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Systematic Literature Review: Cybersecurity by Utilizing Cryptography Using the Data Encryption Standard (DES) Algorithm Annisa Desianty; Imelda Imelda
JURNAL TEKNIK INFORMATIKA Vol 17, No 1: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v17i1.37256

The world of information technology is currently developing very rapidly. This opens up opportunities in the development of computer applications, but it also creates opportunities for threats to alter and steal data or what is often known as cyber-crime. This action is a violation that can cause direct or indirect losses. Therefore, cyber-security is very important to protect user information from cyber-crime. Based on this description, this research will conduct a Systematic Literature Review (SLR) on cyber-security by utilizing cryptography using the DES algorithm. By using the SLR method, literature searches were conducted on Google Scholar or Garuda with the keywords for national journals "Data Encryption Standard Algorithm (DES)" and keywords for international journals "Data Encryption Standard Algorithm (DES)" from both national and international journals, and limiting articles from 2019 to 2023, and obtained selection results as many as 10 articles used from national journals and 10 articles used from international journals. So that this research is expected to increase the understanding of literature that reviews cyber-security by utilizing cryptography using the DES algorithm.

Implementasi Algoritma Apriori dalam Meningkatkan Strategi Penjualan pada Toko Miring Hertyana, Hylenarti; Desianty, Annisa; Rahmawati , Eva; Mufida , Elly
MEANS (Media Informasi Analisa dan Sistem) Volume 6 Nomor 2
Publisher : LPPM UNIKA Santo Thomas Medan

Toko Miring is one of the stores that sell various daily completeness needs such as food, drinks, household appliances, and others placed on shelves or storefronts. Each sales transaction data is recorded in a database system through the cashier application. According to Rahmat Fathi, supervisor at Toko Miring, at the beginning of 2020 precisely in March, The Tilt store experienced a decrease in the number of sales transactions compared to the previous year, this is because the buying and selling process in this Tilt store has many problems, one of which is the storage of sales data is still in writing. This causes buyers to have difficulty finding the desired product because the preparation of the product is not separated by type. From the problems that occurred, researchers together with Toko Miring proposed to rearrange a sales strategy to increase sales at Tilt Stores. In devising sales strategies, researchers utilize sales transaction data in previous years to be reprocessed using data mining techniques. Based on the description above, the researcher will analyze sales transaction data using data mining techniques by implementing a priori algorithms with a support value and confidence value of 50% and implementing it into the python programming language. The result of this study is that researchers managed to get sales patterns that can improve sales strategies that produce information that is useful for related parties in making sales strategy decisions such as sales packages for promos, recommending products to customers and maintaining product availability in order to increase sales intensity in some stores such as in Tilt Stores.

Systematic Literature Review: Cybersecurity by Utilizing Cryptography Using the Data Encryption Standard (DES) Algorithm Desianty, Annisa; Imelda, Imelda
JURNAL TEKNIK INFORMATIKA Vol. 17 No. 1: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v17i1.37256

The world of information technology is currently developing very rapidly. This opens up opportunities in the development of computer applications, but it also creates opportunities for threats to alter and steal data or what is often known as cyber-crime. This action is a violation that can cause direct or indirect losses. Therefore, cyber-security is very important to protect user information from cyber-crime. Based on this description, this research will conduct a Systematic Literature Review (SLR) on cyber-security by utilizing cryptography using the DES algorithm. By using the SLR method, literature searches were conducted on Google Scholar or Garuda with the keywords for national journals "Data Encryption Standard Algorithm (DES)" and keywords for international journals "Data Encryption Standard Algorithm (DES)" from both national and international journals, and limiting articles from 2019 to 2023, and obtained selection results as many as 10 articles used from national journals and 10 articles used from international journals. So that this research is expected to increase the understanding of literature that reviews cyber-security by utilizing cryptography using the DES algorithm.

SOLARISLIGHT : SISTEM PENERANGAN BERKELANJUTAN MENGGUNAKAN IOT DAN SOLAR CELL SYSTEM UNTUK EFISIENSI ENERGI PADA DESA WISATA CIASMARA Syifa Nurgaida Yutia; Aisyah Novfitri; Annisa Desianty; Alva Nurvina Sularso; Hakim Giraldi Saputra; Muhammad Nur Rizqi
Jurnal Pengabdian Masyarakat FKIP UTP Vol 7 No 1 (2026): PROFICIO : Jurnal Abdimas FKIP UTP
Publisher : FKIP UNIVERSITAS TUNAS PEMBANGUNAN SURAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36728/jpf.v7i1.6134

Kegiatan Pengabdian Masyarakat yang diadakan di desa Ciasmara di kabupaten Bogor bertujuan untuk meningkatkan infrastruktur berupa fasilitas umum penerangan lampu jalan sebagai bagian dari rencana desa Ciasmara sebagai desa wisata. Fasilitas penerangan lampu jalan berbasis IoT dan solar panel bertujuan untuk memberikan lingkungan yang aman, nyaman bagi para wisatawan, dan menciptakan energi bersih. Penerangan jalan menggunakan teknologi IoT dan Solar Panel menawarkan perawatan yang mudah dan tahan lama, dan tidak membebani biaya listrik desa. Sehingga teknologi ini menjadi solusi terbaik untuk alternatif di daerah terpencil. Tahapan implementasi program SolarisLight dimulai dengan kegiatan observasi untuk melakukan pemetaan titik penanaman tiang lampu. Proses perancangan dan pembuatan alat membutuhkan waktu satu minggu sebelum dilakukan pemasangan solar panel dan sistem IoT. Lima titik lampu penerangan ditenagai dengan kapasitas baterai sebesar 12V 300Ah dalam panel box mampu memberi ketahanan pencahayaan hingga 2 hari di malam hari. Sistem IoT yang diintegrasikan dengan panel surya memungkinkan adanya pemantauan parameter kelistrikan secara real time. Pemberian buku manual dan kegiatan sosialisasi penggunaan SolarisLight dilakukan agar masyarakat desa wisata Ciasmara dapat memonitoring sistem Solarislight melalui aplikasi yang diakses menggunakan smartphone. Hasil survei kepuasan mitra menunjukan adanya peningkatan jumlah wisatawan di desa Ciasmara setelah implementasi sitem SolarisLight. Dengan adanya hasil ini, diharapkan dapat menjadi program pengabdian masyarakat yang berkelanjutan.

STOCK PRICE PREDICTION FOR MATERIALS SECTOR USING CNN AND BI-LSTM ALGORITHM Annisa Desianty; Widang Muttaqin
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 12 No. 1 (2025): Desember 2025
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v12i1.4372

Abstract: The materials sector is one of the stock markets sectors that attracts investors due to the high level of construction activity in Indonesia, which supports long-term growth. Stock price movements are influenced by various factors, requiring investors to determine the appropriate timing for buying, selling, or holding stocks. Therefore, this study aims to predict stock prices in the materials sector using a combination of CNN–BiLSTM algorithms. The research data were obtained from Yahoo Finance and processed through min–max normalization, data splitting, sliding window, model implementation, and evaluation stages. Testing was conducted on INTP and SMGR stocks with data split scenarios ranging from 60:40 to 90:10. The results show that CNN–BiLSTM performs best with a 90:10 data split, with minimum MSE and MAPE values of 0.000153 and 2.471% for INTP, and 0.000199 and 2.208% for SMGR, respectively. These findings indicate that increasing the proportion of training data improves the model's ability to learn historical patterns and produce more stable predictions. Keywords: CNN-BILSTM; materials sector; stock Abstrak: Sektor materials merupakan salah satu sektor saham yang diminati investor karena tingginya aktivitas pembangunan di Indonesia yang mendorong pertumbuhan jangka panjang. Pergerakan harga saham dipengaruhi oleh berbagai faktor sehingga investor perlu menentukan waktu transaksi yang tepat. Oleh karena itu, penelitian ini bertujuan memprediksi harga saham sektor materials menggunakan kombinasi algoritma CNN–BiLSTM. Data penelitian diperoleh dari Yahoo Finance dan diproses melalui tahapan normalisasi min–max, pembagian data, sliding window, implementasi model, serta evaluasi. Pengujian dilakukan pada saham INTP dan SMGR dengan skenario pembagian data 60:40 hingga 90:10. Hasil menunjukkan bahwa CNN–BiLSTM menghasilkan performa terbaik pada pembagian data 90:10, dengan nilai MSE dan MAPE minimum masing-masing sebesar 0.000153 dan 2.471% untuk INTP, serta 0.000199 dan 2.208% untuk SMGR. Temuan ini mengindikasikan bahwa peningkatan porsi data latih meningkatkan kemampuan model dalam mempelajari pola historis dan menghasilkan prediksi yang lebih stabil. Kata kunci: CNN-BILSTM; saham; sektor materials

DEVELOPMENT OF PORTABLE DIAGNOSTIC TOOLS FOR RAPID DETECTION OF METAPNEUMOVIRUS IN HUMANS Widang Muttaqin; Annisa Desianty; Khansa Farah Fitriani; Aurellia Fira Artanti; Daniswara Rafi Pandora
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 12 No. 2 (2026): Maret 2026
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v12i2.4410

Abstract: Human metapneumovirus (HMPV) poses a global health threat, but its detection remains challenging due to limited environmental monitoring. This study aims to develop a portable diagnostic tool for rapid HMPV detection by integrating cutting-edge biotechnology (CRISPR-Cas system and immunoassay) with air quality sensors on an Internet of Things (IoT)-based microfluidic platform controlled by an ESP32 microcontroller. The system is supported by a companion application and data analysis using Vertex AI, and is capable of providing results in less than fifteen minutes. The development results demonstrate the potential for improving detection accuracy and reliability, particularly with further development of virus-specific biosensors, sensor optimization, and algorithms. This technology is effective as a complementary tool for early screening and environment-based risk management in areas with limited laboratory facilities, although it does not completely replace molecular diagnostic methods such as PCR. A rapid diagnostic approach based on environmental sensors, IoT, and artificial intelligence is a promising strategy to improve early HMPV detection, accelerate public health responses, and strengthen respiratory infection prevention through integrated environmental monitoring and education functions. Keywords: air quality; CRISPR-Cas; Human Metapneumovirus (HMPV); Internet of Things, portable diagnostic; public health; rapid detection; sensors. Abstrak: Human metapneumovirus (HMPV) merupakan ancaman bagi kesehatan global, namun pendeteksiannya masih sulit akibat keterbatasan pemantauan lingkungan. Studi ini bertujuan mengembangkan alat diagnostik portabel untuk deteksi cepat HMPV melalui integrasi bioteknologi mutakhir (sistem CRISPR-Cas dan immunoassay) dengan sensor kualitas udara pada platform mikrofluida berbasis Internet of Things (IoT) yang dikendalikan mikrokontroler ESP32. Sistem ini didukung aplikasi pendamping dan analisis data menggunakan Vertex AI, serta mampu memberikan hasil dalam waktu kurang dari lima belas menit. Hasil pengembangan menunjukkan potensi peningkatan akurasi dan keandalan deteksi, terutama dengan pengembangan lanjutan berupa biosensor spesifik virus, optimalisasi sensor, dan algoritma. Teknologi ini efektif sebagai alat pelengkap untuk skrining awal dan manajemen risiko berbasis lingkungan di wilayah dengan keterbatasan fasilitas laboratorium, meskipun tidak sepenuhnya menggantikan metode diagnostik molekuler seperti PCR. Pendekatan diagnostik cepat berbasis sensor lingkungan, IoT, dan kecerdasan buatan menjadi strategi menjanjikan untuk meningkatkan deteksi dini HMPV, mempercepat respons kesehatan masyarakat, serta memperkuat pencegahan infeksi saluran pernapasan melalui fungsi pemantauan dan edukasi lingkungan yang terintegrasi. Kata kunci: CRISPR-Cas; diagnostik portabel; deteksi cepat; Human Metapneumovirus (HMPV); kesehatan masyarakat; IoT (Internet of Things); sensor kualitas udara.

PENGUATAN LITERASI AI UNTUK PENCEGAHAN HOAKS DAN PENIPUAN DIGITAL PADA IBU PKK CIRIUNG-CIBINONG Yulianti; Aries Saifudin; Annisa Desianty; Adelia Chitra Sazkia; Ahmad Ridwan Fauzi
Jurnal Pengabdian Masyarakat FKIP UTP Vol 7 No 2 (2026): PROFICIO : Jurnal Abdimas FKIP UTP
Publisher : Fakultas Keguruan dan Ilmu Pendidikan Universitas Tunas Pembangunan Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36728/jpf.v7i2.6857

Kegiatan pengabdian masyarakat ini dilatarbelakangi oleh pesatnya penyebaran hoaks dan penipuan digital berbasis Artificial Intelligence (AI) yang mengancam kelompok dengan literasi digital rendah, khususnya ibu-ibu Pemberdayaan dan Kesejahteraan Keluarga (PKK). Mitra sasaran dalam kegiatan ini adalah anggota PKK RT 004 RW 003, Ciriung, Cibinong, Bogor, yang berperan sebagai manajer informasi keluarga namun rentan terhadap konten deepfake, penipuan voice cloning, serta hoaks produk kesehatan. Program dilaksanakan melalui penguatan kognitif mengenai literasi AI dan pelatihan praktis enam aplikasi verifikasi, yaitu Turn Back Hoax, Cekfakta.com, BPOM Mobile, WizeUp, Google News, dan Aplikasi Mastel, serta penerapan prosedur sederhana S.A.R.I.N.G. (Stop, Check, Evaluate, Action) sebelum membagikan informasi. Workshop dilaksanakan pada 28 April 2026 menggunakan pendekatan Participatory Technology Appraisal dan andragogi. Evaluasi dilakukan melalui kuesioner kepuasan lima pernyataan yang diisi oleh 37 responden mitra menggunakan skala Likert lima poin. Hasil evaluasi menunjukkan tingkat kepuasan yang sangat tinggi, dengan skor rata-rata keseluruhan 4,63 dari 5,00 (kategori “Sangat Baik”) dan 99,46% jawaban berada pada kategori Setuju hingga Sangat Setuju, terutama pada aspek kesesuaian materi dengan kebutuhan masyarakat serta harapan keberlanjutan kegiatan. Kegiatan ini membuktikan bahwa pelatihan literasi digital yang sederhana dan aplikatif diterima dengan sangat baik oleh masyarakat dan mampu memperkuat ketahanan keluarga terhadap misinformasi dan penipuan berbasis AI.

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