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All Journal JAIS (Journal of Applied Intelligent System) RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Applied Information System and Management Journal of Information Systems and Informatics JISA (Jurnal Informatika dan Sains) Jurnal Sistem Informasi dan Sains Teknologi Jurnal Sains dan Edukasi Sains Jurnal Ilmiah Wahana Pendidikan Bulletin of Information Technology (BIT) Academic Journal of Computer Science Research (AJCSR) Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Ilmiah Ilmu Terapan Universitas Jambi JUARA: Jurnal Pengabdian Kepada Masyarakat Jurnal Pelita Pengabdian SWADIMAS: JURNAL PENGABDIAN KEPADA MASYARAKAT
Gatot Tri Pranoto
Universitas Trilogi
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Astronomy Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Physics Social Sciences Other

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South German Credit Data Classification Using Random Forest Algorithm to Predict Bank Credit Receipts Religia, Yoga; Pranoto, Gatot Tri; Santosa, Egar Dika
JISA(Jurnal Informatika dan Sains) Vol 3, No 2 (2020): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v3i2.837

Abstract

Normally, most of the bank's wealth is obtained from providing credit loans so that a marketing bank must be able to reduce the risk of non-performing credit loans. The risk of providing loans can be minimized by studying patterns from existing lending data. One technique that can be used to solve this problem is to use data mining techniques. Data mining makes it possible to find hidden information from large data sets by way of classification. The Random Forest (RF) algorithm is a classification algorithm that can be used to deal with data imbalancing problems. The purpose of this study is to discuss the use of the RF algorithm for classification of South German Credit data. This research is needed because currently there is no previous research that applies the RF algorithm to classify South German Credit data specifically. Based on the tests that have been done, the optimal performance of the classification algorithm RF on South German Credit data is the comparison of training data of 85% and testing data of 15% with an accuracy of 78.33%.
Sentiment Analysis Review Threads Google Play Store with RoBERTa Model Natan Kharisma A; Dewi Lestari; Gatot T Pranoto
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 14 No 4: November 2025
Publisher : This journal is published by the Department of Electrical and Information Engineering, Faculty of Engineering, Universitas Gadjah Mada.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v14i4.22038

Abstract

The rapid development of internet technology globally, including in Indonesia, has drastically changed communication and interaction patterns between individuals. One impact is seen in the increasing use of text-based social media applications, such as Threads, developed by Meta. Within a short time, Threads managed to attract millions of users. However, the large number of user reviews on the Google Play Store presents its own challenges, particularly in manual sentiment analysis, which is very time-consuming and prone to bias. This research aims to overcome these challenges by implementing a variant of bidirectional encoder representations from transformers (BERT), the robustly optimized BERT pretraining approach (RoBERTa) model, which has been optimized for natural language processing. The research process followed the cross-industry standard process for data mining (CRISP-DM) framework, including several main stages: understanding the business context, data exploration and model building preparation, performance evaluation, and model deployment. Data were obtained directly from the Google Play Store and then cleaned through deduplication, normalization, and tokenization stages. The RoBERTa model demonstrated strong performance, with an accuracy of 88%. Precision was recorded at 92% for positive sentiment and 81% for negative sentiment, while recall was at 88% and 87%, respectively. The F1 score was also high, at 90% for positive and 84% for negative sentiment. When compared to algorithms like naïve Bayes and support vector machine (SVM), RoBERTa proved superior. This research opens opportunities for exploring other transformer models or using ensembles to improve performance in the future.
Penyuluhan Pemanfaatan Media Sosial yang Kreatif dan Inovatif untuk Masyarakat Desa Nawangsih, Ismasari; Purnamasari, Pupung; Pranoto, Gatot Tri; Majid, Annisa Maulana; Surojudin, Nurhadi
JUARA (Jurnal Pengabdian Kepada Masyarakat) Vol. 1 No. 1 (2023): JUARA: Jurnal Pengabdian Kepada Masyarakat
Publisher : Lembaga Riset, Inovasi, dan Pengabdian Kepada Masyarakat, Universitas Saintek Muhammadiyah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56459/1yry2464

Abstract

Media sosial merupakan sarana  yang di tunjukan kreatif seseorang dengan  didukung oleh perangkat aplikasi dan internet.  Media Sosial dalam mengakses tanpa mengenal  komunikasi jarak, waktu dan tempat. Serta kemudahan untuk mendapatkan  dan mengelola  informasi penggunanya.Kreativitas yang ditunjukan dalam media sosial berupa video, tulisan, cerita, gambar dan lain-lain akan menjadi nilai tambah. Penggunaan media sosial harus diimbangi dengan pengetahuan akan dampak positif dan negatifnya. Kegiatan pengabdian kepada masyarakat memberikan pelatihan dan peyuluhan tentang  bijak dalam menggunakan media sosial dilakukan di balai desa, pakis jaya karawang. Sasaran dari kegiatan Pegabdian kepada masyarakat ini adalah masyarakat desa. Kegiatan dilakukan secara tatap muka yang diawali dengan observasi wawancara dan koordinasi. Mengenai rencana kegiatan yang akan dilakukan di lingkungan tersebut. Kegiatan pengabdian dilakukan dengan menggunakan beberapa tahapan: Tahap persiapan; Tahap implementasi sosialisasi mengenai edukasi bijak dalam menggunakan media sosial. Metode yang digunakan dalam melaksanakan kegiatan pengabdian kepada masyarakat adalah sosialisasi dengan teknik penyuluhan berupa ceramah atau penyampaian materi berupa teori, video dan praktek penggunaan media sosial terkait dengan tema, tanya jawab dan game yang menarik. Hasil kegiatan  menunjukkan meningkatnya penggunaan media sosial secara  kreativitas  dan inovatif bagi masyarakat desa.
Optimasi Algoritma K- Nearest Neighbor Berbasis Particle Swarm Optimization Untuk Meningkatkan Kebutuhan Barang Taofik Safrudin; Gatot Tri Pranoto; Wahyu Hadikristanto
Bulletin of Information Technology (BIT) Vol 4 No 3: September 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i3.724

Abstract

Abstract− The application of the K-Nearest Neighbor algorithm can be implemented where the results also show a new insight, namely predicting the level of need. With a ratio of 90%:10%, where there are 50 data objects tested to predict the level of needs in 2 groups, namely low needs or high needs. The results of the model scenario show that there are 2 objects in the Low needs group and 1 object in the High needs group. In evaluating this model, it was obtained from 10 fold Cross Validation that the Accuracy value was 82%, then the Precision value was 87.50%, and the Recall value was 80%. By measuring the performance of the model with Cross Validation, the resulting accuracy has a standard value or standard deviation, which aims to see the distance between the average accuracy and the accuracy of each experiment. While the Test Results using PSO In the evaluation of this model, it is obtained from 10 fold Cross Validation the Accuracy value is 100%, then the Precision value is 100%, and the Recall value is 100%, the test results have increased significantly
SISTEM PENDUKUNG KEPUTUSAN UNTUK MENENTUKAN PENDAKIAN GUNUNG TERBAIK DI JAWA TENGAH MENGGUNAKAN METODE SAW (SIMPLE ADDITIVE WEIGHTING) Wahyu Hadikristanto; Gatot Tri Pranoto
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 8 No 2 (2023): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v8i2.3557

Abstract

The level of interest in mountain climbing activities has increased significantly, this is inseparable from the development of social media technology which exposes the charm of each mountain itself, so as to attract interest in climbing from various groups, both beginners and experienced. Because each climber has their own characteristics and needs and each mountain also has its own character, so that it will affect each climbing destination, prospective climbers must be able to determine which mountain will be chosen as the best mountain in Central Java province to be chosen. as a climbing location. This research uses secondary data, the alternative to be compared is a list of mountains in Central Java province with several criteria to be used. The method for processing data is the Simple Additive Weighting (SAW) method. This method is used to find the weighted sum and rating of each alternative and all attributes. The results of this study can be a reference for climbers in determining the best mountain to be used as a climbing location in Central Java province.
OPTIMALISASI DIGITAL MARKETING UMKM MELALUI PENGEMBANGAN IDENTITAS VISUAL DAN MEDIA PROMOSI DIGITAL DI DESA IWUL KECAMATAN PARUNG KABUPATEN BOGOR Syifa Amalia; Muhamad Syafareno; Diana Mulhimah; Gatot Tri Pranoto; Faizah Syihab
SWADIMAS: JURNAL PENGABDIAN KEPADA MASYARAKAT Vol 4, No 2 (2026): SWADIMAS EDISI JULI 2026
Publisher : Institut Teknologi dan Bisnis Swadharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56486/swadimas.vol4no2.1364

Abstract

Micro, Small, and Medium Enterprises (MSMEs) play a crucial role in supporting the economic growth of rural communities. However, most MSMEs still face challenges with product branding and with using digital media as a marketing tool. This community service program aims to improve the digital branding capacity of MSMEs in Iwul Village, Parung District, Bogor Regency, through the use of Google Maps and Facebook, product packaging development, and the use of ChatGPT for developing promotional captions. The methods used included observation, training, mentoring, and direct implementation with MSMEs. Seven MSMEs participated in this program. The results showed an improvement in product visual identity, an increased understanding of digital marketing among business owners, and an increase in promotional media that can be utilized independently. The use of Google Maps helped increase business visibility, while Facebook and ChatGPT supported the development of more attractive and effective promotions. The program also introduced Artificial Intelligence (AI)-based promotional content creation using ChatGPT to support MSME digital transformation. Overall, this program contributed to increasing MSME competitiveness and encouraging digital transformation at the village level..Usaha Mikro, Kecil, dan Menengah (UMKM) memiliki peran penting dalam mendukung pertumbuhan ekonomi masyarakat desa. Namun demikian, sebagian besar pelaku UMKM masih menghadapi kendala dalam aspek branding produk dan pemanfaatan media digital sebagai sarana pemasaran. Kegiatan pengabdian kepada masyarakat ini bertujuan meningkatkan kapasitas digital branding UMKM Desa Iwul, Kecamatan Parung, Kabupaten Bogor melalui pemanfaatan Google Maps, Facebook, pengembangan kemasan produk, serta penggunaan ChatGPT untuk penyusunan caption promosi. Metode yang digunakan meliputi observasi, pelatihan, pendampingan, dan implementasi langsung kepada pelaku UMKM. Sebanyak tujuh UMKM menjadi mitra dalam kegiatan ini. Hasil kegiatan menunjukkan adanya peningkatan identitas visual produk, meningkatnya pemahaman pelaku usaha terhadap pemasaran digital, serta bertambahnya media promosi yang dapat dimanfaatkan secara mandiri. Pemanfaatan Google Maps membantu meningkatkan visibilitas usaha, sedangkan Facebook dan ChatGPT mendukung penyusunan promosi yang lebih menarik dan efektif. Program ini juga memperkenalkan pembuatan konten promosi berbasis Kecerdasan Buatan (AI) menggunakan ChatGPT untuk mendukung transformasi digital UMKM. Secara keseluruhan kegiatan ini berkontribusi terhadap peningkatan daya saing UMKM dan mendorong transformasi digital di tingkat desa
PENERAPAN TEKNOLOGI DIGITAL DAN EDUKASI KREATIF UNTUK DAYA SAING PRODUK UMKM DESA IWUL, PARUNG, BOGOR Qinara Azra Puja Kaspia; Fajar Ariya Putra; Rifai Ady Setiawan; Syafatul Fida; Henifa Henifa; Tchinda Eliza Piliang; Muhammad Ramadhan; Almira Ayumi Prijanisa; Gatot Tri Pranoto; Faizah Syihab
SWADIMAS: JURNAL PENGABDIAN KEPADA MASYARAKAT Vol 3, No 2 (2025): SWADIMAS EDISI JULI 2025
Publisher : Institut Teknologi dan Bisnis Swadharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56486/swadimas.vol3no2.902

Abstract

This community service program aims to enhance the competitiveness of local MSME products in Iwul Village, Parung, Bogor, by applying digital technology and creative education. The main challenges faced by local entrepreneurs include the lack of effective digital marketing strategies and limited skills in creating visually appealing content. The implementing project conducted a series of training sessions and mentoring activities, including the use of social media, digital catalog creation, and visual content design using Canva. Additionally, creative educational activities were provided to elementary school students, and a hydroponic installation was developed to support the village's environmental aesthetics. The results showed an increase in digital marketing awareness among MSMEs and an improvement in technological skills. The creative education initiatives received positive feedback from both students and teachers. Overall, the program successfully contributed to the economic and social empowerment of Iwul Village.Kegiatan pengabdian ini bertujuan untuk meningkatkan daya saing produk UMKM Desa Iwul, Parung, Bogor melalui penerapan teknologi digital dan edukasi kreatif. Permasalahan utama yang dihadapi pelaku UMKM di desa tersebut adalah kurang optimalnya strategi pemasaran digital dan keterbatasan dalam pembuatan konten visual yang menarik. Tim pelaksana melakukan serangkaian pelatihan dan pendampingan, mulai dari penggunaan media sosial, pembuatan katalog digital, hingga pelatihan desain konten visual menggunakan Canva. Selain itu, dilakukan kegiatan edukatif berbasis kreativitas kepada siswa SD dan pembuatan instalasi hidroponik untuk mendukung estetika lingkungan desa. Hasil kegiatan menunjukkan peningkatan pemahaman pelaku UMKM terhadap pemasaran digital dan meningkatnya keterampilan masyarakat dalam menggunakan teknologi informasi. Program edukasi kreativitas juga mendapat respons positif dari siswa dan guru. Secara keseluruhan, kegiatan ini berhasil memberikan kontribusi nyata terhadap pemberdayaan ekonomi dan sosial masyarakat Desa Iwul.
Penerapan Konten Digital Pendidikan Untuk Meningkatkan Kualitas Belajar di Madrasah Ibtidaiyah Al Khoiriyah Ismasari Nawangsih; Pupung Purnamasari; Gatot Tri Pranoto; Annisa Maulana Majid; Candra Naya
Jurnal Pelita Pengabdian Vol. 2 No. 1 (2024): Januari 2024
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/jpp.v2i1.3161

Abstract

Perkembangan konten digital di dalam dunia pendidikan sangat penting di zaman era digital di dukung dengan berbagai perangkat aplikasi dan keberadaan internet saat ini memudahkan proses belajar mengajar, interaksi serta kebutuhan informasi bagi penggunanya. Pembuatan dan pemakaian konten digital ini harus diimbangi pengetahuan dampak positif dan negatif. Kegiatan pengabdian kepada masyarakt berupa penyuluhan dan pelatihan konten digital untuk dunia pendidikan dilaksanakan di Madrasah Ibtidaiyah Al Khoiriyah. Sasaran pada kegiatan PKM ini adalah para siswa ” sebanyak 20 dan 4 guru. Kegiatan ini dilaksanakan secara tatap muka (On the spot training) yang dimulai dengan observasi dan koordinasi dan perizinan dengan kepala Sekolah setempat mengenai rencana kegiatan yang akan dilakukan di lingkungan tersebut mengenai ketersediaan tempat, waktu, dan peserta. Kegiatan pengabdian dilaksanakan menggunakan beberapa tahapan: Tahap persiapan; Tahap pelaksanaan sosialisasi mengenai konten digital untuk siswa sekolah . Metode yang digunakan dalam pelaksanaan kegiatan PKM adalah sosialisasi dengan teknik penyuluhan dalam bentuk ceramah atau memaparkan materi berupa teori dan video yang berhubungan dengan tema yang kita ambil, tanya jawab, kreasi, dan permainan. Hasil kegiatan menunjukan meningkatnya cara belajar yang kreatif untuk siswa.
Optimasi memori dengan mesh simplification pada aplikasi Augmented Reality metode Marker Based Calvin Manayang; Gatot Tri Pranoto; Yaddarabullah
Jurnal Sains dan Edukasi Sains Vol. 9 No. 2 (2026): Jurnal Sains dan Edukasi Sains
Publisher : Faculty of Science and Mathematics, Universitas Kristen Satya Wacana, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/juses.v9i2p9-17

Abstract

Augmented Reality (AR) telah dikembangkan sebagai media pendidikan interaktif, termasuk untuk memperkenalkan buah-buahan yang bermanfaat bagi kesehatan kulit anak-anak. Studi ini mengembangkan aplikasi AR yang menyajikan visualisasi 3D dari lima jenis buah, yaitu pisang, anggur, semangka, jeruk, dan apel. Tantangan utama yang dihadapi adalah penggunaan memori yang tinggi akibat model 3D resolusi tinggi, yang dapat mengurangi kinerja aplikasi pada perangkat dengan spesifikasi rendah. Untuk mengatasi masalah tersebut, penelitian ini menerapkan teknik penyederhanaan mesh, sebuah metode untuk mengurangi jumlah poligon dalam model 3D tanpa secara signifikan menurunkan kualitas visual. Dua versi aplikasi dikembangkan untuk perbandingan: satu menggunakan model asli dan satu lagi menggunakan model yang disederhanakan yang dibuat dengan Blender. Pengujian dilakukan dengan menjalankan kedua aplikasi selama 30 menit pada perangkat yang sama untuk mengukur penggunaan RAM dan ukuran file aplikasi. Aplikasi ini juga dikembangkan menggunakan standar resolusi visual 720p untuk memastikan penggunaan yang nyaman bagi anak-anak tanpa membebani sistem. Hasilnya menunjukkan bahwa penyederhanaan mesh secara signifikan meningkatkan efisiensi aplikasi. Penggunaan RAM menurun dari 463 MB menjadi 287 MB (peningkatan efisiensi sebesar 37,9%), dan ukuran file aplikasi berkurang dari 290 MB menjadi 233 MB (penurunan sebesar 19,65%). Temuan ini menunjukkan bahwa optimasi model 3D dapat membuat aplikasi AR lebih ringan, lebih stabil, dan lebih efisien.
EXPLAINABLE MACHINE LEARNING FRAMEWORK FOR HOTEL CUSTOMER LOYALTY PREDICTION USING TRANSACTIONAL BEHAVIORAL DATA Pranoto, Gatot Tri; Pebrianti, Dwi; Religia, Yoga; Agusalim, Lestari
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 10 No. 3 (2026): Volume 10, Nomor 3, June 2026
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jiituj.v10i3.56180

Abstract

Customer loyalty has become a critical factor for sustaining competitiveness in the hotel industry, particularly in increasingly digital and data-driven business environments. Although hotels continuously generate large volumes of transactional customer data, transforming this data into actionable insights for customer retention and marketing decision-making remains a significant challenge. This study proposes an Explainable Machine Learning Framework for hotel customer loyalty prediction using transactional behavioral data. The study used a publicly available hotel customer transaction dataset from the Mendeley Data repository, comprising 2,000 customer records. A supervised machine learning approach was employed using Logistic Regression, Decision Tree, Random Forest, XGBoost, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Naïve Bayes. Model performance was evaluated using Stratified K-Fold Cross-Validation and classification metrics, including Accuracy, Precision, Recall, F1-Score, and ROC-AUC. Experimental results demonstrated that all evaluated models achieved perfect classification performance, with Accuracy, Precision, Recall, F1-Score, and ROC-AUC values reaching 1.000. SHAP analysis revealed that frequency_of_bookings, days_since_last_booking, total_meal_charges, and total_revenue_generated were the primary drivers of customer loyalty prediction, while average_stay_duration showed minimal influence. The findings indicate that booking frequency and customer recency are the most influential behavioral factors affecting loyalty outcomes. From a managerial perspective, the proposed framework provides actionable insights for customer retention, customer segmentation, loyalty programs, and personalized marketing strategies. This study contributes to predictive customer analytics and Explainable Artificial Intelligence by integrating predictive accuracy with transparent interpretation of customer behavior in hotel loyalty management.
Co-Authors Almira Ayumi Prijanisa Amali Amali Annisa Maulana Majid Bajsair, Faik Baskara, Jaka Adi Budiarto, Eko Calvin Manayang Candra Naya Dewi Lestari Diana Mulhimah Donny Maulana Dwi Pebrianti Edy Widodo Elia Syalom Faizah Syihab Fajar Ariya Putra Fauzi Baisyir Henifa Henifa Henny Yulianti Intan Sari Rahayu Lestari Agusalim Majid, Annisa Maulana Maulana Majid, Annisa Maulana, Donny Muhamad Ilham Fauzan Muhamad Syafareno Muhammad Darwis Muhammad Ramadhan Natan Kharisma A Nawangsih, Ismasari Pebrianti, Dwi Pupung Purnamasari Putri, Wahyuningdiah Trisari Harsanti Qinara Azra Puja Kaspia Ramadhan, Raka Hikmah Rifai Ady Setiawan romanuddin, ahmad Rudi Setiawan Samidi Samidi, Samidi Santosa, Egar Dika Satria Abadi Surojudin, Nurhadi Suwancita, I Made Syafatul Fida Syafran Nurrahman Syifa Amalia Syihab, Faizah Taofik Safrudin Tchinda Eliza Piliang Tjahjanto, Tjahjanto Wahyu Hadikristanto Wicaksana, Yusuf Eka Yaddarabullah, Yaddarabullah Yoga Religia Yoga Religia Yusman, Roni Zed Abdullah Zy, Ahmad Turmudi