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All Journal Techno.Com: Jurnal Teknologi Informasi Prosiding SNATIF Jurnal Edukasi dan Penelitian Informatika (JEPIN) JAIS (Journal of Applied Intelligent System) Journal of Information System Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Infotekmesin Abdimasku : Jurnal Pengabdian Masyarakat Journal of Soft Computing Exploration Community: Jurnal Pengabdian Pada Masyarakat Jurnal Informatika Polinema (JIP) Jurnal Abdi Negeri Journal of Soft Computing Exploration
Lalang Erawan
Universitas Dian Nuswantoro
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mechanical Engineering Social Sciences

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Pelatihan Pemanfaatan Google Sites Untuk Pembuatan Media Pembelajaran Berbasis Website Untuk Guru Dan Dosen Pada Perkumpulanprofesi Multimedia Dan Teknologi Informasi (PPMULTINDO) Jatmoko, Cahaya; Rakasiwi, Sindhu; Widya Laksana, Deddi Award; Erawan, Lalang; Rizqa, Ifan; Astuti, Erna Zuni
Community : Jurnal Pengabdian Pada Masyarakat Vol. 4 No. 2 (2024): Juli : Jurnal Pengabdian Pada Masyarakat
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi - Studi Ekonomi Modern

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/community.v4i2.535

Abstract

Conveying appropriate information to be understood quickly and accurately is very important in various areas of life, both academic and non-academic. A teacher or lecturer is a teacher whose job is to educate and provide instruction to students or students. Data visualization is one way that can be used to present data. The advantage of this method is the availability of statistical graphics which can enrich the display of information so that the results are more interactive for the audience. Google Sites is a service owned by the Google company that can be used for e-learning. That way, the information becomes more appropriate to understand quickly and accurately.
Pemanfaatan Google Drive Untuk Backup dan Akses File Bersama Pada CV Berkah Cimandiri Makmur erawan, lalang; Agus Winarno; Candra Irawan
Jurnal Abdi Negeri Vol 1 No 2 (2023): September 2023
Publisher : Informa Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63350/jan.v1i2.11

Abstract

CV. Berkah Cimandiri Makmur merupakan perusahaan pengiriman barang sembako dan kebutuhan pokok masyarakat Kalimantan yang melalui jalur laut dengan armada Dump truk melalui kapal laut dan sebaliknya dari kalimantan membawa barang barang hasil hutan seperti rotan, kayu serta yang lain untuk dikirim ke Semarang dengan memanfatkan Ekspedisi melalui kapal laut. Dalam pelaksanaan operasional administrasinya dibutuhkan penggunaan file yang terintegrasi yang tersimpan di perangkat apapun pada satu tempat yang aman serta sinkronisasi dan bagikan file yang tak terbatas dan fleksibel. Dengan memanfaatkan Google Drive yang memiliki fungsi antara lain dapat berbagi file, menyimpan link, membuat catatan dari Google keep, backup file, backup Chart WhatsApp, dan mengedit file merupakan solusi yang paling murah dan mudah dipahami. Tujuan Program Kemitraan Masyarakat ini untuk memberikan peningkatan pengetahuan, keterampilan para karyawan, sehingga akan meningkatkan kinerja dan pelayanan operasional perusahaan. Luaran Program Kemitraan Masyarakat ini antara lain peningkatan pengetahuan dalam bidang Teknologi Informasi, Jurnal Nasional serta Dokumentasi Video dan menggunakan 3 tahap pelaksanaan yaitu tahap pretest, pengkayaan dan pendalaman materi, dan post test.
Optimization of Heart Failure Classification on Imbalanced Data Using a Supervised Learning Approach Based on Logistic Regression, Random Forest, and K-Nearest Neighbor: Optimalisasi Klasifikasi Gagal Jantung pada Data Imbalanced Menggunakan Pendekatan Supervised Learning Berbasis Regresi Logistik, Random Forest, dan K-Nearest Neighbor agustina, feri; Irawan, Candra; Erawan, Lalang; Suprayogi; Award Widya Laksana, Deddy; Jatmoko, Cahaya; Sinaga, Daurat; Lestiawan, Heru
Jurnal Informatika Polinema Vol. 12 No. 1 (2025): Vol. 12 No. 1 (2025)
Publisher : UPT P2M State Polytechnic of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jip.v12i1.9071

Abstract

Heart failure remains one of the leading causes of mortality worldwide, posing significant challenges for early diagnosis and patient management. One of the major obstacles in developing predictive models for heart failure is the class imbalance problem, where the number of surviving patients far exceeds those who experience death events. This imbalance often leads machine learning algorithms to bias toward the majority class, reducing sensitivity to critical minority cases. To address this issue, this study applies the Synthetic Minority Oversampling Technique (SMOTE) to balance the dataset and improve model performance. Three supervised learning algorithms, namely Logistic Regression (LR), Random Forest (RF), and K-Nearest Neighbor (KNN), were implemented and compared on the UCI Heart Failure Clinical Records dataset containing 299 patient samples with 13 clinical attributes. Experimental results show that the Random Forest model achieved the highest performance with 90% accuracy, precision, recall, and F1-score, outperforming both LR and KNN. The findings demonstrate that combining data balancing with ensemble learning effectively enhances prediction accuracy and sensitivity toward minority classes. The main contribution of this research lies in optimizing supervised models for medical data with skewed class distributions, providing a more reliable and interpretable approach for early heart failure detection. Future research may extend this work by integrating advanced ensemble or hybrid deep learning models and expanding the dataset for multi-institutional validation
Penerapan Algoritma K-Means untuk Identifikasi Pola Spasial Insidensi Demam Berdarah Dengue: Studi Kasus Kota Semarang Putra, Wahyu Bagus Wicaksono; Fahmi, Amiq; Erawan, Lalang
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 11, No 3 (2025): Volume 11 No 3
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v11i3.101302

Abstract

Demam Berdarah Dengue (DBD) merupakan ancaman kesehatan masyarakat yang signifikan di wilayah tropis, termasuk Kota Semarang, Jawa Tengah, Indonesia, dengan tingkat heterogenitas spasial insidensi yang bervariasi antar kecamatan. Penelitian ini bertujuan untuk mengidentifikasi pola spasial insidensi DBD melalui pendekatan pembelajaran tanpa pengawasan (unsupervised learning) menggunakan algoritma K-Means clustering. Data epidemiologis yang bersifat komprehensif pada periode 2020–2024, mencakup variabel jumlah populasi, kasus terkonfirmasi, dan fatalitas, diekstraksi dari sistem informasi publik TUNGGAL DARA yang dikelola oleh Dinas Kesehatan Kota Semarang. Metodologi yang diterapkan meliputi pra-pemrosesan data, penentuan jumlah klaster optimal dengan metode Elbow dan Silhouette Score, serta validasi menggunakan statistik nonparametrik dengan uji Kruskal-Wallis. Hasil klasterisasi menunjukkan lima kelompok wilayah dengan karakteristik epidemiologis yang berbeda. Temuan penting mengindikasikan bahwa zona dengan kepadatan populasi rendah secara proporsional menanggung rasio morbiditas dan mortalitas yang lebih tinggi. Pendekatan ini terbukti efisien dalam mereduksi dimensi data epidemiologis menjadi pola spasial yang informatif dan mudah diinterpretasikan. Penelitian ini berkontribusi pada pengembangan pemetaan risiko DBD yang lebih adaptif dan berbasis data serta menyediakan landasan strategis yang kuat bagi intervensi kesehatan masyarakat yang lebih terarah dan tepat sasaran, khususnya dalam konteks studi kasus Kota Semarang.
Transformasi Digital melalui Pembuatan Website Profil Rukun Tetangga (RT) sebagai Media Informasi Digital Warga Kardianawati, Acun; Suharnawi, Suharnawi; Erawan, Lalang; Nurhindarto, Aris
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 9, No 1 (2026): JANUARI 2026
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/ja.v9i1.3163

Abstract

Transformasi digital menjadi kebutuhan utama dalam meningkatkan efisiensi layanan publik, termasuk di tingkat komunitas lokal. Namun, banyak Rukun Tetangga (RT) masih menggunakan cara konvensional dalam penyampaian informasi, sehingga partisipasi warga rendah dan dokumentasi kegiatan kurang optimal. Pengabdian masyarakat ini bertujuan mengembangkan website profil RT sebagai media komunikasi, dokumentasi, dan transparansi program kerja di RT.001/RW.003 Kelurahan Plombokan, Kota Semarang. Metode pelaksanaan meliputi analisis kebutuhan, pengembangan website berbasis prototyping, serta evaluasi tingkat penerimaan pengguna. Hasil menunjukkan bahwa website profil RT mampu meningkatkan aksesibilitas informasi, memperbaiki dokumentasi kegiatan, dan mendorong partisipasi warga. Implementasi website terbukti menjadi solusi efektif untuk modernisasi komunikasi komunitas berbasis teknologi informasi.
Application of multi-chaotic map cascade in video encryption to overcome statistical and differential attacks and performance evaluation Jatmoko, Cahaya; Lestiawan, Heru; Rafrastara, Fauzi Adi; Erawan, Lalang; Irawan, Candra; Doheir, Mohamed
Journal of Soft Computing Exploration Vol. 7 No. 1 (2026): March 2026
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v7i1.6

Abstract

The rapid proliferation of digital video across domains such as healthcare, surveillance, and communications has increased the demand for secure and efficient video encryption techniques. However, video data presents unique challenges, including large data volume and high spatial–temporal correlation, which limit the effectiveness and efficiency of conventional encryption approaches, particularly in real-time scenarios. In this context, the objective of this study is to evaluate the feasibility of a chaos-based video encryption in achieving both strong cryptographic security and acceptable computational performance. To accomplish this, the proposed scheme is tested through two controlled experiments. The evaluation focuses on cryptographic strength using the Number of Pixel Change Rate (NPCR) to measure sensitivity to minor input changes, the Unified Average Changing Intensity (UACI) to quantify average pixel intensity variation, and Shannon entropy to assess the randomness of the encrypted frames. In parallel, computational performance is analyzed through encryption time and throughput. The procedure involves frame extraction from video, followed by preprocessing to reduce pixel correlation, and subsequent application of the chaos-based encryption algorithm on a per-frame basis. The results from both experiments show NPCR values exceeding 99.5% and encrypted frame entropy of approximately 7.74 bits/pixel, indicating strong resistance to differential attacks and near-optimal randomness. However, the observed throughput of 0.07–0.09 frames per second highlights a limitation in meeting real-time processing requirements. These findings suggest that while the proposed scheme is cryptographically robust and suitable for offline or batch-processing applications.
Co-Authors Acun Kardianawati Afif, Rizal Naufal Agus Winarno Agus Winarno Agus Winarno, Agus Agustina, Feri Ajib Susanto Alzami, Farrikh Award Widya Laksana, Deddy Cahaya Jatmoko Candra Irawan Candra Irawan Christy Atika Sari De Rosal Ignatius Moses Setiadi Dhia Adikusuma Adikusuma Doheir, Mohamed Eko Hari Rachmawanto Erna Zuni Astuti Fahmi Amiq Fauzi Adi Rafrastara Heru Lestiawan Ifan Rizqa Krismawan, Andi Danang Laksana, Deddy Award Widya Mahardika, Nur Raditya Marshela Dinda Amalia Maulydea Ramayanti Megantara, Rama Aria Moh Yusuf, Moh Moh. Yusuf Muslih Muslih Nurhindarto, Aris Priskila Penny Ardiana Putra, Wahyu Bagus Wicaksono Ricardus Anggi Pramunendar Saputra, Resha Mahardhika Sinaga, Daurat Sindhu Rakasiwi Sintia Rahma Herdajanti Suharnawi Suharnawi Suharnawi Suharnawi Suharnawi Sumarni Adi, Sumarni suprayogi Tan Samuel Permana Wellia Shinta Sari Widya Laksana, Deddi Award Yaacob, Noorayisahbe Mohd Yudistira Dian Hastiti Yuventius Tyas Catur Pramudi Zaenal Arifin