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All Journal ILKOM Jurnal Ilmiah Journal of Computer Scine and Information Technology 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) Indonesian Journal of Informatic Research and Software Engineering Innovative: Journal Of Social Science Research Journal Of Indonesian Social Society The Indonesian Journal of Computer Science
Pratiwi, Mutiana
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Penerapan Sistem Pakar Dalam Diagnosa Pengguna Narkoba Menggunakan Metode Naïve Bayes Marfalino, Hari; Pratiwi, Mutiana; Arief Wisky, Irzal; Akhiyar, Dinul
Jurnal Sains Informatika Terapan Vol. 2 No. 2 (2023): Jurnal Sains Informatika Terapan (Juni, 2023)
Publisher : Riset Sinergi Indonesia (RISINDO)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62357/jsit.v2i2.159

Abstract

Perkembangan teknologi saat ini terasa sangat membantu pengguna dalam hal apapun. Tidak terkecuali membantu pihak berwajib dalam menentukan seseorang melakukan penyalahangunaan narkoba. Penyalahgunaan narkoba merupakan masalah serius yang mempengaruhi Kesehatan dan kualitas hiduo individu. Penelitian ini bertujuan untuk mengembangkan sebuah sistem pakar yang dapat membantu dalam proses diagnosa pengguna narkoba menggunakan metode Naïve Bayes. Metode Naïve Bayes adalah salah satu metode klasifikasi yang berdasarkan teorema bayes dengan asumsi bahwa semua atribut yang digunakan diklasifikasi adalah independent. Atribut yang digunakan dalam penelitian ini adalah usia, jenis kelamin, Riwayat pengguna narkoba, dan gejala. Penelitian ini menggunakan data dari individu yang telah terdiagnosis sebagai pengguna narkoba. Hasil penelitian ini adalah menghasilkan diagnosa jenis narkoba yang dikonsumsi dengan nilai akurasi. Terdapat salah satu pengguna narkoba yang terdiagnosa penyalahgunaan narkoba jenis Sabu dengan nilai akurasi 0.4468.
DECISION SUPPORT SYSTEM FOR SCHOLARSHIP RECIPIENT SELECTION USING THE SIMPLE ADDITIVE WEIGHTING (SAW) METHOD Mardhiah, Putri; Pratiwi, Mutiana; Akhiyar, Dinul; Arsyah, Ulya Ilhami
Jurnal Sains Informatika Terapan Vol. 3 No. 2 (2024): Jurnal Sains Informatika Terapan (Juni, 2024)
Publisher : Riset Sinergi Indonesia (RISINDO)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62357/jsit.v3i2.380

Abstract

The advancement of science facilitates the development of new technologies that signify the progress of society. MTsS Muhammadiyah Kurai Taji aims to incorporate information technology into its data processing activities. Currently, the school relies on manual methods for processing student data, which often results in inaccuracies, particularly in classifying underprivileged students and other categories. This manual approach has led to challenges in maintaining valid data, which in turn complicates the decision-making process for scholarship allocations. To address these issues, the author proposes the development of a web-based A decision Support System (DSS). A DSS is a computer-based information system designed to support organizational decision-making. The proposed system will utilize MySQL database management to ensure the accuracy and validity of the data. By implementing this web-based information system, the school will benefit from increased time efficiency in data retrieval and scholarship processing. Additionally, this system will streamline reporting processes and improve the identification of students eligible for scholarship assistance, thereby addressing the current challenges faced by the school.
Sistem Inventory Menggunakan Metode Supply Chain Management dalam Mengatur Jumlah Ketersediaan Obat pada Apotik Pratiwi, Mutiana; Ilhami Arsyah, Ulya; Pramana Gusman, Aggy; Muhammad, Abulwafa
Indonesian Journal of Informatic Research and Software Engineering (IJIRSE) Vol. 1 No. 2 (2021): Indonesian Journal of Informatic Research and Software Engineering
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (628.294 KB) | DOI: 10.57152/ijirse.v1i2.143

Abstract

The development of information technology provides great benefits and convenience, both in terms of data processing and presentation of information on inventory of existing goods in organizations, agencies or companies. One of the business processes that can be developed through information technology is the company's supply chain management process. An inventory information system using a good Supply Chain Management (SCM) method will increase the productivity and performance of the company. In conducting the research conducted at the pharmacy, the aim was to improve the old system. By conducting direct observations in the field, several weaknesses were found from the system that was running at the Arafah Padang Pharmacy. The results of the analysis are applied in an application that is able to process inventory system data using the Supply Chain Management (SCM) method. With the design of an inventory system with the Supply Chain Management (SCM) method, it can be more helpful in processing drug inventory data and the existing inventory system can increase the effectiveness and work efficiency of Pharmacy employees.
Medical Record Information System with Rapid Application Development (RAD) Method Pratiwi, Mutiana; Mayola, Liga; Kris Hiburan Laoli, Vince; Ilhami Arsyah, Ulya; Pratiwi, Nila
Journal of Information Systems and Technology Research Vol. 1 No. 2 (2022): May 2022
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/jistr.v1i2.170

Abstract

Computer technology that is increasingly developing has created a situation that demands everything to be computerized. Science from technology has also changed the way of life of most Indonesians. The presence of information and communication technology affects the technology applied in information systems, especially the input and output mechanisms. One of them is at the Clinic which requires computer technology in its operations. The design of this website also uses 3 stages of Rapid Application Development (RAD) system design, the result of which is a website for a medical record information system. In order for clinical activities to run smoothly at the Clinic, an information system using the Rapid Application Development (RAD) method is needed because the software development process model is classified as an incremental technique and emphasizes short, short, and fast development cycles. Medical record system testing will be tested using Blackbox Testing and User Acceptance Test (UAT) testing.
Deep Learning Based Technical Classification of Badminton Pose with Convolutional Neural Networks Tukino, Tukino; Pratiwi, Mutiana; Defit, Sarjon
ILKOM Jurnal Ilmiah Vol 16, No 1 (2024)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v16i1.1951.76-86

Abstract

This research aims to identify and categorize badminton strategies using a Convolutional Neural Network (CNN) model combined with BlazePose architecture and Mediapipe Pose Solution tools, yielding understandable and practical results. The challenge of finding the best mobility strategy for badminton serves as the primary motivation for this study. The research employs an image recognition and supervised learning approach to classify poses in badminton training videos. The training data comprises various photos and images representing different badminton techniques, such as Service Technique and Smash Technique. After data processing, the CNN model is trained using the training data to identify and classify poses in badminton training videos. Testing is conducted using test data, and classification accuracy is evaluated using the CNN method. The results show that the CNN model implemented alongside BlazePose and Mediapipe Pose Solution achieves significant classification accuracy, ranging from 80% to 90%. Thus, this research presents an effective and practical method for classifying badminton strategies based on poses in training videos.
Recommendation for Prospective Permanent Employees using the Simple Additive Weighting Method Haidir, Ahmad; Gushelmi; Pratiwi, Mutiana
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
Analysis of Shape and Texture Identifying and Detecting Apple Fruit Pratiwi, Mutiana; Arsyah, Ulya Ilhami
Innovative: Journal Of Social Science Research Vol. 5 No. 1 (2025): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

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

Abstract

Penelitian ini mengusulkan sebuah sistem untuk mengklasifikasikan tingkat kematangan apel dengan menggunakan metode K-Nearest Neighbor (KNN) berdasarkan fitur bentuk dan tekstur apel. Tujuan dari penelitian ini adalah untuk membantu sistem membedakan antara apel hijau dan apel merah. Proses identifikasi dimulai dengan segmentasi citra menggunakan metode KNN. Hasil segmentasi citra terlebih dahulu diubah menjadi citra biner, kemudian diubah menjadi citra grayscale. Kinerja sistem dicapai dengan mengombinasikan metode KNN dengan ekstraksi fitur citra grayscale. Fitur-fitur yang diekstraksi meliputi nilai metrik sebesar 0,5, eksentrisitas 0,2, kontras 0,1, korelasi 0,9, energi 0,3, dan homogenitas 0,9. Berdasarkan nilai-nilai tersebut, sistem mampu mengidentifikasi apel merah dengan akurat.
Pengelolaan dan Pemanfaatan Manajemen Referensi pada Penulisan Ilmiah Arsyah, Ulya Ilhami; Pratiwi, Mutiana
Journal Of Indonesian Social Society (JISS) Vol. 3 No. 1 (2025): JISS - Februari
Publisher : PT. Padang Tekno Corp

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59435/jiss.v3i1.475

Abstract

Teknologi informasi dan komunikasi telah memengaruhi hampir semua aspek kehidupan, termasuk pendidikan. Penting bagi mahasiswa untuk mengembangkan keterampilan yang diperlukan untuk beradaptasi dengan perkembangan teknologi ini. Saat ini penerapan teknologi sudah mulai pesat, tidak ada satupun kegiatan yang tidak melibatkan penggunaan komputer. Salah satu software gratis yang dapat digunakan untuk manajemen referensi pada penulisan karya ilmiah atau tugas akhir.  Pelatihan manajemen referensi merupakan kebutuhan penting bagi mahamahasiswa, khususnya dalam mendukung penyusunan karya ilmiah yang terstruktur dan terorganisir. Program pengabdian kepada masyarakat ini bertujuan untuk memberikan pelatihan manajemen referensi bagi mahamahasiswa organisasi Al-Makki Universitas Al-Azhar, Mesir. Pelatihan ini berfokus pada penggunaan perangkat lunak manajemen referensi, seperti Mendeley dan Zotero, yang memungkinkan mahamahasiswa untuk menyimpan, mengelola, serta menyusun daftar pustaka secara efisien. Metode pelatihan meliputi pembekalan teoretis, demonstrasi, dan praktik langsung, sehingga peserta dapat memahami cara mengintegrasikan aplikasi manajemen referensi dalam penulisan ilmiah mereka. Hasil dari kegiatan ini menunjukkan peningkatan kemampuan peserta dalam mengelola referensi secara otomatis, mengurangi kesalahan pengutipan, serta meningkatkan produktivitas dalam penulisan karya ilmiah. Program ini juga menjadi langkah awal dalam membangun budaya akademik yang lebih profesional di kalangan mahamahasiswa Universitas Al-Azhar, Mesir. Dari 40 peserta baik secara offline maupun online yang mengikuti kegiatan ini, sebanyak 83% berhasil memahami penggunaan aplikasi Mendeley, sementara sisanya (17%) masih mengalami kesulitan, terutama karena keterbatasan, seperti tidak memiliki laptop. Berdasarkan hasil tersebut, aktivitas ini dinilai berhasil mencapai tujuan yang diharapkan dalam program pengabdian kemitraan masyarakat.
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 (IJCS)
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 (IJCS)
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%.
Co-Authors Aggy Pramana Gusman Aminuyati Arsyah, Rahmatul Husna Arsyah, Ulya Ilhami Devia Kartika Dinul Akhiyar Gema, Rima Liana Gushelmi Haidir, Ahmad Irzal Arief Wisky Jihan Sy, Yulia Kris Hiburan Laoli, Vince kurnia, rahmi putri Liana Gema, Rima Liga Mayola Lusinia, Shary Armonitha Mardhiah, Putri Marfalino, Hari Muhammad, Abulwafa safira, silky Sarjon Defit Surmayanti, Surmayanti Tukino, Tukino Yori Adi Atma