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All Journal Knowledge Engineering and Data Science Journal of Telecommunication, Electronics and Control Engineering (JTECE) Jurnal Abdi Masyarakat Multidisiplin Jurnal Informatika Progres J-Icon : Jurnal Komputer dan Informatika
Nia Yuningsih
Universitas Gunadarma
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Social Sciences

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REAL-TIME STRUCTURAL ANALYSIS BASED ON MACHINE LEARNING FOR CUSTOM PRODUCT DESIGN: A CASE STUDY OF ORTHOPEDIC FIXATOR PRODUCT Aji Digdoyo; Adhitio Satyo Bayangkari Karno; Widi Hastomo; Agita Tunjungsari; Nada Kamilia; Indra Sari Kusuma Wardhana; Nia Yuningsih
J-ICON : Jurnal Komputer dan Informatika Vol 11 No 1 (2023): Maret 2023
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v11i1.9919

Abstract

Mass customization is related to increasing the balance between the needs of companies that are focused on customers on conditions of production flexibility and efficiency. Product adjustment according to customer needs can increase the company's competitiveness. However, special production processes and adjustments are time consuming and cost inefficient. Parametric product modeling is a fairly popular technique for dealing with this problem. However, it still has challenges related to the high cost of software and a workforce that has special expertise in the field of quality control. In addition, product-specific designs cannot be tested quickly, resulting in a long production time. This study proposes a machine learning (ML) method that aims to obtain a fast time structure to analyze the production of orthopedic fixators. This research process requires a collection of training data with product attributes, physical characteristics, quality, selected ML techniques, and determination of the appropriate set of hyperparameters. Optimization results were obtained using the gradient boosting method with a value of . With these results, the orthopedic fixation device can be used in the case study of developing this machine learning model.
Exploratory Data Analysis for Building Energy Meters Using Machine Learning Rudy Yulianto; Sukardi Sukardi; Faqihudin Faqihudin; Meika Syahbana Rusli; Adhitio Satyo Bayangkari Karno; Widi Hastomo; Nia Yuningsih; Nada Kamilia
Journal of Telecommunication Electronics and Control Engineering (JTECE) Vol 5 No 2 (2023): Journal of Telecommunication, Electronics, and Control Engineering (JTECE)
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/jtece.v5i2.934

Abstract

The purpose of this research was to apply exploratory data analysis techniques to building energy meters, such as electricity, cold, heat, and steam meters. A thorough understanding of energy usage patterns becomes increasingly vital in an era of growing awareness of energy management and sustainability. Trends, patterns, and anomalies can be identified in building energy meter data using meticulous data exploration approaches, which can give significant insights for increasing energy efficiency. Exploratory data analysis combined with machine learning approaches may be was used to reveal hidden patterns of energy usage and examine the links between relevant factors. The findings of this exploratory data analysis gave vital insights into building energy use trends. Some significant and hidden information that was crucial for understanding energy usage within a certain time frame in each building was discovered via the investigation of the data used in this study. Steam had the highest use, whereas electricity had the lowest. Utilities were more popular before 5 a.m., followed by healthcare, with daytime use hours beginning around 10 a.m., depending on the area. During the working day, the industry needs more energy. Places of worships use more energy on weekends. There was a significant relation between the number of floors and spaces per level of a building and the height meter reading between May and October. There is a significant association between the kind of buildings used for schools, workplaces and high energy use. This study significantly contributed to the management of the energy and sustainability domains. Using exploratory data analysis and machine learning approaches to building energy meters could optimize energy usage, minimize running costs, and enhance overall energy efficiency. This research is still very open to be continued using other methods, to obtain other hidden information.
PENGABDIAN MASYARAKAT KEMAMPUAN SPEAKING BERDASARKAN ILMU LANGUAGE SKILL Felisia, Raden Roro Shinta; Tommy Kuncara; Wisnu Sukma Maulana; Nia Yuningsih; Andre Pratama Adiwijaya; Immi Fiska Tarigan
 Jurnal Abdi Masyarakat Multidisiplin Vol. 3 No. 1 (2024): April: JURNAL ABDI MASYARAKAT MULTIDISIPLIN
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/jammu.v3i1.1548

Abstract

Latar belakang pengabdian kepada masyarakat ini berakar dari kebutuhan untuk meningkatkan kemampuan speaking berdasarkan Ilmu Language Skill. Kerjasama antara Universitas Gunadarma dan Asosiasi Dosen Muda Indonesia (ADMI) bertujuan memberikan kontribusi positif kepada masyarakat melalui pengenalan dan pengembangan kemampuan speaking. Tujuan utama kegiatan ini adalah untuk membantu masyarakat, khususnya di kota Bekasi, dalam menguasai kemampuan speaking yang dapat digunakan dalam pekerjaan maupun kehidupan sehari-hari. Kegiatan ini dilaksanakan sepanjang tahun ajaran ATA 2023-2024 dengan metode pertemuan online dan offline. Metode pelaksanaan kegiatan pengabdian ini melibatkan 4 Fakultas dan 10 bidang ilmu terkait di Universitas Gunadarma, seperti sistem informasi, sistem komputer, akuntansi, manajemen, teknik elektro, teknik industri, teknik mesin, teknik sipil, ilmu komunikasi, dan Sastra Inggris. Pendekatan ini didukung oleh Teknologi Informasi dan Komunikasi (TIK) melalui Training, Education and Research Center. Hasil yang diharapkan dari kegiatan ini adalah peningkatan kemampuan speaking peserta, publikasi jurnal, dan luaran IPTEK lainnya seperti video dokumentasi kegiatan. Selain itu, diharapkan adanya peningkatan angka partisipasi dosen dalam kegiatan pengabdian masyarakat. Hasil pelaksanaan kegiatan ini dilaporkan kepada Lembaga Pengabdian kepada Masyarakat Universitas Gunadarma (LPM-UG) untuk keperluan monitoring dan evaluasi.
PENINGKATAN KOMPETENSI PELAKU UMKM DALAM STRATEGI BRANDING BERBASIS TEKNOLOGI Sandy Suryady; Wisnu Sukma Maulana; Tati Noviati; Nia Yuningsih
 Jurnal Abdi Masyarakat Multidisiplin Vol. 3 No. 3 (2024): Desember: JURNAL ABDI MASYARAKAT MULTIDISIPLIN
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/jammu.v3i3.1883

Abstract

This community service program aims to provide training and guidance for Micro, Small, and Medium Enterprises (MSMEs) in implementing technology-based branding strategies. The activity is a collaboration between Gunadarma University and the Indonesian Young Lecturers Association (ADMI), conducted throughout the PTA 2024-2025 academic year. The program employs a hybrid implementation method (online and offline), tailored to the needs of MSMEs. The primary focus of this program is to enhance MSMEs’ understanding and skills in utilizing technology for digital branding, covering creative content creation, social media utilization, and market target analysis using digital tools. This initiative involves six fields of study—Accounting, Management, Industrial Engineering, Mechanical Engineering, Information Systems, and English Literature—to provide a comprehensive interdisciplinary approach. The expected outcomes include improving MSMEs' competencies in building a strong brand identity, managing digital branding campaigns, and expanding market reach through technology. Program outputs include journal publications, activity documentation in the form of videos, and increased lecturer participation. All program results will be reported to Gunadarma University’s Community Service Institution (LPM-UG) as part of program evaluation.
PENERAPAN METODE PROTOTYPE DALAM PENGEMBANGAN WEBSITE KONVERSI GAMBAR VEKTOR KE MODEL 3D Yuningsih, Nia; Rachman, Zaidan Ramadhan; Prananingrum, Lely
PROGRESS Vol 18 No 1 (2026): April
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v18i1.538

Abstract

This research aims to design and build a static website capable of automatically converting SVG vector images into 3D objects. The main problem addressed is the lack of user-friendly and efficient web-based tools for converting SVG files into 3D models, which are important for 3D designers and 3D printing. The development applies the Prototype method, allowing initial prototypes to be tested and refined based on user feedback. The website is developed using JavaScript with the Three.js library for 3D object processing and visualization, and Vite as a modern development tool to ensure responsiveness. Users are able to upload SVG files, adjust object thickness, preview the conversion in real-time, and export the 3D model in STL format. The results show that this website provides a practical and interactive solution for users who require fast conversion from SVG images to 3D objects through a web platform, accessible at https://sv3dkonversi.xyz. User Acceptance Testing was conducted and achieved a score of 82.2%, indicating that users can operate the website effectively in terms of layout, interface, system, and ease of use. This demonstrates the potential of the website to support 3D designers in digital manufacturing and 3D printing workflows.
Edukasi Literasi Keuangan Digital bagi Siswa Sekolah Dasar melalui Pengenalan Uang Elektronik dan Keamanan Bertransaksi Tommy Kuncara; Nia Yuningsih; Budhi Sriyono Prasetyo; Eko Aprianto Nugroho; Abdul Muchlis
 Jurnal Abdi Masyarakat Multidisiplin Vol. 5 No. 2 (2026): Agustus: JURNAL ABDI MASYARAKAT MULTIDISIPLIN
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/jammu.v5i2.2957

Abstract

The development of digital payment systems has increasingly exposed elementary school students to electronic money cards, digital wallets, and QR-code payments through their families and everyday experiences. However, familiarity with payment technology is not always accompanied by an adequate understanding of digital balances, personal-data protection, and transaction security. This community service program aimed to improve elementary school students’ digital financial literacy through the introduction of electronic money and safe transaction practices. The program was conducted at SDN Margahayu XIII, Bekasi City, on June 15, 2026, involving 30 fifth-grade students. The program applied a Digital Financial Safety Lab model consisting of a diagnostic test, learning-station rotations, case-based games, balance-management exercises, confidential-information identification, and safe digital-transaction simulations. Evaluation was conducted using pre-tests and post-tests, student worksheets, performance assessments, and behavioral observations. The results showed that the students’ average digital financial literacy score increased from 48.2 in the pre-test to 88.3 in the post-test, representing an improvement of 40.1 points. The percentage of students achieving the minimum competency score increased from 13.3% to 93.3%, while 96.7% of participants demonstrated improved scores.
Analisis Perubahan Perilaku Berutang Peserta setelah Edukasi “Baca–Hitung–Cek sebelum Klik Setuju”: Studi pada Strategi Penggunaan Pinjol Legal yang Aman dan Bertanggung Jawab Immi Fiska Tarigan; Ariyanto Ariyanto; Nia Yuningsih; Wendra Afriana; Sri Wahyuni Handayani
 Jurnal Abdi Masyarakat Multidisiplin Vol. 4 No. 03 (2025): Desember: JURNAL ABDI MASYARAKAT MULTIDISIPLIN
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/jammu.v4i03.2573

Abstract

Kemudahan akses pinjaman online (pinjol) mendorong peningkatan penggunaan layanan kredit digital, namun sering diikuti perilaku berutang yang kurang terencana akibat minimnya pemahaman biaya, tenor, dan risiko, termasuk risiko layanan ilegal dan penyalahgunaan data pribadi. Penelitian ini bertujuan menganalisis perubahan perilaku berutang peserta setelah edukasi “Baca–Hitung–Cek sebelum Klik Setuju” sebagai strategi penggunaan pinjol legal yang aman dan bertanggung jawab. Metodologi menggunakan pendekatan campuran (mixed methods) dengan desain pretest–posttest dan pendalaman kualitatif. Responden merupakan peserta kegiatan edukasi literasi keuangan digital pada komunitas/instansi mitra. Data kuantitatif dikumpulkan melalui kuesioner yang mengukur pemahaman struktur biaya (bunga, biaya layanan, denda), kemampuan perencanaan pembayaran (cashflow sederhana), perilaku verifikasi legalitas, serta indikator kehati-hatian digital (izin aplikasi, OTP, phishing). Data kualitatif diperoleh melalui wawancara singkat/FGD untuk menangkap alasan perubahan keputusan berutang dan hambatan penerapan strategi. Analisis kuantitatif dilakukan dengan statistik deskriptif dan uji beda berpasangan, sedangkan data kualitatif dianalisis tematik. Temuan menunjukkan peningkatan signifikan pada pemahaman komponen biaya dan kemampuan menghitung total kewajiban, peningkatan kepatuhan verifikasi legalitas sebelum meminjam, serta penurunan kecenderungan mengambil pinjaman tanpa perencanaan. Peserta juga melaporkan perubahan strategi penggunaan pinjol menjadi lebih selektif, seperti membatasi nominal, memilih tenor realistis, dan mengutamakan kebutuhan produktif. Implikasi penelitian menegaskan bahwa strategi edukasi sederhana dan operasional “Baca–Hitung–Cek” efektif mendorong perilaku pinjol yang lebih aman, dan dapat dijadikan model intervensi literasi keuangan digital berbasis komunitas/sekolah. Orisinalitas penelitian terletak pada pengukuran perubahan perilaku berutang yang dikaitkan langsung dengan langkah praktis pengambilan keputusan pinjol (membaca ringkasan, menghitung total biaya, dan mengecek legalitas) serta integrasinya dengan praktik keamanan data pribadi.
Stacked LSTM-GRU Long-Term Forecasting Model for Indonesian Islamic Banks Sujatna, Yayat; Karno, Adhitio Satyo Bayangkari; Hastomo, Widi; Yuningsih, Nia; Arif, Dody; Handayani, Sri Setya; Kardian, Aqwam Rosadi; Wardhani, Ire Puspa; Rere, L.M Rasdi
Knowledge Engineering and Data Science
Publisher : citeus

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

Abstract

The development of the Islamic banking industry in Indonesia has become a significant concern in recent years, with rapid growth in the number of banks operating based on Sharia principles. To face emerging challenges and opportunities, a deep understanding of the long-term financial behavior of Islamic banks is becoming increasingly important. This study aims to predict the share price of PT Bank Syariah Indonesia Tbk, over 28 days using the LSTM-GRU stack. The observation stage includes importing the dataset, data separation, model variations, the training process, output, and evaluation. Observations were conducted using 10 model variations from 4 stacks of LSTM and GRU. Each model performs the training process in four epochs (200, 500, 750, and 1000). The results of observations in this study show that long-term predictions (28 days ahead) using four stacks of LSTM-GRU and daily training accumulation techniques produce better accuracy than the general method (using multiple outputs). From the observations we have made for predictions for the next 28 days, the model with the LGLG stack arrangement (LSTM-GRU-LSTM-GRU) produces the best accuracy at epoch 750 with an MSE LSTM-GRU 63.43762863. This study will undoubtedly continue in order to achieve even better precision, either by utilizing a new design or by further improving the technology we are now employing.
Co-Authors Abdul Muchlis Agita Tunjungsari Aji Digdoyo Andre Pratama Adiwijaya Arif, Dody Ariyanto Bayangkari Karno, Adhitio Satyo Budhi Sriyono Prasetyo Eko Aprianto Nugroho Faqihudin Faqihudin Felisia, Raden Roro Shinta Handayani, Sri Setya Immi Fiska Tarigan Indra Sari Kusuma Wardhana Ire Puspa Wardhani Kardian, Aqwam Rosadi Lely Prananingrum Meika Syahbana Rusli Nada Kamilia Nada Kamilia Rachman, Zaidan Ramadhan Rere, L.M Rasdi Rudy Yulianto Sandy Suryady Sri Wahyuni Handayani Sukardi, Sukardi Tati Noviati Tommy Kuncara Tommy Kuncara Wendra Afriana Widi Hastomo Wisnu Sukma Maulana Yayat Sujatna, Yayat