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All Journal Techno.Com: Jurnal Teknologi Informasi Jurnal Pseudocode Jurnal Transformatika Jurnal Edukasi dan Penelitian Informatika (JEPIN) JUSIFO : Jurnal Sistem Informasi Jurnas Nasional Teknologi dan Sistem Informasi Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer Jurnal Teknik Komputer AMIK BSI JURNAL MEDIA INFORMATIKA BUDIDARMA Machine : Jurnal Teknik Mesin JURNAL REKAYASA TEKNOLOGI INFORMASI Justek : Jurnal Sains Dan Teknologi JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Sisfokom (Sistem Informasi dan Komputer) NUSANTARA : Jurnal Ilmu Pengetahuan Sosial CYBERNETICS BULETIN AL-RIBAATH Global Health Management Journal Jurnal Tekno Insentif JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) J-Dinamika: Jurnal Pengabdian Kepada Masyarakat Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Progresif: Jurnal Ilmiah Komputer bit-Tech Jurnal Teknika Jurnal Sains Komputer dan Teknologi Informasi Jurnal Computer Science and Information Technology (CoSciTech) JUTECH : Journal Education and Technology Journal of Artificial Intelligence and Engineering Applications (JAIEA) Journal of Comprehensive Science J-ABDIPAMAS (Jurnal Pengabdian Kepada Masyarakat) International Journal of Health, Engineering and Technology The Indonesian Journal of Computer Science Advance Sustainable Science, Engineering and Technology (ASSET) Journal of Digital Business and Data Science JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) Jurnal Publikasi Teknik Informatika TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Asrul Abdullah
Universitas Muhammadiyah Pontianak
Agriculture, Biological Sciences & Forestry Humanities 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 Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Veterinary Other

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Design Of A Drinking Water Feasibility Identification System Using The Random Forest Algorithm And Principal Component Analysis (PCA) Khusnul Karomah; Asrul Abdullah; Barry Ceasar Octariadi
International Journal of Health Engineering and Technology Vol. 5 No. 2 (2026): Vol 5. No. 2 JULY 2026
Publisher : CV. AFDIFAL MAJU BERKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55227/ijhet.v5i2.952

Abstract

Clean and safe drinking water is a basic need for society. Based on clean water statistical data from Statistic Indonesia (BPS), the average percentage of households in West Kalimantan Province with access to safe drinking water sources in urban areas was 89.21%, while in rural areas it was 77.76% in 2023. With a population growth that outpaces the available reserves of safe drinking water, there is a clear need to monitor and analyze water quality more carefully and on a data-driven basis. This research aims to design and implement a drinking water suitability classification system using the Random Forest method as the main classification algorithm, with Principal Component Analysis (PCA) serving as the data dimensionality reduction technique. The interactive visualization was built using Python and Streamlit, taking into account User Interface (UI) and User Experience (UX) aspects, which are divided into two access levels: Public Access (for the community) and Officer Access (for agencies). Water quality data is identified based on standards from the Ministry of Health (Permenkes No. 492/MENKES/PER/IV/2010), reduced in dimensionality using PCA, and subsequently classified for its suitability using Random Forest. The test results demonstrate that this system is capable of classifying the suitability status with an accuracy of 95.35%. to ensure the model does not experience overfitting, K-Fold Cross-Validation (5-Fold) testing was conducted, yielding an average accuracy of 94.94% and proving the model’s stability. Furthermore, the User Acceptance Testing (UAT) results indicate an excellent level of user acceptance regarding the bulk upload feature and the monitoring of drinking water quality in a fast, accurate, and data-driven manner.
Perancangan Alat Pendeteksi Kadar Polusi Udara Berbasis I0T Menggunakan Sensor MQ-2 dan Sharp GP2Y1014AU0F Ewa Oktaviaghi Prasetya; Asrul Abdullah
Journal of Comprehensive Science Vol. 5 No. 7 (2026): Journal of Comprehensive Science
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/jcs.v5i7.4235

Abstract

Polusi udara menjadi salah satu permasalahan lingkungan yang berdampak terhadap kesehatan manusia, terutama pada kawasan dengan aktivitas kendaraan, perdagangan, dan aktivitas pembakaran yang tinggi. Pasar Teratai di Jalan Komodor Yos Sudarso, Kota Pontianak, merupakan salah satu area yang berpotensi mengalami peningkatan polusi udara akibat emisi kendaraan bermotor, asap rokok, dan debu dari aktivitas sekitar. Penelitian ini bertujuan untuk merancang dan membangun prototipe alat pendeteksi kadar polusi udara berbasis Internet of Things (IoT) menggunakan sensor MQ-2 untuk mendeteksi asap/gas dan sensor Sharp GP2Y1014AU0F untuk mendeteksi kepekatan debu dengan NodeMCU ESP8266 sebagai pengendali utama serta sistem notifikasi melalui aplikasi Telegram. Metode penelitian yang digunakan adalah penelitian terapan dengan tahapan identifikasi masalah, pengumpulan data melalui studi literatur, wawancara, observasi, dan kuesioner, perancangan sistem, implementasi perangkat, serta pengujian sensor dan komunikasi IoT. Hasil penelitian menunjukkan bahwa prototipe mampu melakukan pendeteksian kadar asap/gas dan debu secara real-time, memberikan indikator visual melalui LED, serta mengirimkan notifikasi otomatis melalui Telegram ketika nilai pengukuran melewati ambang batas yang ditentukan. Pengujian menunjukkan bahwa sensor MQ-2 dan Sharp GP2Y1014AU0F dapat merespons berbagai sumber polutan, meskipun terdapat variasi pembacaan akibat karakteristik sumber asap, kondisi lingkungan, dan keterbatasan proses kalibrasi sensor. Implementasi di Pasar Teratai menunjukkan bahwa alat mampu memonitor perubahan kualitas udara secara langsung. Penelitian ini memberikan kontribusi dalam pengembangan sistem monitoring polusi udara berbasis IoT yang praktis, namun masih diperlukan pengembangan lanjutan melalui peningkatan akurasi sensor dan proses kalibrasi agar dapat diterapkan pada skala yang lebih luas.
Sistem Informasi Geografis Berbasis Web Untuk Pemetaan Penerima BPJS Dengan Algoritma Dijkstra Muhamad Reynaldi Rendi; Rachmat Wahid Saleh Insani; Asrul Abdullah
Jurnal Pseudocode Vol 13 No 1 (2026): Volume 13 Nomor 1 Februari 2026
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/pseudocode.13.1.75-81

Abstract

The Sungai Raya Village apparatus faces challenges in managing BPJS beneficiaries due to the lack of mapping and route optimization tools. This research aims to build a web-based Geographic Information System (GIS) to visualize recipient locations and implement Dijkstra's Algorithm for determining the shortest visit routes. Developed using Laravel, MySQL, and Leaflet.js following the Waterfall methodology, the system successfully maps data with hamlet-based filtering features. Testing confirms that Dijkstra's Algorithm generates valid routes, which were verified against Google Maps. Black Box testing showed all functions perform correctly, and User Acceptance Testing (UAT) yielded a score of 81.75%. These results indicate the system effectively supports the efficiency of data verification and field visit planning.
Prediksi Banjir Di Kota Pontianak Menggunakan Metode Decision Tree C4.5 Mifthahul Fitrah; Asrul Abdullah; Istikoma Istikoma
Justek : Jurnal Sains dan Teknologi Vol 8, No 1 (2025): Maret
Publisher : Unversitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/justek.v8i1.29343

Abstract

Abstract:  – The city of Pontianak is prone to flooding during the rainy season due to its low land surface elevation of 0.1–1.5 meters above sea level and its location along the Kapuas River. Flood prediction in Pontianak needs to be conducted using predictive techniques from data mining. One of the predictive analysis methods is the C4.5 decision tree. This study aims to design a flood prediction model for Pontianak using the C4.5 decision tree method and to determine the obtained accuracy results. The research methodology follows several stages, including problem identification, literature review, data collection, data processing, testing, and conclusion. In this study, three experiments were conducted with different treatments. The model performance evaluation for these three experiments was carried out using a confusion matrix. Based on the evaluation results, the best model for flood prediction was obtained from the second experiment, achieving an accuracy, precision, recall, and F1-score of 98%, 72%, 76%, and 74%, respectively, on the test dataAbstrak: Kota Pontianak merupakan daerah rentan terjadinya bencana banjir saat musim hujan tiba karena memiliki ketinggian permukaan tanah 0,1-1,5 meter diatas permukaan laut dan dilalui oleh aliran Sungai Kapuas. Prediksi banjir di Kota Pontianak perlu dilakukan dengan memanfaatkan teknik prediksi dari data mining. Salah satu metode analisis prediktif adalah decision tree C4.5. Tujuan Penelitian ini adalah merancang model prediksi banjir di Kota Pontianak menggunakan metode decision tree C4.5 serta mengetahui hasil akurasi yang diperoleh. Metode penelitian pada penelitian ini melalui beberapa tahapan yaitu identifikasi masalah, studi Pustaka, pengumpulan data, pengolahan data, pengujian, dan Kesimpulan. Pada penelitian ini dilakukan tiga percobaan dengan perlakuan yang berbeda. Pengecekan kinerja model dari tiga percobaan tersebut mengunakan confusion matrix. Dari pengecekan tiga percobaan tersebut didapatkan model terbaik untuk memprediksi banjir yaitu pada percobaan kedua dengan hasil akurasi, presisi, recall, dan F1-score sebesar 98%, 72%, 76% dan 74% pada data uji.
Klasifikasi Penyakit Kanker Paru-Paru Menggunakan Metode Decision Tree C4.5 Khorlis Jainudin; Asrul Abdullah; Sucipto Sucipto
Justek : Jurnal Sains dan Teknologi Vol 8, No 3 (2025): September
Publisher : Unversitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/justek.v8i3.31981

Abstract

The incidence of lung cancer in Indonesia has shown a significant increase, positioning the country as the eighth highest in Southeast Asia, with a growth rate of 10.85% over the past five years. A considerable number of lung cancer cases remain undiagnosed at earlier stages due to difficulties in detection, which contributes to the high mortality rate associated with this disease. Consequently, there is a need for a relatively efficient and straightforward technique to uncover knowledge, patterns, and interrelationships among data. The objective of this study is to develop a classification model for lung cancer using the C4.5 decision tree method and to evaluate its predictive performance. The methodology comprises several stages, including data preprocessing, exploratory data analysis (EDA), handling of missing values, identification of duplicate records, assessment of feature correlations, separation of features and target variables, partitioning of data into training and testing sets, model implementation, and performance evaluation through a confusion matrix. The experimental results demonstrate that the proposed model achieves a recall of 90%, a precision of 86%, an F1-score of 88%, and an overall accuracy of 89%. These findings indicate that the C4.5 decision tree method is effective in classifying lung cancer cases and holds potential as a reliable approach in medical data analysis for early detection and diagnosis.
Penggunaan Information Retrieval untuk Mendeteksi Kesamaan Judul Skripsi dengan Modified Cosine Similarity Sri Wahyuni; Asrul Abdullah; Sucipto Sucipto
Justek : Jurnal Sains dan Teknologi Vol 8, No 2 (2025): Juni
Publisher : Unversitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/justek.v8i2.30146

Abstract

Abstract:  This research develops a web-based system to detect the similarity of thesis titles using the Modified Cosine Similarity method and TF-IDF weighting. This system helps students in evaluating the similarity of titles automatically, so as to avoid plagiarism and increase the originality of research. The process used includes text preprocessing (case folding, tokenizing, stopword removal, stemming), TF-IDF calculation for word weighting, and the use of Modified Cosine Similarity to measure the level of similarity between titles. The test results show that the system is able to identify the similarity of titles with a 100% recall rate, where titles with >70% similarity need to be revised, 31%-70% similarity can be clarified by adding words, and ≤30% similarity is potentially accepted as an original title. With this implementation, it is expected that students can more easily determine a thesis title that is unique and in accordance with academic standards.Abstrak: Penelitian ini mengembangkan sistem berbasis web untuk mendeteksi kemiripan judul skripsi menggunakan metode Modified Cosine Similarity dan pembobotan TF-IDF. Sistem ini membantu mahasiswa dalam mengevaluasi kemiripan judul secara otomatis, sehingga dapat menghindari plagiarisme dan meningkatkan orisinalitas penelitian. Proses yang digunakan meliputi text preprocessing (case folding, tokenizing, stopword removal, stemming), perhitungan TF-IDF untuk pembobotan kata, dan penggunaan Modified Cosine Similarity untuk mengukur tingkat kemiripan antar judul. Hasil pengujian menunjukkan bahwa sistem mampu mengidentifikasi kemiripan judul dengan tingkat recall 100%, di mana judul dengan kemiripan >70% perlu direvisi, kemiripan 31%-70% dapat diperjelas dengan penambahan kata, dan kemiripan ≤30% berpotensi diterima sebagai judul orisinil. Dengan implementasi ini, diharapkan mahasiswa dapat lebih mudah menentukan judul skripsi yang unik dan sesuai dengan standar akademik.
SIG BERBASIS WEB UNTUK PEMETAAN DAN PENGUKURAN LUAS TANAH DENGAN METODE SHOELACE FORMULA Virgilius Dalta Suprias Nandigna; Asrul Abdullah; Rachmat Wahid Saleh Insani
NUSANTARA : Jurnal Ilmu Pengetahuan Sosial Vol 13, No 8 (2026): NUSANTARA: Jurnal Ilmu Pengetahuan Sosial
Publisher : Universitas Muhammadiyah Tapanuli Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31604/jips.v13i8.2026.2230-2237

Abstract

Pengelolaan aset dan pengukuran luas tanah di Desa Paloan masih dilakukan secara manual sehingga berpotensi menimbulkan kesalahan, sulit diverifikasi, dan kurang mendukung transparansi. Oleh karena itu, diperlukan sistem berbasis digital yang dapat membantu perangkat desa dalam memetakan aset sekaligus menghitung luas lahan secara otomatis. Penelitian ini bertujuan  membangun Sistem Informasi Geografis (SIG) berbasis web untuk pengelolaan aset desa serta menerapkan algoritma Shoelace Formula dalam perhitungan luas lahan berdasarkan titik koordinat. Metode penelitian yang digunakan meliputi studi pustaka, observasi lapangan, dan wawancara dengan perangkat desa. Pengambilan titik koordinat dilakukan menggunakan GPS Garmin GPSMap 78s. Sistem dikembangkan menggunakan framework Laravel sebagai backend, Leaflet JS untuk visualisasi peta interaktif, dan MySQL sebagai basis data. Perhitungan luas lahan dilakukan dengan menerapkan algoritma Shoelace Formula. Hasil implementasi menunjukkan bahwa sistem mampu mengelola data aset desa seperti tanah, bangunan, dan jalan secara terintegrasi melalui fitur CRUD, proses persetujuan oleh Kepala Desa, serta penyajian peta aset yang dapat diakses secara publik. Pengujian sistem menggunakan metode Blackbox Testing menunjukkan bahwa seluruh fungsi berjalan sesuai dengan kebutuhan pengguna. Selain itu, pengujian akurasi pengukuran luas lahan menunjukkan bahwa penerapan Shoelace Formula menghasilkan tingkat akurasi antara 98,16% hingga 98,83%. Sistem ini diharapkan dapat meningkatkan efisiensi, akurasi, dan transparansi dalam pengelolaan aset desa
Co-Authors Abrar, Ihya' Nashirudin Adi, Pranowo Aditya Wicaksono Alda Cendekia Siregar Aldi Mulia Rismanto Alkhairi, Muhammad Ghozy Anita Apriliasari, Betty Arni - Yanti Arochman Barry Ceasar Octariadi Dedy Susanto Doddy Irawan Dwika, Arya Sukma Putra Egy Andryan Eka Indah Raharjo Ema Utami Ervayana Sari Ewa Oktaviaghi Prasetya Fadillah Bergas Fakhruzi, Izhan Fenni Supriadi G. Gunawan Gunarto Gunarto Gusti Ardhasna Fauzan Hermansyah, Hermansyah Indah Budiastutik Iskandar Hadiatma Isra Pebrianti Istikoma Istikoma Istikoma Istikoma Istikoma Istiqoma Iwan, Muhammad Juliana Panemaan, Anita Karisma, Nova Khairah, Della Udya Khairul Khorlis Jainudin Khusnul Karomah Lea Candra Lidia Lidia, Lidia Linda Suwarni Marlenywati Marlenywati Maryogi Menur Wahyu Pangestika, Menur Wahyu Mifthahul Fitrah Muhamad Reynaldi Rendi Muhammad Agus Muljanto Muhammad Fikri Bagus Pratama Muhammad Iwan Nur Rali Rahma Wati Octariadi, Barry Ceasar Pedi Irawan Putri Utami, Putri Putri Yuli Utami Rachmat Wahid Saleh Insani Rachmat Wahid Saleh Insani Ramadhan, Dwi Rohmat Rizki Faizal Rizki Faizal Rizky Wahyu Prasetyo Roni, Roni Sahid Agustian Hudjimartsu Salim, Vilvilia Selviana Selviana Setyawan, Rizki Fajar Siregar, Alda Cendekia SITI AMINAH Siti Aminah Sri Wahyuni Sucipto Sucipto Sucipto Sucipto Sucipto Syafaat Agung Prakoso Syarifah Putri Agustini Alkadri Taruk, Medi Try Kardina Unitama Utami, Nur Sri Utami, Putri Yuli Vidyastuti, Vidyastuti Viona, Tiara Aurilia Virgilius Dalta Suprias Nandigna Wawan Setiawan Yanto, Maryogi Zulfan Ahmadi