dan stok barang serta memudahkan dalam pembuatan laporan lebih cepat sesuai pengguna sistem.
Sentiment Analysis of Gojek Application User Reviews Using the Long Short-Term Memory (LSTM) Algorithm Firdaussani, Ahmad; Oktavianto, Hardian; Suharso, Wiwik
Smart Techno (Smart Technology, Informatics and Technopreneurship) Vol. 8 No. 1 (2026)
Publisher : Primakara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59356/smart-techno.v8i1.167

Abstract

This study was conducted to perform sentiment analysis by identifying patterns or trends in user reviews of the Gojek application using the Long Short-Term Memory (LSTM) algorithm, which was implemented in the form of a simple web-based application or dashboard. In today’s digital era, technological advancements have significantly influenced various aspects of life, particularly the mobile-based transportation service industry. One of the most widely used online transportation services in Indonesia is Gojek. It is essential for Gojek to listen to customer reviews; therefore, sentiment analysis is required to identify patterns or trends within user feedback so the application can better respond to user needs. This research utilizes the Long Short-Term Memory (LSTM) algorithm, a variant of the Recurrent Neural Network (RNN) that incorporates a cell state and gating mechanisms (input, forget, and output gates) to regulate the flow of information. This structure enables LSTM to retain relevant information while discarding irrelevant data, allowing it to capture both short-term and long-term patterns in text reviews. The model was used to analyze sentiment within a dataset collected from 2021 to 2024. The experimental results show that LSTM achieved an optimal accuracy of 78% using a 70:30 dataset split, providing balanced performance across both majority and minority classes, with a significant improvement in the f1-score for each class (0: 0.73; 1: 0.75; 2: 0.85) after applying the SMOTE technique to address class imbalance. Without SMOTE, the highest accuracy reached 83% with the same split (70:30); however, the neutral class could not be detected (f1-score = 0). With SMOTE, although accuracy slightly decreased, the overall performance became more balanced as the neutral class could be properly recognized.
Topic Analysis in Political Speech Video Transcripts Using the Latent Dirichlet Allocation (LDA) Method Dhea Intan Septiara; Deni Arifianto; Wiwik Suharso
JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) Vol. 11 No. 1 (2026): JUSTINDO
Publisher : Universitas Muhammadiyah Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32528/justindo.v11i1.4044

Abstract

Political speeches are an important medium for conveying a country’s leader’s vision, mission, and policy directions to the public. This study aims to identify and analyze the main topics in the video transcripts of President Joko Widodo’s political speeches during the 2014–2024 period using the Latent Dirichlet Allocation (LDA) method. The data consist of 185 press conference speech videos obtained from the Indonesian Cabinet Secretariat’s YouTube channel and converted into text using speech-to-text technology. The dataset is divided into 81 videos from the 2014–2023 period as training data and 104 videos from 2024 as testing data. The analysis process includes text preprocessing, rule-based automatic labeling, LDA model training, and evaluation using coherence score and perplexity. The results show that in the training data, the topics of Infrastructure and Economy are the dominant topics, reflecting the government’s focus on physical development and economic growth. In contrast, in the 2024 testing data, Healthcare emerges as the most dominant topic, followed by the topics of Infrastructure, Economy, Education, and Technology. The Infrastructure topic consistently achieves the highest coherence score of 0.85, indicating strong semantic consistency among its constituent terms. This study contributes to understanding the temporal dynamics of political communication and demonstrates the effectiveness of LDA in analyzing political speech data derived from video transcripts.
Sentiment Classification of Aci Application Reviews Using N-Gram Features And Support Vector Machine (SVM) Algorithm Ageng Wijaya Kusuma; Moh. Dasuki; Wiwik Suharso
JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) Vol. 11 No. 1 (2026): JUSTINDO
Publisher : Universitas Muhammadiyah Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32528/justindo.v11i1.5020

Abstract

The transformation of information technology has created significant opportunities for the application of Natural Language Processing (NLP) in text-based sentiment analysis, particularly in exploring user opinions toward application-based services. This study aims to analyze the sentiment of user reviews of the ACI (Aku Cinta Indonesia) online motorcycle taxi application available on the Google Play Store by applying the N-gram method and the Support Vector Machine (SVM) algorithm. A total of 1,419 reviews were collected, and after data preprocessing and lexicon-based sentiment labeling, 239 final samples were obtained and categorized into positive and negative sentiments. Feature extraction was performed using combinations of unigram, unigram + bigram, and unigram + trigram, with Term Frequency–Inverse Document Frequency (TF-IDF) weighting. Furthermore, the classification process was carried out using a linear kernel Support Vector Machine with an 80:20 split between training and testing data. The experimental results show that the unigram+ bigram model achieved the highest accuracy of 96%, followed by unigram + trigram at 94% and unigram at 90%, with all precision, recall, and F1-score values across the three models exceeding 88%. These findings indicate that the unigram + bigram combination represents word context more effectively than unigram while remaining more efficient than unigram + trigram, thereby improving the sentiment classification accuracy of the SVM model without significantly increasing computational complexity.
Website-Based STEM Learning Using Encyclopedias for Students with Special Needs Ilham Saifudin; Wiwik Suharso; Syahrul Mubaroq
JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) Vol. 11 No. 1 (2026): JUSTINDO
Publisher : Universitas Muhammadiyah Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32528/justindo.v11i1.5029

Abstract

In the world of education, we continue to create and innovate to improve the learning process and achieve desired learning outcomes. One of them is using digital-based learning (Digital Learning) which can be accessed with information technology. This research aims to determine the response to implementing a video blog-based learning system with a STEM (Science, Technology, Engineering, and Mathematics) approach. Apart from that, students will be given assignments using the Encyclopedia Website tool which contains formulas and logical flows related to Algorithms and Complexity courses. This will produce meaningful, quality learning that can be used by the wider community, especially to make it easier for students with special needs to learn to compile a simple algorithm. The method applied in implementing a website for students with special needs is a usability test with Nielsen' Attributes of Usability (NAU). Researchers carry out website evaluations with the aim of measuring and knowing the level of success of the website, how easy it is for users to understand. The research results showed that (1) the usability test with Nielsen' Attributes of Usability (NAU) can be used to measure the quality of website usability; (2) testing success rate of 100% because there were no failures in testing the search feature. Testing found a test pattern, namely that the more search keywords there are, the greater the number of document links produced, and the time required, however, it can significantly increase the highest similarity value of 0.21; (3) the respondents' conclusions show that the learnability, memorability, efficiency, errors attributes have an average helpful conclusion of 11, while the Satisfaction attribute has a very helpful average conclusion of 7.
Inovasi Pengembangan Web Sekolah Dan Media Pembelajaran Interaktif Dalam Kurikulum Merdeka SD Muhammadiyah Kaliwates Jember Wiwik Suharso; Trias Setyowati; Deni Arifianto; Wahju Dyah Laksmi Wardhani
Journal of Community Development Vol. 6 No. 2 (2025): Desember
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/comdev.v6i2.1476

Abstract

Revolusi Industri 4.0 mempengaruhi kebijakan pembelajaran pada satuan pendidikan dasar. Pendidik merancang pembelajaran interaktif agar dapat menghasilkan peserta didik yang berprestasi. Pemerintah menerapkan Kurikulum Merdeka 2022 untuk menguatkan karakter dan kompetensi peserta didik. Penerapan Kurikulum Merdeka menuntut pendidik memiliki kompetensi teknologi dan kurikulum. Kompetensi teknologi berfokus pada kemampuan TIK untuk menciptakan pembelajaran interaktif. Kompetensi kurikulum berfokus pada pengembangan capaian pembelajaran sesuai dengan tujuan pembelajaran dalam suatu mata pelajaran, dikenal sebagai Alur Tujuan Pembelajaran (ATP). Wawancara bersama mitra SD Muhammadiyah Kaliwates Jember menemukan permasalahan prioritas. Diantaranya adalah sebagian besar Guru kesulitan dalam menyusun dokumen ATP sesuai Kurikulum Merdeka, Tenaga Kependidikan (Tendik) tidak optimal memberikan dukungan teknologi, dan tidak tersedianya web sekolah sebagai media informasi dan promosi. Oleh karena itu, kegiatan pengabdian ini bertujuan mengembangkan web sekolah dan dokumen ATP untuk mendukung pembelajaran interaktif dan operasional sekolah. Tim Pelaksana telah melaksanakan sosialisasi program, pengembangan web sekolah, penyusunan dokumen ATP terdiri dari IPAS (IPA dan IPS), Matematika dan Bahasa Inggris, pendampingan pengelolaan web sekolah dan implementasi dokumen ATP dalam pembelajaran, pemberian LCD Proyektor. Hasil kegiatan ini berupa web sekolah dan dokumen ATP yang mengintegrasikan profile sekolah, penerimaan peserta didik baru, ensiklopedia, dan pembelajaran berbasis dokumen ATP. Tim pelaksana sebagai pendamping, sedangkan Guru dan Tendik sebagai peserta. Metode pelatihan, pendampingan dan penugasan digunakan sebagai pendekatan yang efektif. Kegiatan ini berhasil memenuhi tujuan dan luaran yang diharapkan, dan peningkatan kualitas pembelajaran dan promosi sekolah
SENTIMENT ANALYSIS OF COMMENTS ON THE TRAGEDY OF JULIANA MARINS' FALL ON MOUNT RINJANI ON APPLICATION X USING THE MULTINOMIAL NAÏVE BAYES METHOD ika putri maulida; Wiwik Suharso; Ginanjar Abdurramanc
Computing and Information System Journal Vol. 2 No. 1 (2026): Inovasi Teknologi Cerdas Berbasis AI, IoT, dan Data Mining di Era Digital
Publisher : IndoCompt Publisher

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

Abstract

This study aims to analyze the sentiment of user comments on the X (Twitter) platform regarding the tragic fall of Brazilian hiker Juliana Marins on Mount Rinjani. A total of 1006 comments were collected through a crawling process from June 21, 2025, to July 11, 2025. The research stages include data labeling, text preprocessing (cleaning, case folding, tokenizing, stopword removal, and stemming), N-Gram formation, and feature weighting using TF-IDF. The Multinomial Naïve Bayes algorithm was employed for sentiment classification into three categories: positive, negative, and neutral. Data imbalance was addressed using the Random Oversampling (ROS) technique. Model performance was evaluated using a confusion matrix with accuracy, precision, recall, and F1-Score metrics. The results show that the model achieved an accuracy of 85%, with precision, recall, and F1-Score values indicating effective sentiment classification. Neutral sentiment was found to be the most dominant category among user comments. These findings offer a comprehensive overview of public perception regarding the incident and can serve as a useful reference for decision-making and communication strategies related to similar issues
Comparative Analysis of TF-IDF, TF-IDF+WordNet, and Sentence-BERT for News Document Retrieval Using Cosine Similarity Galib Haftha Zuhayir; Wiwik Suharso; Nanda Kurnia Wardati
Journal of Computer Science and Informatics Engineering Vol 5 No 3 (2026): July
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v5i3.1835

Abstract

The rapid growth of digital news volume has produced information overload, while exact keyword-matching retrieval remains vulnerable to synonymy and polysemy, causing relevant documents to be missed. Prior studies generally compare only two document representation methods on small-scale datasets, leaving a gap in controlled evaluations that jointly compare statistical, lexical-hybrid, and neural approaches on a large-scale news domain. This study compares three document representation methods, namely Term Frequency-Inverse Document Frequency (TF-IDF), TF-IDF with WordNet-based query expansion, and Sentence-BERT (all-MiniLM-L6-v2), for news document retrieval using Cosine Similarity on the BBC News Dataset (14,305 documents with a hierarchical Ground Truth of 5 Topics and 51 Subtopics). Ten queries were evaluated using Precision@K, Recall@K, F1-Score@K (K=5, 10, 20), and execution time. The results show that Sentence-BERT consistently outperforms the other methods with a Precision@5 of 0.84, compared to TF-IDF (0.56) and TF-IDF+WordNet (0.52), while TF-IDF remains the fastest at online query time (23.86 ms per query). WordNet expansion actually reduces precision and increases execution time without a proportional accuracy gain. These findings confirm that transformer-based semantic representations are superior for news domains with high lexical variation, while TF-IDF remains relevant for computationally constrained real-time systems
Co-Authors Afandi, Abidah Wafiyah Ramadhaniah Afinda Arum Melathi Ageng Wijaya Kusuma Ahmad Fauzan Arifianto, Deni A`yun, Qurrota Bagus Setya Rintyarna Dhea Intan Septiara Elfien Herrianto Firdaussani, Ahmad Galib Haftha Zuhayir Ginanjar Abdurramanc Gufron Fauzi, Gufron Hasanah, Umi Kulsum Hengky Susanto, Hengky Herrianto, Elfien ika putri maulida Ike Fibriani Komarayanti, Sawitri LUSIANA, DEWI Melathi, Afinda Arum Mochamad Alfan Moh. Dasuki Mufarida, Nely Ana Nanda Kurnia Wardati Oktavianto, Hardian Permataning Tyas, Salsabila Mazya Permatasari, Arifani Putri Rahman, Miftahur Rivansyah, Muhammad Saifudin, Ilham Sawitri Komarayanti Shofiyah, Rohimatush Syahrul Mubaroq Trias Setyowati Wahju Dyah Laksmi Wardhani Yanuarsa, Eko Fajar