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All Journal JURNAL SISTEM INFORMASI BISNIS Teknika Pro Bisnis RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Jurnal Teknologi Informasi dan Multimedia Journal of Information Systems and Informatics JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) Jurnal E-Komtek IJIIS: International Journal of Informatics and Information Systems Madani : Indonesian Journal of Civil Society Journal of Computer Networks, Architecture and High Performance Computing ABSYARA: Jurnal Pengabdian Pada Masyarakat Nusantara Hasana Journal Jurnal Pengabdian Masyarakat (ABDIRA) Jurnal Ilmiah IT CIDA : Diseminasi Teknologi Informasi Jurnal Ilmu Komputer dan Teknologi (IKOMTI) Journal of Practical Computer Science (JPCS) Jurnal Pengabdian Mitra Masyarakat (JPMM) Padma: Jurnal Pengabdian Kepada Masyarakat Jurnal Rekayasa Informasi Gotong Royong Edu Komputika Journal
Ranggi Praharaningtyas Aji
Universitas Amikom Purwokerto
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Other

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PENGUATAN EKOSISTEM WISATA DAN INDUSTRI KOPI DESA MELUNG MELALUI PENGELOLAAN DAN PROMOSI BERBASIS DIGITAL Ranggi Praharaningtyas Aji; Dwi Krisbiantoro; Rida Purnama Sari; Hasirun, Hasirun; Rian Hidayat; Ibnu Romadhon
Nusantara Hasana Journal Vol. 5 No. 4 (2025): Nusantara Hasana Journal, September 2025
Publisher : Yayasan Nusantara Hasana Berdikari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59003/nhj.v5i4.1695

Abstract

This community service program (PMM scheme) aimed to empower the BUMDes and Pokdarwis of Melung Village through an integrated digital intervention to address coffee management and tourism marketing issues. Utilizing participatory methods, including Focus Group Discussions (FGD), student-led mentoring (KKN), and the provision of appropriate technology (TTG), the program successfully developed the web application `simelung.org` for asset and financial recording, established standardized coffee processing SOPs, created structured tourism packages, and installed 13 directional signs and 1 mini map. The intervention strengthened institutional governance, improved coffee quality consistency, professionalized destination branding, and built local human resource capacity. In conclusion, synergistic academia-community collaboration supported by a digital approach proved effective in creating a replicable, integrated empowerment model to drive sustainable village economy in line with the SDGs.
SOSIALISASI ANCAMAN DAN MANFAAT PENGGUNAAN MEDIA DIGITAL UNTUK SISWA MENENGAH ATAS SEDERAJAT DITINJAU DARI IT ETHIC, REGULATION AND CYBER LAW Ranggi Praharaningtyas Aji; Albana, Ilham
Nusantara Hasana Journal Vol. 3 No. 10 (2024): Nusantara Hasana Journal, March 2024
Publisher : Yayasan Nusantara Hasana Berdikari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59003/nhj.v3i10.1040

Abstract

Using the concept of an independent learning curriculum for students at Miftahul Huda Rawalo Vocational School to express themselves and create digitally. Therefore, the digital work of Miftahul Huda Rawalo Vocational School students needs to be ensured in accordance with ethical and legal principles. It is important to instill knowledge about IT ethics, digital world rules and Indonesian cyber law in these students. With this problem, it is necessary to provide direction and explanation regarding applicable ethics and law, both formal and digital ethics and law. The AMM team will explain matters related to IT ethics and cyber law in attractive and digitalized packaging so that it is easy fors participants to understand and understand. The result of this activity is that students know the issues regulated by IT ethics related to the ITE Law and regulations related to content and digital media created by students. Know the limits of what is and is not allowed in digital media. And awareness of the importance of maintaining digital content created by students in the field of ethics and IT regulations.
Performance Comparison of CART And KNN Algorithms for Analyzing Early Predictions of Mental Health Anggraeni, Eling Sekar; Fitriya Maharani, Lulu Amnah; Desi Riyanti; Aji, Ranggi Praharaningtyas; Pungkas Subarkah
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4232

Abstract

Currently, mental health is an unresolved mental health problem both at the national and international levels. Mental health disorders are conditions where a person has difficulty in adjusting to the conditions around them. Mental Health is an important aspect of overall health. Efforts to maintain and improve it can help a person achieve better well-being in everyday life.  This research aims to conduct Early Prediction Analysis related to mental health problems experienced by students by measuring the accuracy level of the analysis. This research was conducted using the CART (Classification and Regression Trees) and KNN (K-Nearest Neighbor) algorithms with a set of Mental Health Datasets consisting of 11 attributes and 101 data.  The data is processed using the Weka Application and the accuracy results of each algorithm are obtained, amounting to 94.0594% for the CART Algorithm and 91.0891% for the KNN Algorithm. From this achievement, it can be concluded that the performance of the CART and KNN algorithms falls into the Excellent Classification category. Judging from the accuracy obtained, the CART algorithm has a higher accuracy value than the KNN algorithm, so the CART algorithm has a high performance for analyzing early prediction of mental health of students who do not take steps in seeking mental health support.
Pelatihan Digital Marketing Untuk Meningkatkan Penjualan Produk Bumdes Berkah Sentosa Di Desa Pangebatan Aji, Ranggi Praharaningtyas; Khairunnisa, Salsabila Iftinan; Mahardhika, Gilang Satria; Albana, Ilham
Gotong Royong Vol. 2 No. 3 (2025)
Publisher : CV. Akira Java Bulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63935/gr.v2i3.246

Abstract

BUMDes Berkah Sentosa di Desa Pangebatan menghadapi over stok produk turunan singkong, pisang, perikanan, dan pertanian akibat pemasaran tradisional yang terbatas, sehingga mengganggu cash flow dan keberlanjutan usaha. Pengabdian ini bertujuan meningkatkan pengetahuan serta keterampilan pemasaran digital, memperluas jangkauan pasar, dan mereduksi over stok melalui pelatihan bagi 23 kelompok produsen. Metode mengadopsi Community-Based Participatory Action Research (CBPAR) dengan siklus plan-act-observe-reflect, melibatkan kuliah interaktif, pelatihan langsung, dan simulasi kampanye; data diperoleh via pre-post test (N=45), survei kepuasan, observasi, serta monitoring laporan BUMDes, dianalisis dengan paired t-test, analisis tematik NVivo, dan Kirkpatrick's Four-Level Model. Temuan utama menunjukkan peningkatan pengetahuan 42,7% (t(44)=14,67, p<0,001), kepuasan peserta 92,9%, adopsi digital oleh 86,7% kelompok, serta reduksi over stok 28,4% disertai kenaikan penjualan digital 35,2% dalam tiga bulan pasca-program. Program berhasil mengoptimalkan strategi pemasaran, memperkuat daya saing UMKM pedesaan, dan mencapai indeks Kirkpatrick 87,5%, dengan saran mentoring berkelanjutan serta replikasi modul e-commerce nasional.
Kewirausahaan Berbasis Mahasiswa (KBM) bidang Ekonomi Kreatif Tahyudin, Imam; Dianingrum, Melia; Hermawan, Hellik; Aji, Ranggi Praharaningtyas; Wahyudin, Widya Cholid
Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Vol 9, No 1 (2026): Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstormin
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/japhb.v9i1.9733

Abstract

Pengembangan usaha kampus melalui program kewirausahaan berbasis Mahasiswa sangat bermanfaat dan penting untuk diterapkan. Pengembangan usaha kampus dalam bidang ekonomi kreatif urgen untuk memberikan pengalaman belajar yang baru bagi mahasiswa dalam merintis usaha, dan meningkatkan citra kampus di mata masyarakat. Tujuan dari kegiatan ini adalah untuk melatih mengembangkan usaha bidang ekonomi kreatif dengan memberdayakan mahasiswa. Untuk mewujudkan usaha tersebut dilakukan melalui beberapa langkah diantaranya tahap persiapan yaitu seleksi peserta KBM, Pembekalan usaha KBM ekonomi kreatif, proses pendampingan. selanjutnya tahap pelaksanaan kegiatan, dan tahap evaluasi.Hasil kegiatan menunjukkan bahwa 30 mahasiswa peserta memperoleh pengetahuan dan keterampilan kewirausahaan yang mencakup penyusunan business plan, manajemen keuangan usaha, strategi pemasaran, dan pengelolaan usaha di berbagai bidang ekonomi kreatif (fashion, desain grafis, coffee shop, kuliner). Peserta mampu mengaplikasikan pengetahuan tersebut dengan membentuk 11 kelompok rintisan usaha yang telah beroperasi dan melaksanakan pelaporan berkala mencakup omset serta kendala operasional. Program ini juga memberikan pengakuan akademik berupa konversi nilai maksimal 20 SKS, dipublikasikan pada media massa Harian Radar Banyumas, dan didokumentasikan dalam konten video di kanal YouTube.
Transformasi Pengelolaan Pariwisata Desa Tambaknegara melalui Aplikasi WISME dan Penerapan Prinsip Saptapesona Anugerah Bagus Wijaya; Zanuar Rifai; Rujianto Eko Saputro; Fiby Nur Afiana; Ranggi Praharaningtyas Aji; Primandani Arsi; Bunga Asriandhini; Rida Purnama Sari
PADMA Vol 5 No 2 (2025): JURNAL PENGABDIAN KEPADA MASYARAKAT (PADMA)
Publisher : LPPM Politeknik Piksi Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56689/padma.v5i2.2155

Abstract

This community service program aims to improve the management capacity of Tambaknegara Tourism Village in Banyumas through the implementation of the WISME (Wisata Manajemen Elektronik) application and the strengthening of the Saptapesona principle. The main challenges include limited digital skills, insufficient online promotion, and inconsistent service quality based on Saptapesona values. The program was carried out using a participatory approach, involving training, mentoring, implementation, and evaluation stages. The results show improved digital literacy among tourism managers and the successful integration of Saptapesona values into tourism services. In addition, a Village Digital Creative Team was formed to promote tourism through social media and the WISME platform. This program demonstrates that the integration of digital technology and Saptapesona values can strengthen sustainable community-based tourism management
Sentiment Analysis of Google Maps Reviews on Temple Tourism in Central Java Using IndoBERT Embeddings and BiLSTM Ranggi Praharaningtyas Aji; Primandani Arsi
Journal of Information System and Informatics Vol 8 No 3 (2026): June
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i3.1589

Abstract

The rapid growth of user-generated content provides valuable insights into tourists’ perceptions of destinations. This study analyzes sentiment in Google Maps reviews of temple tourism destinations in Central Java using IndoBERT embeddings and a Bidirectional Long Short-Term Memory (BiLSTM) model. A total of 10,714 Indonesian-language reviews were collected through web scraping and processed through preprocessing, pseudo-labeling, embedding generation, and model training. To prevent data leakage, the dataset was divided into stratified training and testing sets, while Random OverSampling (ROS) was applied only to the training data. Since manually annotated labels were unavailable, sentiment categories were generated automatically using a pre-trained IndoBERT classifier. The BiLSTM model achieved 80.25% accuracy on the imbalanced dataset and approximately 95% accuracy against IndoBERT-generated pseudo-labels under balanced training conditions. Improvements in Macro F1-score and balanced accuracy indicate better recognition of minority classes. However, the results should be interpreted cautiously because pseudo-labeling and oversampling may affect performance. Overall, this exploratory study demonstrates the potential of IndoBERT and BiLSTM for Indonesian tourism sentiment analysis while highlighting the need for human-annotated data and stronger validation in future research.
IMPLEMENTASI CONTENT-BASED FILTERING UNTUK REKOMENDASI PRODUK PADA WEBSITE E-COMMERCE: THE APPLICATION OF CONTENT-BASED FILTERING FOR PRODUCT RECOMMENDATIONS ON E-COMMERCE WEBSITES Devan Rizky Saputra Zebua; Ranggi Praharaningtyas Aji; Nandang Hermanto
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8006

Abstract

The growth of e-commerce in the fashion sector has driven the need for systems that can help users discover products more efficiently amid an abundance of available choices. This study aims to implement a smart recommendation system based on content-based filtering on the Dinara Konveksi e-commerce website using the TF-IDF (Term Frequency–Inverse Document Frequency) method and cosine similarity.The dataset consists of 35 active products registered in the Dinara Konveksi e-commerce system. The data used consists of product attributes including name, category, description, variant colors, and sizes, which are combined into text documents and processed through preprocessing steps comprising case folding, tokenization, and stopword removal. Feature weighting is performed using TF-IDF to generate a vector representation for each product, while cosine similarity is used to measure the degree of similarity between products. The system produces two types of recommendations: similar product recommendations displayed on product detail pages, and personalized recommendations tailored to users' purchase history, shopping cart, and product view history. The implementation uses a two-tier architecture consisting of a Python script with scikit-learn for batch computation and a PHP service as the runtime interface. Evaluation results show a Precision@4 of 0.75, Recall@4 of 0.60, F1-Score of 0.67, and a Hit Rate of 1.00. The developed system is capable of providing relevant and responsive product recommendations while supporting a more personalized shopping experience for users of the Dinara Konveksi website.
Public Sentiment Classification of Danantara in Social Media X Using Support Vector Machine and Random Forest Primandani Arsi; Pungkas Subarkah; Ranggi Praharaningtyas Aji
Edu Komputika Journal Vol. 12 No. 2 (2025): Edu Komputika Journal
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/edukom.v12i2.38254

Abstract

The increasing use of social media as a platform for public discourse provides valuable data for understanding societal responses to national strategic policies. One prominent example is the establishment of Danantara (Daya Anagata Nusantara), a sovereign wealth fund launched by the Indonesian government in February 2025. This study aims to analyze public sentiment toward Danantara using Indonesian-language posts collected from social media platform X and to comparatively evaluate the performance of Support Vector Machine (SVM) and Random Forest (RF) algorithms. A dataset of 1,434 public tweets was collected through web scraping and processed using text preprocessing techniques, including cleaning, tokenization, stopword removal, stemming, and TF-IDF feature extraction. Sentiment labels were generated using an Indonesian RoBERTa model and validated by a linguistic expert. Class imbalance was addressed using the Synthetic Minority Oversampling Technique (SMOTE). Model performance was evaluated using 5-fold stratified cross-validation with accuracy, precision, recall, and F1-score metrics. Experimental results show that Random Forest achieved slightly superior performance, reaching an average accuracy of 91.47%, compared to 91.06% obtained by SVM. Confusion matrix analysis indicates that RF better distinguishes neutral sentiment, while SVM performs competitively in identifying strong sentiment polarity. This study contributes by providing the first empirical comparison of classical machine learning approaches for analyzing public sentiment toward Indonesia’s sovereign wealth fund discourse, offering methodological insights and practical implications for data-driven policy evaluation using social media analytics.
Klasifikasi Kualitas Air Menggunakan CNN Berbasis Warna Citra Digital Ari Tri Wibowo; Ranggi Praharaningtyas Aji
TEKNIKA Vol. 20 No. 1 (2026): Teknika Januari 2026
Publisher : Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.18530664

Abstract

Air merupakan kebutuhan utama bagi kehidupan manusia, sehingga kualitasnya harus dijaga agar tetap aman digunakan. Namun, meningkatnya pencemaran lingkungan menyebabkan air menjadi tidak layak konsumsi dan berpotensi menimbulkan penyakit. Diperlukan upaya untuk memantau kualitas air secara efisien dan akurat, salah satunya melalui pemanfaatan teknologi pengolahan citra digital. Penelitian ini berfokus pada penerapan algoritma Convolutional Neural Network untuk mengklasifikasikan kondisi air berdasarkan warna pada citra digital. Dataset yang digunakan berjumlah 364 gambar yang diperoleh dari situs Kaggle dan Unsplash, terbagi dalam dua kategori, yaitu air bersih dan air tercemar. Proses penelitian meliputi pra-pemrosesan data melalui normalisasi dan augmentasi citra, pelatihan model dengan optimizer Adam selama 15 epoch, serta evaluasi menggunakan metrik akurasi, precision, recall, dan f1-score. Hasil pengujian menunjukkan akurasi sebesar 92,63%, precision 92,67%, recall 92,59%, dan f1-score 92,62%. Nilai tersebut menunjukkan bahwa model CNN mampu mengenali pola warna dan tekstur air dengan baik. Penerapan metode CNN terbukti efektif dalam membantu proses klasifikasi kualitas air berbasis citra digital dan dapat menjadi dasar untuk penelitian lebih lanjut di bidang pemantauan lingkungan.
Co-Authors Abdul Azis Abdul Azis Akmal, Rafii Nur Albana, Ilham Anggraeni, Eling Sekar Anggraini, Yulia Anugerah Bagus Wijaya Aprilia, Kharisma Argiyan Dwi Pritama Ari Tri Wibowo Ari Waluyo Ari Waluyo Aulia Difa, El Syafangatun Aulia Hamdi Banu Dwi Putranto Banu Dwi Putranto Bunga Asriandhini Choerunnisa, Alfina Darso Darso Desi Riyanti Devan Rizky Saputra Zebua Dhanar Intan Surya Saputra Dhanar Intan Surya Saputra Dwi Krisbiantoro Fariz Nur Fikri Zaki Fiby Nur Afiana Fiby Nur Afiana Fitriya Maharani, Lulu Amnah Hanun Karomatunnisa Hasirun, Hasirun Hellik Hermawan Hidayah, Debby Ummul Ibnu Romadhon Ika Ayu Pratiwi Ika Romadoni Yunita ilham albana Imam Tahyudin Ito Setiawan Khairunnisa, Salsabila Iftinan Luzi Dwi Oktaviana Maghfira, Rahajeng Sasi MAHARDHIKA, GILANG SATRIA Maruf Maftukhin Melia Dianingrum Muhamad Awiet Wiedanto Prasetyo Mustofiyah, Widiyana Nandang Hermanto Nur Azizah, Resti Primandani Arsi Pritama, Argiyan Dwi Pungkas Subarkah Putranto, Banu Dwi Putri Awaliatuz Zahra Resti Nur Azizah Retno Waluyo Rian Hidayat Rida Purnama Sari Rida Purnama Sari Riska Praise Riska Praise Rizki, Sofi Alfiona Rizky Bangkit Bachtiar Rujianto Eko Saputro Sarmini - Sarmini Sarmini Sarmini Toni Anwar Trianita, Isni Vidia Alma Cyrilla Wahyu Latifatun Wahyuningsih, Melisa Waluyo, Retno Wati, Eka Setia Widya Cholid Wahyudin Yuliawan Adi Wibowo Zanuar Rifai Zanuar Rifai