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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 Jurnal Informasi dan Komputer Indonesian Journal of Applied Informatics JUTIS : Jurnal Teknik Informatika 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
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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. 
OPTIMASI ALGORITMA K-NEAREST (KNN) NEIGHBORS PADA PREDIKSI RISIKO PENYAKIT KARDIOVASKULAR Hidayat, Peri; Kurniawan, Rudi; Wijaya, Yudhitira Arie; Suprapti, Tati
Jurnal Informatika dan Teknik Elektro Terapan Vol. 13 No. 1 (2025)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v13i1.5864

Abstract

Penyakit kardiovaskular merupakan penyebab utama kematian di dunia, dipengaruhi oleh berbagai faktor risiko yang kompleks. Deteksi dini sangat penting untuk mencegah komplikasi serius. Penelitian ini bertujuan mengembangkan model prediksi risiko penyakit kardiovaskular menggunakan algoritma K-Nearest Neighbors (K-NN) dan menentukan nilai K optimal untuk meningkatkan akurasi prediksi. Metodologi yang digunakan adalah Knowledge Discovery in Databases (KDD), mencakup pemilihan data, pembersihan data, transformasi data, pemilihan atribut, evaluasi, dan validasi model. Dataset yang digunakan terdiri dari variabel medis seperti usia, berat badan, tekanan darah, kadar kolesterol, dan riwayat medis lainnya. Data dibagi dengan rasio 70:30 dan 80:20 untuk mengevaluasi performa model pada pembagian data yang berbeda. Hasil menunjukkan bahwa nilai K = 40 memberikan akurasi terbaik sebesar 71,00% pada rasio 70:30, sedangkan nilai K = 25 menghasilkan akurasi 71,16% pada rasio 80:20. Kesimpulan penelitian ini adalah algoritma K-NN mampu memprediksi risiko penyakit kardiovaskular dengan baik, bergantung pada pemilihan nilai K dan rasio pembagian data yang optimal. Penelitian ini berkontribusi dalam pengembangan model prediksi risiko penyakit kardiovaskular dan menjadi referensi untuk diagnosis dini di masa depan.
ALGORITMA NAIVE BAYES UNTUK MENINGKATKAN MODEL KLASIFIKASI PENERIMA PROGRAM INDONESIA PINTAR DI SDN 2 PURWAWINANGUN Darussalam, Luthvi Nurfauzi; Kurniawan, Rudi; Wijaya, Yudhistira Arie; Suprapti, Tati
Jurnal Informatika dan Teknik Elektro Terapan Vol. 13 No. 1 (2025)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v13i1.5882

Abstract

Penelitian ini bertujuan meningkatkan keakuratan klasifikasi penerima Program Indonesia Pintar (PIP) di SDN 2 Purwawinangun, Kabupaten Kuningan. Metode yang lambat dan kurang akurat digantikan dengan algoritma Naive Bayes untuk menganalisis data siswa berdasarkan kriteria tertentu. Proses penelitian meliputi pengumpulan data sekunder, preprocessing data, dan implementasi algoritma Naive Bayes. Hasilnya, model ini mencapai akurasi 96,47% dalam menentukan kelayakan penerima PIP, dengan mempertimbangkan atribut seperti latar belakang sosial ekonomi dan kinerja akademik siswa. Temuan menunjukkan bahwa algoritma ini efisien dalam mengolah dataset kompleks dibandingkan metode manual. Namun, kinerja model sangat bergantung pada kualitas data awal, sehingga data yang tidak lengkap dapat mempengaruhi hasil.Penelitian merekomendasikan penerapan metode ini di sekolah lain dan integrasi algoritma tambahan, seperti Decision Tree, untuk validasi hasil. Dengan pendekatan ini, seleksi penerima PIP menjadi lebih tepat sasaran, efisien, dan transparan.
PENERAPAN MODEL EXPERIENTAL LEARNING MELALUI METODE DISKUSI PADA MATERI PENGELOLAAN KEUANGAN SEDERHANA UNTUK MENINGKATKAN HASIL BELAJAR SISWA KELAS XII MANAJEMEN PERKANTORAN1 SMK NEGERI 1 TASIKMALAYA Suprapti, Tati
Jurnal Inovasi dan Teknologi Pendidikan Vol. 2 No. 3 (2024): Jurnal Inovasi dan Teknologi Pendidikan
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/jurinotep.v2i3.76

Abstract

The problem in this research is whether the application of the Experiential Learning Model through the Discussion Method can improve the learning outcomes of class XII MP1 students at SMK Negeri 1 Tasikmaya. The aim of the research is to increase the effectiveness of implementing the Experiential Learning Model through the Discussion Method in an effort to improve learning outcomes for Simple Financial Management Material. Perpetual Assessment Method for class The subjects in this research were 35 students of Class XII Office Management1 at SMK Negeri 1 Tasikmalaya for the 2022/2023 academic year. Student learning effectiveness is measured based on individual learning completeness criteria. The results of the research show that through the application of the Experiential Learning Model through the Discussion Method it can increase student activity and competence in simple Financial Management subjects. . This can be seen from: (1) there is an increase in student activity in each cycle. Student activity in cycle I was 37.13%, and cycle II was 76.16%; (2) there is an increase in class averages and student learning completeness. The class average in cycle I was 80 and cycle II was 87. Student learning completeness as measured by the cognitive competency test in cycle I was 66%, and cycle II was 91.62%. The conclusion from the research results regarding the Application of the Experiential Learning Model Through the Discussion Method in Class XII Office Management 1 SMK Negeri 1 Tasikmalaya was declared successful
Peningkatan Pengetahuan Masyarakat tentang Pemanfaatan Seledri (Apium graveolens L.) sebagai Antimikroba Sari, Putri Eka; Suprapti, Tati; Elsha, Dwi
Jurnal Pengabdian kepada Masyarakat Wahana Usada Vol. 7 No. 2 (2025): Desember: Jurnal Pengabdian kepada Masyarakat Wahana Usada
Publisher : Sekolah Tinggi Ilmu Kesehatan KESDAM IX/Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47859/wuj.v7i2.744

Abstract

Infections caused by pathogenic microorganisms remain a major health challenge. One preventive promotive effort to reduce infection incidence is through the use of traditional medicinal plants, such as celery (Apium graveolens L.) which is known to have antimicrobial activity. This community service program aimed to increase the knowledge of PKK cadres in Klender Urban Village regarding the antimicrobial benefits of celery through educational outreach. The activity was held on June 12, 2025, involving 14 PKK cadres as participants. Evaluation was carried out using pre-test and post-test questionnaires, analyzed using the Wilcoxon test. The results showed a significance value of 0.002 (p<0.05), indicating a significant increase in knowledge after the intervention. The average percentage of correct answer increased by 37.2%. Additionally, all of participants demonstrated good knowledge levels in the post-test and none were in the poor category. These findings indicate that education through outreach is effective in improving community understanding of celery’s antimicrobial potential. Local plant-based education is expected to be a sustainable preventive strategy to improve public health.Keywords: education, celery, antimicrobial, knowledge PKK cadres
Evaluasi Prediksi Harga Saham Nokia Menggunakan LSTM Univariat dengan Pendekatan Walk-Forward Validation Saputra, Roni; Martanto, Martanto; Dana, Raditya dana; Solihudin, Dodi; Suprapti, Tati
JURNAL TEKNIK INFORMATIKA UNIS Vol. 13 No. 2 (2025): Jutis (Jurnal Teknik Informatika)
Publisher : Universitas Islam Syekh Yusuf

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

Abstract

Prediksi harga saham merupakan tantangan sentral di pasar modal yang kompleks dan volatil.Meskipun model pembelajaran mendalam seperti Long Short-Term Memory (LSTM) telahmenunjukkan potensi, banyak penelitian mengabaikan masalah multikolinearitas pada modelmultivariat dan menggunakan metode evaluasi yang tidak realistis. Untuk mengatasi ini,penelitian ini mengembangkan model prediksi harga saham Nokia menggunakan arsitekturLSTM univariat yang hanya memanfaatkan harga penutupan, sebuah keputusan yangdidasarkan pada bukti empiris multikolinearitas tinggi antar fitur harga. Kinerja modeldievaluasi secara ketat menggunakan Walk-Forward Validation (WFV) untuk mensimulasikankondisi perdagangan nyata dan menghindari bias evaluasi. Hasilnya menunjukkan performayang sangat baik dan stabil, dengan model mampu menjelaskan 94.46% varians data (R² =0.9446) dan mencapai Mean Absolute Percentage Error (MAPE) sebesar 2.75%. Konsistensiini terbukti melalui 30 iterasi WFV, yang mengonfirmasi ketahanan model di berbagai kondisipasar. Penelitian ini menyimpulkan bahwa pendekatan model LSTM univariat yang dievaluasidengan WFV terbukti efektif dan andal, bahkan dapat menjadi pilihan superior dibandingkanmodel yang lebih kompleks. Temuan ini menegaskan bahwa relevansi fitur dan standarevaluasi yang ketat lebih krusial daripada kompleksitas arsitektur, memberikan kontribusimetodologis penting bagi pengembangan model prediksi finansial yang andal di masa depan.
Klasifikasi Telur Fertil dan Infertil Berbasis Hybrid MobileNetV3 dengan Mekanisme Attention dan Texture Fusion Bani Nurhakim; Dadang Sudrajat; Tati Suprapti; Ade Rizki Rinaldi; Agus Bahtiar
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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

Abstract

Accurate fertile-infertile egg classification is crucial to improve hatching productivity and sorting efficiency. This study proposes MobileFusionV3, a MobileNetV3 architecture enriched with CBAM (Convolutional Block Attention Module) and Hybrid Texture Fusion (LBP and GLCM) to combine deep and texture features to be more robust to candling illumination variations. A dataset of 1,275 candling images (675 fertile, 600 infertile) was subjected to preprocessing (resizing, normalization, background enhancement) and realistic data augmentation (rotation, brightness/contrast changes, Gaussian noise, illumination variations). The model was trained using transfer learning, early stopping, and an evaluation scheme based on accuracy, precision, recall, F1-score, and AUC. The test results showed an accuracy of 97.2%, precision of 96.8%, recall of 97.5%, F1 of 97.1%, and AUC of 0.99, surpassing previous designs that did not use attention mechanisms and texture fusion. Grad-CAM++ analysis confirms the model's focus on physiologically relevant regions (embryonic shadow and air-cell), thus improving the reliability of interpretation. These findings indicate that lightweight, efficient designs based on attention and texture fusion have the potential to be implemented in smart hatchery systems and edge/mobile devices while maintaining high accuracy.
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 Aini, NoviFirda Aldi Setiawan Ali Ali Alpian Novansyah, Indi Alwan Azhar Amaliah, Novi Andi Ardiansyah Andri Yanto Apriliani, Yuni Aribah, Firyal Arif Rinaldi Dikananda Arif Rinaldi Dikananda ASEP SAEFUDDIN Athaullah Abrar Bayan Auliya Bani Nurhakim Beby Maryam Camelia Putri Lestari Cep Lukman Rohmat Christian Anderson Wint's II, Hans Dadang Sudrajat Dana, Raditya dana Darussalam, Luthvi Nurfauzi Dayanti, Resda Dian Ade Kurnia Dian Ade Kurnia Dikananda, Arif Rinaldi Dodi Solihin Dodi Solihudin Doni Anggara Dwi Prasetyo Elsha, Dwi Fathurrohman, 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 Muhammad Hilmy Naufan Mulyawan Nana Siti Nurjanah Narasati, Riri Narasati Nining Rahaningsih 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 Rizki Ani, Fitri Roni Saputra, Roni 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 Solihudin, Dodi 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 Yufita, Ayura Yusuf Sidiq, Yusuf Sidiq Zaki Nur Rahmat Hidayat Zulfa Hana Aqliyah