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All Journal JAIS (Journal of Applied Intelligent System) RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JISA (Jurnal Informatika dan Sains) Jurnal Sistem Informasi dan Sains Teknologi 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) 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 Social Sciences Other

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Pelatihan Menggunakan Canva Untuk Meningkatkan Kreatifitas Design Grafis Pada Madrasah Ibtidaiyah Al-Khoiriyah.: Pelatihan Menggunakan Canva Untuk Meningkatkan Kreatifitas Design Grafis Pada Madrasah Ibtidaiyah Al-Khoiriyah. Nawangsih, Ismasari; Purnamasari, Pupung; Maulana, Donny; Maulana Majid, Annisa; Budiarto, Eko; Tri Pranoto, Gatot
Jurnal Pelita Pengabdian Vol. 2 No. 2 (2024): Juli 2024
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/jpp.v2i2.4710

Abstract

The development of creativity and teaching and learning activities for students and teachers in the world of education continues to develop along with the times. The digital era is supported by various application devices and the existence of the internet currently helps the teaching and learning process. Students need Canva training as a promotional media and information on school activities. The uses for students are making posters, class presentations and so on. Meanwhile, for teachers, it is a teaching presentation. This training is assisted and supported by the Lecturer Team as tutors because community service activities are part of the tri dharma of lecturers which must be carried out as a form of service and concern for the surrounding community. Activities in the form of counseling and design training using Canva were carried out at Madrasah Ibtidaiyah Al Khoiriyah. The target group for this PKM activity is 20 students and 2 teachers. This activity is carried out face to face (On the spot training) which begins with observation and coordination and permission with the local school principal regarding planned activities to be carried out in that environment regarding availability. place, time and participants. Service activities are carried out using several stages: Preparation stage; Stage of implementing socialization regarding digital content for school students. The method used in implementing PKM activities is socialization using counseling techniques in the form of lectures or presenting material in the form of theory and videos related to the theme we are taking, questions and answers, creations and games. The results of the activity show an increase in creative ways of learning for students
K-MEANS ALGORITHM IN CLUSTERING SALES DATA FOR CALCULATING ESTIMATED HOUSE PRICES Pranoto, Gatot Tri
(JAIS) Journal of Applied Intelligent System Vol. 9 No. 2 (2024): Journal of Applied Intelligent System
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jais.v9i2.11027

Abstract

Determination of the value of the guarantee to the Bank in the process of applying for Home Ownership Credit (KPR) submitted by prospective customers still refers to the provisions of the Financial Services Authority, where the assessment must follow the existing rules and be carried out by public appraisals or commonly called the Office of Public Appraisal Services (KJPP). Currently the analyst credit officer cannot validate the results of the assessment report from KJPP, so if an error occurs either intentionally or not by KJPP or appraisal parties continue to process according to the given value. In the event of default of payment by the customer due to the lower collateral value of the loan provided, the bank violates Bank Indonesia Regulation number 18/16/PBI/2016 concerning loan to value ratio. This study aims to apply the K-Means algorithm in grouping home sales so that it can be used for the calculation of the estimated value of house prices, and develop a prototype of the house price estimation information system. Data retrieval using crawling or scrapping techniques on the website makes it easier to fulfill data on a dataset. The result of this study is the data of home sales for kebon Jeruk area spread across the internet can be grouped into 3 clusters with the value of David Bouldin Index in duri Kepa sub area, which is 0.096, in South Kedoya sub area of 0.087, in North Kedoya sub area of 0.071, and Kelapa Dua sub area of 0.117. By combining clusterization results using K-Means methodology with land price calculation formula obtained land price estimation in sub area. Keywords: K-Means, KPR, Data Scraping, KJPP, MAPPI
English Class Scheduling Information System at Indonesian-American Educational Institutions Bajsair, Faik; Baisyir, Fauzi; Pranoto, Gatot Tri
(JAIS) Journal of Applied Intelligent System Vol. 9 No. 2 (2024): Journal of Applied Intelligent System
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jais.v9i2.11304

Abstract

The purpose of the research is to create and implement a simple class scheduling application that is useful to minimize the occurrence of clashes of time, classes, levels, teachers and students at the same time. The research method used is the Descriptive Method with the type of case study research. The descriptive method is a method of researching the status of a group of people, an object, a set of conditions, a system of thought or an event in the present. From this Thesis or Final Project, the author can draw the conclusion that the English Class Scheduling Information System in Indonesian-American Educational Institutions is more effective, fast, conceptual, and up to date in data processing
PENERAPAN TEKNOLOGI DIGITAL DAN EDUKASI KREATIF UNTUK DAYA SAING PRODUK UMKM DESA IWUL, PARUNG, BOGOR Kaspia, Qinara Azra Puja; Putra, Fajar Ariya; Setiawan, Rifai Ady; Fida, Syafatul; Henifa, Henifa; Piliang, Tchinda Eliza; Ramadhan, Muhammad; Prijanisa, Almira Ayumi; Pranoto, Gatot Tri; Syihab, Faizah
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.
Classification of Oil Loss Levels in Palm Oil Processing Using Near-Infrared Spectroscopy with Machine Learning Muhamad Ilham Fauzan; BAskara, Jaka Adi; Putri, Wahyuningdiah Trisari Harsanti; Pranoto, Gatot Tri
(JAIS) Journal of Applied Intelligent System Vol. 10 No. 1 (2025): April 2025
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jais.v10i1.13037

Abstract

Oil losses in palm oil processing materials, such as Final Effluent, Empty Fruit Bunches, Kernels, Pressed Fiber, and Decanter Solids, pose significant challenges in ensuring production efficiency. FOSS-NIRS technology has been proven capable of quickly and efficiently detecting oil content, but its detection accuracy requires further analytical support. This study aims to develop a machine learning model that can accurately classify FOSS-NIRS data to detect oil losses that are either above the standard (red category) or below the standard (green category). By utilizing FOSS-NIRS data across five material categories, the proposed model is expected to provide precise predictions and support decision-making in palm oil production processes. The results of the study indicate that applying machine learning methods to FOSS-NIRS data can enhance the accuracy of oil loss classification, making it a potential solution for broader implementation in the palm oil processing industry to optimize production efficiency.
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.
Comparison of Holt Winters and Simple Moving Average Models to Identify the Best Model for Predicting Flood Potential Based on the Normalized Difference Water Index Ramadhan, Raka Hikmah; Yusman, Roni; Pranoto, Gatot Tri
JISA(Jurnal Informatika dan Sains) Vol 5, No 2 (2022): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v5i2.1316

Abstract

Flood is a condition in which water cannot be accommodated in a drainage channel such as a river or river. An area is said to be flooded if the water in the area is inundated in large quantities so that it can cover all or most of a large area. Determining forecasting or prediction on a potential in the long or short term, especially changes in water content levels in an area, requires a method, model, or approach that must be well tested. The lower the error value in a model, the better the model for testing a forecast. One of the data that can be used for analysis of potential flood models is the use of remote sensing data with technology from Landsat 8. The advantage of sensing data from Landsat 8 is that it has data good history and allows to see changes in land cover from year to year in an area. The purpose of this study was to determine the best model for forecasting the potential for flooding in an area using the Holt Winters model and the Simple Moving Average. The result of this research is that the RMSE, MAE, MAPE, MSE values in the Holt Winters model are 0.03598683, 0.02748707, 0.13944356, 0.00129505 while the RMSE, MAE, MAPE, MSE values on the Simple Moving Average are 0, 09681483, 0.06338657, 0.53775228, 0.00937311. The Holt Winters model is the best model of the Simple Moving Average because the forecast error value has a low value. 
Decision Support System to Select the Best Customers Using Analytical Hierarchy Process (AHP) Methods, Simple Additive Weighting (SAW) Methods, Weight Aggregated Sum Product Assessment Methods (WASPAS) at the Kebaya Shop Nurrahman, Syafran; Pranoto, Gatot Tri; Tjahjanto, Tjahjanto; Samidi, Samidi
JISA(Jurnal Informatika dan Sains) Vol 5, No 2 (2022): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v5i2.1317

Abstract

Style Queen Kebaya Store (SQ Kebaya) is a store that is engaged in apparel, its product sales focus includes adult and children's kebaya. The negative impact of the Covid 19 Pandemic has proven that the Store (SQ Kebaya) has experienced a decline in sales turnover in 2020, therefore the SQ Kebaya Store's efforts to restore its sales activities are by giving gifts for customer appreciation during the COVID 19 season through selecting the best customers for the 2020 period. However, the problem faced by SQ Kebaya Stores in the process of evaluating the best customer selection is that there is no criterion weight so that the decision making is not right on target, making the best customer decisions less efficient because they have to look for customer sales records manually in the sales record book. This study produces a web-based decision support system for selecting the best customers at SQ Kebaya Stores using the AHP (criteria weight), SAW and WASPAS (best customer ranking) methods, this study produces priority weights and importance levels of each criterion, namely status (0.37 ), method of payment (0.23), total spending (0.14), quantity (0.13), intensity of visits (0.07), length of subscription (0.07) and the result of ranking the percentage of the largest alternative value is the alternative SAW method with an average of 0.6952 , while the WASPAS method is 0.6405. It can be concluded that the right method used to obtain the best alternative value is the SAW method.  
DECISION SUPPORT SYSTEM FOR DETERMINING DEPARTMENT USING THE PROFILE MATCHING INTERPOLATION METHOD AT WIKRAMA VOCATIONAL SCHOOL, BOGOR Pranoto, Gatot Tri; Nugroho, Agung; Zy, Ahmad Turmudi
JISA(Jurnal Informatika dan Sains) Vol 6, No 1 (2023): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v6i1.1625

Abstract

Wikrama Vocational High School is one of the schools that routinely carries out the determination of majors every year. The majors process at Wikrama is carried out in the tenth grade by the Guidance and Counseling Teacher (BK Teacher) and the Head of Expertise Competence (Kakomli). BK and Kakomli teachers have difficulty determining the results of majors when there are more interest in one major than other majors, there is a mismatch of majors results because they are not in accordance with the existing majors in the chosen field of expertise and the process of majors is not accurate and fast. This is because it has not used an objective mechanism for determining majors, there is no weighting process, and there is no information system available. Therefore, it is necessary to develop a decision support system (DSS) to assist the process of determining majors using Profile Matching and Interpolation methods. The Profile Matching method is used for appraising decisions, while the Interpolation method is used for the weighting process. The criteria used in each field of expertise are Informatics Engineering with 11 criteria and Computers, Business Management with 8 criteria, and Tourism with 7 criteria. Based on the results of testing and validation that have been carried out by experts, it has an accuracy value of 93%. The accuracy value indicates that the system can provide recommendations for determining the right major. In addition, the interpolation weighting method is proven to increase the accuracy value compared to the ordinal weighting value in Profile Matching. The results of this study are in the form of a decision support system that helps in determining majors objectively, quickly and accurately.
Implementation of TF-IDF Algorithm and K-mean Clustering Method to Predict Words or Topics on Twitter Darwis, Muhammad; Pranoto, Gatot Tri; Wicaksana, Yusuf Eka; Yaddarabullah, Yaddarabullah
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.v3i2.831

Abstract

The social media time line, especially Twitter, is still interesting to follow. Various tweets delivered by the public are very informative and varied. This information should be able to be used further by utilizing the topic of conversation trends at one time. In this paper, the authors cluster the tweet data with the TF-IDF algorithm and the K-Mean method using the python programming language. The results of the tweet data clustering show predictions or possible topics of conversation that are being widely discussed by netizens. Finally, the data can be used to make decisions that utilize community sentiment towards an event through social media like Twitter.  
Co-Authors Amali Amali Annisa Maulana Majid Bajsair, Faik Baskara, Jaka Adi Budiarto, Eko Dewi Lestari Donny Maulana Edy Widodo Fauzi Baisyir Fida, Syafatul Henifa, Henifa Henny Yulianti Intan Sari Rahayu Ismasari Nawangsih Kaspia, Qinara Azra Puja Majid, Annisa Maulana Maulana Majid, Annisa Maulana, Donny Muh. Darwis Muhamad Ilham Fauzan Muhammad Darwis Muhammad Ramadhan Natan Kharisma A Nawangsih, Ismasari Naya, Candra Nugroho, Agung Nurhadi Surojudin Piliang, Tchinda Eliza Prijanisa, Almira Ayumi Pupung Purnamasari Pupung Purnamasari Putra, Fajar Ariya Putri, Wahyuningdiah Trisari Harsanti Ramadhan, Raka Hikmah romanuddin, ahmad Samidi Samidi, Samidi Santosa, Egar Dika Setiawan, Rifai Ady Suwancita, I Made Syafran Nurrahman Syihab, Faizah Taofik Safrudin Tjahjanto, Tjahjanto Wahyu Hadikristanto Wicaksana, Yusuf Eka Yaddarabullah, Yaddarabullah Yoga Religia Yusman, Roni Zy, Ahmad Turmudi