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All Journal Scientific Journal of Informatics Minda Baharu Amalee: Indonesian Journal of Community Research & Engagement Jurnal Teknik Informatika (JUTIF)
Afrizal Doewes, Afrizal
Sebelas Maret University
Humanities Computer Science & IT Public Health Social Sciences Other

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The Effect of Best First and Spreadsubsample on Selection of a Feature Wrapper With Naïve Bayes Classifier for The Classification of the Ratio of Inpatients Wijaya, M Rizky; Saptono, Ristu; Doewes, Afrizal
Scientific Journal of Informatics Vol 3, No 2 (2016): November 2016
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v3i2.7910

Abstract

Diabetes can lead to mortality and disability, so patients should be inpatient again to undergo treatment again to be saved. On previous research about feature selection with greedy stepwise forward fail to predict classification ratio inpatient of patient with the result of recall and precision 0 on data training 60%, 75%, 80%, and 90% and there is suggestion to handle unbalanced class data problem by comparison of data readmitted 6293 and the otherwise 64141. The research purposed to know the effect of choosing the best model using best first instead of greedy stepwise forward and data sampling with spreadsubsample to resolve unbalanced class data problem. The data used was patient data from 130 American Hospital in 1999 until 2008 with 70434 data. The method that used was best first search and spreadsubsample. The result of this research are precision found 0.4 and 0.333 on training dataset 75% and 90% with best first method, while spreadsubsample method found that value of precision and recall is more significantly increased. Spreadsubsample has more effect with the result of precision and recall rather than using best first method.
The Effect of Best First and Spreadsubsample on Selection of a Feature Wrapper With Nave Bayes Classifier for The Classification of the Ratio of Inpatients Wijaya, M Rizky; Saptono, Ristu; Doewes, Afrizal
Scientific Journal of Informatics Vol 3, No 2 (2016): November 2016
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v3i2.7910

Abstract

Diabetes can lead to mortality and disability, so patients should be inpatient again to undergo treatment again to be saved. On previous research about feature selection with greedy stepwise forward fail to predict classification ratio inpatient of patient with the result of recall and precision 0 on data training 60%, 75%, 80%, and 90% and there is suggestion to handle unbalanced class data problem by comparison of data readmitted 6293 and the otherwise 64141. The research purposed to know the effect of choosing the best model using best first instead of greedy stepwise forward and data sampling with spreadsubsample to resolve unbalanced class data problem. The data used was patient data from 130 American Hospital in 1999 until 2008 with 70434 data. The method that used was best first search and spreadsubsample. The result of this research are precision found 0.4 and 0.333 on training dataset 75% and 90% with best first method, while spreadsubsample method found that value of precision and recall is more significantly increased. Spreadsubsample has more effect with the result of precision and recall rather than using best first method.
The Effect of Best First and Spreadsubsample on Selection of a Feature Wrapper With Naïve Bayes Classifier for The Classification of the Ratio of Inpatients Wijaya, M Rizky; Saptono, Ristu; Doewes, Afrizal
Scientific Journal of Informatics Vol 3, No 2 (2016): November 2016
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v3i2.7910

Abstract

Diabetes can lead to mortality and disability, so patients should be inpatient again to undergo treatment again to be saved. On previous research about feature selection with greedy stepwise forward fail to predict classification ratio inpatient of patient with the result of recall and precision 0 on data training 60%, 75%, 80%, and 90% and there is suggestion to handle unbalanced class data problem by comparison of data readmitted 6293 and the otherwise 64141. The research purposed to know the effect of choosing the best model using best first instead of greedy stepwise forward and data sampling with spreadsubsample to resolve unbalanced class data problem. The data used was patient data from 130 American Hospital in 1999 until 2008 with 70434 data. The method that used was best first search and spreadsubsample. The result of this research are precision found 0.4 and 0.333 on training dataset 75% and 90% with best first method, while spreadsubsample method found that value of precision and recall is more significantly increased. Spreadsubsample has more effect with the result of precision and recall rather than using best first method.
Enhancing Participatory Learning at SMP Negeri 2 Jaten Karanganyar through the Integration of Technology Cahyono, Hasan Dwi; Wardani, Dewi Wisnu; Setiadi, Haryono; Wijayanto, Ardhi; Doewes, Afrizal
Amalee: Indonesian Journal of Community Research and Engagement Vol 5 No 1 (2024): Amalee: Indonesian Journal of Community Research and Engagement
Publisher : LP2M INSURI Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37680/amalee.v5i1.4816

Abstract

The development of knowledge and technology significantly impacts literacy skills, essential for academic growth and school adaptation. Technology literacy is crucial for awareness and academic support, but a lack of technological knowledge can hinder education. To address this, the Indonesian government introduced the belajar.id platform, integrating Google Suite for Education (GSuite) to aid academic activities during the pandemic. Challenges like limited teacher-student interaction persist, necessitating the encouragement of electronic media and diverse educational material availability. They aimed to bridge teaching gaps, enhance technological skills, and ensure effective knowledge sharing, using participatory rural appraisal (PRA). The team of Research Group Data Information Knowledge and Engineering (RG DIKE) at the Universitas Sebelas Maret (UNS) Surakarta conducted a study on technology literacy's importance for students in SMP Negeri 2 Jaten Karanganyar. It emphasized technology's role in disaster management and prevention, striving for a strategic approach to technology-based education. Training sessions were conducted on August 15 and October 26, 2023, focused on belajar.id, GSE, and OBS integration. Teachers played a key role in guiding and updating their GSE and OBS knowledge. In summary, these sessions aimed to equip teachers and students with vital GSE and OBS skills, enhancing education quality and learning outcomes.
PENINGKATAN KEAMANAN LINGKUNGAN DENGAN PENERAPAN CCTV DI DUKUH SRIMULYO Cahyono, Hasan Dwi; Wardani, Dewi Wisnu; Hendrasuryawan, Brilyan; Setiadi, Haryono; Doewes, Afrizal; Anggrainingsih, Rini; Wijayanto, Ardhi
MINDA BAHARU Vol 8, No 2 (2024): Minda Baharu
Publisher : Universitas Riau Kepulauan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33373/jmb.v8i2.7015

Abstract

. Berdasarkan kegiatan Pengabdian kepada Masyarakat (PkM) yang sudah terlaksana, yakni penerapan closed-circuit television (CCTV) di Dukuh Srimulyo, Boyolali, didapatkan hasil bahwa dapat membantu menyelesaikan masalah mitra. Adapun permasalahan yang ditemukan adalah kurangnya pengawasan yang dapat memberikan rasa aman kepada warga. Hal ini terjadi akibat banyaknya jalur kendaraan yang dapat melintasi wilayah tersebut tetapi belum diterapkan adanya pengawasan secara real-time. PkM ini bertujuan untuk mengatasi masalah keterbatasan tersebut. Solusi yang ditawarkan kepada mitra adalah penerapan CCTV yang dapat merekam kejadian di titik yang penting. Pendampingan dilakukan dalam bentuk pelatihan penggunaan CCTV dan penyediaan fasilitas untuk pengawasan yang akan digunakan oleh mitra. Adapun hasil dari PkM ini adalah ditemukan bahwa para warga memberikan sambutan baik dengan diterapkannya CCTV ini pada kegiatan yang dilakukan berdasarkan umpan balik yang diberikan setelah kegiatan selesai. Selanjutnya CCTV yang terpasang pada titik penting berjumlah dua dan telah melalui proses penelaahan bersama dengan warga. Adapun dampak yang diperoleh secara nyata setelah PkM ini berakhir adalah sebagian besar peserta dapat melakukan pengawasan secara mandiri menggunakan aplikasi aplikasi CCTV yang telah terpasang
Enhancing Participatory Learning at SMP Negeri 2 Jaten Karanganyar through the Integration of Technology Cahyono, Hasan Dwi; Wardani, Dewi Wisnu; Setiadi, Haryono; Wijayanto, Ardhi; Doewes, Afrizal
Amalee: Indonesian Journal of Community Research and Engagement Vol. 5 No. 1 (2024): Amalee: Indonesian Journal of Community Research and Engagement
Publisher : LP2M INSURI Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37680/amalee.v5i1.4816

Abstract

The development of knowledge and technology significantly impacts literacy skills, essential for academic growth and school adaptation. Technology literacy is crucial for awareness and academic support, but a lack of technological knowledge can hinder education. To address this, the Indonesian government introduced the belajar.id platform, integrating Google Suite for Education (GSuite) to aid academic activities during the pandemic. Challenges like limited teacher-student interaction persist, necessitating the encouragement of electronic media and diverse educational material availability. They aimed to bridge teaching gaps, enhance technological skills, and ensure effective knowledge sharing, using participatory rural appraisal (PRA). The team of Research Group Data Information Knowledge and Engineering (RG DIKE) at the Universitas Sebelas Maret (UNS) Surakarta conducted a study on technology literacy's importance for students in SMP Negeri 2 Jaten Karanganyar. It emphasized technology's role in disaster management and prevention, striving for a strategic approach to technology-based education. Training sessions were conducted on August 15 and October 26, 2023, focused on belajar.id, GSE, and OBS integration. Teachers played a key role in guiding and updating their GSE and OBS knowledge. In summary, these sessions aimed to equip teachers and students with vital GSE and OBS skills, enhancing education quality and learning outcomes.
Aspect-Based Sentiment Analysis of Access by KAI Application Reviews Using IndoBERT for Multi-Label Classification Tasks Nur Alfiana, Hilda; Doewes, Afrizal; Widoyono, Bambang
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 1 (2026): JUTIF Volume 7, Number 1, February 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.1.5402

Abstract

Ratings and reviews on mobile applications provide valuable insights into user experience and satisfaction with app features and services. However, ratings are subjective and often inconsistent with the content of the reviews. Therefore, a more in-depth analysis of the review content is necessary to identify evaluation points accurately. This study aims to evaluate the performance of IndoBERT in Aspect-Based Sentiment Analysis (ABSA) on Access by KAI application reviews. Data were collected by scraping user reviews from the Google Play Store, then annotated using a hybrid labeling approach. The resulting dataset was used to fine-tune the IndoBERT model across three ABSA tasks: aspect classification, sentiment classification for each aspect, and joint aspect-sentiment classification. We also benchmarked the model against baseline models to demonstrate its effectiveness. The results show that IndoBERT achieved the best performance across all tasks, specifically aspect classification (accuracy 0.928, F1-score 0.785), sentiment classification (accuracy 0.928, F1-score 0.752), and joint aspect-sentiment classification (accuracy 0.962, F1-score 0.549). Overall, IndoBERT successfully outperformed SVM and XGBoost with TF-IDF, BiLSTM with pre-trained IndoBERT embeddings, mBERT, and XLM-R. This study contributes a new dataset that provides resources for further research and development in Indonesian Natural Language Processing (NLP). These findings also highlight the advantages of a monolingual model trained specifically on Indonesian-language data.
Co-Authors Dewi Wisnu Wardani Hasan Dwi Cahyono Hendrasuryawan, Brilyan M Rizky Wijaya, M Rizky Nur Alfiana, Hilda Rini Anggrainingsih Ristu Saptono Setiadi, Haryono Widoyono, Bambang Wijayanto, Ardhi