Article Per Year (5 Year)
p-Index From 2021 - 2026
5.232
P-Index
This Author published in this journals
All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Dinamik Sainteks Interaksi : Jurnal Ilmu Komunikasi Jurnal Simetris Bulletin of Electrical Engineering and Informatics Jurnal Transformatika Jurnal Edukasi dan Penelitian Informatika (JEPIN) Jurnal Informatika Upgris E-Dimas: Jurnal Pengabdian kepada Masyarakat Jurnal Ilmiah KOMPUTASI Journal of Applied Information, Communication and Technology (JAICT) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Sains dan Informatika Jurnal Pengembangan Rekayasa dan Teknologi Jurnal Surya Masyarakat Sarwahita : Jurnal Pengabdian Kepada Masyarakat Jurnal Tekno Kompak Building of Informatics, Technology and Science Journal of Information Systems and Informatics Abdimasku : Jurnal Pengabdian Masyarakat Aiti: Jurnal Teknologi Informasi Jurnal Surya Masyarakat Jurnal Computer Science and Information Technology (CoSciTech) Information Science and Library Jurnal Pengabdian Masyarakat Intimas (Jurnal INTIMAS): Inovasi Teknologi Informasi Dan Komputer Untuk Masyarakat SmartComp Tematik International Journal of Information Technology and Business Systematic Literature Review Journal Jurnal DIMASTIK
Prind Triajeng Pungkasanti, Prind Triajeng
Universitas Semarang
Religion Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Transportation Other

Published : 49 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 49 Documents
Search

 1   2   3   4   5 
A Systematic Review on Data Fusion Techniques for Agri-cultural Yield Prediction: Integrating Satellite Imagery with Climatic Data Khoirudin, Khoirudin; Pungkasanti, Prind Triajeng; Hidayati, Nurtriana
Systematic Literature Review Journal Vol. 1 No. 4 (2025): October: Systematic Literature Review Journal
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/slrj.v1i4.245

Abstract

An answer to the worldwide need for solutions to food security, data fusion technology that combines climate data with satellite imagery greatly improves the accuracy of agricultural yield predictions; this study intends to examine the advancements, methods, and key contributions of this area. By sifting through 62 papers pulled from Scopus, this research employs the SLR methodology. Document type, data source, open access, subject area, and year of publication (2020–2024) are some of the categories filtered through by Boolean keywords in the selection process. To assess patterns in publications, the efficacy of machine learning models, and key contributions, bibliometric analysis was performed. An upward tendency in publication has been identified by the analysis, particularly beyond the year 2023. Integrating geographical and temporal data has been a great success with machine learning models like Random Forest, Random Forest, and Gradient Boosting. Data resolution, integration of data from several sources, and a real-time framework are still missing pieces to the puzzle when it comes to generalizing research outcomes. More complex data fusion approaches, multiregional datasets, and advanced machine learning models to back more accurate agricultural predictions are all things that this study notes as needing additional investigation in the future. To further innovate agricultural yield prediction, multidisciplinary collaboration is also crucial.
Mengatasi Hambatan Literasi Digital: Strategi Pemasaran Digital bagi Pelaku UMKM Desa Truko Agusta Praba Ristadi Pinem; Prind Triajeng Pungkasanti; Gita Aprinta
Jurnal Surya Masyarakat Vol 6, No 2 (2024): Mei 2024
Publisher : Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsm.6.2.2024.251-256

Abstract

The development of information technology that is not accompanied by the acceleration of digital literacy, especially in the MSME sector, can result in failure to compete in an era of high use of digital marketing. This service activity aims to increase understanding and use of digital marketing among MSMEs in Truko Village, Kendal Regency. Through training and mentoring activities using the Participatory Action Research (PAR) method, MSMEs are actively involved in the digital marketing learning process. The results of the situation analysis show that although the majority of MSMEs have basic knowledge about digital marketing, implementation is still limited. Training activities are focused on digitalizing products and promotions, using tools such as photoroom, single landing page, Linktree, and WA Business. Evaluation of the results shows a significant increase in the use of digital marketing tools, reaching an 80% increase in the use of Linktree. This article summarizes the process, results and positive impact of community service activities in improving the skills and business competitiveness of Truko Village MSMEs in the digital era.
Implementasi Metode Elimination Et Choice Transiting Reality (Electre) Dalam Penentuan Provider Internet Annisa Cahya Listya; Diah Ayu Putri Larasati; Prind Triajeng Pungkasanti
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 14, No 4 (2025): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v14i4.7054

Abstract

Perkembangan teknologi informasi di Indonesia saat ini semakin cepat dan telah banyak mengalami perubahan. Internet menjadi salah satu hal penting dalam kemajuan teknologi informasi. Penggunaannya saat ini sangat dibutuhkan untuk menunjang aktivitas dalam kehidupan sehari-hari seperti media penghubung komunikasi, mencari berita terkini, sarana hiburan, serta mengakses sumber informasi dan ilmu pengetahuan yang mudah, cepat, dan akurat sesuai dengan kebutuhan masing-masing. Dengan demikian, faktor penentuan dalam memilih provider internet terbaik sangat dibutuhkan masyarakat saat ini. Penelitian ini bertujuan  mengimplementasikan  metode Elimination Et Choice Transiting Reality (Electre) dalam menentukan provider internet. Adapun pada penelitian ini menggunakan lima kriteria yaitu meliputi harga, kemudahan pemasangan, gangguan jaringan, pelayanan, dan paket layanan yang ditawarkan berbagai provider internet tersebut. Berdasarkan hasil kuesioner dari 110 orang responden bahwa hasil perhitungan menggunakan metode Electre yang mendapat ranking satu adalah  Alternatif A1 dengan nama yaitu Indihome memperoleh  nilai 125,609 sebagai alternatif yang terbaik, ranking dua dengan nama yaitu MNCPlay sebagai Alternatif A2 memperoleh nilai 112,217, dan Biznet sebagai Alternatif A3 memperoleh nilai 60,048.
Mengatasi Hambatan Literasi Digital: Strategi Pemasaran Digital bagi Pelaku UMKM Desa Truko Agusta Praba Ristadi Pinem; Prind Triajeng Pungkasanti; Gita Aprinta
Jurnal Surya Masyarakat Vol 6, No 2 (2024): Mei 2024
Publisher : Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsm.6.2.2024.251-256

Abstract

The development of information technology that is not accompanied by the acceleration of digital literacy, especially in the MSME sector, can result in failure to compete in an era of high use of digital marketing. This service activity aims to increase understanding and use of digital marketing among MSMEs in Truko Village, Kendal Regency. Through training and mentoring activities using the Participatory Action Research (PAR) method, MSMEs are actively involved in the digital marketing learning process. The results of the situation analysis show that although the majority of MSMEs have basic knowledge about digital marketing, implementation is still limited. Training activities are focused on digitalizing products and promotions, using tools such as photoroom, single landing page, Linktree, and WA Business. Evaluation of the results shows a significant increase in the use of digital marketing tools, reaching an 80% increase in the use of Linktree. This article summarizes the process, results and positive impact of community service activities in improving the skills and business competitiveness of Truko Village MSMEs in the digital era.
A Robustness-Oriented Evaluation of LSTM, GRU, and Hybrid LSTM-GRU Models for ANTM.JK Stock Price Forecasting Khoirudin; Prind Triajeng Pungkasanti; Nur Wakhidah; Vinay Rishiwal
Journal of Information System and Informatics Vol 8 No 3 (2026): June
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i3.1660

Abstract

Accurately forecasting stock prices remains challenging because of the nonlinear and volatile nature of financial markets, particularly during periods of heightened uncertainty, such as the COVID-19 pandemic. This study evaluates the robustness of three models, LSTM, GRU, and Hybrid LSTM-GRU, for ANTM.JK stock price forecasting using a volatility-oriented evaluation framework. Historical stock data from September 2005 to May 2022 were transformed into supervised time-series datasets using a 15-lag sliding window. The model performance was evaluated using baseline prediction accuracy, 5-fold chronological cross-validation consistency, and synthetic stress scenarios consisting of controlled price drops, price rises, and high-volatility noise. Evaluation metrics included RMSE, MSE, MAE, R, and R^2. The GRU model delivered the top baseline prediction results, achieving the smallest RMSE of 52.95 and MAE of 28.14. In cross-validation, the LSTM model recorded the lowest average RMSE of 119.41. Meanwhile, the Hybrid LSTM-GRU exhibited the highest prediction consistency and robustness across various synthetic stress scenarios. In contrast to earlier research that mainly focused on prediction precision, this study presents a comprehensive framework for evaluating robustness. This framework combines baseline accuracy, consistency through cross-validation, and an analysis of synthetic stress scenarios. The generated robustness map offers a systematic interpretation of model strengths across diverse evaluation goals, facilitating a more thorough assessment of stock-forecasting models in different market environments.
Python-based stock price prediction using backpropagation neural networks: a case study on ANTM Prind Triajeng Pungkasanti; Febrian Wahyu Christanto; Fadhilatut Tasyriqul Hajjas Sabat; Christine Dewi; Eryan Ahmad Firdaus
Bulletin of Electrical Engineering and Informatics Vol 15, No 1: February 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i1.9760

Abstract

Accurate stock price prediction is critical for informed investment decisions. Today, stock trading has become a popular option as a source of income among people, due to its potential for rapid gains in a short time, but, due to fluctuating stock prices, it can cause great losses in exchange. This study aims to forecast the closing price using the backpropagation neural network algorithm so that it can be used as a decision support for potential investors and traders in this research, the system was built using the Python programming language, and the stock price data used were shares of the company Aneka Tambang Tbk (ANTM). The results of this research are root mean squared error (RMSE) values, additional labels for prediction results, and graphs for comparison of the original data with the predicted data. Based on the testing result, the best value of RMSE is 3.786, the mean absolute percentage error (MAPE) value is 0.001 which indicates that the prediction results are very close to the actual value.
Pemilihan Layanan Dompet Digital Berdasarkan Preferensi Gen Z Menggunakan Integrasi Metode SAW, MOORA, dan ORESTE Raihan Ary Prabowo; Dzanuar Auzi Wildan; Prind Triajeng Pungkasanti
Sainteks Vol. 23 No. 1 (2026): April
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/sainteks.v23i1.29477

Abstract

Penetrasi ekonomi digital di era Revolusi Industri 4.0 telah mengubah perilaku transaksi Generasi Z menjadi sangat bergantung pada dompet digital, namun kompleksitas fitur sering kali menyulitkan pemilihan platform yang ideal. Penelitian ini bertujuan membangun Sistem Pendukung Keputusan (SPK) untuk pemilihan layanan dompet digital yang paling sesuai dengan preferensi pengguna. Kebaruan metodologis dalam penelitian ini terletak pada integrasi tiga metode pengambilan keputusan, yaitu Simple Additive Weighting (SAW), Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA), dan ORESTE, untuk memberikan hasil evaluasi yang lebih objektif dan komprehensif. Data dikumpulkan melalui kuesioner dari 40 responden yang divalidasi dengan tingkat reliabilitas tinggi (Cronbach's Alpha 0,953). Hasil analisis menunjukkan kriteria keamanan menjadi prioritas utama dengan bobot 30%. Implementasi algoritma mengungkap bahwa metode SAW dan MOORA secara konsisten merekomendasikan Dana sebagai platform terbaik karena keunggulannya pada kriteria berbobot besar. Sebaliknya, metode ORESTE menetapkan OVO sebagai prioritas utama karena konsistensi peringkat yang lebih stabil di seluruh parameter. Kontribusi penelitian ini memberikan kerangka kerja analitis bagi akademisi dan praktisi dalam membandingkan efektivitas berbagai metode SPK, serta menjadi panduan strategis bagi industri teknologi finansial dalam memahami prioritas pengguna. Integrasi metode ini terbukti mampu meminimalkan subjektivitas dan memberikan rekomendasi yang lebih berimbang bagi konsumen digital. 
PENERAPAN AI DAN MANAJEMEN REFERENSI DALAM MENINGKATKAN MUTU KARYA TULIS ILMIAH SISWA SMA MASEHI 2 PSAK SEMARANG Prind Triajeng Pungkasanti; Fajriannoor Fanani; Basworo Ardi Pramono; Nurtriana Hidayati
Jurnal DIMASTIK Vol. 4 No. 2 (2026): Juli
Publisher : Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/dimastik.v4i2.15904

Abstract

Siswa SMA Masehi 2 PSAK Semarang masih belum menguasai teknik penulisan karya tulis ilmiah (struktur, sitasi, dan daftar pustaka) serta belum optimalnya pemanfaatan perangkat digital untuk mendukung proses kepenulisan. Kegiatan Pengabdian kepada Masyarakat (PkM) ini bertujuan untuk menguatkan literasi akademik siswa melalui pelatihan penyusunan karya tulis ilmiah yang terintegrasi dengan manajemen referensi serta pemanfaatan tools Artificial Intelligence (AI) secara etis dan efektif. Metode pelaksanaan dirancang dalam format workshop interaktif berbasis praktik langsung. Materi kegiatan mencakup pelatihan penggunaan aplikasi manajemen referensi serta pemanfaatan AI writing assistant untuk penyuntingan, pengembangan gagasan, dan perbaikan kualitas naskah dengan tetap memperhatikan kaidah akademik. Sebagai instrumen keberlanjutan, PkM ini juga menyediakan modul pembelajaran digital bagi siswa. Hasil dan luaran kegiatan menunjukkan adanya peningkatan kompetensi siswa dalam penulisan karya ilmiah. Selain itu, luaran PkM ini telah menghasilkan produk berupa modul pelatihan digital, publikasi media daring, serta video dokumentasi kegiatan. Melalui PkM ini, siswa menjadi lebih adaptif terhadap perkembangan teknologi pendidikan sekaligus memperkuat budaya literasi akademik serta penggunaan AI yang bertanggung jawab di lingkungan sekolah. Kata Kunci: Literasi AI, Literasi Akademik, Karya Tulis Ilmiah, Manajemen Referensi
Klasifikasi Akun Palsu Pada Pengikut Akun Rental Cosplay Averentcos Di Instagram Menggunakan Metode K-Nearest Neighbour (KNN) Hafidz Mufrodi S.Kom. Odi; Nur Wakhidah; Prind Triajeng Pungkasanti
Jurnal Transformatika Vol. 23 No. 2 (2026): January 2026
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v23i2.12287

Abstract

Technological advances have given business people several options to develop their business. One of them is using Instagram social media as a promotional tool. However, using social media as a promotional medium has its own problems. Fake accounts spread on Instagram can reduce the reach of business accounts. Until now, there are more than millions of fake accounts. Instagram continues to increase its efforts to detect and delete these fake accounts. This study was conducted to be able to classify accounts suspected of being fake accounts on the followers of the averentcos account using the k-NN method. The data used were 500 follower accounts with various backgrounds. This study used several variables, namely Profile Photo, Username Length, Number of Name Words, Similarity of Name to Username, Bio Length, External Links, Public Accounts, Number of Posts, Number of Followers, Number of Followed so that accuracy of 86,666% can be achieved.
PERANCANGAN SISTEM PEMILIHAN BUDIDAYA IKAN AIR TAWAR BERBASIS WEB Prind Triajeng Pungkasanti; Saifur Rohman Cholil; B. Very Christioko
Jurnal Pengembangan Rekayasa dan Teknologi Vol. 3 No. 1 (2019): Mei (2019)
Publisher : Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/jprt.v15i1.1485

Abstract

Pertumbuhan perekonomian Indonesia dan potensi budidaya ikan air tawar semakin meningkat, hal ini terjadi  karena kesadaran masyarakat akan pentingnya mengkonsumsi ikan yang terus meningkat serta adanya program Gemar Makan Ikan yang dipopulerkan oleh KKP (Kementerian Kelautan dan Perikanan). Potensi Budidaya air tawar memiliki prospek yang baik kedepannya diantaranya ikan Lele, ikan Gurame, ikan Nila, ikan Mujair dan ikan Patin. Alternatif ikan ini memiliki karakteristik yang berbeda untuk masing-masing jenis pembudidayaannya. Kriteria dipengaruhi pada faktor kesesuaian air yang meliputi: suhu, kecerahan, DO (Disolved Oxygen), keasaman (pH). Namun belum ada alat bantu yang dapat memudahkan petani ikan air tawar dalam melakukan pemilihan ikan air tawar. Maka dibutuhkan sistem pemilihan ikan air tawar untuk memberikan informasi kepada para petani ikan air tawar. Perancangan sistem pemilihan air tawar ini menggunakan tahap pelaksanaan komunikasi, analisis, dan desain. Perancangan desain dilakukan dengan UML (Unified Modeling Language) yang terdiri dari : use case diagram, sequence diagram, activity diagram, class diagram; perancangan interface menggunakan bahasa pemrograman PHP dan perancangan database menggunakan MySQL.
Co-Authors Agusta Praba Ristadi Pinem Aldiansyah Fathul Majid Anggi Farika Sari Annisa Cahya Listya Ardianto, Brian Ardima, Muhammad Basyier Ari Muhamad Imran Aria Hendrawan, Aria Badroe Zaman Basworo Ardi Pramono Bimo Wahyu Syahputro, Bimo Wahyu Syahputro Christine Dewi Diah Ayu Putri Larasati Didin Herlinudinkhaji, Didin Dimas Dwi Budiarjo Dzanuar Auzi Wildan EB, Gita Aprinta Edi Widodo Edi Widodo, Edi Eryan Ahmad Firdaus Fadhilatut Tasyriqul Hajjas Sabat Fajriannoor Fanani Febrian Wahyu Christanto Gita Aprinta Hadi, Soiful Hafidz Mufrodi S.Kom. Odi Hamron Sulistyo Purnomo Handayani, Sri Henny Indriyawati Henny Indriyawati Indah Permatasari Nurma’arif Irfan, Muhammad Nur Ismanto Ismanto Khoirudin Khoirudin Khoirudin Khoirudin, Khoirudin Khoirul Fahmi Lingga Arum Nugroho Mahendra, Rifqi Gusnar Mochamad Bagus Okta Eka Pramuditya Mohammad Sani Suprayogi Muhammad Basyier Ardima Nur Wakhidah Nurtriana Hidayati Nutriana Hidayati Palupi, Kinanthi Sekar Pangesti, Mey Tri Widya Putra, Rafli Danu Kusuma Raihan Ary Prabowo Ramadhania, Salwa Rizal Rafli Fajar Kurniawan Safira Nuraisha Saifur Rohman Cholil Septia Nike Bela Sapira Susanto Susanto Susanto, Susanto Titis Handayani Trenady, Revangga Alif Victor Gayuh Utomo Victor Gayuh Utomo Vinay Rishiwal Winarti, Titin Yulinda Kusumaningrum