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Implementasi Machine Learning Untuk Prediksi Penyakit Jantung Menggunakan Algoritma Support Vector Machine Hidayat, Rahmat; Sy, Yandiko Saputra; Sujana, Teguh; Husnah, Mirdatul; Saputra, Haris Tri; Okmayura, Finanta
BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Vol 5 No 2 (2024): September
Publisher : Puslitbang Sinergis Asa Professional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37148/bios.v5i2.152

Abstract

Heart disease is currently a disease that has taken over many human lives. Data shows that more than 17 million people have died from heart disease. The high number of deaths, therefore, requires special handling to treat and prevent heart disease. In the development of technology, diagnosis of heart disease can be done with the help of information technology, one of which is through machine learning. This study aims to implement machine learning through the SVM algorithm to predict heart disease. The model formed by SVM produces an evaluation value indicated by an accuracy value of 0.85, a precision of 0.93, a recall of 0.76, and an f-1 score of 0.83. This model is used as training data to predict heart disease which is then successfully used to create a system through the Streamlit library which can be easily accessed via the website.
Implementasi Algoritma Random Forest Regression Untuk Memprediksi Penjualan Produksi di Supermarket Hidayat, Rahmat; Tri Saputra, Haris; Husnah, Mirdatul; Nabila, Nabila; Hidayatullah, M Bintang; Naufal Nazhmi, Muhammad; Azra, Jauzaa; Rana, Astri
Jurnal Sistem Informasi dan Sistem Komputer Vol 10 No 1 (2025): Vol 10 No 1 - 2025
Publisher : STIMIK Bina Bangsa Kendari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51717/simkom.v10i1.703

Abstract

Prediksi penjualan merupakan aspek penting dalam pengelolaan operasional Supermarket. Algoritma Machine Learning dapat dimanfaatkan untuk menghasilkan prediksi yang akurat. Supermarket mencatat transaksi penjualan setiap harinya, data transaksi tersebut dapat dimanfaatkan untuk mendapatkan informasi dalam memperoleh keuntungan. Pada penelitian ini, algoritma Random Forest Regression digunakan dengan tujuan untuk memprediksi penjualan di Supermarket. Data dalam dataset berjumlah 1000 data. Proses preprocessing data dimulai dengan menentukan fitur yang paling relevan sebagai variabel independen dan variabel dependen. Selanjutnya, entri kosong pada data numerik diisi dengan nilai rata-rata (mean), sedangkan pada data kategori, entri kosong diisi dengan nilai modus. Evaluasi kinerja model algoritma diukur dengan menggunakan beberapa metrik, yaitu Out-of-Bag (OOB) score sebesar 0.9999, Mean Squared Error (MSE) sebesar 2.4899, R-squared atau koefisien determinasi mencapai 0.9999, dan Mean Absolute Error (MAE) bernilai 0.9305. Secara keseluruhan, nilai-nilai metrik menunjukkan model Random Forest Regression sangat akurat untuk prediksi penjualan di supermarket.
Analysis of Public Perception on Domestic Violence Cases using Support Vector Machine Algorithm Husnah, Mirdatul; Hidayat, Rahmat
Sistemasi: Jurnal Sistem Informasi Vol 14, No 1 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i1.4724

Abstract

Domestic violence is currently a case that is easily exposed by the public. People can easily find many cases through social media. The latest case was experienced by a social media influencer, Cut Intan. This case has attracted public attention and is widely discussed on several social media, one of which is on the X app. With this phenomenon, an analysis of public sentiment towards domestic violence cases that occur in Indonesia is needed. The analysis was conducted using the Support Vector Machine algorithm, a classification algorithm that can classify values into certain classes and has a good level of accuracy. Experiments on analyzing public sentiment towards domestic violence cases using the SVM algorithm resulted in an accuracy score of 95%. The precision score for negative sentiment is 94%, neutral sentiment is 100%, and positive sentiment is 100%. The recall result for negative sentiment is 100%, neutral sentiment is 67%, and positive sentiment has a value of 77%. The results of the f-1 score on negative sentiment are 97%, 80% neutral sentiment, and 87% positive sentiment. While the percentage of community sentiment obtained is 84.40% having negative sentiment, 8.24% having positive sentiment, and 7.36% having neutral sentiment.
Sistem Informasi Manajemen Pelatihan dengan Pendekatan Research and Development di Balai PPM Pekanbaru Yani, Reny Fitri; Hidayat, Rahmat; Husnah, Mirdatul; Andriyani, Yanti; Andria, Ayu
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 5 No 1 (2025): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol5No1.pp76-84

Abstract

Adaptation to the rapid development of information technology today is something that cannot be avoided by government agencies. The Pekanbaru Community Empowerment and Training Center (Balai PPM Pekanbaru) is one of the agencies that can easily adapt to these developments. The problem faced by Balai PPM Pekanbaru is the large number of training participants in five provinces in Sumatra, making it difficult to manage training participants. This study aims to create an information system for managing training participants at Balai PPM Pekanbaru. The method used in this study is the Research and Development method. The results of the research that has been carried out are to help the Balai PPM Pekanbaru admin in managing training participants easily so that all data is centralized in a system that can work more easily and efficiently.
Users’ Perception of the Task Management System for Undergraduate Information Systems Students at Universitas Riau: Persepsi Pengguna terhadap Sistem Manajemen Tugas pada Mahasiswa Sarjana Sistem Informasi di Universitas Riau Meitarice, Sonya; Andriyani, Yanti; Aminuddin, Al; Yani, Reny Fitri; HS, Yandiko Saputra; Husnah, Mirdatul; Rahim, Normala Binti
Indonesian Journal of Informatic Research and Software Engineering (IJIRSE) Vol. 5 No. 2 (2025): Indonesian Journal of Informatic Research and Software Engineering (IJIRSE)
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/ijirse.v5i2.2302

Abstract

Dalam era persaingan akademik yang ketat, mahasiswa dihadapkan pada berbagai tanggung jawab yang sering kali sulit dikelola akibat manajemen waktu yang kurang efektif. Sistem Manajemen Pembelajaran (LMS) yang ada belum mampu membantu mahasiswa secara optimal dalam mengatur waktu dan memenuhi tenggat tugas karena keterbatasan fitur dalam mendeteksi keterlambatan sejak dini maupun melakukan pemantauan kinerja secara berkelanjutan. Penelitian ini tidak mengusulkan pengembangan sistem manajemen tugas otomatis, melainkan berfokus pada pengukuran persepsi mahasiswa terhadap kebutuhan akan task management system. Studi pendahuluan dilakukan untuk mengidentifikasi masalah yang dihadapi mahasiswa dalam pengelolaan tugas serta dampaknya terhadap kinerja akademik. Responden dalam penelitian ini terdiri dari 137 mahasiswa program sarjana yang terdaftar pada Program Studi Sistem Informasi, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Riau. Para peserta mewakili berbagai tingkat akademik, mulai dari semester dua hingga semester delapan, sehingga mencerminkan pengalaman yang beragam dalam mengelola tugas-tugas akademik.. Hasil studi menunjukkan sebagian besar responden merasa perlu meningkatkan keterampilan manajemen waktu (µ=4,32) dan menyatakan ketertarikan terhadap adanya sistem pendukung pengelolaan tugas akademik (µ=3,42). Temuan ini menegaskan bahwa mahasiswa memiliki kebutuhan yang cukup tinggi terhadap aplikasi berbasis internet yang dapat membantu memantau serta mendukung manajemen tugas secara berkesinambungan
Evaluating the Usability of Canva Among University Students in Pekanbaru Using the WEBUSE Method Hidayat, Rahmat; Andriyani, Yanti; Husnah, Mirdatul; Sinaga, Irfan; Avelia, Ririn; Maisarah, Dina; Fentika, Winda; Wulandari, Nindya
Journal of Applied Informatics and Computing Vol. 9 No. 5 (2025): October 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i5.10351

Abstract

Canva is a design platform used to create social media graphics, presentations, posters, documents, and other visual content. This study aims to evaluate user satisfaction with the web-based version of Canva using the WEBUSE method, which covers four main aspects: Content, Organization and Readability, Navigation and Links, User Interface Design, and Performance and Effectiveness. Data were collected through an online questionnaire distributed to university students in the Pekanbaru area via WhatsApp and Instagram. A total of 65 respondents were obtained through the data collection and screening process. The evaluation results show that all aspects fall into the "Good" usability category, with the highest average score in User Interface Design (0.75) and the lowest in Performance and Effectiveness (0.70), resulting in an overall average score of 0.725. Therefore, Canva’s website is considered to have good usability according to user perceptions. This study is expected to serve as input for feature development and service quality improvement of Canva in the future.