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All Journal Jurnal Informatika dan Teknik Elektro Terapan Jurnal Informatika KOPERTIP: Jurnal Ilmiah Manajemen Informatika dan Komputer Jurnal Informasi dan Komputer Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Accounting Information System (AIMS) JURSIMA (Jurnal Sistem Informasi dan Manajemen) JATI (Jurnal Mahasiswa Teknik Informatika) ICIT (Innovative Creative and Information Technology) Journal E-Link: Jurnal Teknik Elektro dan Informatika Jurnal Riset Sistem Informasi dan Teknologi Informasi (JURSISTEKNI) MEANS (Media Informasi Analisa dan Sistem) Tematik : Jurnal Teknologi Informasi Komunikasi Jurnal Teknik Informatika (JUTIF) Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD Instal : Jurnal Komputer Journal of Artificial Intelligence and Engineering Applications (JAIEA) JURSIMA BULLET : Jurnal Multidisiplin Ilmu AMMA : Jurnal Pengabdian Masyarakat Jurnal Sistem Informasi dan Manajemen Jurnal Accounting Information System (AIMS) Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer Jurnal Inovasi dan Teknologi Pendidikan SISFOTENIKA Informasi interaktif : jurnal informatika dan teknologi informasi Jurnal Informatika dan Rekayasa Perangkat Lunak
Tati Suprapti
STMIK IKMI Cirebon
Humanities Automotive Engineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Nursing Social Sciences Other

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Perbandingan Akurasi Algoritma Random Forest Dan Naïve Bayes Dalam Memprediksi Risiko Hipertensi Suprapti, Tati; Anwar, Saeful
BULLET : Jurnal Multidisiplin Ilmu Vol. 2 No. 2 (2023): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

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Abstract

Hypertension is one of the leading causes of serious health complications. Therefore, it is crucial to predict hypertension risks early to take preventive measures. This study aims to compare the accuracy of two machine learning algorithms, Random Forest and Naïve Bayes, in predicting hypertension risks using a dataset containing information about factors affecting health. Both algorithms were applied to classify patient data into two categories: high hypertension risk and low hypertension risk. Based on testing using evaluation metrics such as accuracy, precision, recall, and F1-score, the results showed that the Random Forest algorithm performed better than Naïve Bayes, with higher accuracy and more consistent performance. This finding can be used as a reference for the development of a decision support system for early hypertension detection in the community.
Pelatihan Keamanan Siber Dasar Untuk Pelajar Dan Guru Di Sekolah Menengah Suprapti, Tati; Hayati, Umi; Azhar, Alwan; Ardiansyah, Andi
AMMA : Jurnal Pengabdian Masyarakat Vol. 2 No. 4 (2023): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

Cybersecurity is an effort that aims to protect computer systems, networks, software, and data from various digital threats such as hacking, malware, phishing, ransomware, and other attacks that can cause both material and non-material losses. In the rapidly growing digital era, especially in educational environments such as secondary schools, awareness of the importance of cybersecurity is crucial. Students and teachers who use digital devices in the teaching and learning process are often easy targets for cyber criminals who are looking for loopholes to exploit security vulnerabilities. A basic understanding of cybersecurity needs to be instilled in students and teachers so that they can identify potential threats and implement appropriate preventive measures. This article aims to provide practical guidance in recognizing common types of cyber threats, such as phishing attacks that masquerade as legitimate sites or messages, malware that infiltrates through infected software, and ransomware attacks that encrypt data for ransom. In addition, the article also outlines a number of prevention strategies that students and teachers can implement, including the use of strong passwords, regular software updates, and managing privacy on social media. By understanding the basic concepts of cybersecurity and adopting best practices in protecting digital data and devices, it is hoped that students and teachers can reduce the risks that may arise from unsafe digital activities. Furthermore, effective cybersecurity implementation can create a safer and more conducive learning environment for all parties involved.
Digitalisasi Administrasi Desa Melalui Pelatihan Pengelolaan Data Berbasis Sistem Informasi Arie Wijaya, Yudhistira; Suprapti, Tati; Abrar Bayan, Athaullah; Maryam, Beby
AMMA : Jurnal Pengabdian Masyarakat Vol. 2 No. 4 (2023): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

The rapid development of information technology has encouraged educational institutions and village government institutions to improve the efficiency of administrative services, one of which is in terms of recording attendance. This research aims to develop a QR Code-based attendance system implemented for schools and village institutions as a solution to the manual attendance system that is still vulnerable to fraud and inefficiency. The system development method used is the waterfall method which includes the stages of needs analysis, system design, implementation, testing, and maintenance. This system is designed using PHP programming language and MySQL database, and integrated with QR Code technology that allows users to scan through mobile devices. The test results show that this system is able to record attendance in real-time, generate reports automatically, and improve the accuracy and efficiency of the attendance process. Users also responded positively to the system's simple and easy-to-use interface. With this system, educational institutions and villages can manage attendance data more effectively and transparently. In conclusion, this QR Code-based attendance system is a relevant and applicable innovation in supporting administrative digitization at the local level. This research is expected to be a reference for the development of similar systems in other environments.
Peningkatan Kompetensi Guru melalui Pelatihan Google Workspace dalam Pembelajaran Digital Tati Suprapti; Umi Hayati; Abdul Hakim; Abdul Mukhyidin
AMMA : Jurnal Pengabdian Masyarakat Vol. 1 No. 04 (2022): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

The development of information and communication technology (ICT) requires the world of education to adapt, especially in the learning process. Teachers as the frontline in education must have competence in utilizing ICT, one of which is through the use of Google Workspace. This study aims to improve teachers' competence in utilizing Google Workspace through training activities. The method used is training with a participatory approach and hands-on practice. This activity was carried out in the form of workshops attended by teachers from various levels of education, focusing on the utilization of Google applications such as Google Classroom, Google Drive, Google Docs, and Google Meet. The results of the activity show an increase in teachers' understanding and skills in operating Google Workspace, which has an impact on increasing the effectiveness of online and offline learning. This training also encourages teachers to be more creative in preparing teaching materials, managing digital classes, and building better interactions with students. The conclusion of this activity is that training on the use of Google Workspace is effective in improving teacher competence in the use of learning technology. It is expected that similar activities can be carried out in a sustainable manner to support digital transformation in education.
OPTIMASI NILAI DAVIES BOULDIN INDEX PADA PROGRAM PENDAFTARAN TANAH SISTEMATIS LENGKAP (PTSL) MENGGUNAKAN ALGORITMA K-MEANS DAN PCA Naufan, Muhammad Hilmy; Kurniawan, Rudi; Suprapti, Tati
E-Link: Jurnal Teknik Elektro dan Informatika Vol. 20 No. 1: Mei 2025
Publisher : Universitas Muhammadiyah Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30587/e-link.v20i1.9063

Abstract

Penelitian ini bertujuan mengoptimalkan proses clustering data program Pendaftaran Tanah Sistematis Lengkap (PTSL) dengan mengimplementasikan algoritma K-Means yang dikombinasikan dengan Principal Component Analysis (PCA) dan mengevaluasi hasilnya menggunakan Davies Bouldin Index (DBI). Dalam metode penelitian yang diterapkan meliputi pengumpulan data dari Desa Bandorasawetan, Kecamatan Cilimus, Kabupaten Kuningan, pemilihan data, transformasi data, data mining, dan interpretasi/evaluasi. Hasil penelitian menunjukkan bahwa klaster yang optimal dicapai pada K = 5 dengan pendekatan Fixed Number menggunakan 1 Number of Components yang mempertahankan atribut NJOP Bangunan. Atribut ini memiliki distribusi yang lebih terpusat dalam satu cluster dalam arti memiliki pola yang konsisten, dengan nilai DBI sebesar 0.049, memiliki kinerja lebih baik dibandingkan K-Means tanpa PCA dengan DBI mencapai 0.466. Dari total 5 klaster yang terbentuk, cluster terbaik yang teridentifikasi berdasarkan hasil selisih rata-rata antara avg. within centroid distance dan avg. within centroid distance_cluster yaitu cluster 0, karena memiliki jarak terdekat dengan komponen utama (PC1) sebesar 128918767.1. Studi ini diharapkan dapat meningkatkan kualitas dalam pengelolaan data pertanahan agar menjadi lebih efektif.
ANALISIS SISTEM INFORMASI STMIK IKMI CIREBON MENGGUNAKAN WEBQUALITY (WEBQUAL) Saefuddin, Asep; Suprapti, Tati; Wijaya, Yudhistira Arie
MEANS (Media Informasi Analisa dan Sistem) Volume 8 Nomor 1
Publisher : LPPM UNIKA Santo Thomas Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54367/means.v8i1.2502

Abstract

This study focuses on the quality of STMIK IKMI Cirebon's website, which serves as an information system for the campus. The website provides information on various aspects of the school and can significantly impact user satisfaction. The study aims to measure the website's quality based on user perceptions using Webqual, a technique that measures usability, information, and interaction quality. The results can help improve the information system of the website and provide data on its quality. The study highlights the importance of website quality and user satisfaction, and the usefulness of Webqual as a tool for measuring website quality and improving user experience. By prioritizing website quality and user satisfaction, organizations can create more effective and efficient information systems that meet users' needs
Analisis Sentimen Program Tabungan Perumahan Rakyat Menggunakan Metode Naïve Bayes Amaliah, Novi; Kurniawan, Rudi; Suprapti, Tati
SISFOTENIKA Vol. 15 No. 2 (2025): SISFOTENIKA
Publisher : STMIK PONTIANAK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30700/sisfotenika.v15i2.553

Abstract

Tabungan Perumahan Rakyat (Tapera) adalah program pemerintah yang mewajibkan pekerja berpenghasilan sebesar upah minimum untuk menyisihkan 3% dari gaji mereka untuk iuran kepada BP Tapera. Program ini telah memicu berbagai tanggapan dari masyarakat yang diungkapkan melalui media sosial, khususnya Twitter. Penelitian ini bertujuan untuk menganalisis sentimen publik terhadap Tapera dan menentukan rasio dari training dan testing data yang menghasilkan nilai akurasi terbaik menggunakan algoritma Naïve Bayes. Data dikumpulkan melalui crawling dari Twitter kemudian diproses dengan tahap pre-processing, pelabelan manual oleh ahli ke dalam sentimen positif, netral, dan negatif, dan dilakukan resampling agar data seimbang. Kemudian, visualisasi data dan pengujian model Naïve Bayes dengan tiga rasio yaitu 70:30, 80:20, dan 90:10. Hasil penelitian menunjukkan bahwa pada rasio 70:30, model memperoleh akurasi sebesar 85%. Akurasi meningkat menjadi 87% pada rasio 80:20, namun sedikit menurun menjadi 86% pada rasio 90:10. Temuan ini mengindikasikan bahwa rasio 80:20 memberikan akurasi tertinggi dan merupakan rasio yang paling optimal untuk model. Penelitian ini menegaskan pentingnya distribusi data yang seimbang dan pemilihan rasio data yang tepat dalam meningkatkan performa model Naïve Bayes pada analisis sentimen.
Optimalization of Grouping Models on Sales Transaction Data in the Josi.Id Store Using the K-Means Algorithm Dayanti, Resda; Kurniawan, Rudi; Suprapti, Tati
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 6 No. 1 (2025): Volume 6 Number 1 March 2025
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jatika.v6i1.21

Abstract

This study aims to optimize the K-Means algorithm to improve the clustering model of fashion goods sales transaction data at the josi.id store over a period of seven months. One of the main challenges is the lack of understanding of the characteristics of sales transaction data at the josi.id store, as well as the difficulty in identifying products that cause spikes on big days. With the K-Means clustering method used to group data, the optimal K value, attributes that affect the Davies Bouldin index (DBI) value. The analysis of the results shows that the key attribute that affects the k value is the TYPE OF ITEM with K = 3 as the optimal value, has the lowest DBI value of 0.258 compared to other cluster configurations. With the characteristics of cluster 0 (429 items) showing dominant sales during the Eid season. Cluster 1 (343 items) shows high sales during the holiday period. Cluster 2 (309 items) has stable sales during weekdays. These results show good separation and uniformity of clusters in each cluster. The attribute of ITEM TYPE, based on the characteristics of each cluster is Bracket clothes products show the highest total sales of up to 7 million, supported by traffic (love feature) that is often viewed. Blouses have total sales of under 2 million, while dresses show great variation with total sales between 1 and more than 3 million. Skirts have a more diverse sales distribution, with transactions reaching 3 million. which includes categories such as Dresses, bracket clothes, Tops, and Skirts, plays an important role in grouping sales transaction data, especially for seasonal products such as during Eid.
A Decision Tree Model with Grid Search Optimization for Scholarship Recipient Classification Suprapti, Tati; Nurhakim, Bani; Warni Ayu Hermina, Bintang; Syahputra Simbolon, Vrendi Amro
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 5 (2025): JUTIF Volume 6, Number 5, Oktober 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.5.5235

Abstract

This study aims to classify scholarship recipients using the Decision Tree algorithm implemented in RapidMiner. The dataset consists of 1.404 records with socioeconomic and academic attributes. Preprocessing was conducted using two Replace Missing Value operators, where categorical attributes such as No. BANTUAN, No. KKS, and Prestasi were filled with "Tidak Punya," while Kepemilikan Rumah was imputed using the average value. The model was built using a Decision Tree algorithm, optimized with the Optimize Parameters (Grid) operator to determine the best values for maximal depth and confidence. Evaluation was performed using 10-fold Cross Validation to ensure reliability. The results show that the optimized Decision Tree model achieved a high accuracy of 97.72%, with strong precision, recall, and F1-score values in both the "Eligible" and "Not Eligible" classes. These findings demonstrate that the Decision Tree algorithm, when properly optimized and validated, can effectively support decision-making processes in scholarship eligibility classification. The model provides an interpretable and robust tool for educational institutions to evaluate student applications based on critical socioeconomic features, This research contributes to educational data mining by offering a validated and interpretable model that enhances fairness, transparency, and efficiency in the scholarship selection process.
IMPLEMENTASI ALGORITMA K-MEANS DALAM MENGELOMPOKAN KABUPATEN/KOTA DI JAWA BARAT BERDASARKAN JENIS DAN JUMLAH POTENSI OBJEK DAYA TARIK WISATA Habiballoh, Hafshoh; Faqih, Ahmad; Suprapti, Tati
Jurnal Informatika dan Teknik Elektro Terapan Vol. 12 No. 2 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i2.4270

Abstract

Penelitian ini bertujuan untuk mengelompokan wilayah potensi objek daya tarik wisata (ODTW) di Jawa Barat berdasarkan jenis dan jumlah lokasi menggunakan algoritma K-Means Clustering. Data yang digunakan diperoleh dari Open Data Jabar yang mencakup jumlah potensi objek daya tarik wisata (ODTW) berdasarkan jenis dan wilayah di Jawa Barat tahun 2022. Metode penelitian yang digunakan adalah Knowledge Discovery in Database (KDD) yang meliputi tahapan pendahuluan, Literature Review, pengumpulan data, analisis data, dan penutup. Hasil analisis menunjukkan adanya tiga klaster utama: Klaster 0 dengan kategori tinggi, Klaster 1 dengan kategori sedang, dan Klaster 2 dengan kategori rendah. 
Co-Authors Abdul Hakim Abdul Mukhyidin Abrar Bayan, Athaullah Achmad Suharno Adam Firmansyah Ade Irma Purnamasari Ade Irma Purnamasari Aditia agus bahtiar Ahmad Faqih Ahmad Faqih Aldi Setiawan Ali Ali Alpian Novansyah, Indi Amaliah, Novi Andi Ardiansyah Andri Yanto Apriliani, Yuni Aribah, Firyal Arif Rinaldi Dikananda ASEP SAEFUDDIN Auliya Azhar, Alwan Cep Lukman Rohmat Christian Anderson Wint's II, Hans Darussalam, Luthvi Nurfauzi Dayanti, Resda Dian Ade Kurnia Dodi Solihin Doni Anggara Dwi Prasetyo Faujatun Hasanah Fazrian, Vivi Feri Irawan Irawan Fikri, Achmad Fitri Adha Hariyati Airi Fitriani Agustina Fitriani Fitriani Gifthera Dwilestari Gifthera Dwilestari Gilang Perwati, Intan Gilang Ramadhan Gustiani Regina Pratama Putri Gustino, Gustino Habiballoh, Hafshoh Hadianti, Isan Hafshoh Habiballoh Hajaroh, Hajaroh Hartati Hartati Hayati, Umi Hendriyansyah, Hendriyansyah Hidayat, Manarul Hidayat, Muhamad Taufiq Hidayat, Peri Husni Mubarok Ilham Kurniawan Imam Arifin imam maulana, imam Indrawan, Heru Irfan Ali Irma Purnamasari, Ade Kaslani Khoirunisa, Irma Lestari, Hasanah Lukman Rohmat, Cep Mahda, Muhammad Manarul Hidayat Martanto . Maryam, Beby Muhaimin, Ahmad Muhamad Basysyar, Fadhil Mulyawan Nana Siti Nurjanah Narasati, Riri Narasati Naufan, Muhammad Hilmy Nining Rahaningsih Nur Amalia Nurhakim, Bani Nurmala, Sri Pratiwi, Intan Purnamasari, Ade Irma Raditya Danar Dana Rananda Deva Rian Raudotul Janah, Fina Rini Astuti Rini Astuti Riri Narasati Rizki Ani, Fitri Rosdiana Rosdiana Rudi Kurniawan Rudi Kurniawan Rudi Kurniawan Ruli Herdiana Ryan Hmonangan Saeful Anwar Saeful Anwar, Saeful Sajidan, Dzikri Santi Nurjulaiha Shalihah, Ghina Shinta Virgiana Silalahi, Ryan H Siti Aisah, Iis siti azhar Sri Nurmala, Ai Suarna, Nana Suharno, Achmad Sukma Maula, Intan Syahputra Simbolon, Vrendi Amro Syajida, Hanna Syaripah, Imas Tegar Lazuardi, Muhammad Tengku Riza Zarzani N Tohidi, Edi Tri Aditama Tri Gustiane, Indri Umi Hayati Umi Hayati Utami Aryanti Vinna Agustina Wahyudin, Edi Warni Ayu Hermina, Bintang Widiawati, Fitri Widisa Adi Kumara Wijaya, Yudhitira Arie Willy Prihartono Yudhistira Arie Wijaya Yusuf Sidiq, Yusuf Sidiq Zaki Nur Rahmat Hidayat Zulfa Hana Aqliyah