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All Journal PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic IJCIT (Indonesian Journal on Computer and Information Technology) Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta Jurnal Teknik Komputer AMIK BSI Paradigma Jurnal Manajemen Informatika JOISIE (Journal Of Information Systems And Informatics Engineering) Jurnal Mantik JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Jurnal Teknik Informatika (JUTIF) Jurnal Sistem Informasi International Journal of Educational Research and Social Sciences (IJERSC) Indonesian Journal of Networking and Security - IJNS SPEED - Sentra Penelitian Engineering dan Edukasi Paradigma Info Abdi Cendekia Ardhi: Jurnal Pengabdian dalam Negri Jurnal Pengabdian Masyarakat
Hari Sugiarto - UBSI
Universitas Bina Sarana Informatika
Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Social Sciences Other

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Optimasi Kernel SVM dengan PSO untuk Gagal Jantung Nurdin, Hafis; Sugiarto, Hari; Yuliandari, Dewi; Wuryanto, Anus; Nawawi, Imam
Jurnal Manajemen Informatika JAMIKA Vol 15 No 2 (2025): Jurnal Manajemen Informatika (JAMIKA)
Publisher : Program Studi Manajemen Informatika, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jamika.v15i2.14409

Abstract

Accurate early detection is important to improve the quality of life of patients and reduce mortality and a major burden on the public health system caused by heart failure. This study aims to improve the accuracy of heart failure prediction using Support Vector Machine (SVM). SVM is used as a strong classifier for high-dimensional data, then optimizes its kernel using Particle Swarm Optimization (PSO), which has not been widely applied in similar studies. The method used includes computational experiments with a quantitative approach based on heart failure datasets from the UCI Repository which are analyzed using SVM with three types of kernels: Dot, Radial, and Polynomial. PSO is used to optimize the selection of kernel parameters in SVM to improve classification accuracy. The results show that SVM + PSO kernel Dot gives the best performance, with an AUC of 0.865 and an accuracy of 83.97%, and this difference is confirmed significant through a paired t-test (p <0.05) compared to SVM without optimization. PSO optimization consistently improves precision and recall in the tested kernels, indicating stability and effectiveness in classification. The impact of the research is to make a significant contribution to early detection efforts for heart failure which can lead to faster treatment and improved quality of life for patients, but also adds clinical value for medical practitioners seeking efficient and accurate classification methods.
PENGENALAN JENIS TERAPI BAGI ORANG TUA DALAM KEBERHASILAN PROSES PEMBELAJARAN KEPADA ABK DENGAN METODE MULTIMEDIA DI KAZAMA Asmadi, Iwan; Zahra, Zahra; Sugiarto, Hari; Adiwihardja, Cep
BESIRU : Jurnal Pengabdian Masyarakat Vol. 1 No. 11 (2024): BESIRU : Jurnal Pengabdian Masyarakat, November 2024
Publisher : Lembaga Pendidikan dan Penelitian Manggala Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62335/h0hyk157

Abstract

Anak Berkebutuhan Khusus (ABK) adalah anak dengan karakter khusus yang berbeda pada anak-anak umumnya tanpa selalu melihat pada ketidak mampuan mental, emosi atau fisik. Dalam setiap penanganan anak berkebutuhan khusus seringkali ditemui pemberian pendidikan ataupun penanganan berupa terapi yang kurang tepat, ini semua dapat terjadi dikarenakan berbagai hal, seperti kurangnya pemahaman pendidik ataupun orangtua terhadap hal tersebut. Pelatihan pengenalan jenis terapi bagi orang tua ini bertujuan untuk meningkatkan  pengetahuan maupun ketrampilan, bagi orang tua mau terapis dalam keberhasilan proses pembelajaran pada ABK. Kegiatan pelatihan pengenalan jenis -jenis terapi mampu menunjang efektifitas pembelajaran Anak Berkebutuhan Khusus setelah mereka belajar disekolah orang tua dapat membantu pembelajaran dirumah. Pelatihan ini juga memperkenalkan metode multimedia kepada peserta pelatihan.
NAIVE BAYES AND PARTICLE SWARM OPTIMIZATION IN EARLY DETECTION OF CHRONIC KIDNEY DISEASE Nurdin, Hafis; Suhardjono, Suhardjono; Wuryanto, Anus; Yuliandari, Dewi; Sugiarto, Hari
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 3 (2024): JUTIF Volume 5, Number 3, June 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.3.1750

Abstract

Chronic Kidney Disease (CKD) is a global health problem that requires early detection to reduce the risk of complications and disease progression. The Naïve Bayes (NB) algorithm has been proven effective in detecting CKD but its accuracy still varies. The problem with previous research is that it has not fully optimized existing algorithms in terms of accuracy and efficiency. This research aims to develop a more accurate and efficient early detection method for CKD using the NB algorithm and Particle Swarm Optimization (PSO). The NB method is known for its speed and ease of implementation, with global search capabilities and PSO for parameter optimization. Dataset from the UCI repository, which includes data pre-processing, NB implementation, performance evaluation, and enhancement with PSO. The results of NB+PSO show a significant increase in accuracy of 95.75% from 95.00% and Area Under Curve (AUC) value of 0.910% from 0.802% compared to the use of NB alone. The conclusion of this study is that the combination of NB+PSO increases effectiveness in early detection of CKD. This research opens up opportunities for further development in the medical field, especially in improving the diagnostic accuracy of other diseases.
Pengembangan Kegiatan Belajar Mengajar Berbasis Digital Melalui Program Literasi Dan Numerasi Di SDN Srimukti 1 Tambun Utara Cep Adiwiharja; Diah Wijayanti; Zahra Zahra; Hari Sugiarto; Melsa Rahmadania; Devina Brigitta Azahra; Firdaus Ibrahim
ARDHI : Jurnal Pengabdian Dalam Negri Vol. 1 No. 6 (2023): ARDHI : Jurnal Pengabdian Dalam Negri
Publisher : Asosiasi Riset Pendidikan Agama dan Filsafat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/ardhi.v1i6.88

Abstract

This literacy and numeracy training and mentoring service activity is to prepare the nation's next generation to face challenges in the global era, where to produce selective education requires quality human resources, including the development of literacy and numeracy in learning at SDN Sri Mukti 01, North Tambun, use digital-based technology at SDN Sri Mukti 01 Tambun Utara and knowledge for teachers and parents and guardians regarding the use of digital-based technology in learning. Training and development methods are carried out offline or face-to-face by students through lecturer assistance which includes introducing the scope of literacy and numeracy learning, as well as supporting teachers in developing literacy and numeracy by utilizing digital-based technology in learning and teaching activities. It is hoped that with this training, SDN Sri Mukti 01 Tambun Utara students and teachers can develop digital-based learning and teaching activities for numeracy literacy
Prediksi Keterlambatan Pembayaran Mahasiswa untuk Mitigasi Risiko Cuti Menggunakan SVM Optimasi PSO Hafis Nurdin; Imam Nawawi; Anus Wuryanto; Dewi Yuliandari; Hari Sugiarto
JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Vol. 7 No. 1 (2025): Juni 2025
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jasiek.v7i1.15483

Abstract

Delayed tuition payments present challenges for higher education institutions, impacting both financial stability and students’ academic progress. This study proposes a predictive model using Support Vector Machine (SVM) optimized by Particle Swarm Optimization (PSO) to identify students at risk of payment delays. The dataset includes academic and social attributes. A dot kernel SVM was evaluated using 10-fold cross-validation. Results show that PSO optimization significantly improved model performance, particularly in recall, which increased from 36.10% to 65.51%, indicating better identification of delayed payment cases. The analysis also reveals that social factors, such as employment and academic status, strongly influence prediction outcomes. These findings highlight the potential of the SVM-PSO model as a decision-support tool for early intervention, enabling institutions to mitigate dropout risks and enhance financial planning. By leveraging this approach, universities can better support students while maintaining administrative efficiency and institutional sustainability.
Application Design "Test Job Application" On Android OS Using The AHP Algorithm Suharjono; Hari Sugiarto; Istiqomah Sumadikarta; Muhammad Ryansyah; Muhammad Hilman Fakhriza; Arman Syah Putra
International Journal of Educational Research & Social Sciences Vol. 2 No. 5 (2021): October 2021
Publisher : CV. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51601/ijersc.v2i5.185

Abstract

The background of this research is how to make an application that makes it easier for job seekers to find work with an Android-based application method so that it can be done anywhere and anytime with a very small quota. Helped and employers and companies will also be helped. The method used in this research is to use the method of studying literature or literature by reading many journals related to this research, after that make a prototype so that it can be given an appearance. This research will be able to see whether it is successfully used or not. The problem raised in this research is how to help job seekers find work without leaving the house and being able to search for jobs around the world using only an Android based application that can be done from home. This research produces a prototype system that will be made in the future, so that it can help workers in finding work and companies in finding workers.
Co-Authors A.A. Ketut Agung Cahyawan W Ade Setiawan Adjat Sudradjat Anus Wuryanto Arjie Desmanto Arman Syah Putra Cep Adiwihardja, Cep Cep Adiwiharja Devina Brigitta Azahra Devina Brigitta Azahra Dewi Yuliandari Diah Wijayanti Diah Wijayanti Firdaus Ibrahim Firdaus Ibrahim Hafis Nurdin Hafis Nurdin Imam Nawawi Imam Nawawi, Imam Istiqomah Sumadikarta Iwan Asmadi Jamaludin - AMIK BSI Bekasi M Abi Zakaria Maria, Vivi Melsa Rahmadania Melsa Rahmadania Muhammad Hilman Fakhriza Muhammad Ryansyah Priyono Priyono Puspa Rini Rachmat Hidayat Rahdian Kusuma Atmaja Rinandi Awan Sagita - AMIK BSI Bekasi Rohimah, Luthfia Ronaldo Sibarani Siti Nurajizah Sugiono Suhardjono S Suhardjono Suhardjono Suharjono Suria Atningsih - AMIK BSI Bekasi Titik Misriati Wahid, Bilal Abdul Wahyu Nurhayati Zahra Zahra Zahra Zahra Zahra Zahra