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Yerix Ramadhani
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(JISCO) Journal of Information System and Computing
Published by Universitas Islam Negeri Sulthan Thaha Saifuddin Jambi
ISSN : -     EISSN : 30907721     DOI : https://doi.org/10.30631/jisco.v3i2
Core Subject : Science,
Computer Science & IT
Journal of Information System and Computing (JISCO) adalah jurnal ilmiah yang diterbitkan oleh Fakultas Sains dan Teknologi, UIN Sulthan Thaha Saifuddin Jambi dan dikelola oleh Program Studi Sistem Informasi. Jurnal ini bertujuan untuk menjadi wadah publikasi penelitian dan inovasi terbaru dalam bidang teknologi informasi, sistem informasi, dan ilmu komputer, khususnya yang memberikan kontribusi teoretis dan praktis untuk perkembangan disiplin ilmu tersebut Tujuan (Aim) - Mendukung penyebaran hasil penelitian berkualitas tinggi di bidang sistem informasi, teknologi informasi, dan ilmu komputer. - Menyediakan forum ilmiah bagi akademisi, peneliti, dan praktisi untuk berbagi temuan teoritis dan aplikatif dalam disiplin ilmu tersebut Fokus dan Ruang Lingkup Jurnal Sistem Informasi dan Komputer mencakup berbagai topik, antara lain: - Sistem Informasi : Analisis dan desain sistem informasi, implementasi sistem, manajemen data dan informasi, sistem informasi bisnis, dan teknologi dalam organisasi. - Ilmu Komputer : Kecerdasan buatan, pemrograman, algoritma dan struktur data, arsitektur komputer, komputasi awan, serta keamanan siber. - Teknologi Informasi : Pengembangan aplikasi, Internet of Things (IoT), Big Data, teknologi jaringan, dan sistem terdistribusi. - Manajemen SI / TI : Tata kelola teknologi, audit sistem informasi, serta kebijakan dan perencanaan strategis teknologi informasi.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 5 Documents
 1 
Search results for , issue "Vol 3 No 2 (2025): Jurnal of Information System and Computing" : 5 Documents clear
Klasifikasi Berita Hoaks Di Media Sosial Menggunakan Algoritma Naive Bayes dan RapidMiner Karimah, Ummul; Fatah, Zaehol
JISCO : Journal of Information System and Computing Vol 3 No 2 (2025): Jurnal of Information System and Computing
Publisher : UIN Sulthan Thaha Saifuddin Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30631/jisco.v3i2.4028

Abstract

The development of information technology and social media has made the distribution of information easier, but it has also increased the prevalence of fake news or hoaxes. This research aims to classify hoax and non-hoax news on social media using the Naïve Bayes algorithm with the assistance of the RapidMiner application. The data used is secondary data obtained from the Kaggle website and processed thru text preprocessing stages including tokenization, stopword removal, stemming, and TF-IDF weighting. The classification process was carried out using the Cross Validation method to measure model performance. The research results show that the Naïve Bayes algorithm has an accuracy of 90.20%, and precision values of 92.25% for the hoax class and 88.33% for the non-hoax class, with recall values of 87.78% and 92.62% respectively. These values indicate that the built classification model can easily identify hoax news. Thus, the Naïve Bayes algorithm has proven to be effective and efficient for use as a method for detecting fake news on social media. Keywords: Naïve Bayes, RapidMiner, Classification, Hoax News, Text Mining
Prediksi Resiko Penyakit Menggunakan Algoritma Random Forest sebagai Upaya Pencegahan Kesehatan Masyarakat Firdaus, Alvina Jelita; Fatah, Zaehol
JISCO : Journal of Information System and Computing Vol 3 No 2 (2025): Jurnal of Information System and Computing
Publisher : UIN Sulthan Thaha Saifuddin Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30631/jisco.v3i2.4029

Abstract

Chronic diseases influenced by lifestyle factors are a crucial public health issue, while predictive models are often limited by class imbalance and a lack of clinical interpretability. This research aims to build an accurate and transparent disease risk prediction model based on lifestyle factors. The method used is hybrid classification, combining the Random Forest algorithm with the SMOTE (Synthetic Minority Oversampling Technique) technique to effectively address the initial data imbalance (3:1 ratio) in the Health Lifestyle Dataset. This balanced data was then split 80:20 for testing. The test results show the model achieved an aggregate accuracy of 74.43%, with strong precision (79%) for the risk class, indicating prediction reliability. Feature Importance analysis provides significant clinical insights, identifying Daily Water Intake (water_intake_l) and Sleep Duration (sleep_hours) as the most dominant predictive factors, even surpassing physiological factors. The conclusion indicates that this hybrid approach is effective as an early screening instrument, with the main advantage being the transparency of lifestyle variable interpretation, which directly supports data-driven prevention strategies
Penerapan Algoritma Decision Tree untuk Klasifikasi Kelulusan Mahasiswa Berdasarkan Faktor Akademik dan Sosial Dofiyanto; Fatah, Zaehol
JISCO : Journal of Information System and Computing Vol 3 No 2 (2025): Jurnal of Information System and Computing
Publisher : UIN Sulthan Thaha Saifuddin Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30631/jisco.v3i2.4030

Abstract

This research aims to employ the C4.5 Decision Tree technique to classify the results of student graduation. This is achieved by taking into account both their scholastic performance and social factors. Scholastic performance indicators encompass the student's overall grade average, their academic status, and how often they attend classes, whereas social factors include their age, whether they are married, and their engagement in extracurricular activities. The information utilized was taken from an internal compilation of student information, which was refined and modified with the RapidMiner program. To ensure the correctness of the predictions, the categorization model was confirmed through the implementation of a 10-fold cross-validation strategy. The results of the tests demonstrated an 89.44% level of correctness, as well as a 91.38% level of precision and a 90.28% rate of recall, showing that the model functions at a level that is both remarkably successful and reliable. These discoveries reinforce the idea that the C4.5 Decision Tree algorithm is capable of accurately determining the patterns in student graduation through the integration of both scholastic and social elements. This can then act as a foundation for making scholastic decisions to improve the efficiency of the process of higher education.
Pemodelan Sistem Informasi Penggajian Berbasis Website Pada YPLP PGRI Provinsi Jambi Menggunakan Unified Modeling Language (UML) Nuraini, Adelya Pasya; Salsabila, Dinda Aura; Maryana, Siti
JISCO : Journal of Information System and Computing Vol 3 No 2 (2025): Jurnal of Information System and Computing
Publisher : UIN Sulthan Thaha Saifuddin Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30631/jisco.v3i2.5652

Abstract

Pengelolaan penggajian merupakan salah satu proses penting dalam organisasi karena berkaitan langsung dengan hak pegawai dan akuntabilitas lembaga. YPLP PGRI Provinsi Jambi masih menghadapi kendala dalam pengelolaan penggajian yang dilakukan secara semi-manual, seperti potensi kesalahan perhitungan, keterlambatan informasi, dan kesulitan dalam pengelolaan data. Penelitian ini bertujuan untuk melakukan pemodelan Sistem Informasi Penggajian berbasis website sebagai dasar pengembangan sistem yang lebih terstruktur dan efisien. Metode penelitian yang digunakan adalah analisis dan perancangan sistem dengan pendekatan Unified Modeling Language (UML). Pengumpulan data dilakukan melalui observasi, wawancara, dan studi dokumentasi untuk mengidentifikasi kebutuhan sistem. Pemodelan sistem disajikan dalam bentuk diagram UML yang meliputi use case diagram, activity diagram, sequence diagram, dan class diagram. Hasil penelitian berupa model sistem yang menggambarkan alur proses penggajian, interaksi pengguna dengan sistem, serta struktur data yang dibutuhkan. Model yang dihasilkan diharapkan dapat menjadi acuan dalam pengembangan dan implementasi sistem informasi penggajian berbasis website di YPLP PGRI Provinsi Jambi, sehingga mampu meningkatkan efektivitas, akurasi, dan transparansi pengelolaan penggajian.
Implementasi Framework Django Dalam Sistem Penjualan Sparepart Motor Menggunakan Metode Agile Irawan, Dodi; Mujahid, Putra Edi
JISCO : Journal of Information System and Computing Vol 3 No 2 (2025): Jurnal of Information System and Computing
Publisher : UIN Sulthan Thaha Saifuddin Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30631/jisco.v3i2.5672

Abstract

Bengkel Kevin Motor merupakan usaha yang bergerak di bidang penjualan suku cadang dan layananservis motor. Dalam menjalankan kegiatan operasionalnya, bengkel ini masih menggunakan sistempenjualan dan pencatatan servis secara manual, sehingga menimbulkan berbagai permasalahan sepertiduplikasi data, kesulitan dalam pencarian informasi, serta keterlambatan dalam pembuatan laporan.Tujuan dari penelitian ini adalah menganalisis dan memahami permasalahan pada sistem penjualanyang berjalan di Bengkel Kevin Motor, serta merancang sistem informasi penjualan suku cadang danservis motor berbasis web menggunakan bahasa pemrograman Python dengan framework Django.Metode pengembangan sistem yang digunakan adalah Agile dengan pendekatan pemodelan UnifiedModeling Language (UML) yang meliputi diagram aktivitas dan diagram kelas. Hasil penelitian iniberupa sistem informasi yang mempermudah pencatatan transaksi, pengelolaan stok, serta pembuatanlaporan sehingga dapat mengurangi kesalahan dan duplikasi data.

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