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INDONESIA
Indonesian Journal of Applied Informatics
Published by Universitas Sebelas Maret
ISSN : 25483846     EISSN : 25985981     DOI : -
Core Subject : Science,
Computer Science & IT
Indonesian Journal of Applied Informatics publishes articles that are of significance in their respective fields whilst also contributing to the discipline of informatics as a whole and its application. Every incoming manuscript will first be examined by the Editorial Board in accordance with sub-fields of research and attention to elements of conformity with the format and guidelines for writing Indonesian Journal of Applied Informatics. Each manuscript is declared eligible by the editor will be returned to the author (if there are repairs) or can be directly issued (if there is no revision required).
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Articles 23 Documents
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Search results for , issue "Vol 10, No 1 (2025)" : 23 Documents clear
Back Matter IJAI Back Matter IJAI
IJAI (Indonesian Journal of Applied Informatics) Vol 10, No 1 (2025)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijai.v10i1.114893

Abstract

Sistem Rekomendasi Penentuan Majelis Hakim Perkara Tingkat Pertama Menggunakan Metode Support Vector Machine (SVM) pada Pengadilan Agama Sragen Shoffia Fajrin; Joni Maulindar; Afu Ichsan Pradana
IJAI (Indonesian Journal of Applied Informatics) Vol 10, No 1 (2025)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijai.v10i1.103979

Abstract

Abstrak : Penetapan majelis hakim secara manual di Pengadilan Agama Sragen sering kali memerlukan waktu hingga tiga hari dan berisiko menimbulkan ketidakefisienan, terutama ketika jumlah perkara tinggi dan ketua pengadilan berhalangan hadir. Penelitian ini bertujuan mengembangkan sistem rekomendasi susunan majelis hakim perkara tingkat pertama dengan metode Support Vector Machine (SVM) untuk memberikan rekomendasi yang lebih cepat dan efisien kepada Ketua Pengadilan Agama Sragen. Sistem dibangun menggunakan pendekatan hybrid, menggabungkan model klasifikasi SVM untuk perkara umum dan rule-based untuk perkara khusus seperti ekonomi syariah dan dispensasi kawin. Dataset yang digunakan terdiri atas 1.428 data perkara dan delapan profil hakim, yang diproses melalui tahap pembersihan teks, ekstraksi kata kunci, transformasi fitur dengan TF-IDF dan one-hot encoding, serta balancing data menggunakan SMOTE. Model dilatih dengan kernel RBF dan divalidasi melalui 5-fold cross-validation. Hasil pengujian menunjukkan model ketua majelis mencapai F1-score 64%, akurasi 63%, presisi 66%, dan recall 63%. Sementara model anggota 2 memperoleh F1-score 56%, dan anggota 1 sebesar 36%. Confusion matrix memperlihatkan bahwa sistem dapat mengenali pola penugasan hakim dominan namun masih kesulitan menangani kelas minoritas. Sistem ini menunjukkan potensi sebagai alat bantu rekomendasi yang mampu meningkatkan efisiensi, akurasi, dan konsistensi dalam penetapan majelis hakim.=================================================Abstract :Manual assignment of judicial panels at the Sragen Religious Court often takes up to three days and poses a risk of inefficiency, especially when the case load is high and the chief judge is unavailable. This study aims to develop a recommendation system for composing first-instance judicial panels using the Support Vector Machine (SVM) method, in order to provide faster and more efficient recommendations to the Chief Judge of the Sragen Religious Court. The system is built using a hybrid approach, combining an SVM classification model for general cases and a rule-based approach for special cases such as Islamic finance and marriage dispensation. The dataset used consists of 1,428 case records and eight judge profiles, processed through text cleaning, keyword extraction, feature transformation using TF-IDF and one-hot encoding, and class balancing using SMOTE. The model is trained with the RBF kernel and validated using 5-fold cross-validation. Evaluation results show that the model for the chief judge achieved an F1-score of 64%, accuracy of 63%, precision of 66%, and recall of 63%. Meanwhile, the model for member 2 reached an F1-score of 56%, and member 1 only 36%. The confusion matrix reveals that the system can recognize dominant judge assignment patterns, although it still struggles with minority classes. This system demonstrates strong potential as a recommendation tool that can enhance efficiency, accuracy, and consistency in judicial panel assignments.
Sistem Monitoring Lingkungan Berbasis IoT pada Aplikasi Smart Farming Berbasis Arduino Menggunakan Protokol MQTT Latifah Citra Mahkota; Medilla Kusriyanto
IJAI (Indonesian Journal of Applied Informatics) Vol 10, No 1 (2025)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijai.v10i1.109177

Abstract

Abstrak : Meskipun sumber daya pertaniannya melimpah, Indonesia masih berjuang untuk mencapai swasembada pangan. Indonesia masih bergantung pada impor untuk beberapa bahan pangan, yang menunjukkan produktivitas pertanian nasional belum optimal. Tantangan utama meliputi terbatasnya akses petani terhadap informasi, ketergantungan pada metode konvensional yang tidak efisien, dan kurangnya pemanfaatan teknologi modern di lapangan. Penelitian ini mengatasi kendala tersebut dengan merancang dan menguji sistem pemantauan lingkungan berbasis Internet of Things (IoT) untuk mendukung pertanian cerdas. Sistem ini memanfaatkan empat sensor utama, yaitu sensor DHT11, Soil Moisture Hygrometer, LDR, serta sensor curah hujan. Data sensor dikumpulkan oleh Arduino Uno, disimpan di MicroSD Card, dan dikirimkan ke NodeMCU ESP8266 untuk diteruskan ke broker  MQTT HiveMQ. Data sensor divisualisasikan secara real-time pada dashboard  web yang dilengkapi sistem notifikasi ambang batas. Hasil pengujian menunjukkan bahwa sensor DHT11 stabil dalam mengukur suhu (30–32 °C) dan sensitif terhadap kelembaban (76–92 %), Soil Moisture Hygrometer mampu membedakan kondisi tanah dari kering hingga jenuh, LDR menunjukkan variasi nilai sesuai intensitas cahaya (47–667), dan sensor hujan efektif mendeteksi kondisi basah maupun kering (620–846). Sistem ini berhasil memantau kondisi lingkungan pertanian secara real-time, memberikan notifikasi ketika parameter melewati ambang batas, dan mendukung pengambilan keputusan dalam pengelolaan pertanian cerdas dan berkelanjutan.================================================Abstract :Indonesia, despite abundant agricultural resources, continues to face challenges in achieving food self-sufficiency. Reliance on imports highlights suboptimal national productivity. Key obstacles include farmers’ limited access to information, dependence on inefficient conventional methods, and underutilization of modern technology. This research addresses these issues by designing and testing an Internet of Things (IoT)-based environmental monitoring system to support smart agriculture. The system employs four sensors: DHT11, Soil Moisture Hygrometer, LDR, and a rainfall sensor. Data from these sensors is collected by an Arduino Uno, stored on a MicroSD Card, and transmitted via NodeMCU ESP8266 to the HiveMQ MQTT broker . A web dashboard  visualizes the data in real-time and provides threshold-based notifications. Test results show the DHT11 sensor is stable in measuring temperature (30–32°C) and sensitive to humidity (76–92%). The Soil Moisture Hygrometer effectively distinguishes soil conditions from dry to saturated. The LDR records variations in light intensity (47–667), while the rainfall sensor reliably detects wet and dry states (620–846). Overall, the system successfully monitors agricultural environmental conditions in real-time, issues alerts when parameters exceed thresholds, and supports informed decision-making for smart, sustainable agricultural management.

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