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All Journal Jurnal Informatika dan Teknik Elektro Terapan Jurnal Informatika KOPERTIP: Jurnal Ilmiah Manajemen Informatika dan Komputer Angkasa: Jurnal Ilmiah Bidang Teknologi Pelita : Jurnal Penelitian dan Karya Ilmiah Jurnal Informasi dan Komputer Indonesian Journal of Applied Informatics 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 Jurnal Mahasiswa Sistem Informasi (JMSI) Instal : Jurnal Komputer Jurnal Pengabdian kepada Masyarakat Wahana Usada Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) 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 Jurnal Informatika
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 Health Professions 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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Peningkatan Efisiensi Model Asosiasi Pada Data Transaksi Penjualan Sembako Dengan Algoritma FP-Growth Yusuf Sidiq, Yusuf Sidiq; Kurniawan, Rudi; Suprapti, Tati
Informasi Interaktif : Jurnal Informatika dan Teknologi Informasi Vol 10 No 1 (2025): JII Volume 10, Number 1, Januari 2025
Publisher : Program Studi Informatika Fakultas Teknik Universitas Janabadra

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Abstract

Dengan meningkatnya volume data transaksi di sektor ritel, termasuk toko sembako, analisis pola transaksi menjadi kebutuhan penting untuk mendukung pengambilan keputusan berbasis data. Penelitian ini bertujuan untuk mengidentifikasi aturan asosiasi yang memenuhi kriteria minimum support sebesar 0,95 dan minimum confidence sebesar 0,94, serta mengungkap pola transaksi signifikan dalam data penjualan. Analisis ini diharapkan dapat memberikan wawasan penting untuk mengoptimalkan pengelolaan stok dan merancang strategi promosi yang lebih efektif. Penelitian ini menerapkan metode Knowledge Discovery in Database Process (KDD), yang meliputi beberapa tahapan: pengumpulan data transaksi penjualan, preprocessing untuk membersihkan dan menyusun data, transformasi data ke format yang sesuai untuk analisis, penerapan algoritma FP-Growth untuk menghasilkan aturan asosiasi, serta evaluasi hasil. Data yang digunakan berasal dari transaksi toko sembako dalam periode tertentu yang mencakup berbagai jenis produk.Hasil eksperimen menunjukkan bahwa tidak ada aturan asosiasi yang memenuhi kriteria minimum support 0,95 dan minimum confidence 0,94. Namun, analisis lebih lanjut menemukan bahwa item dengan nilai support tertinggi adalah beras, dengan nilai sebesar 0,912. Selain itu, pola asosiasi dengan confidence tertinggi adalah kombinasi daging sebagai premis dan beras sebagai konklusi, dengan nilai confidence sebesar 0,941. Hasil ini menunjukkan bahwa meskipun kriteria awal tidak terpenuhi, pola pembelian tertentu tetap dapat dimanfaatkan untuk analisis mendalam. Diskusi penelitian ini menyoroti potensi algoritma FP-Growth dalam mengidentifikasi pola transaksi yang relevan, meskipun diperlukan penyesuaian parameter awal. Penelitian ini memberikan kontribusi praktis bagi pengelolaan toko sembako, khususnya dalam pengaturan stok dan strategi promosi berbasis data. Penelitian lanjutan disarankan untuk menggunakan dataset yang lebih besar serta parameter yang lebih fleksibel guna mendapatkan hasil yang lebih komprehensif.
Optimizing Sentiment Analysis on the Linux Desktop Using N-Gram Features Hidayat, Muhamad Taufiq; Kurniawan, Rudi; Suprapti, Tati
Jurnal Informatika Vol 12, No 1 (2025): April
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/inf.v12i1.24773

Abstract

Linux, or GNU/Linux, is a widely used open-source operating system built on the Linux kernel that is available for anyone to use, known for its security and privacy advantages. With advancements in information technology, protecting privacy has become increasingly challenging due to data extraction practices done by major tech companies. This has encouraged some Mastodon users to switch to Linux, with many expressing their opinions on using Linux as their main operating system. This research seeks to analyze the sentiments of Mastodon users toward Linux through sentiment analysis to understand whether the trend is predominantly positive, negative, or neutral. The methodology used includes collecting data with the help of the Mastodon.py library witch then gets manually labelled with the assistance of a linguistic expert as well as a linguistic rule proposed by previous research. The text mining process includes preprocessing steps which includes feature extraction with n-Gram to gain the most optimize result as well as employing feature selection using TF-IDF. The Naïve Bayes algorithm is employed for text classification. The entire process of data analysis is conducted with the help of AI Studio (RapidMiner) software. The results show that the highest-performing model for sentiment analysis is achieved with an n-gram value of 3, revealing user sentiment polarity towards Linux on Mastodon as follows: 42% positive, 28% negative, and 30% neutral. The sentiment analysis model has an accuracy of 63%, with a precision of 70%, recall of 80%, and an f1-score of 74% which shows that this method is able to optimize the sentiment analysis process.
Clustering Data on Participants’ Reactions to Online Shop Posts on Facebook Using K-Means Algorithm With Elbow Method Technique Arifin, Imam; Rahaningsih, Nining; Suprapti, Tati; Narasati, Riri
Bahasa Indonesia Vol 15 No 02 (2023): Instal : Jurnal Komputer Periode (Juli-Desember)
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalkomputer.v15i02.132

Abstract

One of the social media platforms that not only serves as a place to share stories and statuses but also as a place to sell is Facebook. The data used is a dataset from Kaggle totaling 6666 data with 10 attributes and then sampled with the Slovin technique and obtained 377 sample data which will be processed using RapidMiner software with K-Means Algorithm and then optimized with Elbow Method technique, evaluation using (Cluster Distance Performance) to find the average within centroid distance value and the Davies-Bouldin Index (DBI) value. The results obtained are, the average within centroid distance value of the 3rd clustering is proven in the cluster distance performance operator obtained ???? = 3: 200237.353, ????=5: 118343.557, ????=7: 75339.476, then the ideal of clusters in this study proven by the Elbow Method is when ???? = 5, and Davies-Bouldin Index (DBI) value which is close to zero is when ???? = 3 with a value of k = 3: 0.394. In addition, clustering based on the number of likes and comments can help sellers identify the most active group of participants and potentially become loyal customers.
Implementasi Game Edukasi Berbasis Android Dalam Pembelajaran Alat Musik Tradisional Jawa Barat Suprapti, Tati; Apriliani, Yuni
BULLET : Jurnal Multidisiplin Ilmu Vol. 3 No. 2 (2024): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

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Abstract

Indonesia is a country that is rich in culture, one of the famous ones from Indonesia is its traditional musikal instruments, especially the West Java area which has many musikal instruments called waditra. Waditra is a term for sound instruments commonly used as traditional musikal instruments. Limitations occur because of the impossibility of teaching staff to directly show some musikal instruments from West Java in the learning process of Cultural Arts in recognizing musikal instruments. By utilizing the provision of applications that contain elements of education, it gives birth to new ways in one's learning process. From the problems that occur, to overcome them by making an educational game in introducing musikal instruments from the regions in Indonesia. By introducing the identity of each of these musikal instruments, it is able to provide insight to the children of SD Negeri Cidenok, Majalengka Regency. Based on the ADDIE development method (Analysis, Design, Development, Implementation, Evaluation), able to make educational games that are useful for learning media systematically for children at SD Negeri Cidenok, Majalengka Regency. The results obtained from blackbox testing, which is to test the functions in the game so that it runs well. In this trial, it was found that every game scene functions and runs properly so that this research is said to be successful because the game is worthy of being used as an innovative and creative learning medium and helps children in understanding local musikal instruments.
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.
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 Achmad Fikri Achmad Suharno Adam Firmansyah Ade Irma Purnamasari Ade Irma Purnamasari Ade Rizki Rinaldi Aditia agus bahtiar Ahmad Faqih Ahmad Faqih Ahmad Muhaimin Ahmad Rifai Ikhsanudin Ai Sri Nurmala Aldi Setiawan Ali Ali Alpian Novansyah, Indi Alwan Azhar Amaliah, Novi Andi Ardiansyah Andri Yanto Apriliani, Yuni Aribah, Firyal Arif Rinaldi Dikananda ASEP SAEFUDDIN Athaullah Abrar Bayan Auliya Ayura Yufita Bani Nurhakim Beby Maryam Camelia Putri Lestari Cep Lukman Rohmat Christian Anderson Wint's II, Hans Dadang Sudrajat Darussalam, Luthvi Nurfauzi Dayanti, Resda Dian Ade Kurnia Dian Ade Kurnia Dodi Solihin Dodi Solihudin Doni Anggara Dwi Prasetyo Elsha, Dwi Fathurrohman Faujatun Hasanah Fazrian, Vivi Feri Irawan Irawan 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 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 Mahda, Muhammad Manarul Hidayat Martanto . Muhamad Basysyar, Fadhil Muhamad Taufiq Hidayat Muhammad Hilmy Naufan Mulyawan Nana Siti Nurjanah Narasati, Riri Narasati Nining Rahaningsih NoviFirda Aini Nur Amalia Nurhakim, Bani Nurmala, Sri Odi Nurdiawan Pratiwi, Intan Purnamasari, Ade Irma PUTRI EKA SARI, PUTRI EKA Raditya Danar Dana Rananda Deva Rian Raudotul Janah, Fina Rini Astuti Rini Astuti Riri Narasati Rizaldy, Farhan 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 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 Utami Aryanti Vinna Agustina Wahyudin, Edi Warni Ayu Hermina, Bintang Widiawati, Fitri Widisa Adi Kumara Wijaya, Yudhitira Arie Willy Prihartono Yoga Nugraha Yudhistira Arie Wijaya Yusuf Sidiq, Yusuf Sidiq Zaki Nur Rahmat Hidayat Zulfa Hana Aqliyah