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All Journal Jurnal Dedikasi Sainteks Transmisi: Jurnal Ilmiah Teknik Elektro CommIT (Communication & Information Technology) Jurnal Ilmiah Kursor Jurnal Informatika Telematika SMATIKA UNEJ e-Proceeding Jurnal Ilmiah KOMPUTASI JURNAL MEDIA INFORMATIKA BUDIDARMA Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Pendas : Jurnah Ilmiah Pendidikan Dasar MATAPPA: Jurnal Pengabdian Kepada Masyarakat Multitek Indonesia : Jurnal Ilmiah JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Teknologi Dan Sistem Informasi Bisnis JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Tekinkom (Teknik Informasi dan Komputer) Journal of Computer System and Informatics (JoSYC) Infotek : Jurnal Informatika dan Teknologi Indonesian Journal of Cultural and Community Development Indonesian Journal of Law and Economics Review Journal of Computer Networks, Architecture and High Performance Computing J-SAKTI (Jurnal Sains Komputer dan Informatika) Indonesian Journal of Education Methods Development Indonesian Journal of Innovation Studies Aptekmas : Jurnal Pengabdian Kepada Masyarakat PELS (Procedia of Engineering and Life Science) Procedia of Social Sciences and Humanities Jurnal Algoritma JOINCS (Journal of Informatics, Network, and Computer Science) Journal of Artificial Intelligence and Digital Business Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) SENAPAS Komunita: Jurnal Pengabdian dan Pemberdayaan Masyarakat Jurnal Informatika Polinema (JIP) Indonesian Journal of Applied Technology Journal for Technology and Science semanTIK IJHCS Computing and Information System Journal Smatika Jurnal : STIKI Informatika Jurnal Academia Open Jurnal Komunikasi Bisnis dan Teknologi Digital Jurnal Elektronika dan Telekomunikasi Proceeding of Informatics Collaborations and Dessimenation Meeting (Infocoding) Journal of Multidisciplinary Informatics, Artificial Intelligence, and Business Innovation
Hindarto
Program Studi Teknik Informatika, Universitas Muhammadiyah Sidoarjo, Indonesia
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Web-Based Library Information System for Prasung Village Community Services: Sistem Informasi Perpustakaan Berbasis Web untuk Layanan Masyarakat Desa Prasung Ivan Khasani; Hindarto; Sumarno; Nuril Lutvi Azizah
Indonesian Journal of Cultural and Community Development Vol. 16 No. 3 (2025): September
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/4vzd0h26

Abstract

General Background: Information technology adoption in community facilities is increasingly necessary to support organized public services. Specific Background: The Prasung Village Hall library managed borrowing, returns, and membership records manually, leading to inefficiencies and data risks. Knowledge Gap: Limited implementation of structured web-based systems in village libraries constrains systematic data management and service delivery. Aims: This study designed and implemented a website-based library information system tailored to the operational needs of the Prasung Village library. Results: The system computerized member registration, book cataloging, borrowing–return transactions, barcode generation, reporting, and fine management, verified through black-box testing with successful functional outcomes. Novelty: The integration of flowchart, DFD, ERD, and the waterfall model produced a context-specific digital library system for village-level services. Implications: The system supports organized library administration, reduces paper-based records, and provides structured access to educational resources for the local community.
WEB-BASED INFORMATION SYSTEM FOR SALES OF PRODUCTS LABELED HALAL IN KHANZA ONLINE SHOP Muhammad Rozzaq; Ade Eviyanti; Nuril Lutvi Azizah; Hindarto
Journal for Technology and Science Vol. 1 No. 1 (2024): Journal for Technology and Science
Publisher : PT ANTIS INTERNATIONAL PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61796/ipteks.v1i1.97

Abstract

The times are getting more advanced, the price of necessities is also increasing, many elements justify any means to sell food/products that are not suitable for consumption in order to get abundant profits. which has neglected an important point, namely the halalness of the product. Therefore I made research on how to create an online shop that can sell halal products that are guaranteed to be halal. The Information Sistem for Sales of Halal Labeled Products at the Web-Based Khanza Online Shop is an online shop that sells products labeled as halal, the products being sold are products that have passed the test of the Indonesian Ulema Council (LPPOM MUI) Food and Drug Research Institute. Final result of This research is a sistem that makes it easier for Muslim communities in Indonesia, especially Sidoarjo, to be able to shop online for halal products that have been tested for halal
SOSIOLOGI PENDIDIKAN DI ERA KECERDASAN BUATAN: ANTARA INOVASI PEMBELAJARAN DAN KETIMPANGAN DIGITAL DI TINGKAT SEKOLAH DASAR Wahyu Haspri; Haryanto, Sigit; Hindarto, Hindarto; Jasno, Jasno
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 11 No. 03 (2026): Volume 11 Nomor 03, September 2026 Publish
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v11i03.56492

Abstract

This study explores educational sociology in the AI era, focusing on the intersection of learning innovation and digital inequality in elementary education. While rapid advancements in artificial intelligence offer new avenues for adaptive, interactive, and personalized learning, their implementation across elementary schools remains highly uneven. This disparity is driven by gaps in internet access, device availability, teacher competence, student digital literacy, and socioeconomic backgrounds. Utilizing a qualitative descriptive design through library research, this study gathered data from scientific articles, books, policy documents, and institutional reports, which were then evaluated using content analysis. The findings reveal that although AI effectively assists teachers in curriculum design, assessment, and student engagement, digital inequality hinders the fair distribution of these benefits. Viewed through the lens of educational sociology, this gap reflects the reproduction of social inequality via unequal access to resources—where well-funded schools successfully adopt AI while under-resourced ones lag. Consequently, integrating AI in elementary schools requires systematic support through infrastructure equity, teacher training, student literacy programs, and inclusive policies.
Epilepsy Classification Using Support Vector Machine with Frequency Domain Feature Extraction Hindarto Hindarto; Ade Eviyanti; Ahmad Ahfas; Egha Arya Affandi
Jurnal Elektronika dan Telekomunikasi Vol. 26 No. 1 (2026)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/jet.797

Abstract

Epilepsy is a brain-related condition characterized by abnormal electrical activity in the brain. This condition can be identified by observing EEG signals, which record the brain's electrical activity. Automatically detecting seizures using EEG signals helps doctors diagnose the condition more quickly and accurately. In this study, a method is proposed that uses a Support Vector Machine (SVM) to classify EEG signals. The features used for classification are extracted from the frequency domain using a technique called Fast Fourier Transform (FFT). The dataset used is called the UCI Epileptic Seizure Recognition Dataset, which includes 11,500 EEG samples divided into five classes. These samples are then categorized into two main types: seizures and non-seizures. The research process includes data preprocessing with MinMaxScaler normalization, feature extraction using FFT, and data classification using SVM with varying numbers of features. Model performance is measured using several metrics, including accuracy, precision, recall, F1 score, and ROC-AUC. The results showed that the use of 21 features with the SVM model provided the best performance, with an accuracy of 97.7%, a precision of 93.2%, a recall of 95.4%, an F1 score of 94.3%, and an AUC value of 0.9930. These results are better than previous studies using similar methods, indicating that the combination of FFT and SVM is effective for detecting epilepsy using EEG signals. These findings help build a more reliable system for medical diagnosis and highlight the importance of using balanced evaluation measures in healthcare.
Analisis Frekuensi pada Sinyal EEG menggunakan Fast Fourier Transform Hindarto Hindarto; Akhmad Ahfas; Ade Eviyanti; Egha Karya Affandi
Proceeding of Informatics Collaborations and Dessimenation Meeting Vol. 1 No. 1 (2025)
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Analisis sinyal Elektrode Encephalo Graph (EEG) menunjukkan bahwa rentang frekuensi serangan epilepsi pada gangguan neurologis perlu dideteksi sejak dini untuk mengetahui kebutuhan spesifik mereka dan membantu mereka bertahan hidup dengan masalahnya. K-Nearest Neighbor (KNN) dan analisis diskriminan linier digunakan untuk mendeteksi emosi diskrit manusia (kejutan, senang, takut, netral dan jijik) melalui sinyal EEG. Tujuan dari penelitian ini adalah mengukur rentang frekuensi sinyal EEG yang berkaitan dengan epilepsi, membaginya menjadi lima domain berbeda seperti α, β, γ, δ dan θ yang terkait dengan rentang total, serta menghilangkan distribusi frekuensi. Metode Fast Fourier Transform (FFT) pada sinyal EEG digunakan untuk membandingkan perbedaan antara epilepsi dan sehat subjek. Hasil yang didapatkan pada penelitian ini, yaitu terdapat perbedaan frekuensi dan perbedaan amplitudo antara subyek sehat dan subjek yang menderita epilepsi.sehingga dengan adanya perbedaan ini, maka untuk proses klasifikasi akan menjadi lebih mudah.
Penerapan Algoritma Support Vector Machine dalam Memprediksi Tingkat Partisipasi Pemilu Berdasarkan Data Indeks Desa Membangun pada Wilayah Tapal Kuda M Bahrul Ulum; Arif Senja Fitrani; Hindarto Hindarto; Uce Indahyanti
Journal of Multidisciplinary Informatics, Artificial Intelligence, and Business Innovation Vol. 1 No. 1 (2026)
Publisher : Universitas Widya Gama Mahakam Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24903/minabis.v1i1.9

Abstract

Tingkat partisipasi pemilih mencerminkan tidak hanya kualitas demokrasi, tetapi juga kesadaran sosial masyarakat. Di wilayah Tapal Kuda, Jawa Timur, variasi partisipasi antar desa menunjukkan adanya pengaruh dari kondisi pembangunan yang beragam. Penelitian ini mengkaji penerapan Indeks Desa Membangun (IDM) untuk memprediksi tingkat partisipasi pemilih menggunakan algoritma Support Vector Machine (SVM). Data penelitian berasal dari publikasi IDM tahun 2024 yang memuat ribuan data desa dengan indikator sosial, ekonomi, dan infrastruktur. Hasil analisis menunjukkan bahwa model SVM mencapai akurasi sebesar 76%, dengan nilai precision 0,75 dan recall 0,76. Model terbukti lebih efektif dalam mengenali pola partisipasi tinggi, menandakan bahwa kemajuan desa dan akses terhadap layanan dasar berperan penting dalam meningkatkan partisipasi masyarakat. Temuan ini menegaskan bahwa pendekatan SVM berbasis data IDM dapat menjadi landasan bagi perumusan strategi kebijakan untuk mendorong keterlibatan politik masyarakat, khususnya di wilayah pedesaan.
Implementasi Segmentasi Citra Menggunakan YOLOv8 untuk Penilaian Kondisi Jalan Otomatis Jurnal Manager; Muhammad Zamroni Abdillah; Hindarto Hindarto
Journal of Multidisciplinary Informatics, Artificial Intelligence, and Business Innovation Vol. 1 No. 1 (2026)
Publisher : Universitas Widya Gama Mahakam Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24903/minabis.v1i1.10

Abstract

Kondisi infrastruktur jalan memiliki peranan krusial dalam menunjang keselamatan, kenyamanan, dan efisiensi transportasi. Namun, proses inspeksi kondisi jalan di Indonesia hingga saat ini masih banyak dilakukan secara manual sehingga cenderung subjektif, memerlukan waktu lama, dan berbiaya tinggi. Penelitian ini mengimplementasikan model YOLOv8 dengan pendekatan segmentasi citra berbasis deep learning untuk mendeteksi dan menilai kerusakan jalan, khususnya lubang (pothole). Dataset citra jalan digunakan sebagai data latih dan uji, dengan proses pelabelan berbasis mask segmentasi. Model dilatih menggunakan arsitektur YOLOv8-seg dan dievaluasi berdasarkan metrik performa seperti precision, recall, dan mean Average Precision (mAP) Sistem yang dikembangkan tidak hanya mendeteksi kerusakan jalan berupa lubang (pothole), tetapi juga melakukan segmentasi piksel untuk menghitung persentase luas kerusakan terhadap permukaan jalan secara kuantitatif. Hasil penelitian diharapkan mampu menghasilkan sistem penilaian kondisi jalan secara otomati yang objektif dan efisien, serta memberikan dukungan dalam pengambilan keputusan oleh instansi terkait.
Co-Authors Abdul Haris Setya Nugraha Abdul Rochim Ach Nur Ardyansyah Achmad Fathoni Adam Laxmana Mufti Ade Efiyan Ade Efiyanti Ade Efiyanti Ade Eviyanti Adisya Ayustina Agung, Aprelareza Ahmad Ahfas Ahmad Ahfas, Ahmad aini firdausi nuzulla Akhmad Ahfas Akhmad Jazuli Al Faris Al-Faruq, Rizqi Noval Alshaf Pebrianggara Amwalinsanu Amwalinsanu Ananda Firly Amelia Anisatul Makfiroh Arginanta, M. Arief Wisaksono Arif Senja Fitrani Azmuri Wahyu Azinar Bimo, Muhammad Nur Bisri, Muhammad Anhar Bramatya Mahendra V.N Cahyono, Priyo Imam Cindy Taurusta Daffa Fauzanrio Iswinarko Dian Amalia Dimas Bayu, Dimas Dimas Tri Anggara Donni Adeleo Ardana Efendy, Egha Arya Efiyanti, Ade Egha Arya Egha Arya Affandi Egha Karya Affandi Endang Fauziati Eriec Priyono Erika Anjani Putri fahrezi auliasyafa Fina Rahma Dewi Fitria Eka Wulandari Fitriah Fitriah Gilang Dwi Anggoro Guko, William Yviis Hamid, Moch Siddiq Hamzah Setiawan Harsono Harsono Hendrik Kusnanto Ika Ratna Indra Astutik Ilham Rofiqi, Mochammad Ilham Wahyu Firmansyah Imanda, Almyra Gitta Imroatus Sholikhah, Imroatus Indah Apriliana Sari Wulandari Indrawati, Marcella Irwan Alnarus Kautsar Istya, Riska Adi Ivan Khasani Izza Anshory Jasno, Jasno Javier, Gomes Noor jurnal manager Kautsar, Irwan Alnaurus KHOIRI Kurnianto, Happy Lailia, Jauharotul Lorin, Emelin Yuan M Bahrul Ulum Maghdhuroh, Umi Mahdhuroh, Umi MARIA BINTANG Maulana Iqbhal Prayogha Slamet maulana, Metatia intan Mauridhi Hery Purnomo Moch Gesang Akbar Jani Moch Ridwan Alwi Moch Ridwan Alwi Moch Siddiq Hamid Moch. Hariadi Mochamad Alfan Rosid Mochammad Luthfan Hakim Mochammad Luthfan Hakim Mochammad Septa Sandy Mohammad Suryawinata Muchammad Issom Agustian Mufti, Adam Laxmana Muhammad Arshiel Naufal Dzaki Muhammad Danil Haqewi Muhammad Fahruddin Mahfudhoni Muhammad Rozzaq Muhammad Zamroni Abdillah Muhammad, Fajar Nisa, Umi Khoirun Ni’mah, Alfa Nouval Aulia Rachman Novia Ariyanti NUR KHOLIFAH Nur Maslikhatun Nisak Nuril Lutvi Azizah Paramitha Amelia Kusumawardani Prasetyo, Yoga Eko Priyambodo, Dimas Puspitasari, Kiki Candra Putra, Rio Ananda Quraini, Isyaffina Rachmad Aditya Pratama Ramadhan, Mochammad Hisyam Syah Ribangun Bamban Jakaria Riski Yulianto Riski Yulianto Rizky Ndaru Wicaksono Rohman Dijaya Rosa, Yoshinta Maylia Rosid, Muhammad Alfan Sabar Narimo Safir Saputra Setiawan sandy, Mochamad septa Setyawati, Enik Shiddiq, Zulfian Syahril Sigit Haryanto Slamet, Maulana Iqbhal Prayogha Suhendro Busono Sumarno Sumarno . Sumarno Sumarno Supartini, Windah Suprianto Sutama Suyadi, Tarekh Alif Firmansyah Syafii, Olynda Mufariihana Nur Syahfrizka Dyah Nazwa Umbara Syahrorini, Syamsudduha Syamsiar, Syamsiar Tarekh Alif Firmansyah Suyadi Tassa, Tara Januar Abwina Triwahono, Handi Uce Indahyanti Utama, Bagas Riski Vania, Talitha Viyanti, Amalia Wahyu Haspri Wahyu, Muhamamad Widiantoro, Rulli Windah Supartini Wulandari, Alidza Septiam Yoga Eko Prasetyo Yulian Findawati Yunianita Rahmawati Zahputra, Aldy Trisza