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All Journal International Journal of Electrical and Computer Engineering JRSI (Jurnal Rekayasa Sistem dan Industri) ILKOM Jurnal Ilmiah Jurnal Sains dan Informatika : Research of Science and Informatic KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Jurnal Teknologi Journal of Applied Data Sciences Majalah Ilmiah UPI YPTK Journal of Computer Scine and Information Technology Jurnal Ipteks Terapan : research of applied science and education Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Jurnal Pustaka Mitra : Pusat Akses Kajian Mengabdi Terhadap Masyarakat Jurnal Pustaka Data : Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitektur Komputer Journal of Information Systems and Technology Research Jurnal Sains Informatika Terapan (JSIT) Jurnal Komtekinfo Indonesian Journal of Informatic Research and Software Engineering Innovative: Journal Of Social Science Research Jurnal Teknologi Journal Of Indonesian Social Society JOURNAL OF COMMUNITY SERVICE AND APPLICATION SCIENCE (JCSAS) The Indonesian Journal of Computer Science Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi
Mutiana Pratiwi
Universitas Putra Indonesia YPTK Padang
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Perancangan Dan Implementasi Supply Chain Management Untuk Stok Dan Pemasaran Herbisida Pada UD. Anugrah Jaya Tani Dengan Bahasa Pemrograman PHP Dan Database MySQL Fitri Amelia Sari Lubis; Surmayanti Surmayanti; Mutiana Pratiwi
Bridge : Jurnal Publikasi Sistem Informasi dan Telekomunikasi Vol. 2 No. 2 (2024): Mei : Bridge : Jurnal Publikasi Sistem Informasi dan Telekomunikasi
Publisher : Asosiasi Profesi Telekomunikasi Dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/bridge.v2i2.52

Abstract

Advances in information and communication technology are growing rapidly in all directions so that a lot of information is produced from technology and is applied in various fields. In the field of information technology, Supply Chain Management is also needed, which is used to monitor inventory and marketing of goods at UD. Anugrah Jaya Tani. UD. Anugrah Jaya Tani is a kiosk that sells various herbicides. Supply chain management (SCM) is one part that can also be developed with the existence of internet resources. The internet can play a role in facilitating SCM activities. This is because SCM activities require communication between the parties involved in this matter. The purpose of using supply chain management, where the most basic is to be able to align customer demand with existing supply. The results of this study are to determine the amount of stock of goods to be marketed, create a system that can be accessed by anyone, and create an attractive consultation layout.
Sistem Pakar Diagnosis Anak Inklusi Memanfaatkan Fasilitas Interaksi Berbasis Multimedia Pratiwi, Mutiana
Jurnal Rekayasa Sistem & Industri Vol 5 No 01 (2018): Jurnal Rekayasa Sistem & Industri - Juni 2018 (In Press)
Publisher : School of Industrial and System Engineering, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/jrsi.v4i02.284

Abstract

Inklusif merupakan sebuah pendidikan yang memberikan kesempatan kepada semua peserta didik yang memiliki kelainan dan memiliki potensi kecerdasan dan atau bakat istimewa untuk mengikuti pendidikan atau belajar dalam satu lingkungan pendidikan secara bersama-sama dengan peserta didik pada umumnya. Saat sekarang orang tua sangat tidak peka terhadap tumbuh kembang anaknya. Tumbuh kembang anak paling sering terabaikan karena banyak faktor salah satunya karena sibuk mengurus pekerjaan. Maka dari itu, penelitian ini dibuat agar membantu orang tua mengetahui tumbuh kembang anak dari perilaku sehari-hari. Karena banyak yang tidak menyadari, kalau perilaku keseharian anak-anak dapat menjadi faktor munculnya sebuah syndrome atau dikenal dengan anak kebutuhan khusus. Salah satu syndrom yang paling banyak berada pada pendidikan inklusif adalah Tunagrahita. Anak Tunagrahita merupakan anak yang mempunyai tingkat intelektual dibawah rata-rata. Maka dari itu orang tua harus mengenali lebih dini ciri-ciri tunagrahita pada anak. Untuk itu Penelitian ini juga bertujuan membangun sistem pakar untuk diagnosa anak tunagrahita. Metode yang digunakan pada sistem pakar ini adalah metode Forward Chaining.
ACLM Model: A CNN-LSTM and Machine Learning Approach for Analyzing Tourist Satisfaction to Improve Priority Tourism Services Arsyah, Ulya Ilhami; Pratiwi, Mutiana; Fryonanda, Harfeby; Anam, M. Khairul; Munawir, Munawir
Journal of Applied Data Sciences Vol 6, No 4: December 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i4.974

Abstract

Tourist satisfaction is a key proxy for destination service quality, yet automatic sentiment analysis of online reviews still faces class imbalance, overfitting, and limited deployability. This study proposes ACLM, a hybrid sentiment classification pipeline that learns semantic and temporal features with a CNN-LSTM backbone and evaluates three classifier heads (Softmax, Logistic Regression, XGBoost) on a three-class corpus (neutral, satisfied, dissatisfied). The objective is to deliver an accurate and operational model for decision support in tourism services. The idea combines Word2Vec embeddings, a compact CNN for local patterns, an LSTM for sequence dependencies, and a training workflow with text cleaning, SMOTE based balancing, and regularization to curb overfitting; outputs are exposed through a simple Streamlit interface. Results show that CNN-LSTM with a Softmax head attains accuracy 0.89, macro precision 0.89, macro recall 0.84, and macro F1 0.86, outperforming Logistic Regression (accuracy 0.87, macro precision 0.84, macro recall 0.82, macro F1 0.82) and XGBoost (accuracy 0.85, macro precision 0.80, macro recall 0.82, macro F1 0.80). The findings indicate that deep sequence features paired with a simple Softmax head provide the best tradeoff between accuracy and stability for three-way sentiment classification. The contribution is a reusable, end to end blueprint from preprocessing and balanced training to quantitative evaluation and an inference GUI, and the novelty lies in testing interchangeable classifier heads on a single CNN-LSTM feature extractor while explicitly addressing data imbalance and deployment constraints. The GUI is implemented using the highest accuracy model, namely CNN-LSTM with Softmax.
Digital Entrepreneurship with Training in Making Handicraft Accessories for Students at the PGAI Padang Orphanage MUHAMMAD, ABULWAFA; Mutiana Pratiwi; Rima Liana Gema
Journal of Community Service and Application of Science Vol. 4 No. 2 (2025): COMMUNITY SERVICE AND APPLICATION SCIENCE (JCSAS)
Publisher : KPN Kopertis X

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62769/deagn415

Abstract

  The PGAI Foundation (Persatuan Guru Agama Islam) is a foundation that manages orphanages, schools and several other units in the city of Padang. Specifically, the children living in the orphanages come from various backgrounds and school age levels. They live and attend school at schools managed by the foundation, and some also attend public schools. One of the problems faced by these children is that they are accustomed to waiting for donations from donors for various activities. Although this is not the case for every child, it is certainly not good for their future. We provide handicraft training in the form of making accessories using digital technology. The students are given several product design examples and then given the freedom to develop their own products. The products produced are accessories such as bracelets, necklaces, rings and others made from beads. After the students are able to make the products, they are given knowledge on how to package the products. The students are also equipped with knowledge on how to utilise digital technology in obtaining product design references, promotion and marketing of their products. After this training, the children in the orphanage have acquired the skills to make various accessory products and have knowledge of digital entrepreneurship. This training has produced over 50 pieces of accessory products, including bracelets, rings, and several other items that are ready for marketing.
Twitter Sentiment Analysis of Public Space Opinions using SVM and TF-IDF Methods Arsyah, Ulya Ilhami; Pratiwi, Mutiana; Muhammad, Abulwafa
The Indonesian Journal of Computer Science Vol. 13 No. 1 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i1.3594

Abstract

Public space opinion reviews are currently a source of information for interested parties and decision-makers. Twitter is a social media that is a means of expressing themselves for people to express their opinions and criticize the current situation. This becomes information for readers. Information published on Twitter contains elements of commentary on a situation or object Sentiment analysis of public space opinion on Twitter using Machine Learning with the Support Vector Machine (SVM) method with the data weighting process using the Term Frequency-Inverse Document Frequency (TF-IDF) method. Dataset obtained by scraping using the Twitter API as much as 5000 data then labeled where the goal is to get accuracy on positive, negative, or neutral sentiment. The results of research conducted experiments on three Machine Learning algorithms with the extraction function "TF-IDF" obtained an accurate training model with good classification capabilities, especially SVM of 91,6% on data distribution 70: 30; SVM is 92.8% in the case of data distribution of 80: 20; the SVM is 91,8% in the case of 90:10 decomposition data.
Machine Learning on Opinion Mining of Netizen's Hate Speech Pratiwi, Mutiana; Liana Gema, Rima
The Indonesian Journal of Computer Science Vol. 13 No. 1 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i1.3617

Abstract

Netizen comments written in an online news portal through social media platforms, one of which is Instagram, can be used as material in the sentiment analysis process, which can be classified into positive, negative, or neutral sentiments. Sentiment analysis is part of the study of text mining, the science of discovering unknown knowledge by automatically extracting information from large volumes of unstructured text into useful information. The resulting information is in the form of sentiment towards a topic, whether it tends to be positive, negative, or neutral. The classification method used in this research is Support Vector Machine (SVM) and TF-IDF data weighting to classify text. Stages to perform data analysis are pre-processing to clean data, word weighting, labeling data into positive, negative, or neutral classes, and classifying and visualizing data with graphs. Accuracy tests using 70:30 split data showed that the accuracy reached 98%. Tests with 80:20 and 90:10 split data also showed high accuracy of 98% and 99%.
Recommendation for Prospective Permanent Employees using the Simple Additive Weighting Method Ahmad Haidir; Gushelmi; Mutiana Pratiwi
Journal of Computer Scine and Information Technology Volume 10 Issue 4 (2024): JCSITech
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/jcsitech.v10i4.113

Abstract

The rapid development of technological progress has made the use of personal computer technology increase significantly, where this use has made computers into branches that can still be developed, one of which is creating a decision-making system. Decision Support System is a computer-based system that is intended to assist decision making by utilizing certain data and models to solve various semi-structured problems. The application of Decision Support Systems can be found in various fields, one of which is a decision support system for prospective employees. This study aims to design a system that can provide the best decision in determining permanent employees at J&T Express Kotanopan. The method used in this study is the SAW (Simple Additive Weighting) method, with a website-based decision support system that can be used without time and place constraints, it can help J&T Express in selecting permanent employees. The results of testing this method have an accuracy level of more than 90% based on the data tested. Based on the results of the highest value obtained using the SAW method, this study was successful in determining permanent employees at J&T Express Kotanopan
Adaptive Integration of Optuna Optimization and Stacking Ensemble Learning for Automated Work Competency Classification Mutiana Pratiwi; Sarjon Defit; Muhammad Tajuddin
Journal of Applied Data Sciences Vol 7, No 2: May 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i2.1228

Abstract

Artificial intelligence and machine learning are increasingly used to automate analytical and decision processes, including the evaluation of human competencies. However, traditional models often face challenges in accuracy and generalization when applied to linguistic data from interviews. This study aims to develop a model that integrates Optuna optimization and stacking ensemble learning to enhance the accuracy and interpretability of competency classification. Interview transcript data were processed using natural language processing techniques such as cleaning, tokenization, case folding, stopword removal, and stemming to ensure textual consistency. The text was then transformed into numerical representations using term frequency inverse document frequency weighting. To handle class imbalance, the synthetic minority oversampling technique was employed. Optuna was applied to optimize the hyperparameters of base models, including support vector classifier, Naïve Bayes, random forest, gradient boosting, and XGBoost. These optimized models were combined through a stacking ensemble to form the final classifier. The proposed model achieved an accuracy of 94 percent and a precision of 95 percent with macro and weighted F1 scores of 0.94. The results demonstrate stable and balanced performance across all competency categories, including analytical thinking, initiating action, problem solving, and work standards. Comparative analysis with previous studies in sentiment analysis, medical diagnosis, and financial forecasting confirmed that the integration of Optuna and stacking produces more robust and generalizable outcomes. The integration of Optuna optimization and stacking ensemble learning effectively improves classification performance while maintaining interpretability. The model demonstrates strong potential for automated competency evaluation in recruitment and human resource analytics. This framework can be extended to other linguistic datasets to support transparent and data-driven decision-making in artificial intelligence applications.
Penerapan Metode TOPSIS untuk Penilaian Tingkat Gemar Membaca (TGM) di Wilayah Sumatera Gema, Rima Liana; Kartika, Devia; Pratiwi, Mutiana; Safira, Silky; Surmayanti, Surmayanti
Jurnal Pustaka Data (Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitektur Komputer) Vol 5 No 1 (2025): Jurnal Pustaka Data (Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitekt
Publisher : Pustaka Galeri Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55382/jurnalpustakadata.v5i1.1012

Abstract

Tingkat Gemar Membaca (TGM) adalah indikator penting yang digunakan untuk mengukur minat dan kebiasaan membaca masyarakat. TGM dipengaruhi oleh berbagai faktor, seperti frekuensi membaca per minggu, durasi membaca per hari, jumlah bahan bacaan per triwulan, frekuensi penggunaan internet per minggu, dan durasi akses internet per hari. Penelitian ini bertujuan untuk mengevaluasi TGM di sepuluh provinsi di Pulau Sumatera serta menganalisis faktor-faktor yang mempengaruhi perbedaan TGM antar provinsi. Untuk itu, digunakan metode TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), yang memungkinkan perankingan provinsi berdasarkan kedekatannya dengan solusi ideal. Data yang digunakan bersumber dari publikasi Perpustakaan Nasional tahun 2023. Hasil penelitian menunjukkan bahwa Sumatera Barat memperoleh peringkat tertinggi dengan nilai preferensi 74,04%, disusul oleh Jambi dengan nilai 62,94%, dan Sumatera Utara dengan nilai 51,69%. Temuan ini mengindikasikan bahwa provinsi-provinsi ini memiliki tingkat gemar membaca yang lebih tinggi dibandingkan provinsi lainnya di Pulau Sumatera. Penelitian ini menyimpulkan bahwa faktor-faktor seperti kebiasaan membaca dan penggunaan internet berpengaruh terhadap TGM, dan provinsi dengan TGM lebih tinggi memiliki peluang besar untuk memperkuat budaya literasi di wilayah mereka.
Digitalisasi Tulisan Adat: Pengembangan E-Book Berbasis Teknologi untuk Pelestarian Budaya Lokal di Nagari Lasi Ilhami Arsyah, Ulya; Atma, Yori Adi; Jihan SY, Yulia; Pratiwi, Mutiana; Kurnia, Rahmi Putri; Arsyah, Rahmatul Husna
Jurnal Pustaka Mitra (Pusat Akses Kajian Mengabdi Terhadap Masyarakat) Vol 5 No 5 (2025): Jurnal Pustaka Mitra (Pusat Akses Kajian Mengabdi Terhadap Masyarakat)
Publisher : Pustaka Galeri Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55382/jurnalpustakamitra.v5i5.1283

Abstract

Tim pengabdian Politeknik Negeri Padang bekerja sama dengan Kerapatan Adat Nagari (KAN) Lasi di Nagari Lasi, Kecamatan Canduang, Kabupaten Agam, melaksanakan program pelestarian budaya melalui digitalisasi tulisan adat. Aktivitas ini mengubah karya tulis adat yang sebelumnya berbentuk cetak menjadi e-book interaktif, memadukan tradisi dan teknologi modern agar warisan budaya dapat diakses dengan lebih mudah dan menarik. Sebanyak 15 dokumen adat berhasil didigitalisasikan dalam program ini sebagai langkah konkret pelestarian dan dokumentasi budaya lokal. Selain itu, dilaksanakan pula pelatihan sosialisasi yang diikuti oleh 20 orang peserta, terdiri dari ketua KAN Nagari Lasi dan perangkat adat, guna meningkatkan pemahaman serta keterampilan dalam memanfaatkan teknologi digital untuk menjaga keberlanjutan budaya. Inisiatif ini menekankan pentingnya inovasi dalam menjaga identitas budaya lokal sekaligus merespons tantangan era digital. Dengan demikian, program ini diharapkan menjadi model pelestarian budaya yang adaptif dan dapat menginspirasi nagari-nagari lain di Sumatera Barat untuk melakukan transformasi digital serupa. Melalui pendekatan ini, nilai-nilai adat tidak hanya terjaga keberlanjutannya, tetapi juga mampu memperkuat daya saing dan eksistensi budaya masyarakat di era globalisasi.
Co-Authors Aggy Pramana Gusman Ahmad Haidir Aminuyati Anam, M Khairul Arsyah, Ulya Ilhami Ayu Mahessya, Raja Devia Kartika Dinul Akhiyar Efendi, Gustiawan Eva Rianti Fajrul Islami Firna Yenila Fitri Amelia Sari Lubis Fryonanda, Harfebi Gema, Rima Liana Gushelmi Gustiawan Efendi Husna Arsyah, Rahmatul Irawadi Putra Irzal Arif Wisky Jihan Sy, Yulia Johan Harlan Jufriadif Na`am, Jufriadif Kris Hiburan Laoli, Vince kurnia, rahmi putri Liga Mayola Lusinia, Shary Armonitha Mardhiah, Putri Marfalino, Hari Marta, Widia Muhammad Tajuddin Muhammad, Abulwafa Munawir Munawir NILA PRATIWI Nitami, Dian Panggranatama, Nanda Randi Riskian Tahmid Romi Hardianto Ruri Hartika Zain Sarjon Defit Shary Lusinia Silky Safira Sovia, Rini Surmayanti, Surmayanti Tahmid, Riskian Tukino, Tukino Ulya Ilhami Arsyah Widia Marta Yori Adi Atma