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All Journal Jurnal Dedikasi SMATIKA Journal of Information Technology and Computer Science (JOINTECS) Jurnal Sains dan Informatika Jurnal Teknoinfo Multitek Indonesia : Jurnal Ilmiah JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) JSAI (Journal Scientific and Applied Informatics) Progresif: Jurnal Ilmiah Komputer Jurnal ABDINUS : Jurnal Pengabdian Nusantara JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Tekinkom (Teknik Informasi dan Komputer) Jurnal Abdi Insani Indonesian Journal of Cultural and Community Development Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Pengabdian Masyarakat Abdimas Madani International Journal of Engineering, Science and Information Technology Abdimas Singkerru JTECS : Jurnal Sistem Telekomunikasi Elektronika Sistem Kontrol Power Sistem dan Komputer Jurnal Abdimas Indonesia : Jurnal Abdimas Indonesia Bulletin of Computer Science Research Decode: Jurnal Pendidikan Teknologi Informasi Bulletin of Information Technology (BIT) Proceedings Series on Physical & Formal Sciences Indonesian Journal of Innovation Studies Aptekmas : Jurnal Pengabdian Kepada Masyarakat PELS (Procedia of Engineering and Life Science) Procedia of Social Sciences and Humanities Prosiding University Research Colloquium JOINCS (Journal of Informatics, Network, and Computer Science) Jurnal Sarjana Ilmu Komunikasi (J-SIKOM) Jurnal Informatika Polinema (JIP) Physical Sciences, Life Science and Engineering Indonesian Journal of Applied Technology Journal of Technology and System Information Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Journal of Electrical Engineering Journal for Technology and Science Tepak Sirih : Jurnal Pengabdian Kepada Masyarakat Madani semanTIK Journal of Blockchain, Nfts and Metaverse Technology IJHCS JCOSIS (Journal Computer Science and Information Systems) Journal of Information Technology Smatika Jurnal : STIKI Informatika Jurnal Academia Open Jurnal Komunikasi Bisnis dan Teknologi Digital
Hamzah Setiawan
Program Studi Informatika, Universitas Muhammadiyah Sidoarjo, Indonesia
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Sidohibah: Web-Based Application for Grant Applications for Private Elementary School Facilities and Infrastructure in Sidoarjo Regency Kurnia Ningtiyas; Ade Eviyanti; Hamzah Setiawan; Azmuri Wahyu Azinar
SaNa: Journal of Blockchain, NFTs and Metaverse Technology Vol. 4 No. 1 (2026): February 2026
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/sana.v4i1.730

Abstract

The process of applying for facilities and infrastructure grants at private elementary schools in Sidoarjo Regency is still mostly handled manually, which sometimes results in delays, recording errors, and difficulties in collecting data for each application. Therefore, researchers developed a web-based information system called Sidohibah. The system was developed in stages, adapting to user needs. The implementation results show that this system is capable of improving administrative efficiency while strengthening transparency in grant management.
Rancang Bangun Aplikasi Notifikasi Dan Geolocation Pada Pedagang Keliling Terdekat Berbasis Android Rina Safitri; Hamzah Setiawan; Novia Ariyanti; Rohman Dijaya
Decode: Jurnal Pendidikan Teknologi Informasi Vol. 4 No. 1: MARET 2024
Publisher : Program Studi Pendidikan Teknologi Infromasi UMK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51454/decode.v4i1.173

Abstract

Maraknya pedagang keliling di Indonesia menjadi suatu tantangan tersendiri bagi masyarakat dalam mencari pedagang keliling terdekat. Oleh karena itu, dibutuhkan suatu aplikasi yang dapat membantu calon pembeli dalam mencari pedagang keliling terdekat dengan mudah dan efisien. Rancang Bangun Aplikasi Notifikasi dan Geolocation pada Pedagang Keliling Terdekat Berbasis Android merupakan aplikasi yang dirancang dengan tujuan untuk memudahkan calon pembeli dalam mencari pedagang keliling di sekitar lokasi mereka berada. Aplikasi ini memanfaatkan fitur geolocation pada perangkat Android dan menggunakan algoritma Haversine untuk menghitung jarak antara lokasi calon pembeli dengan lokasi pedagang keliling. Selain itu, aplikasi ini juga dilengkapi dengan fitur notifikasi yang akan memberikan informasi kepada calon pembeli jika ada pedagang keliling terdekat yang sedang berada di sekitar lokasi mereka. Aplikasi ini dirancang dengan menggunakan metode penelitian Software Development Life Cycle (SDLC) dengan model pengembangan Waterfall yang terdiri dari 5 tahapan yaitu analisis kebutuhan, desain sistem, perancangan sistem, pengujian sistem, serta tahapan implementasi dan evaluasi sistem. Perancangan sistem menggunakan bahasa pemrograman Kotlin serta menggunakan Android Studio sebagai platform pengembangan. Hasil pengujian blackbox menunjukkan bahwa aplikasi dapat berjalan dengan baik dan memberikan hasil yang akurat.
Optimization of Feature Selection on Student Complaint Data Using Recursive Feature Elimination to Improve Academic Service Quality Hamzah Setiawan; Arief Senja Fitrani; Yunianita Rahmawati; Cakra Wirabumi Putra; Firdausi Usqi Salsabila
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.707

Abstract

This study aims to optimize the feature selection process on student complaint data regarding academic services in universities using the Recursive Feature Elimination (RFE) method. Student complaints' diverse and complex nature requires in-depth analysis to identify crucial features that affect service satisfaction. An accurate feature selection process can help universities understand the most frequently reported issues, enabling them to respond and improve services more effectively. The research utilizes complaint data from various aspects of academic services, such as administration, facilities, and faculty interactions. After preprocessing the data to remove noise and irrelevant entries, RFE is applied to select the most relevant features. Subsequently, a classification model is built using the selected features to identify the most significant complaint patterns. Model evaluation is conducted through cross-validation techniques to ensure accuracy and reliability, with metrics such as accuracy, precision, recall, and F1-score. The results demonstrate that the RFE method significantly enhances model performance in selecting essential features, making the classification model more efficient and accurate in predicting student complaints. Thus, this study contributes significantly to assisting universities in enhancing the quality of academic services through a more targeted analysis of student complaints. Implementing this method will improve the complaint-handling process and increase overall student satisfaction
Analysis and Design of Integrated Waste Disposal System Information Based on Website Denny Gunawan; Hamzah Setiawan; Hindarto; Suprianto
SaNa: Journal of Blockchain, NFTs and Metaverse Technology Vol. 4 No. 1 (2026): February 2026
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/sana.v4i1.733

Abstract

This study aims to design a website-based information system for waste management at the Integrated Waste Processing Site (TPST) in Siwalanpanji Village, Sidoarjo Regency. This system is designed to facilitate the recording and analysis of waste data, including recycled waste and waste disposed of at the Waste Processing Site (TPS). The method used is Rapid Application Development (RAD), which includes the stages of planning needs, design, construction, and testing using Black Box Testing. The results of this study are expected to improve the efficiency of waste management and support better decision making in waste management in the village.
The Optimalisasi Pemanfaatan Aplikasi “Sayang Warga” bagi Kader Surabaya Hebat Tingkat RT Novia Ariyanti; Hamzah Setiawan
Jurnal Abdimas Indonesia Vol. 6 No. 3 (2026)
Publisher : Perkumpulan Dosen Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34697/jai.v6i3.3575

Abstract

Abstrak: Kegiatan Pengabdian kepada Masyarakat ini bertujuan untuk meningkatkan kemampuan digital Kader Surabaya Hebat (KSH) dalam menggunakan aplikasi Sayang Warga. Aplikasi ini berfungsi sebagai media untuk memberikan layanan sosial yang berbasis digital. Kegiatan ini dilakukan pada 16 April 2026 di Balai RT 05 RW 01 di Kelurahan Dukuh Pakis, Surabaya, dan dihadiri oleh 5 orang kader. Cara pelaksanaan mencakup pengamatan, penyuluhan, pelatihan, pendampingan, dan penilaian. Hasil kegiatan menunjukkan bahwa kemampuan kader dalam menggunakan aplikasi meningkat, terutama dalam proses login, memasukkan data warga, dan memperbarui data. Selain itu, kegiatan ini juga membuat arsip data warga menggunakan Google Sheet. Ini bertujuan untuk menyimpan data dengan cara yang lebih teratur dan berkelanjutan. Kegiatan ini diharapkan bisa membantu meningkatkan pelayanan sosial yang didasarkan pada data di tingkat RT.
Development of a CNN-Based Household Waste Image Classification Model for Automatic Identification Achmad isra; Azmuri Wahyu Azinar; Suhendro Busono; Hamzah Setiawan
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 16 No 03 (2026): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v16i03.2436

Abstract

The problem of household waste in Indonesia remains a major challenge due to the low level of waste sorting and the lack of technology utilization in the waste identification process. This study aims to develop a Deep Learning-based inorganic waste identification system using the Convolutional Neural Network (CNN) method to improve the accuracy of automatic classification in the household environment. The research method used is an experiment with a quantitative approach. The dataset used consists of 92 images of inorganic waste covering the categories of plastic, paper, glass, and metal. The data went through a preprocessing stage in the form of image resizing to 224 × 224 pixels, normalization, and data augmentation, then divided into training and testing data with a ratio of 80:20. The CNN model was trained using variations in epoch parameters, batch size, and learning rate, then evaluated using metrics of accuracy, precision, recall, F1-score, and confusion matrix. The results showed that the training parameters had a significant effect on model performance. The optimal value was obtained at epoch 20 with 97% accuracy, a batch size of 8 with 97% accuracy, and a learning rate of 1×10⁻³ with 90% accuracy. The best parameter combination produced a model with 97% classification accuracy, along with balanced precision, recall, and F1-score values. These results demonstrate the effectiveness of the CNN method in automatically identifying inorganic waste types. The developed system has the potential to be applied in household environments to assist waste sorting, improve waste management efficiency, and support environmental conservation by raising public awareness of the importance of sustainable waste management. Although the model achieved 97% accuracy under a single 80:20 train-test split, its performance decreased substantially to 32.69% ± 6.93% under stratified 5-fold cross-validation, indicating potential overfitting and limited generalization.
Multi-Task Learning Berbasis Seleksi Fitur Stabil untuk Klasifikasi Komplikasi Mikrovaskular Diabetes Hamzah Setiawan; Ade Eviyanti
JCOSIS (Journal Computer Science and Information Systems) Vol. 3 No. 2 (2026): October
Publisher : Institute for Research and Community Service

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61567/jcosis.v3i2.313

Abstract

Tujuan : Mengevaluasi pengaruh seleksi fitur berbasis stabilitas dan pembobotan kelas terhadap klasifikasi retinopati, neuropati, dan nefropati diabetik menggunakan multi-task learning (MTL). Metode/Design/Pendekatan: Dari 100.000 rekam dataset publik, 27.407 rekam berstatus diabetes positif dianalisis. Sebanyak 18 dari 41 prediktor numerik dipilih menurut frekuensi ranking ANOVA F pada 20 subsampel pelatihan. Model logistic regression dan tiga konfigurasi MTL diuji dengan pembagian train/validasi/test sebesar 19.184/4.111/4.112 rekam. Average precision (AP) digunakan untuk setiap label, sedangkan macro-AUPRC merupakan rata-rata AP ketiga label. Hasil MTL dilaporkan sebagai rerata ± simpangan baku dari tiga seed. Hasil/Temuan: MTL 41 fitur memperoleh macro-AUPRC tertinggi (0,1485 ± 0,0028), dibandingkan MTL 18 fitur (0,1454 ± 0,0024) dan MTL 18 fitur dengan weighted BCE (0,1449 ± 0,0043). AP per label pada MTL 41 fitur adalah 0,1440 (retinopati), 0,1847 (neuropati), dan 0,1167 (nefropati). Pengurangan prediktor sebesar 56,1% belum memperbaiki kinerja rata-rata. Kebaharuan/Originalitas/Nilai: Studi ablasi pada tiga label komplikasi secara bersama memperlihatkan bahwa konsistensi seleksi fitur pada subsampel tidak menjamin peningkatan macro-AUPRC. Evaluasi satu pembagian data belum membuktikan kesiapan klinis.   Kata Kunci: diabetes; komplikasi mikrovaskular; multi-task learning; seleksi fitur berbasis frekuensi resampling; klasifikasi multilabel.
Co-Authors Abidin, Husnul Achmad isra Ade Eviyanti Adi Putra, Lutfi Adiffanani Ramdansyah Alshaf Pebrianggara Amelia, Paramitha Angga Wibawa Saputra Angga Arief Senja Fitrani Arief Wicaksono, Arief Arif Senja Fitrani Arif Senja Fitriani Arisandi, Ricky Renaldo Asiddiq, Afnizar Maulana Aulia Aliffiandi, Rizca Aziziyah, Ismi Anisa Azmuri Wahyu Azinar Azmuri Wahyu Azinar Azmuri Wahyu Azinar Cakra Wirabumi Putra Cindy Taurusta Denny Gunawan Duwi Rahayu Enggi Sabrilla Assara Evi Rinata Firdausi Usqi Salsabila Fuad Azis Muslim Gilang Pralaya Grahita Albarika, Ayu Hari Moerti Hindarto Hindarto Hindarto Hindarto Ika Ratna Ika Ratna Indra Astutik Imanda, Almyra Gitta Intan Nuraini Irwan A. Kautsar Irwan Alnarus Kautsar Jamal Hasan Jefry Fernando Kurnia Ningtiyas Luluk Asti Qomariah M Cholis Afandi M. Alfan Rosyid Moch Bagus Tri Cahyo Moch Ridwan Alwi Moch Ridwan Alwi Mochamad Alfan Rosid Mochamad Surohadi Mochammad Septa Sandy Mohamad Haris Muzadi Muhammad Agung Laksono Muhammad Fikri Muhammad Mursidil Arif Muhammad Saddam Heykal Bustomy Muhammad, Fajar Muhammad, Khithoh Sabda Nanda Fitriana Novia Ariyanti Nur Maslikhatun Nisak Nuril Lutvi Azizah Paramitha Amelia Kusumawardani Pratiwi, Rosa Machmuda Qur'ani, Meisyilia Difanada Rachmat Firdaus Ratih Sri Yunarti Rayhanantha Akbar Putra Prasetyo Ribangun Bamban Jakaria Rina Safitri Riswanto Rizky Budi Aprianto Rizky Rahmahdian Sandy Rohman Dijaya sandy, Mochamad septa Saputra Budianto Putra Sinta Nuriyah, Rizky Siti Cholifah Siti Cholifah SITI CHOLIFAH Steven Gerrard Suhendro Busono Sumarno . Sumarno Sumarno Suprianto Suprianto Suprianto1, Suprianto Triwahono, Handi Uce Indahyanti Vidya Wati Dwi Ramadhani Wildan Arif Hidayatulloh Wiwik Sumarmi Yunianita Rahmawati Yunianita Rahmawati Zulham Efendi, Muhammad