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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Wikrama Parahita : Jurnal Pengabdian Masyarakat Jurnal Teknik Informatika (JUTIF) Journal of Soft Computing Exploration
Setiyawan, Ramadhana
Universitas Negeri Yogyakarta, Indonesia
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Social Sciences

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Analisis Pengaruh Kebiasaan Belajar, Minat Belajar, Lingkungan Belajar Siswa Terhadap Prestasi Belajar Pemrograman Dasar Kelas X Teknik Komputer dan Jaringan (Studi Kasus: SMKN 5 Malang) Ramadhana Setiyawan; Retno Indah Rokhmawati; Satrio Hadi Wijoyo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 8 (2019): Agustus 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (821.052 KB)

Abstract

This study is a descriptive study designed to discuss the implications of learning habits, learning interests, and learning environments on the learning progress of Basic Class X programming in computer and network technology in SMK 5 Malang. Data collection uses a questionnaire methodology to obtain data related to study habits, learning interests, learning environment, and the use of documentation methods to determine students' learning performance. This study also uses a purposive methodology with a population of 80 students in Class X computer and network engineering from SMKN 5 Malang. The instrument tests were conducted by 32 students in Class XI computer and network technology. Multiple linear regression was used to analyse the data before being entered into the analysis step, the data was first tested using the analysis precondition test, and the results of the data were normalized, linear, and there was no heterokesdastisitas.This study found that (1) partially learning habits have a positive and significant impact on class X computer and network learning performance at Malang 5 Vocational High School, (2) partially learning interests have a negative and significant impact on basic programming skills, (3)Learning Achievements Have Class X Computer and Networking Technology at Malang Vocational Secondary School 5 Partly the learning environment is not significant, but it does have a positive impact on the learning performance of basic programming in Class X computer and network engineering at SMK 5 in Malang, (4) Simultaneity Learning interest, learning environment has an impact on the learning performance of basic programming in Class X of computer and network technology in SMK 5 Malang and is significant.
Comparison of the performance of naive bayes and support vector machine in sirekap sentiment analysis with the lexicon-based approach Setiyawan, Ramadhana; Mustofa, Zaenal
Journal of Soft Computing Exploration Vol. 5 No. 2 (2024): June 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v5i2.367

Abstract

The general public often uses the SiRekap application to see the progress of the election and to provide critical statements. Policies made by the government have good and bad outcomes, and users end up leaving their reviews and ratings on the Google Play Store, where the app can be downloaded. These reviews can be collected and processed into useful information such as sentiment analysis using Naïve Bayes and Support Vector Machine methods. Both methods have differences during training and during evaluation. The difference in results from the various scenarios tested was not much different. When training the Support Vector Machine model is able to process comment data labeled with a lexicon 10% better than the Naïve Bayes model by looking at the results of the accuracy of the two models. During the accuracy evaluation process, the two models produce the same accuracy of 72%. Although both models get the same accuracy during the evaluation process, there are differences in precision, recall, and f1 score. The difference is that the Support Vector Machine model is 5% better for precision, 8% for recall, and 3% for f1-score compared to the Naïve Bayes model. This research is limited to only knowing the performance of two machine learning models, namely the use of naive bayes and svm by using a label lexicon. The results obtained can be improved for the better. Improving the evaluation results can be done by adding data or using text data augmentation and there is creation from experts related to language sentiment.
Learning Management Training Management System at STKIP Pacitan as an Effort to Increase Learning Effectiveness Munir, Agus Qomaruddin; Wardani, Ratna; Nurkhamid, Nurkhamid; Setiyawan, Ramadhana; Mustofa, Zaenal
Wikrama Parahita : Jurnal Pengabdian Masyarakat Vol. 9 No. 1 (2025): May 2025
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jpmwp.v9i1.8986

Abstract

STKIP Pacitan has adopted Moodle as its primary Learning Management System (LMS) to improve the quality of learning and teaching efficiency in the digital era. Adapting to educational technology requires the faculty's deep understanding and effective management skills. Therefore, Moodle management training was conducted to enhance the faculty's abilities in planning, targeting, and producing quality learning outcomes. Through interactive sessions and workshops, faculty members were taught how to design courses, organize content, and utilize Moodle's features for more dynamic and participatory learning activities. The main focus of the training was on integrating assessment tools and discussion forums to enhance interaction and effective feedback. The training evaluation was conducted by measuring the faculty's performance before and after the training using indicators of course planning quality and evaluation tools. The training successfully demonstrated that the use of Moodle not only supports the efficiency of the teaching and learning process but also improves the quality of education at STKIP Pacitan, with increases of 27%, 68%, and 77% over three months in May, June, and July 2024, respectively. In addition, several applied learning methods positively impact students; feedback to students is increasingly focused (LMS record), which shows that learning effectiveness is increasing. This training recommends ongoing training to ensure optimal utilization of educational technology and continuous adaptation to the latest developments in educational technology.
Assistance in Managing Content for the Culinary Park Website to Increase Visits in Katekan Gantiwarno Village, Klaten, Central Jawa Nurkhamid, Nurkhamid; Munir, Agus Qomaruddin; Wardani, Ratna; Setiyawan, Ramadhana; Mustofa, Zaenal
Wikrama Parahita : Jurnal Pengabdian Masyarakat Vol. 9 No. 1 (2025): May 2025
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jpmwp.v9i1.9329

Abstract

Katekan Village Culinary Park, Gantiwarno, Klaten, Central Java, is a culinary tourism spot that was just inaugurated in July 2023 by the Regent of Klaten which aims to develop local MSME activities in the Klaten area of Central Java. Several problems include the need to open insights for culinary MSME actors to participate in developing culinary tourism spots, limited infrastructure, information systems, management, marketing and promotion, product quality and sustainability, and local community participation. The urgency lies in the potential to transform Katekan Village into an attractive tourism destination and provide better business opportunities for surrounding MSMEs. The method used in this PKM activity is Participation Action Research, involving the village government in managing information media and fostering information media management skills through websites, which impacts the increase in the number of visits. The output of this activity is an activity in the form of developing culinary park tourism in Katekan Village, Gantiwarno, Klaten, Central Java, with information technology media in the form of a prototype of a website-based culinary park information system which has an impact on increasing the number of visits by 70%.
Deep Learning Rnn-Lstm Model For Forecasting Tourist Visits In Yogyakarta Using Bps Time-Series Data Munir, Agus Qomaruddin; Wardani, Ratna; Setiyawan, Ramadhana; Mustofa, Zaenal; Nurkhamid, Nurkhamid
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 6 (2025): JUTIF Volume 6, Number 6, Desember 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.6.5467

Abstract

Tourism is a crucial sector in Indonesia's economic growth, particularly in Yogyakarta, contributing significantly to revenue, job creation, and infrastructure development. However, the COVID-19 pandemic has significantly impacted the tourism industry, making tourist arrival forecasting crucial for effective government policy decision-making. This study aims to predict tourist arrivals in Yogyakarta using deep learning models, specifically the Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) algorithms, chosen for their ability to process time series data and address non-linearity issues. Tourist arrival data from the Yogyakarta Central Statistics Agency (BPS) was used to train and test the model. Model evaluation was conducted using the Root Mean Squared Error (RMSE) metric to measure prediction accuracy. The results show that this model can accurately predict tourist arrival patterns, which can support strategic decision-making regarding the procurement of tourism facilities in Yogyakarta. The impact of this research is to provide practical benefits for local governments and tourism industry players in planning tourism promotion and management strategies. With more accurate predictions, relevant parties can prepare necessary resources and optimize tourism services according to projected visitor numbers.
Co-Authors Agus Qomaruddin Munir Nurkhamid, Nurkhamid Ratna Wardani Retno Indah Rokhmawati Satrio Hadi Wijoyo Zaenal Mustofa