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All Journal Jurnal Informatika Perspektif : Jurnal Ekonomi dan Manajemen Universitas Bina Sarana Informatika Jurnal Teknik Komputer AMIK BSI Paradigma Jurnal Pilar Nusa Mandiri Techno Nusa Mandiri : Journal of Computing and Information Technology JURNAL TEKNOLOGI DAN OPEN SOURCE Jurnal Riset Informatika Journal of Information System, Applied, Management, Accounting and Research Jurnal Informatika Kaputama (JIK) JURSIMA (Jurnal Sistem Informasi dan Manajemen) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Community Development Journal: Jurnal Pengabdian Masyarakat JPM: JURNAL PENGABDIAN MASYARAKAT Jurnal Responsif : Riset Sains dan Informatika Bulletin of Computer Science Research Journal of Informatics Management and Information Technology KLIK: Kajian Ilmiah Informatika dan Komputer Computer Science (CO-SCIENCE) Reputasi: Jurnal Rekayasa Perangkat Lunak Jurnal Abdimas Komunikasi dan Bahasa Indonesian Journal of Networking and Security - IJNS JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Interkom : Jurnal Publikasi Ilmiah Bidang Teknologi Informasi dan Komunikasi J-Intech (Journal of Information and Technology) DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY JEECS (Journal of Electrical Engineering and Computer Sciences) JURSIMA Sinergi: Jurnal Pengabdian Kepada Masyarakat Journal of Accounting Information System Bulletin of Informatics and Data Science Jurnal Ilmiah Manajemen Ekonomi Dan Akuntansi (JIMEA) Jurnal Sistem Informasi dan Manajemen Media Teknologi dan Informatika Darma Abdi Karya: Jurnal Pengabdian Kepada Masyarakat Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Komtika (Komputasi dan Informatika)
Riska Aryanti
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Astronomy Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Medicine & Pharmacology Public Health Social Sciences Transportation Other

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Combination of Response to Criteria Weighting Method and Multi-Attribute Utility Theory in the Decision Support System for the Best Supplier Selection Ulum, Faruk; Wang, Junhai; Megawaty, Dyah Ayu; Sulistiyawati, Ari; Aryanti, Riska; Sumanto, Sumanto; Setiawansyah, Setiawansyah
J-INTECH ( Journal of Information and Technology) Vol 13 No 01 (2025): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v13i01.1810

Abstract

Choosing the right supplier is a strategic factor in supporting operational efficiency and a company's competitive advantage. This process requires a decision support system that is able to assess various alternatives objectively and in a structured manner. This study aims to develop a decision support system in the selection of the best supplier by combining the Response to Criteria Weighting (RECA) and Multi-Attribute Utility Theory (MAUT) methods. The RECA method is used to objectively determine the weight of each criterion based on the variation of data between alternatives, so as to reduce subjectivity in the weighting process. Meanwhile, the MAUT method functions to calculate the total utility value of each supplier based on the normalization value and weight that has been obtained. The results of the RECA method show the objective weight of each criterion, which is then used in the MAUT calculation process. The results of the analysis, obtained in the best supplier selection based on the total score of each candidate, it can be seen that PT Global Niaga Mandiri ranks first with the highest score of 0.6512, this shows that this company is the best choice in the supplier selection process. In second place is UD Anugrah Bersama with a score of 0.399, followed by PT Indo Logistik Prima in third place with a score of 0.3451. The combination of the RECA and MAUT methods has been proven to be able to produce accurate, rational, and accountable decisions. This system provides a measurable approach in filtering supplier alternatives efficiently and is relevant to be applied to various other multi-criteria decision-making contexts.
Evaluasi Sistem Pencatatan dan Pelaporan Keuangan UMKM: Wawancara pada Cabang Esteler Barbarita Nova Damai Yanti Bancin; Cindy Sri Wahyuni; Riska Aryanti; Masjuwita Aulia Munthe; Siti Rodiah
Jurnal Ilmiah Manajemen Ekonomi Dan Akuntansi (JIMEA) Vol. 2 No. 4 (2025): Agustus
Publisher : Publikasi Inspirasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62017/jimea.v2i4.5553

Abstract

Usaha Mikro, Kecil, dan Menengah (UMKM) memegang peranan penting dalam perekonomian nasional, namun seringkali menghadapi kendala pada aspek manajemen keuangan, khususnya dalam pencatatan dan pelaporan. Penelitian ini bertujuan untuk mengevaluasi sistem pencatatan dan pelaporan keuangan pada UMKM Esteler Barbarita di Pekanbaru. Penelitian ini menggunakan pendekatan kualitatif dengan metode studi kasus, melalui wawancara mendalam kepada pemilik dan pengelola usaha sebagai informan utama. Hasil penelitian menunjukkan bahwa sistem pencatatan keuangan masih dilakukan secara manual, dengan pelaporan harian yang terstruktur kepada kantor pusat. Meskipun metode ini telah membantu pengawasan operasional, terdapat kelemahan berupa keterlambatan pelaporan dan rendahnya efisiensi akibat belum adanya sistem digital. Rekomendasi yang diusulkan meliputi digitalisasi sistem keuangan, standarisasi format laporan cabang, pelatihan pengelolaan keuangan dasar, serta penguatan mekanisme monitoring dan audit. Diharapkan dengan penerapan rekomendasi ini, tata kelola keuangan UMKM dapat meningkat, mendukung pengambilan keputusan berbasis data, dan mendorong pertumbuhan usaha yang lebih profesional serta berkelanjutan.
Sistem Informasi Pencatatan Permintaan Dan Pengeluaran ATK Pada Balai Pengamanan Alat Fasilitas Kesehatan Jakarta Masngud; Aryanti, Riska
Media Teknologi dan Informatika Vol. 2 No. 1 (2025): Juni
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/pynjvn06

Abstract

Peralatan perkantoran atau sering disebut dengan Alat Tulis Kantor (ATK) dan Barang Habis Pakai (BHP) merupakan suatu kebutuhan yang harus dipenuhi dan diperhatikan penggunaanya pada suatu instansi seperti pada kantor Balai Pengamanan Fasilitas Kesehatan Jakarta. Saat ini BPAFK Jakarta masih menggunakan sistem manual dengan Microsoft Excel dan pencatatan menggunkan formulir kertas untuk mengelola data ATK/BHP mulai dari pendataan alat yang masuk hingga pendistribusian kepada setiap divisi pegawai. Hal ini menyebabkan beberapa masalah signifikan, seperti risiko terjadinya kesalahan dalam pengetikan dan data yang tidak akurat, keterlambatan dalam pembuatan laporan, serta kurangnya efisiensi dalam proses administrative. Oleh karena itu kantor BPAFK Jakarta memerlukan sebuah sistem yang dapat mendukung proses pengolahan data Pencatatan Permintaan dan Pengeluaran ATK/BHP tersebut. Sistem yang akan dikembangkan diharapkan akan dapat membantu dalam membuat laporan Pencatatan Permintaan dan Pengeluaran ATK/BHP. Metode pengembangan sistem yang dipilih dalam penelitian ini adalah model pengembangan sistem Rapid Application Development (RAD). Desain sistem dalam penelitian ini menggunakan Unified Modelling Language (UML). Proses pembuatan program (coding) menggunakan bahasa pemrograman PHP dengan HTML dan MySQL untuk pembuatan database. Pendekatan kasus uji dalam penelitian ini menggunakan pengujian Black Box. Hasil pengujian yang telah dilakukan menunjukkan bahwa semua fungsi yang dimiliki sistem telah berjalan sesuai dengan fungsinya.
Analisis Sentimen Pemanfaatan Artificial Intelligence di Dunia Pendidikan Menggunakan SVM Berbasis Particle Swarm Optimization Saepudin, Atang; Aryanti, Riska; Fitriani, Eka; Royadi, Royadi; Ardiansyah, Dian
Computer Science (CO-SCIENCE) Vol. 4 No. 1 (2024): Januari 2024
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/coscience.v4i1.2921

Abstract

The utilization of Artificial Intelligence (AI) in the field of education in Indonesia has witnessed significant developments in recent years. The advancements in AI technology have opened up new opportunities to enhance the quality of education, and address various challenges faced by the Indonesian education system. This has naturally sparked diverse opinions and comments from the public, particularly on the social media platform X/Twitter. This research focuses on sentiment analysis of reviews expressed on the X/Twitter social media platform. The primary goal of this study is to develop an effective sentiment analysis method by leveraging the Support Vector Machine (SVM) algorithm optimized with Particle Swarm Optimization (PSO) for feature selection. In this research, user reviews from X/Twitter were collected and analyzed to identify positive or negative sentiments within the context of each comment. The SVM algorithm was used to classify sentiments based on similarity to comments with known sentiments. Feature Selection PSO was employed to optimize the parameters within SVM to enhance sentiment analysis accuracy. The results of sentiment analysis on comments or tweets on the X/Twitter social media platform using both SVM and PSO-based SVM algorithms indicated that the PSO-based SVM algorithm achieved a higher accuracy. The SVM algorithm with feature selection PSO produced accuracy 89.50%, precision 86.98%, recall 93.00%, and AUC 0.964. Meanwhile, the SVM algorithm had accuracy 87.50%, precision 85.46%, recall 90.50%, and AUC 0.956. This demonstrates that the use of feature selection PSO in the SVM algorithm is capable of improving the accuracy of the results.
Sentiment Analysis of E-Grocery Application Reviews Using Lexicon-Based and Support Vector Machine Aryanti, Riska; Fitriani, Eka; Royadi, Royadi; Ardiansyah, Dian; Saepudin, Atang
Jurnal Riset Informatika Vol. 6 No. 3 (2024): June 2024
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v6i3.301

Abstract

This research aims to conduct sentiment analysis of e-grocery application reviews using the Support Vector Machine (SVM) algorithm. Sentiment analysis is used to distinguish between positive and negative reviews by users who have provided reviews so that an evaluation of the services offered can be made. This research uses scraping techniques to obtain all the needed review data, focusing only on reviews of the Segari and Sayurbox applications. Datasets were collected from reviews using a library in Python, namely, google-play-scraper, obtained by the sayurbox application 4235 reviews and the segari application 5575. The dataset collected does not yet have a label, and the labeling process is impossible to perform manually by looking at the reviews one by one because it takes a long time and requires an expert in the field of language who can interpret the reviews and group them into positive and negative sentiments. Therefore, the sentiment-labeling process applies a lexicon-based method that works based on the inset lexicon dictionary by calculating each review's polarity value. The analysis process of this research uses the SVM algorithm because the SVM method has been proven to provide consistent and accurate results in various classification tasks, including sentiment analysis. The results show that the lexicon-based method and SVM produce good accuracy in determining the sentiment of e-grocery reviews, with a vegetable box application accuracy rate of 94%. In comparison, the segari application accuracy rate reached 97%.
Waste Classification using EfficientNetB3-Based Deep Learning for Supporting Sustainable Waste Management Agustiani, Sarifah; Junaidi, Agus; Aryanti, Riska; Kamil, Anton Abdul Basah
Bulletin of Informatics and Data Science Vol 4, No 1 (2025): May 2025
Publisher : PDSI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61944/bids.v4i1.108

Abstract

Waste management is a critical issue in sustainable development, particularly in large urban areas that generate a high volume of waste daily. One of the main challenges is the absence of a fast, accurate, and efficient waste sorting system. This study aims to develop a waste classification model using deep learning based on the EfficientNetB3 architecture to support more sustainable waste management. The model was trained on a dataset obtained from a Kaggle repository, consisting of 4,650 images evenly distributed across six waste categories: batteries, glass, metal, organic, paper, and plastic (775 images per class). The training and evaluation were conducted using a supervised image classification approach. The model achieved an overall accuracy of 93%, with average precision, recall, and F1-score values of 93%. Among all categories, organic waste achieved the highest F1-score (0.99), followed by paper (0.97) and batteries (0.97), while plastic and metal categories obtained F1-scores of 0.89. These results demonstrate that the EfficientNetB3 architecture is effective in performing multi-class waste classification. This model has the potential to be implemented in camera-based waste sorting systems such as smart bins or automated recycling units, thereby contributing to the reduction of unprocessed waste and supporting the achievement of Sustainable Development Goal (SDG) 12: responsible consumption and production
Optimalisasi Random Forest dan Support Vector Machine dengan Hyperparameter GridSearchCV untuk Analisis Sentimen Ulasan PrimaKu Misriati, Titik; Aryanti, Riska
Journal of Information System Research (JOSH) Vol 5 No 4 (2024): Juli 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v5i4.5347

Abstract

PrimaKu App has been a pioneer in the field of digital health since 2017. Through this application, parents can regularly and continuously monitor their children’s health and development. PrimaKu also has a formal alliance with the Indonesian Pediatric Association (IDAI) to promote child health in Indonesia. This application can be downloaded through the Google Play Store. Google Play Store has a feature that allows users to review the app before downloading. Sentiment analysis is used to distinguish between positive and negative reviews by users who have provided reviews so that an evaluation of the services provided can be made. This research aims to conduct sentiment analysis of user reviews of the PrimaKu application using Random Forest (RF) and Support Vector Machine (SVM) algorithms with TF-IDF weighting. Optimization was performed using hyperparameters to improve the performance of the Random Forest and SVM algorithms. The data used consisted of the 2,293 most relevant reviews collected from the Google Play Store. The most effective models for the Random Forest and Support Vector Machine were selected by adjusting the hyperparameters using GridSearch CV. The results of this study show that Random Forest has a higher success rate in classifying PrimaKu user review data, with an accuracy of 89%, precision of 88%, recall of 81%, and F1-Score of 85%.
Penerapan Metode Rapid Application Development Dalam Pengembangan Aplikasi Persediaan Material Panel Listrik Berbasis Web Azis, Munawar Abdul; Wahyudi, Mochamad; Aryanti, Riska
Reputasi: Jurnal Rekayasa Perangkat Lunak Vol. 4 No. 2 (2023): November 2023
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/reputasi.v4i2.2496

Abstract

PT Indomitra Global is a company engaged in electrical contracting services and provides various types of electrical panels needed by clients. Electrical panels require many important materials, for example mcb, sockets, cables, and many other important components. The material inventory system carried out at PT Indomitra Global still uses a manual method in the material inventory system. This process has several obstacles, namely not having a centralized database that makes material inventory data vulnerable to loss and there are often differences in the suitability of the amount of material in the warehouse with the amount in Microsoft Excel, because data management is still not easy enough and due to human error or input errors. On the basis of this problem, a web-based material inventory application was made using the Rapid Application Development (RAD) method. The material inventory system produced in this study is able to handle material data management which previously was still not easy enough to do, such as searching for data, managing incoming and outgoing material transaction data and making it easier to generate incoming and outgoing material reports based on time periods
Soft Voting Based Optimized Ensemble for Migraine Type Classification Misriati, Titik; Aryanti, Riska; Leidiyana, Henny
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 6 No. 3 (2025): Volume 6 Number 3 September 2025
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jatika.v6i3.861

Abstract

The accurate classification of migraine subtypes is a complex challenge in neurology, hindered by symptomatic similarities between types. This complexity necessitates advanced computational tools to support diagnostic precision. This study aims to develop and evaluate an optimized soft voting ensemble classifier to automate this multi-class classification task effectively. The methodology involved training eight base models—including Neural Network, Random Forest, and Gradient Boosting—on a publicly available migraine dataset, with an 80-20 train-test split. The top three performers were integrated into a soft voting ensemble, which aggregates their predicted probabilities to enhance decision robustness. Model performance was rigorously assessed using accuracy, precision, recall, F1-score, and AUC-ROC metrics. The results demonstrated that the proposed ensemble achieved superior performance, with an accuracy of 91.67% and an F1-score of 91.50%, outperforming all constituent models. Furthermore, the ensemble attained near-perfect AUC-ROC values across multiple classes, confirming its strong discriminatory capability. The study concludes that the soft voting ensemble is a highly effective and reliable approach for migraine subtype classification, offering significant potential as a decision-support tool in clinical environments. Future work will focus on hyperparameter optimization, explainability, and validation with larger multi-centric datasets to facilitate clinical adoption.
IMPLEMENTASI NILAI PANCASILA SEBAGAI LANDASAN SOSIALISASI ANTI KORUPSI UNTUK MEMBANGUN GENERASI EMAS DI SMK NEGERI 2 PEKANBARU Hariyanto, Gebby Amara Putri Sugeng; Vitantri, Vitantri; Hudi, Ilham; Lubis, Anisah Azzahra; Khairani, Yashinta; Ramadhani, Nadia Thalia; Utami, Ajeng Ayun Dining; Nurazila, Riska; Wahyuni, Cindy Sri; Faradiva, Aulia; Aryanti, Riska
Community Development Journal : Jurnal Pengabdian Masyarakat Vol. 6 No. 1 (2025): Volume 6 No. 1 Tahun 2025
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cdj.v6i1.39466

Abstract

Tindak pidana korupsi merupakan penyakit sosial yang telah merajalela di banyak negara, termasuk Indonesia. Pengabdian ini dilakukan di SMKN 2 Pekanbaru. Pengabdian ini bertujuan untuk mengeksplorasi bagaimana nilai-nilai pancasila dapat diterapkan dalam kehidupan sehari-hari untuk membangun karakter masyarakat yang anti korupsi. Pengabdian ini menggunakan metode sosialisasi dan penyuluhan yang melibatkan pendekatan partisipatif dan edukatif yang dilakukan melalui 4 tahapan yaitu identifitakasi masalah, perijinan, melaksankan sosialisasi dan evaluasi. Hasil sosialisasi menunjukkan bahwa nilai-nilai Pancasila, dapat menjadi landasan moral dalam memperkuat integritas individu dan institusi. Implementasi nilai-nilai tersebut melalui sosialisasi antikorupsi, dan partisipasi masyarakat terbukti efektif dalam menurunkan potensi korupsi.
Co-Authors Agus Junaidi Agustiani, Sarifah Aldian Mauluda Alif Rizqi Mulyawan Andi Saryoko Andreas Roy Prasetya Ari Sulistiyawati Arifin, Yosep Tajul Asriyani Sagiyanto ASRIYANI SAGIYANTO, ASRIYANI Atang Saepudin Atang Saepudin Atang Saepudin Azis, Munawar Abdul Bayu Kusuma Ilyasa Universitas Bina Sarana Informatika Cindy Sri Wahyuni Dahlia Dahlia Darma Setiawan Putra Dede Firmansyah Dede Firmansyah Saefudin Dedi Darwis Deni Gunawan Diah Puspitasari Dian Ardiansyah Dian Ardiansyah Eka Dyah Setyaningsih Eka Fitriani Eka Fitriani Eka Fitriani Eka Fitriyani Fachri, Muhamad Faradiva, Aulia Haliza Ramadhanti, Pristya Harefa, Kristine Hariyanto, Gebby Amara Putri Sugeng Haryani Hasan, Fuad Nur Henny Leidiyana Herdian Pratama I Gede Iwan Sudipa Ilham Hudi Aim Abdulkarim Kokom Komalasari, Ilham Hudi Aim Abdulkarim Irfan Ridwan Jananto Watori Junhai Wang Kamil, Anton Abdul Basah Khairani, Yashinta KOMALASARI, YULI Lubis, Anisah Azzahra Martenia, Rina Masjuwita Aulia Munthe Masngud Megawaty, Dyah Ayu Mesran, Mesran Mochamad Wahyudi Nova Damai Yanti Bancin Nurazila, Riska Oktaviyani Oktaviyani Oprasto, Raditya Rimbawan Pasaribu, A. Ferico Octaviansyah Perani Rosyani Permana, Rifky Pristya Haliza Ramadhanti Rachilsyah Ramdhani Efendi Rahmat Hidayat Rahmat Hidayat Ramadhani, Arya Ramadhani, Nadia Thalia Richardus Eko Indrajit Rifky Permana Rifqi Rizaldi Rina Martenia Rizqi Nur Esmeralda Rosiun Universitas Bina Sarana Informatika Roy Prasetya, Andreas Royadi - Royadi Royadi Royadi, Royadi Salman Alfarizi SALMAN ALFARIZI Samudi Samudi Sari Dewi Universitas Bina Sarana Informatika PSDKU Pontianak Setiawansyah Setiawansyah Siti Khotimatul Wildah Siti Marlina, Siti siti rodiah Sopiyan Dalis Sumanto, Sumanto Titik Misriati tri wahyuni Tri Wahyuni Ulum, Faruk Utami, Ajeng Ayun Dining Vitantri, Vitantri Wahyudi, Agung Deni Wahyuni, Cindy Sri Walim Walim Wang, Junhai Yanto, Andika Bayu Hasta Yarimani Laia