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All Journal Jurnal Algoritma JURNAL MEDIA INFORMATIKA BUDIDARMA JMPM: Jurnal Matematika dan Pendidikan Matematika JSI (Jurnal sistem Informasi) Universitas Suryadarma CSRID (Computer Science Research and Its Development Journal) JOURNAL INFORMATICS, SCIENCE & TECHNOLOGY JISICOM (Journal of Information System, Infomatics and Computing) Journal of Information System, Applied, Management, Accounting and Research Cyber Security dan Forensik Digital (CSFD) Jurnal Jaring SainTek Jurnal Manajemen Informatika Jayakarta Journal of Students‘ Research in Computer Science (JSRCS) Jurnal Algoritma Journal of Information Technology and Cyber Security Journal of Computer Science Contributions (Jucosco) Jurnal Rekayasa Informasi Journal of Informatics and Information Security Journal of Information Technology Jurnal Esensi Infokom : Jurnal Esensi Sistem Komputer dan Informasi
Ratna Salkiawati
Informatika, Fakultas Ilmu Komputer, Universitas Bhayangkara Jakarta Raya
Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics

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PENERAPAN METODE SIMPLE ADDITIVE WEIGHTING UNTUK PENERIMAAN BANTUAN LANGSUNG TUNAI DANA DESA Hendarman Lubis; Ratna Salkiawati; Sudirman Hala
JSI (Jurnal Sistem Informasi) Universitas Suryadarma Vol. 9 No. 1 (2022): JSI (Jurnal sistem Informasi) Universitas Suryadarma
Publisher : Fakultas Ilmu Komputer dan Desain - Unsurya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35968/jsi.v9i1.842

Abstract

The pandemic COVID-19 was entered Indonesia in early 2020 and has impact to economic people. BLT-Dana Desa is a government program to reduce the impact of the pandemic COVID-19. The selection of BLT-Dana Desa recipients still uses the manual method, not mathematically and the number of residents must be selected so that the selection takes longer. The purpose of this study is to design a decision support system in determining the priority of BLT-Village Fund recipients with mathematical calculations so that they can provide priority proposals, speed up the selection process and maximize the level of accuracy of targeting BLT-Village Fund recipients. This determination uses the method Simple Additive Weighting with the criteria of welfare level, age, gender and occupation. This method can make a more precise assessment because it is based on predetermined criteria and preference weights and can rank potential beneficiaries. From the results obtained, Sueb became the main priority for the beneficiary with a preference value of 1, followed by Ucok with a preference value of 0.96 and Udin with a value of 0.8667. Keywords: Bantuan Langsung Tunai Dana Desa (BLT-Dana Desa);  Simple Additive Weighting (SAW); COVID-19.
SISTEM INFORMASI KPR BERBASIS WEB MENGGUNAKAN METODE PROTOTYPE PADA PT XYZ Hendarman Lubis; Ratna Salkiawati; Cornelies Oktavianus
JSI (Jurnal Sistem Informasi) Universitas Suryadarma Vol. 9 No. 2 (2022): JSI (Jurnal sistem Informasi) Universitas Suryadarma
Publisher : Fakultas Ilmu Komputer dan Desain - Unsurya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35968/jsi.v9i2.916

Abstract

Sistem Informasi KPR berbasis Web menggunakan metode Prototype pada PT. XYZ. Penelitian ini membahas tentang sistem informasi KPR dengan teknologi web pada PT. XYZ. Terdapat masalah pada proses penyampaian informasi KPR kepada konsumen dari PT. XYZ yang mengharuskan konsumen datang ke kantor pemasaran untuk mengetahui proses KPR mereka serta pendataan konsumen dan laporan ditulis manual pada kertas yang dapat hilang atau tercecer. Metode yang dipergunakan untuk pengembangan perangkat lunak adalah metode prototipe. Hasilnya menunjukan konsumen dapat mengetahui informasi proses KPR mereka dengan mengakses sistem informasi KPR tanpa harus datang  ke kantor pemasaran, karyawan PT. XYZ dapat menginput data secara komputerisasi pada sistem informasi KPR dan laporan untuk manager tersajikan sesuai kebutuhan. Kata kunci: KPR, Sistem Informasi KPR, Metode Prototype
PENERAPAN IMAGE CLASSIFICATION PADA APLIKASI PEMBELAJARAN BAHASA ISYARAT INDONESIA (BISINDO) BERBASIS ANDROID Ratna Salkiawati; M. Khaerudin; Hendarman Lubis; Bima Bagaskhoro
JSI (Jurnal Sistem Informasi) Universitas Suryadarma Vol. 11 No. 1 (2024): JSI (Jurnal sistem Informasi) Universitas Suryadarma
Publisher : Fakultas Ilmu Komputer dan Desain - Unsurya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35968/jsi.v11i1.1126

Abstract

AbstrakSistem pembelajaran dengan menggunakan image classification dalam pembelajaran bahasa isyarat indonesia atau dikenal dengan BISINDO untuk membantu masyarakat tunarungu maupun masyarakat non tunarungu dalam mempelajari bahasa isyarat masih dibutuhkan. Melihat sistem Android yang saat ini banyak digunakan oleh masyarakat, maka dari itu di kembangkanlah Penerapan Image Classification Pada Aplikasi Pembelajaran Bahasa Indonesia (BISINDO) Berbasis Android. Tujuannya ialah pengguna yang ingin mempelajari bahasa isyarat dapat mempelajarinya secara mandiri, dimana pengecekan pola tangan dilakukan dengan Image Classification secara otomatisasi didalam aplikasi android guna memudahkan pengguna. Pengembangan aplikasi ini menggunakan metode waterfall dan menggunakan citra yang dilatih dengan algoritma Convolutional Neural Network serta pengelolaan data menggunakan Personal Home Page (PHP) dan MySql berbasis restFull API serta Kotlin digunakan dalam pemrograman aplikasi Android. Hasil dari penelitian ini dapat membantu pembelajaran bahasa isyarat indonesia dengan aplikasi android dengan persentase akurasi model sebesar 98% yang dapat membantu pengecekan secara otomatisasi dalam aplikasi android. Keywords: Bahasa Isyarat; BISINDO; Image Classification; Android  
Prediksi Penjualan Produk Sepatu dengan Menggunakan Algoritma K-Nearest Neighbor Regression dan Cross Validation Ratna Salkiawati; Hendarman Lubis; Nurfiyah Nurfiyah
JSI (Jurnal Sistem Informasi) Universitas Suryadarma Vol. 12 No. 1 (2025): JSI (Jurnal sistem Informasi) Universitas Suryadarma
Publisher : Fakultas Ilmu Komputer dan Desain - Unsurya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35968/jsi.v12i1.1329

Abstract

Penjualan sepatu di Toko “X” mencakup berbagai merek, seperti Fladeo, Cardinal, dr. Kevin, dan Jackson. Sistem pengelolaan data penjualan di toko ini pada saat penelitian masih menggunakan pencatatan secara manual, di mana hasil penjualan hanya diproses dalam format MS Excel. Untuk memudahkan pengelolaan dan perencanaan penjualan di masa depan, diperlukan prediksi penjualan menggunakan teknik klasifikasi data mining, yaitu algoritma K-Nearest Neighbor Regression. Berdasarkan hasil penelitian, prediksi penjualan sepatu terlaris menunjukkan bahwa nilai K = 2 menghasilkan RMSE 0,43 untuk produk Fladeo, K = 3 menghasilkan RMSE 0,46 untuk produk Cardinal, K = 13 menghasilkan RMSE 0,46 untuk produk dr. Kevin, dan K = 6 menghasilkan RMSE 0,49 untuk produk Jackson. Berdasarkan pedoman RMSE, dapat disimpulkan bahwa semua model yang diuji menunjukkan tingkat kesalahan sedang, yaitu antara 0,30 hingga 0,56.
Sosialisasi Peningkatan Kesadaran Keamanan Digital dan Etika Bermedia Sosial bagi Kelompok PKK dan Siswa MTSN 3 Bekasi Ratna Salkiawati; Afina Putri Dzulqiyana; Diah Ayu Lestari; Fauzi Muhtadi; Guntur Maulana Hidayah; Haikal Azizan; Handika Gita Prasojo; Herlan Ryuchi Christian; Hudan Aghil Muttaqin; Ihsan Ahmad Fauzan; Ihsan Rahmanda Albar; Ilyas Ahmat Dafianto; Imanuel Rodericus Parlindungan Tempo
Journal Of Computer Science Contributions (JUCOSCO) Vol. 6 No. 1 (2025): Januari 2026
Publisher : Lembaga Penelitian, Pengabdian kepada Masyarakat dan Publikasi Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/592j2v86

Abstract

The rapid growth of digital technology has increased internet and social media usage in urban communities, including Mustika Jaya, Bekasi. However, this growth is not always accompanied by adequate digital literacy, particularly regarding digital security and social media ethics. This community service program aims to improve awareness and understanding of digital security and ethical behavior on social media among PKK women and junior high school students at MTsN 3 Bekasi. The program was conducted through socialization sessions, interactive discussions, demonstrations of digital security practices, and pre-test and post-test evaluations. The results indicate 25.7% increase in participants’ understanding of personal data protection, identification of online fraud, prevention of cyberbullying, and ethical communication on social media. This program contributes to strengthening digital literacy at the community level and supports the creation of a safer and more responsible digital environment.
IDENTIFIKASI KEMATANGAN BUAH ALPUKAT (AVOCADO) MENGGUNAKAN ALGORITMA ADAPTIVE NEURO FUZZY INFERENCE SYSTEM (ANFIS) Nurfiyah Nurfiyah; Hendarman Lubis; Ratna Salkiawati
Journal of Information System, Informatics and Computing Vol 10 No 1 (2026): JISICOM (June 2026)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jisicom.v10i1.2473

Abstract

Avocado (Persea americana) is a horticultural commodity with high economic value but is climacteric, so the ripening process occurs quickly after harvest. Determining the ripeness level is still done conventionally (visually and manually) often results in subjective assessments and damages the fruit. This study aims to develop a non-destructive avocado ripeness identification system (unripe, ripe, and overripe) using the Adaptive Neuro Fuzzy Inference System (ANFIS) algorithm. The input parameters used are based on the Red-Green-Blue (RGB) color features and Gray Level Co-occurrence Matrix (GLCM) texture features extracted from digital images of avocados. The test results show that the combination of the ANFIS network architecture with a Gaussian membership function is able to recognize the ripeness level of avocados with an accuracy of up to 93.3% on the test data. This system is expected to be a technological solution for farmers and distributors in the process of sorting fruit objectively and quickly.
PENERAPAN ALGORITMA FISHER-YATES PADA GAME EDUKASI MATEMATIKA UNTUK MENINGKATKAN MOTIVASI BELAJAR SISWA KELAS SD Dian Hartanti; Ratna Salkiawati; Agil Yudistira; Kusdarnowo Kusdarnowo
Journal of Information System, Applied, Management, Accounting and Research Vol. 10 No. 3 (2026): JISAMAR (August 2026)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jisamar.v10i3.2530

Abstract

Perkembangan teknologi digital memicu transformasi metode instruksional matematika di sekolah dasar. Namun, mayoritas siswa kelas 1-3 SD Negeri Wanasari 12 Cibitung menganggap matematika sebagai materi yang rumit dan menjemukan, sehingga memicu penurunan minat belajar. Siswa kerap kesulitan menguasai operasi dasar seperti penjumlahan bersusun, perkalian, dan pembagian. Studi ini bertujuan merancang game edukasi matematika interaktif guna mendongkrak ketertarikan, motivasi, dan pemahaman konsep siswa. Aplikasi dikembangkan menggunakan Unity Engine untuk platform Windows melalui kerangka Multimedia Development Life Cycle (MDLC). Metode Algoritma Fisher-Yates diimplementasikan guna mengacak urutan soal secara dinamis agar tidak mudah ditebak. Hasil riset menyajikan produk game fungsional yang valid berdasarkan kuesioner yang disebar ke para siswa setelah mereka menggunakan game math ini adalah 87%. Siswa terbantu memahami dalam mengerjakan soal matematika.
Analisis Clustering Pelaku Usaha UMKM Kota Bekasi Menggunakan Algoritma K-Means Michelle Ledisty Aisha; Rafika Sari; Ratna Salkiawati
Jurnal Jaring SainTek Vol. 8 No. 1 (2026): April
Publisher : Fakultas Teknik, Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/d472ha48

Abstract

Micro, Small, and Medium Enterprises (MSMEs) are the backbone of Indonesia's economy, employing over 97% of the workforce. However, the absence of data-driven classification hampers the formulation of effective support policies. This study aims to cluster MSMEs in Bekasi City based on business capital, revenue, and subdistrict location using the K-Means Clustering algorithm. A total of 7,923 entries were analyzed after cleaning the initial 7,964 dataset. The optimal number of clusters was determined using the Davies-Bouldin Index (DBI), with the best score of 0.5940 achieved at K=3. The clustering was conducted in two stages: manual calculation on a sample of 138 data points and automated processing via Python for the full dataset. The manual process converged at the 3rd iteration, where each step involved calculating Euclidean distances to cluster centroids, followed by centroid updates based on the mean of cluster members. The results classified MSMEs into three categories: small-scale, medium-scale, and large-scale enterprises. Small-scale MSMEs, typically with capital and revenue below IDR 5 million, are concentrated in Mustika Jaya, Pondok Gede, and Bantar Gebang. In contrast, large-scale MSMEs with higher financial figures are mostly found in Bekasi Selatan, Medan Satria, and Rawalumbu. This clustering model offers a practical foundation for designing more targeted, spatially informed, and adaptive MSME development policies.
Financial-Capacity Segmentation of Registered MSMEs in Bekasi City: A Reproducible K-Means Study Rafika Sari; Michelle Ledisty Aisha; Ratna Salkiawati; Khairunnisa Fadhilla Ramdhania
Journal of Information Technology and Cyber Security Vol. 4 No. 2 (2026): July (In progress)
Publisher : Department of Information Systems and Technology, Faculty of Intelligent Electrical and Informatics Technology, Universitas 17 Agustus 1945 Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30996/jitcs.133977

Abstract

The heterogeneity of micro, small, and medium enterprises (MSMEs) limits the usefulness of uniform development programmes. This study develops a transparent financial-capacity segmentation of registered MSMEs in Bekasi City using the Knowledge Discovery in Databases framework. The administrative source contained 7,964 records and 15 fields for 2019–2024. After data-quality screening and exclusion of 41 records with unusable capital or turnover values, 7,923 records were analysed. Business capital and turnover were selected as the two K-Means inputs because they directly represent financial capacity and were sufficiently complete for all retained observations. District, a nominal variable, was excluded from Euclidean-distance calculation and used only for post-hoc geographic profiling. The revised implementation specifies k-means++ initialisation, random_state = 42, n_init = 50, max_iter = 300, and tolerance = 10−4. A common candidate range of K = 2–10 was evaluated using inertia and the Davies–Bouldin Index (DBI). Both diagnostics supported K = 3; the minimum DBI was 0.5940. The clusters comprised 7,789 (98.31%), 22 (0.28%), and 112 (1.41%) businesses, representing low capital–low turnover, high capital–very high turnover, and high capital–moderate turnover profiles. The contribution is not a new clustering algorithm, but a reproducible city-scale evidence pipeline that corrects nominal-feature handling, reports the preprocessing audit, and converts financial profiles into testable programme hypotheses. Because the two minority clusters may represent financial extremes, cluster membership should be verified with business sector, age, employment, and stakeholder evidence before policy use.
Co-Authors Achmad Noeman Afina Putri Dzulqiyana Ageng Ridho Ramadhan Agil Yudistira Aida Fitriyani Ajie Prasetya Al Malik MK, Abdillah Syah Alexander, Allan D Allan D. Alexander Apriliani, Lita Bian Raka Firdaus Bima Bagaskhoro Cornelies Oktavianus Dhiya Azizah Hamidah Diah Ayu Lestari Dian Hartanti Dwijayanthi Nirmala, Indah Dwipa Handayani El Ghozy, Ilham Nur Fauzan Kamil Fauzan Kamil Fauzi Muhtadi Firdaus, Imansyah Abinda Guntur Maulana Hidayah Haikal Azizan Handika Gita Prasojo Hendarman Hendarman Lubis Hendarman Lubis Hendarman Lubis Herlan Ryuchi Christian Hidayat, Dian Fitrianto Hudan Aghil Muttaqin Ihsan Ahmad Fauzan Ihsan Rahmanda Albar Ilyas Ahmat Dafianto Imanuel Rodericus Parlindungan Tempo Intan Safira Ismaniah Ismaniah Joniwarta Kamil, Fauzan Khairunnisa Fadhilla Ramdhania Kusdarnowo Kusdarnowo Lubis, Hendarman Lubis, Hendarman Lubis M. Hadi Prayitno M. Khaerudin Markus Ade Putra Michelle Ledisty Aisha Michelle Ledisty Aisha Muhamad Adilla Dhiya Ulhaq Muhamad Akbar Putra Prasetyo Nurfiyah Nur`aini Puji Lestari Prasetya, Ajie Prayitno, M. Hadi Priatna, Wowon Priatna Raden Muhammad Yusuf RAFIKA SARI Ramdhania, Khairunnisa Fadhilla Rasim Rasim Sri Rejeki Sri Rejeki Sudirman Hala Wilhadad, Dadi Ulul Wilhadad, Dadi Ulul