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All Journal Jurnal Informatika Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Prosiding KOMMIT Jupiter Jurnal Media Infotama PROSIDING CSGTEIS 2013 JSI: Jurnal Sistem Informasi (E-Journal) JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Ilmiah Kursor JUITA : Jurnal Informatika Jurnal Informatika dan Teknik Elektro Terapan JPSriwijaya JIEET (Journal of Information Engineering and Educational Technology) JITK (Jurnal Ilmu Pengetahuan dan Komputer) SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JURNAL INSTEK (Informatika Sains dan Teknologi) Martabe : Jurnal Pengabdian Kepada Masyarakat Jurnal ULTIMATICS IJID (International Journal on Informatics for Development) Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Jurnal Informatika Global Antivirus : Jurnal Ilmiah Teknik Informatika bit-Tech Jurnal Abdimas Mandiri Indonesian Journal of Electrical Engineering and Computer Science Reswara: Jurnal Pengabdian Kepada Masyarakat BERNAS: Jurnal Pengabdian Kepada Masyarakat TIN: TERAPAN INFORMATIKA NUSANTARA Journal of Computer Networks, Architecture and High Performance Computing Idealis : Indonesia Journal Information System Jurnal Generic ABSYARA: Jurnal Pengabdian Pada Masyarakat Jurnal Pengembangan Sistem Informasi dan Informatika Lumbung Inovasi: Jurnal Pengabdian Kepada Masyarakat Teknik: Jurnal Ilmu Teknik dan Informatika Algoritme Jurnal Mahasiswa Teknik Informatika Jurnal Teknologi Sistem Informasi Bakti Budaya: Jurnal Pengabdian kepada Masyarakat Jurnal INFOTEL Jurnal Software Engineering and Computational Intelligence Jurnal Teknik Informatika dan Teknologi Informasi Jurnal Publikasi Teknik Informatika
Shinta Puspasari
Universitas Indo Global Mandiri
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TECHNOFAC: APLIKASI ANDROID PENCARIAN FASILITAS KAMPUS BERBASIS SPEECH-TO-TEXT DAN NATURAL LANGUAGE PROCESSING (STUDI KASUS: UNIVERSITAS INDO GLOBAL MANDIRI) Hermaliah, Siti Ayu; Puspasari, Shinta; Permatasari, Indah
Jurnal INSTEK (Informatika Sains dan Teknologi) Vol 10 No 2 (2025): OCTOBER
Publisher : Department of Informatics Engineering, Faculty of Science and Technology, Universitas Islam Negeri Alauddin, Makassar, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/instek.v10i2.60822

Abstract

Aplikasi Technofac dikembangkan untuk memudahkan pencarian fasilitas kampus Universitas Indo Global Mandiri (IGM) dengan integrasi Speech-to-Text dan Natural Language Processing (NLP) melalui metode Hybrid Keyword-Based. Pipeline sistem meliputi Automatic Speech Recognition, preprocessing (normalization, Punctuation Removal, Tokenization, Synonym Mapping, dan Abbreviation Expansion), intent detection berbasis keyword matching, dan Named Entity Recognition (pattern matching, POS tagging, dictionary, serta fuzzy matching). Evaluasi kinerja NLP menunjukkan metode Hybrid Keyword-Based mencapai precision 0.9346, recall 0.9263, dan F1-Score 0.9297 (kategori very good), sedangkan metode Substring Matching mencapai precision 0.7879, recall 0.7512, dan F1-Score 0.7655 (kategori OK). Pengujian blackbox terhadap 13 fitur menunjukkan seluruh fungsi berjalan sesuai spesifikasi. Evaluasi usability menggunakan System Usability Scale pada 20 responden (n=20) menghasilkan skor 82.87 dengan Grade A (Acceptable) dan confidence interval 95% pada rentang 80.8–85.2. Meskipun sistem menunjukkan performa baik, terdapat 16 kasus False Negative akibat query ambigu dan 14 kasus False Positive akibat misclassification entitas. Penelitian ini menunjukkan potensi rule-based NLP untuk aplikasi pencarian fasilitas kampus, namun masih memerlukan dialog management system (follow-up question) dan hierarchical entity recognition untuk menurunkan kesalahan FP/FN.
Analisis Sentimen Masyarakat Terhadap Objek Wisata Di Kabupaten Lahat Menggunakan Algoritma Support Vector Machine Nadia Damayanti; Shinta Puspasari; Nazori Suhandi
Teknik: Jurnal Ilmu Teknik dan Informatika Vol. 6 No. 1 (2026): Mei : Teknik: Jurnal Ilmu Teknik dan Informatika
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi - Studi Ekonomi Modern

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/teknik.v6i1.1226

Abstract

Nature tourism is one of the sectors that plays an important role in supporting the development of regional tourism, including in Lahat Regency, which has significant waterfall tourism potential. Currently, many visitors share their reviews and experiences through digital platforms such as Google Maps. This review can be used as a source of information to understand the public's evaluation of the quality of tourist attractions. This study aims to examine public perception of tourist attractions in Lahat Regency using the Support Vector Machine (SVM) method. Research data were collected through scraping from Google Maps, totaling 500 reviews from five tourist attractions, namely Curup Maung, Curup Buluh, Senyawe Waterfall, Panjang Waterfall, and Green Canyon. The research stages include data preprocessing, consisting of cleaning, case folding, normalization, tokenization, stopword removal, and stemming. After that, feature extraction was carried out using the TF-IDF method and the classification process using the SVM algorithm. Based on the research results, the Support Vector Machine (SVM) method is able to perform sentiment classification quite well, although the accuracy level varies for each tourist attraction. Curup Maung and Panjang Waterfall achieved the highest accuracy level of 90%. Nevertheless, most visitor reviews were dominated by negative sentiments. This indicates that there are still several aspects that need to be improved, particularly related to tourist facilities and services. This research is expected to serve as a consideration for tourism managers and local governments in efforts to improve management quality as well as the development of tourism in Lahat Regency.
Assessing an Innovative Virtual Museum Application using Technology Acceptance Model Shinta Puspasari; Ermatita; Zulkardi
IJID (International Journal on Informatics for Development) Vol. 11 No. 1 (2022): IJID June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri (UIN) Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2022.3758

Abstract

This study discusses the assessment of a virtual museum application development based on machine learning models for Palembang culture education through the Sultan Mahmud Badaruddin II museum cultural heritage by using the Technology Acceptance Model approach. The application was tested to measure the user acceptance of the application and pre-test and post-test to measure the effect size of the application as a learning media. A total of N=32 student participants were involved in testing the Sultan Mahmud Badaruddin II innovative virtual museum application for museum visitors was dominated by students who came to the museum to learn the culture and history of Palembang. Hypothesis testing results show that the perceived usefulness and perceived ease of use variables do not affect the attitude toward the use of the innovative virtual museum application. The attitude toward the use of the variable affects the behavioural intention to use, which directly also has a moderate effect on the actual use of the application where the dependent variables have the value of R2 > 0.5. The developed app is recommended as alternative learning media during a pandemic where the app testing participants express interest in using the app to enhance the Palembang culture learning experience.
Pendampingan Digitalisasi Koleksi Museum Sultan Mahmud Badaruddin II Palembang Puspasari, Shinta; Gustriansyah, Rendra; Sanmorino, Ahmad; Rachmansyah, Rachmansyah; Khadafi, M. Khrisna Brilian; Putra, Aditya
Lumbung Inovasi: Jurnal Pengabdian kepada Masyarakat Vol. 11 No. 3 (2026): September
Publisher : Lembaga Penelitian dan Pemberdayaan Masyarakat (LITPAM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/linov.v11i3.5349

Abstract

Digitalisasi koleksi museum merupakan upaya strategis dalam mendukung pelestarian warisan budaya benda melalui pemanfaatan teknologi informasi. Museum Sultan Mahmud Badaruddin II (SMB II) Palembang sebagai institusi pelestarian budaya memiliki berbagai koleksi benda bersejarah yang merepresentasikan identitas budaya masyarakat, khususnya Palembang. Namun, pengelolaan inventaris masih menghadapi kendala berupa keterbatasan dokumentasi digital, belum tersusunnya data koleksi secara sistematis, serta terbatasnya kemampuan pengelola dalam pengarsipan digital. Kegiatan pengabdian ini bertujuan untuk mendukung revitalisasi pengelolaan koleksi melalui pendampingan digitalisasi inventaris berbasis teknologi digital. Metode pelaksanaan meliputi observasi, identifikasi koleksi, dokumentasi visual, pencatatan metadata, serta pengelolaan data koleksi menggunakan Microsoft Excel. Selain itu, dilakukan pendampingan teknis kepada staf museum dalam digitalisasi visual koleksi museum. Hasil kegiatan pendampingan menunjukkan bahwa sebanyak 100 benda budaya koleksi museum SMB II berhasil didokumentasikan secara sistematis. Kegiatan ini sebagai langkah awal dalam degitalisasi koleksi museum SMBII dan diharapkan dapat meningkatkan efisiensi pengelolaan koleksi, mendukung pelestarian budaya benda, serta diharapkan dapat memperluas akses informasi budaya bagi pengelola museum secara berkelanjutan. Assistance in the Digitalization of the Collections of the Sultan Mahmud Badaruddin II Museum in Palembang Abstract Digitizing museum collections is a strategic effort to support the preservation of tangible cultural heritage through the use of information technology. The Sultan Mahmud Badaruddin II Museum (SMB II) Palembang, as a cultural preservation institution, has a diverse collection of historical objects that represent the cultural identity of the community, especially Palembang. However, inventory management still faces obstacles such as limited digital documentation, the lack of systematic collection data, and limited management skills in digital archiving. This community service activity aims to support the revitalization of collection management through assistance with digital technology-based inventory digitization. Implementation methods include observation, collection identification, visual documentation, metadata recording, and collection data management using Microsoft Excel. In addition, technical assistance was provided to museum staff in the visual digitization of museum collections. The results of the assistance activity indicate that 100 cultural objects from the SMB II museum collection have been successfully documented systematically. This activity is the first step in digitizing the SMBII museum collection and is expected to improve the efficiency of collection management, support the preservation of tangible cultural objects, and is expected to expand access to cultural information for museum managers in a sustainable manner.
Augmented Reality Sebagai Media Edukasi Interaktif Untuk Mengenali Jenis Ikan Konsumsi Pada Siswa Sekolah Dasar Cindy Asyra Fratari; Shinta Puspasari; Lastri Widya Astuti
Jurnal Publikasi Teknik Informatika Vol. 5 No. 1 (2026): Januari: Jurnal Publikasi Teknik Informatika
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupti.v5i1.6579

Abstract

This study aims to develop an interactive learning media using Augmented Reality (AR) to support the introduction of edible fish species for fourth-grade students at SD MIS Adabiyah 02 Palembang. The media is designed to provide an engaging and enjoyable learning experience through the use of marker-based AR technology that can be operated on Android Devices. Fish objects are visualized in three-dimensional (3D) form, allowing students to view and interact with them directly through the camera.The development method used in this study is the Rational Unified Proxess (RUP), which consist of four phases: inception, elaboration, construction, and transition. The design process involves 3D object modelling using Blender 3D and AR integration through Unity and Vuforia SDK. The results of this study are expected to help students better understand the material related to various type of edible fish. The usability using the System Usability Scale (SUS) resulted in an average score of 90 from 31 respondetns, indicating that the appliacation has an excellent level of usability and feasibility.
Aplikasi Prediksi Gaji Bulanan Berbasis Web Menggunakan Ektrapolasi Linear Shinta Puspasari; Dwi Asa Verano; Husnawati
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 18 No 1 (2026): Jurnal Penelitian Ilmu dan Teknologi Komputer (JUPITER)
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.18373671

Abstract

Informasi mengenai rata-rata gaji bersih bulanan di setiap provinsi di Indonesia masih sulit diakses secara cepat dan mudah dipahami oleh masyarakat, sehingga menyulitkan individu dalam memperkirakan kondisi ekonomi di daerah tertentu. Kondisi ini menjadikan pengembangan sistem prediksi gaji sebagai topik penelitian yang penting untuk mendukung pengambilan keputusan, baik bagi pencari kerja maupun pihak terkait lainnya. Penelitian ini bertujuan untuk merancang dan mengimplementasikan aplikasi prediksi gaji sebagai sistem prediksi rata-rata gaji bersih bulanan di Indonesia. Metode yang digunakan adalah ekstrapolasi linier dengan pendekatan metode Newton dan spline kubik Hermite, yang diimplementasikan dalam bahasa pemrograman PHP. Data historis gaji digunakan sebagai dasar perhitungan untuk menghasilkan nilai prediksi pada periode berikutnya. Hasil pengujian menunjukkan bahwa sistem mampu menghasilkan nilai prediksi yang mendekati data aktual dengan nilai gaji rata – rata Rp. 2.631.791,88, nilai Mean Squared Error (MSE) sebesar 1.489 dan Root Mean Squared Error (RMSE) sebesar 38,59. Hasil ini menunjukkan bahwa metode yang diterapkan cukup efektif dan aplikasi prediksi gaji dapat dimanfaatkan sebagai alat bantu estimasi gaji yang informatif dan mudah digunakan.
Peningkatan Daya Saing UMKM Kuliner Kelurahan Talang Jambe Melalui Otomasi Pelayanan Pelanggan Berbasis IT Ahmad Sanmorino; Rendra Gustriansyah; Shinta Puspasari
BERNAS: Jurnal Pengabdian Kepada Masyarakat Vol. 7 No. 3 (2026)
Publisher : Universitas Majalengka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31949/jb.v7i3.18451

Abstract

UMKM kuliner di Kelurahan Talang Jambe memiliki peran penting dalam perekonomian lokal, namun masih menghadapi kendala dalam pelayanan pelanggan akibat penggunaan metode komunikasi yang konvensional. Permasalahan yang ditemukan meliputi rendahnya pemahaman teknologi digital, lambatnya respons terhadap pelanggan, belum optimalnya pengelolaan katalog produk, serta minimnya pemanfaatan sistem otomasi layanan pelanggan. Kegiatan Pengabdian kepada Masyarakat (PkM) ini bertujuan meningkatkan daya saing UMKM melalui penerapan otomasi pelayanan pelanggan berbasis teknologi informasi. Metode yang digunakan meliputi survei kebutuhan, sosialisasi, pelatihan penggunaan WhatsApp Business dan fitur otomasi, serta evaluasi sebelum dan sesudah kegiatan. Hasil kegiatan menunjukkan peningkatan yang signifikan pada berbagai indikator, yaitu pemahaman teknologi digital dari 42% menjadi 88%, penggunaan WhatsApp Business dari 35% menjadi 90%, kecepatan respons pelanggan dari 48% menjadi 85%, dan kemampuan pengelolaan katalog produk dari 30% menjadi 87%. Hasil tersebut menunjukkan bahwa otomasi pelayanan pelanggan mampu meningkatkan kualitas layanan dan daya saing UMKM kuliner di Kelurahan Talang Jambe.
Prediksi Saham IHSG Menggunakan Extreme Gradient Boosting, Support Vector Machine, K-Nearest Neighbors Dan Autoregressive Integrated Moving Average Renaldy Pratama; Shinta Puspasari; Muhammad Haviz Irfani
Jurnal Software Engineering and Computational Intelligence Vol 4 No 01 (2026)
Publisher : Informatics Engineering, Faculty of Computer Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jseci.v4i01.7141

Abstract

The Jakarta Composite Index (JCI) is a key indicator in assessing the performance of the Indonesian capital market. Dynamic stock price fluctuations require accurate prediction methods to assist investors in decision making. This study aims to compare the performance of four prediction algorithms, namely Support Vector Machine (SVM), K-Nearest Neighbors (K-NN), Extreme Gradient Boosting (XGBoost), and Autoregressive Integrated Moving Average (ARIMA) in predicting the closing price of JCI. The data used is the JCI daily historical data for the 2019-2024 period obtained from Yahoo Finance. The research process includes data pre-processing, prediction model implementation, model training and testing, and performance evaluation using Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) metrics on a 0-1 normalization scale.The results showed that the ARIMA model provided the most stable results with an RMSE value of 0.4038 and MAE of 0.3945, followed by K-NN and SVM. Although SVM has the lowest MAE value, its RMSE is still higher than ARIMA and K-NN. SVM showed the lowest performance in this experiment. Based on the evaluation results, ARIMA is recommended as the best algorithm in predicting JCI closing price based on historical data. The Jakarta Composite Index (JCI) is a key indicator in assessing the performance of the Indonesian capital market. Dynamic stock price fluctuations require accurate prediction methods to assist investors in decision making. This study aims to compare the performance of four prediction algorithms, namely Support Vector Machine (SVM), K-Nearest Neighbors (K-NN), Extreme Gradient Boosting (XGBoost), and Autoregressive Integrated Moving Average (ARIMA) in predicting the closing price of JCI. The data used is the JCI daily historical data for the 2019-2024 period obtained from Yahoo Finance. The research process includes data pre-processing, prediction model implementation, model training and testing, and performance evaluation using Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) metrics on a 0-1 normalization scale.The results showed that the ARIMA model provided the most stable results with an RMSE value of 0.4038 and MAE of 0.3945, followed by K-NN and SVM. Although SVM has the lowest MAE value, its RMSE is still higher than ARIMA and K-NN. SVM showed the lowest performance in this experiment. Based on the evaluation results, ARIMA is recommended as the best algorithm in predicting JCI closing price based on historical data.
Co-Authors Abdul Rahman Adesta , Erry Juilan T. Aditya Putra, Aditya Ahmad Ghaly Ahmad Sanmorino Alie, Marzuki Aminuyati Antony, Fery Aprianoputri, Aurahaqqi Ari wiyanto Ariati, Nining Asfinoza Asfinoza Bobby Halim Cindy Asyra Fratari Damayanti, Arda Darussalam, M. Miftah Dedy Hermanto Desfourtheen, Rinda Dewi Eka Sari DEWI SARTIKA Dhamayanti Dhamayanti Dhamayanti Dhamayanti Dhamayanti, Dhamayanti Dien Novita Dwi Asa Verano Dwi Asa Verano Ermatita - Farras Ananta Fery Antony gasim, Gasim Hartini Hartini Hastha Sunardi Haversyalapa, Ditho Herdiansyah, M.I. Hermaliah, Siti Ayu Husnawati Indah Permatasari Juhaini Alie Kanaka, Nayaka Al Syahreal Khadafi, M. Khrisna Brilian Lastri Widya Astuti Lastri Widya Astuti Lastri Widya Astuti Lastri Widya Astuti M. Rahmat Widyanto M. Rahmat Widyanto Marnisah, Luis Mgs. Deny Ramadhan Muhammad Farhan Muhammad Haviz Irfani Mustafa Ramadhan Nadia Damayanti Nadia Damayanti Nazori Suhandi Noviani Kurnia Ambarwati Octaria, Putri Oktalia, Marheska Pameswary, Nathasya Purbasari, Nadira Putri Putri Shabira Pratiwi Rachmansyah Rachmansyah Rachmansyah Rachmansyah Ramadhan, Mustafa Renaldy Pratama Rendra Gustriansyah Reza Iman Pribadi Risky Pranata Rudi Heriansyah, Rudi Saputra, Dimas Riski Sartika, Dewi Sunardi, Hastha Suryati Suryati Vega, Marshanda Amalia Verano, Dwi Asa Wiyanto, Ari Yusuf Akhlun Nazzar Zulkardi