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All Journal International Journal of Electrical and Computer Engineering Riau Journal of Computer Science InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Jurnal Informatika Upgris Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Teknik Komputer AMIK BSI JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Penelitian Pendidikan IPA (JPPIPA) IT JOURNAL RESEARCH AND DEVELOPMENT Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Teknik Informatika UNIKA Santo Thomas Minda Baharu Building of Informatics, Technology and Science Jurnal Mantik Informatika Jurnal Pendidikan Teknologi Informasi dan Vokasional Jurnal Tekinkom (Teknik Informasi dan Komputer) JIIP (Jurnal Ilmiah Ilmu Pendidikan) Community Development Journal: Jurnal Pengabdian Masyarakat MEANS (Media Informasi Analisa dan Sistem) International Journal Of Science, Technology & Management (IJSTM) JPM: JURNAL PENGABDIAN MASYARAKAT SECONDARY : Jurnal Inovasi Pendidikan Menengah (JIPM) Journal La Edusci Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) TEACHING : Jurnal Inovasi Keguruan dan Ilmu Pendidikan EDUTECH : Jurnal Inovasi Pendidikan Berbantuan Teknologi Bulletin of Information Technology (BIT) EXPLORER Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Journal of Computer Science and Information Systems (JCoInS) IKA BINA EN PABOLO : PENGABDIAN KEPADA MASYARAKAT Jurnal Pengabdian Masyarakat Gemilang (JPMG) Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Zadama: Jurnal Pengabdian Masyarakat JPLED Jurnal Arsitektur Jurnal Informatika: Jurnal Pengembangan IT Jurnal Pengabdian Masyarakat dan Riset Pendidikan Jurnal Gemilang Informatika (GIT) EDUCATIONAL: Jurnal Inovasi Pendidikan dan Pengajaran Jurnal Ilmu Komputer Ruru
Iwan Purnama
Universitas Labuhanbatu
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Transportation Other

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Sistem Pakar Untuk Mendiagnosis Penyakit Tubercolosis Mengunakan Metode Bayes Pada Puskesmas Petumbukan Tambak, Riski Romadhon; Purnama, Iwan; Hasibuan, Elysa Rohanayani
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 6 No. 1 : Tahun 2021
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (413.987 KB) | DOI: 10.54367/jtiust.v6i1.1284

Abstract

Tubercolosis adalah infeksi yang disebabkan oleh basil tahan asam ( BTA ). Tubercolosis merupakan penyakit menular yang apat menyerang siapa saja melalui udara. Penyakit tuberculosis merupakan penyakit menular yang berbahaya. Tuberculosis merupakan penyakit menahun atau kronis yang bisa menyerang antar usia 15-35 tahun. Cara mendiagnosa penyakit Tubercolosis adalah dengan cara pakar ahli mewawancari kemudian menguji sampel dahak dengan menggunakan laboratorium untuk mengetahui positif atau negatif penyakit Tubercolosis sehingga memerlukan waktu yang lama. Oleh karena itu dibutuhkan sebuah Sistem Pakar dengan metode Bayes untuk memudahkan dalam mendiagnosa penykit Tubercolosis . Sistem pakar ini dikembangkan menggunakan bahasa pemrograman Microsoft Visual Studio 2010 serta dengan menggunakan database Microsoft Access 2010.
Optimizing convolutional neural network hyperparameters to enhance liver segmentation accuracy in medical imaging Purnama, Iwan; Windarto, Agus Perdana; Solikhun, Solikhun
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 4: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i4.pp3876-3887

Abstract

Liver segmentation in medical imaging is a crucial step in various clinical applications, such as disease diagnosis, surgical planning, and evaluation of response to therapy, which require a high degree of precision for accurate results. This research focuses on increasing the accuracy of liver segmentation by optimizing hyperparameters in the convolutional neural network (CNN) model using the developed ResNet architecture. The uniqueness of this research lies in the application of hyperparameter optimization methods such as random search and Bayesian optimization, which allow broader and more efficient exploration than conventional approaches. The results show that the DeepLabV3Plus model (the proposed model) significantly outperforms the standard ResNet in the image segmentation task. DeepLabV3Plus shows excellent performance with an MIoU score of 0.965, a PA Score of 0.929, and a meager loss value of 0.011. These results show that DeepLabV3Plus is able to recognize and predict segmentation areas very accurately and consistently and minimize prediction errors effectively. In conclusion, the results of this study show a significant improvement in segmentation accuracy, with the optimized model providing better performance in the evaluation.
Sources of Work Stress of English Language Teachers in Secondary Government Schools Harahap, Aziddin; Siregar, Sakinah Ubudiyah; Purnama, Iwan
Journal La Edusci Vol. 6 No. 3 (2025): Journal La Edusci
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallaedusci.v6i3.2516

Abstract

This study aims to analyze the implementation of regional education policies to improve the understanding of the Qur'an in public elementary schools in South Labuhanbatu Regency. This policy is based on Regional Regulation No. 10 of 2015 concerning Improving Understanding of the Holy Book. The study used a naturalistic qualitative approach with interview, observation, and documentation study techniques. The results show that the Qur'an-based education policy is implemented through several main strategies: teacher recruitment based on religious competency, intensive training, the preparation of a standard syllabus, annual work contracts, and the implementation of Qur'an learning outside of main school hours. The success of this program is supported by the synergy between the local government, the Education Office, the Ministry of Religious Affairs, schools, and the community. The analysis shows that this policy is aligned with the principles of strategic management, transformational leadership, and systems theory, despite limitations in funding and teacher capacity. The implications of this study emphasize the importance of regional education policies as a model for improving Qur'an literacy in public elementary schools.
Sistem Informasi Manajemen Pada Puskesmas Kepenuhan Hulu Berbasis Web Purnama, Iwan; Susanti, Susi
Jurnal Pendidikan Teknologi Informasi dan Vokasional Vol 6, No 1 (2024): Jurnal Pendidikan Teknologi Informasi dan Vokasional
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jptiv.v6i1.30698

Abstract

Puskesmas merupakan salah satu instansi pemerintah yang bergerak dibidang pelayanan kesehatan masyarakat di tingkat kecamatan. Peran puskesmas sangatlah penting dalam menopang kinerja dari instansi kesehatan diatasnya seperti rumah sakit, sebagai upaya pencegahan dan penanggulangan kesehatan masyarakat. Puskesmas Kepenuhan Hulu memiliki aktifitas pelayanan seperti proses pendaftaran pasien, rekam medis, pendataan apotek. Saat ini sistem pengolahan data pasien pada tiap bagian masih dikerjakan dengan cara sistem manual atau belum memanfaatkan sistem informasi Puskesmas. Dengan masih digunakannya sistem manual dan beberapa puskesmas sudah menggunakan Simpuskesmas, maka muncul berbagai permasalahan dalam pengolahan data pasiennya. Masalah-masalah ini diantaranya adalah tingginya tingkat kesalahan dalam pengolahan data pasien (data pendaftaran, data pemeriksaan, data rujukan, dan data laboratorium) dan lambatnya proses pelayanan pasien misalnya pendataan dan pencarian data pasien. Hasil dari penelitian ini adalah dibangunnya sebuah sistem informasi manajemen pada Puskesmas Kepenuhan Hulu. Sistem informasi manajemen ini diharapkan dapat meningkatkan kinerja puskesmas. Sehingga kualitas dan mutu pelayanan menjadi meningkat.
Advantages and Disadvantages of Virtual Reality in Science Learning Systems in the 21st Century: A Review Khairul; Iwan Purnama; Arie Wahyu Prananta; Ruth Rize Paas Megahati.S; Risnawati Agustin
Jurnal Penelitian Pendidikan IPA Vol 11 No 2 (2025): February
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i2.10214

Abstract

The rapid development of information technology has brought human civilization into the 21st century, which requires mastery of 21st-century skills, such as critical, creative, collaborative, and communicative thinking. Virtual reality offers an immersive and interactive learning experience, allowing students to interact with virtual environments as if they were real, thus potentially increasing conceptual understanding and learning motivation. Virtual reality has advantages and disadvantages in science learning. Where the purpose of the study is to examine the advantages and disadvantages of virtual reality in science learning systems in the 21st century: a Review, namely collecting information from previous studies related to the Advantages and Disadvantages of Virtual Reality in Science Learning Systems in the 21st Century This review was conducted based on the review method. The results of this study explain that there are several advantages and disadvantages of using a science learning system that uses virtual reality, one of the results that explains the advantages of virtual reality is Immersive Learning so that students can see learning concepts more realistically and not only focus on books or material explanations; teachers and one of the disadvantages of virtual reality in science learning is that VR systems can be expensive to develop and maintain, making them less accessible to organizations, educational institutions with limited budgets.
Artificial Intelligence as a Science Teacher Assistant: An Analysis of Machine Learning Utilization in Diagnosing Student Misconceptions: A Review Iwan Purnama; Rian Farta Wijaya; Aziddin Harahap; Firman Edi
Jurnal Penelitian Pendidikan IPA Vol 11 No 12 (2025): December
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i12.13089

Abstract

Diagnosing these misconceptions in a crowded classroom context is very difficult, time-consuming, and subjective when using conventional methods, which often leads to ineffective teaching interventions. To address the urgent need for accurate and objective diagnosis, this article proposes and analyzes the role of Artificial Intelligence (AI), specifically Machine Learning (ML) technologies such as natural language processing (NLP). ML models can analyze student response data (essays) quickly and consistently, acting as science teacher assistants to strengthen diagnostic capabilities. This study uses a systematic literature review method to analyze and synthesize existing research findings regarding Artificial Intelligence as a Science Teacher's Assistant: An Analysis of the Utilization of Machine Learning in Diagnosing Student Misconceptions. This research aims to analyze and explain Artificial Intelligence as a Science Teacher's Assistant: An Analysis of the Utilization of Machine Learning in Diagnosing Student Misconceptions. The brief objectives of this study are as follows: to analyze the utilization of Machine Learning (ML) models in objectively diagnosing, categorizing, and predicting students' misconceptions in science. The findings of this review study indicate that student misconceptions are a persistent barrier to learning, and conventional (manual, paper-based) diagnostic methods have proven inefficient and subjective for crowded classrooms. This validates the urgent need for technological solutions.
Peningkatan Pengarahan Beam dan Estimasi Sudut Kedatangan Berbasis CNN untuk Sistem Antena MIMO Cerdas Karim, Abdul; Purnama, Iwan; Ernawati, Andi
Explorer Vol 6 No 1 (2026): January 2026
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/explorer.v6i1.2592

Abstract

This study proposes a Convolutional Neural Network (CNN)–based approach to enhance the intelligence of MIMO antenna systems in Internet of Things (IoT) environments, particularly for modeling the relationship between wireless channel characteristics and achievable communication capacity. Modern MIMO systems face complex challenges due to dynamic channel conditions such as noise, path loss, and multipath fading, which significantly affect data transmission quality. In this research, channel-related features are processed through a structured preprocessing stage before being fed into a CNN model to learn nonlinear relationships among channel parameters. The developed model is designed to predict achievable channel capacity accurately as part of an adaptive and intelligent wireless communication framework. Experimental results show that the proposed CNN model achieves a Test Loss of 0.0317 and a Mean Absolute Error (MAE) of 0.1267 on unseen test data. Visualization of actual versus predicted values indicates that the model demonstrates good generalization across most data ranges, although some deviations remain at extremely high capacity values. Compared to conventional approaches, the CNN-based method shows superior capability in capturing complex correlations among MIMO channel parameters. Therefore, this approach contributes to the development of adaptive and efficient intelligent antenna systems, supporting the growing demands of next-generation IoT communication networks.
Komparasi Perbandingan Algoritma C4.5, Naive Bayes, K-Nearest Neighbor, Random Forest Untuk Prediksi Faktor Penyebab Penyakit Diabetes Muhammad Bagus Fadli; Iwan Purnama; Rohani Rohani
Building of Informatics, Technology and Science (BITS) Vol 7 No 3 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i3.8683

Abstract

Diabetes is a chronic metabolic disease characterized by elevated blood glucose levels and can cause various serious complications and contribute to high mortality rates worldwide. The main problem in managing diabetes is the need for accurate patient status classification based on laboratory test data so that appropriate treatment can be carried out. This study aims to compare the performance of the C4.5 algorithm, Naive Bayes, K-Nearest Neighbor (KNN), and Random Forest in classifying diabetes patient data. The dataset used was sourced from Electronic Health Records (EHRs) with research subjects from Rantauprapat Regional General Hospital, totaling 10,000 data consisting of eight attributes and one class attribute, with 859 diabetes patient data and 9,141 non-diabetes patient data. The research method was carried out by dividing the data into training data and testing data using a ratio of 90:10, 80:20, and 70:30. Evaluation of model performance used accuracy parameters and Receiver Operating Characteristic (ROC) with Area Under Curve (AUC) values. The results showed that the C4.5 and Random Forest algorithms produced higher accuracy values ​​than Naive Bayes and KNN, especially at training data ratios of 90%:10% and 70%:30%. Based on the ROC evaluation, the Random Forest algorithm obtained the highest AUC values ​​at the 70%:30% ratio of 0.972 and 80%:20% of 0.970. Based on these test results, it can be concluded that the C4.5 and Random Forest algorithms have relatively better performance and are almost equivalent in classifying diabetes based on accuracy and AUC values.
Optimizing K-Means Algorithm With Elbow And Silhouette Methods For National Exam Score Data Clustering Ramzi Saputra; Iwan Purnama
Jurnal Ilmu Komputer Ruru Vol. 1 No. 1 (2024): Edisi Januari
Publisher : Yayasan Grace Berkat Anugerah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55338/jikr.v1i1.1

Abstract

The national examination is an evaluation system for basic education standarts that supports student graduation. In accordance with the regulations of the Government of the Republic Indonesia, the evaluation of learning outcomes aims to evaluate the achievement of national graduate students. As the data obtained by the author, namely the National Vocational Exam Value Data for the Vocational High School in Central Java Province for the class of 2019. But the data displayed is still random and less information. Then data mining techniques are needed to classify which schools is carried out using the k-means clustering method and using elbow and silhouette optimization, with optimum k obtained K=3 and K=2 with calculations using RStudio tools. It is expected to produce the best cluster for the grouping
ChatGPT for Teachers and Students in Science Learning: A Systematic Literature Review Iwan Purnama; Firman Edi; Ruth Rize Paas Megahati S; Tiok Wijanarko
Jurnal Penelitian Pendidikan IPA Vol 9 No 10 (2023): October
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v9i10.5259

Abstract

In Indonesia Science education has not reached a portion that is in accordance with the needs of science education. Science learning should not only focus on knowledge but must also be balanced with application in everyday life. With this application, students will know that what they learn in science is applied and useful for life. That way, students will continue to try to experiment because of their high curiosity so that students are able to produce scientific products. Science problems are not only experienced by students, but teachers who teach science at school also have science problems they face. For this reason, Chat GPT (Generative Pre-Trainer Transformer) is used as one of the Open AI (Artificial Intelligence) innovations, a research company engaged in the development of artificial intelligence. The purpose of this research is to explain GPT Chat for Teachers and Students in Science Learning. A review is conducted on the state-of-the-art methods using the preferred reporting items for reviews and meta-analyses (PRISMA) guidelines. The results of this research show that Chat GPT has main functions, Chat GPT also has many uses for teachers and students, and science learning has five domains of science education, which must be supported by appropriate technological sophistication.
Co-Authors Abdul Karim Agus Perdana Windarto Agustina Sidabutar Agustina, Asri Widya Aini, Putri Al Amri Al Maahi, Muhammad Zuhri Ali Akbar Ritonga Ali Akbar Ritonga Ambiyar, Ambiyar Andi Ernawati Andre Ardian Arie Pramana Ashari, Suci Asyahri Hadi Nasyuha Aysyah Rengganis Aziddin Harahap AZIDDIN HARAHAP Balqi, Siti Fadillah Bangun, Budianto D.Leo Surya Duha Dahrul Aman Harahap Danil Polanda Dar Hasibuan, Halmi Deby Lorensyah Rambe Dudes Manalu Duna Sari Hasibuan Elysa Rohayani Hasibuan Elysa Rohayani Hasibuan Elysa Rohayani Hasibuan Fahmi Rizal Faisal Efendi Siregar Fauzan Azim Febriani, Lisa Firman Edi Firman Edi Fitri Indina Dongoran Gomal Juni Yarnis Guna Dharma, Aditya Gunawan, Yogi Harahap, Aziddin Harahap, Nur Salimah Hasibuan, Elysa Rohanayani Hasibuan, Linda Suhela Hasibuan, Mila Nirmala Sari Heni Pujiastuti Ibnu Rasyid Munthe ibnu Rasyid Munthe Ibnu Rasyid Munthe Ibnu Rasyid Munthe Ibu Rasyid Munthe Icha Alvionita Ifdlol Amarullah Hasibuan Indah Lestari, Indah Ira Purnama Sari Irmayani, Deci Jonny Feri Jufri Julmahdi Siregar Junita Khairul Khairul Hadi Khoirunnisaiyah Lubis Listia, Bella Ayu Lubis, Rizky Ramadhan Hasan M. Rafi Mahadi Kesuma Rambe Marha As, Pawa Niassa Marlina Siregar Marlina Siregar Masrizal Masrizal Menrisal Mesran, Mesran Mhd Albani Saskirana Mohamad Fakih Firdaus Monica, Nelly Muhammad Ardansyah Muhammad Ardansyah Muhammad Bagus Fadli Muhammad Halmi Dar Muhammad Hamka Muhmmad Ardansyah Muslim N, M Rizqi Nasution, Muhammad Bobbi Kurniawan Nathania Putri1, Nathania Nelly Monica Nurhayati Nuridin Widya Pranoto Nurintan Asyiah Siregar Nurwijayanti Nur’ainun Gulo Pane, Rahmadani Puput Indrayani Rahel Marianti Ritonga Raja Inganta Sinulingga Ramzi Saputra Rasyid Munthe, Ibnu Reni Kartikaningsih Rian Farta Wijaya Rian Farta Wijaya Rio Septian Hardinata Risnawati Agustin Rizki Hariandi Rohani Rohani Rohani Rohani Rohani Ronal Watrianthos Rosnah Ritonga Ruth Rize Paas Megahati S Ruth Rize Paas Megahati S Ruth Rize Paas Megahati.S Ryan Utama Tambunan Safaridah Rambe Sakinah Sakinah Sandhi, Bagus Hari Sapriyani Sapriyani Saputra, Haris Tri Saputra, Ramzi Saragih, Reagan Surbakti Sempurna, Teguh Silestian, Selvi Siregar, Marlina Siregar, Sakinah Ubudiyah Solikhun Solikhun, Solikhun Sulis Sumitro Sarkum Sumitro Sarkum Sumitro Sarkum Sumitro Sumitro Surya Ramadhan Suryadi, Sudi Susi Susanti Sutrino Dwi Raharjo Sutrisno Dwi Raharjo Suwarti Syahputra Harahap, Hasmi Syahrul Syaiful Zuhri Harahap Syaiful Zuhri Harapan Tambak, Riski Romadhon Tiok Wijanarko Trianovie, Sri Ummy Hairani Unung Verawardina Volante, Kevin Volvo Sihombing Windo Yandri Lesmana Yandri Lesmana Yanris, Gomal Juni Zulfahmi Syahputra Zulkifli Zulkifli Zulkifli