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All Journal EXPERT: Jurnal Manajemen Sistem Informasi dan Teknologi Sistemasi: Jurnal Sistem Informasi JURNAL ILMIAH OBSGIN : Jurnal Ilmiah Ilmu Kebidanan & Kandungan Jurnal Pendidikan dan Teknologi Indonesia Respiratory Science Malcom: Indonesian Journal of Machine Learning and Computer Science SEMINAR TEKNOLOGI MAJALENGKA (STIMA)
Amarudin, Amarudin
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Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Mechanical Engineering Medicine & Pharmacology Nursing Public Health Transportation

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Pengaruh Konsumsi Perasan Kunyit Terhadap Rasa Nyeri Pada Penderita Gastritis Akut Usia 30 – 40 Tahun di Kelurahan BT IX Wilayah Kerja Puskesmas BT X Chintara Wanda, Aulia; Novia Yanti, Masyitah; Rahardiantini, Ikha; Amarudin, Amarudin
JURNAL ILMIAH OBSGIN : Jurnal Ilmiah Ilmu Kebidanan & Kandungan P-ISSN : 1979-3340 e-ISSN : 2685-7987 Vol 16 No 4 (2024): DESEMBER
Publisher : NHM PRESS

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Abstract

Gastritis is the most common disease complained of by the public and is a disease that is often found in clinics or internal medicine polyclinics, both in adolescents and adults. Gastritis is a disease that often recurs so that patients need regular treatment. Gastritis can occur suddenly or gradually. Gastritis or pain in the pit of the stomach is caused by inflammation that occurs in the gastric mucosa. Cases of gastritis cannot damage the stomach permanently, but gastritis sufferers often complain of repeated relapses. Based on data on gastritis incidents and research stating the activity of turmeric to overcome heartburn in gastritis patients, this study was conducted to determine the effectiveness of turmeric with different methods and samples. This study also uses variations in dosage which are expected to provide good results and show the effectiveness of turmeric in helping to reduce heartburn so that it can be an adjunct therapy in pain therapy caused by gastritis. Based on this background, a study was conducted to determine whether turmeric (Curcuma longa) has an activity that can help relieve gastritis pain and obtain an effective dose of turmeric juice to help relieve gastritis pain. Data obtained from this study showed that 20 respondents who received turmeric juice before and after the intervention for 1 week showed a significant decrease in pain scale from an average of 7.736842 to 1.263158 (P <0.001) indicating that turmeric juice has been proven to have an effect in reducing the pain scale caused by gastritis. Research shows that turmeric is a non-pharmacological therapy that has great potential to reduce pain scale.
A Comparative Study of Machine Learning Algorithms for Intrusion Detection Systems using the NSL-KDD Dataset Putra, Rulyansyah Permata; Amarudin, Amarudin
Sistemasi: Jurnal Sistem Informasi Vol 14, No 4 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i4.5246

Abstract

In today’s digital era, cyberattacks are becoming increasingly complex, rendering traditional rule-based Intrusion Detection Systems (IDS) often ineffective in recognizing new attack patterns. The primary objective of this study is to design and implement a machine learning model for detecting network intrusions efficiently while minimizing latency, through a comparative analysis of several algorithms: Decision Tree, Random Forest, Support Vector Machine (SVM), and Boosting. The research methodology includes the collection of the NSL-KDD dataset, followed by data transformation, cleaning, normalization, and partitioning into training and testing sets. Each algorithm was trained using tuned parameters, and performance was evaluated using metrics such as accuracy, precision, recall, F1-score, and an analysis of training and prediction time. The results indicate that the Boosting algorithm stands out, achieving an accuracy rate of 99.36%. Boosting also demonstrated greater reliability in detecting minority classes, despite requiring longer training times. The application of machine learning methods—particularly Boosting—proves to be an effective approach to enhancing intrusion detection and can serve as a foundation for developing more adaptive and reliable cybersecurity systems.
Analisis Kinerja Algoritma Random Forest Dengan Model Machine Learning Pada Dataset Penyakit Diabetes Inonu, Onassis Yusuf; Magda, Kardita; Amarudin, Amarudin
EXPERT: Jurnal Manajemen Sistem Informasi dan Teknologi Vol 15, No 1 (2025): June
Publisher : Universitas Bandar Lampung (UBL)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36448/expert.v15i1.4312

Abstract

Diabetes merupakan penyakit metabolik yang menjadi salah satu masalah kesehatan utama di dunia. Deteksi dini dan diagnosis yang akurat sangat penting untuk mencegah komplikasi jangka panjang. Dengan perkembangan teknologi machine learning, prediksi risiko diabetes berbasis data menjadi lebih efektif dan efisien. Penelitian ini bertujuan untuk menganalisis kinerja algoritma Random Forest dalam memprediksi status diabetes menggunakan dataset Pima Indians Diabetes. Tahapan penelitian meliputi pra-pemrosesan data, pelatihan model, evaluasi kinerja, serta visualisasi hasil.  Dataset yang digunakan terdiri dari 154 sampel dengan delapan fitur klinis dan satu variabel target. Pra-pemrosesan dilakukan untuk menangani nilai nol, normalisasi data, serta pembagian data latih dan uji. Model Random Forest dilatih dan dievaluasi menggunakan metrik akurasi, presisi, recall, F1-score, confusion matrix, dan kurva ROC-AUC. Hasil menunjukkan bahwa model menghasilkan akurasi sebesar 78%, dengan nilai AUC sebesar 0.82, menandakan kemampuan diskriminasi yang sangat baik antara pasien positif dan negatif diabetes.  Visualisasi Confusion Matrix dan kurva ROC membantu memberikan interpretasi yang jelas mengenai performa model secara grafis. Berdasarkan hasil tersebut, dapat disimpulkan bahwa algoritma Random Forest memiliki potensi besar sebagai pendukung keputusan dalam bidang medis, khususnya untuk prediksi risiko diabetes. Penggunaan model ini dapat meningkatkan efisiensi dan akurasi diagnosis awal, serta membantu tenaga medis dalam pengambilan keputusan yang lebih cepat dan objektif. 
Evaluasi Kinerja Model Random Forest Dalam Memprediksi Diabetes Berdasarkan Dataset Kesehatan di Indonesia Susanto, Erliyan Redy; Inzaghi, M. Rana; Amarudin, Amarudin; Neneng, Neneng
Jurnal Pendidikan dan Teknologi Indonesia Vol 5 No 7 (2025): JPTI - Juli 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.871

Abstract

Penyakit  diabetes atau sering disebut dengan penyakit gula darah adalah sekelompok penyakit metabolik yang ditandai dengan tingginya kadar gula darah pada seseorang yang terkena, dan bertahan dalam jangka waktu lama. Di Indonesia sedikitnya terdapat 20 juta orang pada usia 20-79 tahun menderita diabetes pada tahun 2024. Hal ini disebabkan oleh kurangnya akses terhadap alat prediksi yang efektif, serta keterbatasan pada pendekatan tradisional bergantung pada diagnosis medis manual yang memakan waktu dan biaya. Permasalahan ini muncul karena kurangnya pemanfaatan teknologi berbasis data dalam menganalisis faktor risiko yang kompleks dan saling terkait.  Penelitian ini bertujuan menggunakan model random forest untuk melakukan klasifikasi terhadap penyakit diabetes serta mengevaluasi nilai akurasi dengan evaluasi model menggunakan metrik seperti akurasi, presisi, recall, dan F1-score. Teknik akurasi yang digunakan yaitu confusion matrix untuk mengukur performa dalam permasalahan sehingga menghasilkan nilai akurasi yang sesuai. Hasil penelitian ini dapat memberikan wawasan praktis tentang konfigurasi optimal model untuk aplikasi dunia nyata, sehingga meningkatkan akurasi dan keandalan sistem prediksi diabetes. Model diuji menggunakan data uji yang telah dipisahkan sebelumnya dengan rasio 80:20. Hasil evaluasi kinerja model menunjukkan akurasi sebesar 0.99%, presisi 0.99%, recall 0.99%, F1-score 0.99%, Specificity 0.99% dan ROC-AUC Score 89.2%.  Hasil penelitian bermanfaat untuk membantu dokter dan tenaga kesehatan serta masyarkat umum untuk mendeteksi penyakit diabetes sejak dini.
Analisis Serangan Social Engineering melalui Pretexting, Impersonating, dan Phishing pada Pemain Game Mobile Online Indra Richardo, Kelvin; Amarudin, Amarudin
Jurnal Pendidikan dan Teknologi Indonesia Vol 5 No 7 (2025): JPTI - Juli 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.892

Abstract

Penelitian ini menganalisis metode serangan rekayasa sosial (social engineering) yang terjadi dalam konteks permainan mobile online, khususnya pada PUBG Mobile dan Mobile Legends. Studi ini bertujuan untuk mengidentifikasi metode serangan seperti pretexting, impersonation, dan phishing, serta faktor-faktor yang mempengaruhi keberhasilannya. Penelitian dilakukan menggunakan metode kuantitatif, melibatkan simulasi serangan melalui platform media sosial, komunitas game, dan komunikasi dalam game. Hasil penelitian menunjukkan bahwa dari 124 responden yang menjadi target serangan, 88 akun berhasil ditembus. Faktor keberhasilan mencakup tekanan sosial, keterbatasan waktu bermain, rendahnya kesadaran pengguna terhadap risiko keamanan, dan daya manipulasi teknik social engineering. Sebaliknya, aktivasi fitur keamanan seperti autentikasi dua faktor (2FA) menjadi hambatan utama bagi keberhasilan serangan. Hasil dari penelitian ini memberikan strategis untuk meningkatkan kesadaran dan perlindungan pengguna, termasuk edukasi keamanan digital, peningkatan fitur keamanan pada platform game, dan kolaborasi dengan komunitas game. Dengan implementasi langkah-langkah ini, risiko serangan social engineering dapat diminimalkan secara signifikan, menciptakan lingkungan game yang lebih aman bagi pemain.
Association Between Factory Workers’ Profile with Chest X-ray Finding and Spirometry at Industrial Company of X Wijaya, Dewi; Esha, Indi; Adrianison, Adrianison; Simatupang, Elvando Tunggul Mauliate; Amarudin, Amarudin
Respiratory Science Vol. 6 No. 1 (2025): Respiratory Science
Publisher : Indonesian Society of Respirology (ISR)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36497/respirsci.v6i1.198

Abstract

Background: Factory workers are a group at high risk of developing occupational lung abnormalities. Continuous exposure to dust, smoke, or gas particles during work processes may lead to progressive lung damage. Chest X-ray and spirometry are essential diagnostic tools for assessing both structural and functional lung changes, allowing early detection and prevention of occupational lung disability, especially among workers exposed to airborne pollutants. Method: This analytical observational study employed a cross-sectional design to analyze the association between factory workers’ profiles and chest X-ray and spirometry findings. Lung function was assessed using spirometry parameters, including Forced Vital Capacity (FVC), Forced Expiratory Volume in one second (FEV₁), and FEV₁/FVC ratio to identify restrictive or obstructive patterns. Data were collected using total sampling during periodic health examinations and analyzed with SPSS version 26.0. Descriptive statistics were used to summarize characteristics, while inferential analysis using Chi-square or Fisher’s exact tests was conducted to determine associations between categorical variables, with a significance level set at P<0.05. Results: A total of 260 factory workers participated, most with ≤5 years of work experience (60.76%). Comorbidities were significantly associated with both chest X-ray findings and lung function (P=0.034 and P=0.004). Smoking history and length of work also showed significant relationships with lung function (P=0.027 and P=0.019). Conclusion: There is a significant association between smoking history and length of work with changes in lung function. Meanwhile, comorbidities have a significant association with lung structure and lung function. Periodic evaluation using spirometry and chest X-ray is essential for early detection and prevention of occupational lung abnormalities among factory workers.
Integrasi Internet of Things dan Web untuk Monitoring Kendali Irigasi Tates Secara Real Time: Internet of Things and Web Integration for Real-Time Monitoring and Control of Tates Irrigation Fauzi, Fauzi; Amarudin, Amarudin
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 5 No. 4 (2025): MALCOM October 2025
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v5i4.2298

Abstract

Penelitian ini membahas pengembangan sistem irigasi tetes berbasis Internet of Things (IoT) yang terintegrasi dengan aplikasi web untuk monitoring dan kendali secara real-time. Sistem dirancang menggunakan mikrokontroler ESP32 yang terhubung dengan sensor ultrasonik untuk memantau ketinggian air dan pupuk, serta sensor soil moisture untuk mengukur kelembapan tanah. Data yang diperoleh dikirimkan ke server via protokol MQTT dan disimpan dalam basis data MySQL, kemudian ditampilkan melalui aplikasi web dalam bentuk numerik dan grafik. Hasil pengujian menunjukkan kinerja sistem yang andal, dimana sensor ultrasonik memiliki akurasi tinggi dengan error rata-rata 0.67%, sedangkan sensor soil moisture memiliki error di bawah 7%. Pompa air merespons perintah secara akurat baik secara manual maupun otomatis berdasarkan kondisi kelembapan tanah. Mode local server memungkinkan akses dashboard tanpa koneksi internet, sementara antarmuka yang sederhana dan user-friendly memudahkan pengguna dalam pemantauan. Integrasi grafik sensor memperjelas perubahan data secara visual, sehingga mempercepat proses pengambilan keputusan. Secara keseluruhan, sistem ini terbukti mampu meningkatkan efisiensi penggunaan air hingga 30% dan meminimalkan intervensi manual, sehingga menjadi solusi praktis dalam penerapan teknologi IoT untuk mendukung pertanian modern
PERANCANGAN PILAR PORTAL STRUKTUR JEMBATAN CIKERUH RUAS JALAN CICALUNG-SP.SINDANG PT.DELIMA DJAYA INTILAND Amarudin, Amarudin; Kholiq, Abdul
SEMINAR TEKNOLOGI MAJALENGKA (STIMA) Vol 5 (2021): STIMA 5.0 Kebangkitan Nasional Digital Era Industri 4.0
Publisher : Universitas Majalengka

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Abstract

The Cikeruh Bridge is a bridge that crosses the Cikeruh river with a river width of 65 meters, on the west it is a steep slope of 900 in the east there are landslides with a depth of 11 meters where there are rocks of varying sizes. So the construction of the pillar as a support for the superstructure must be very carefully calculated so that it is able to transfer the weight of the upper structure to the ground. The type of pillar chosen at the location of the Cikeruh bridge is a portal pillar with a different construction between one pillar and another, adjusted to the contour of the land and the flow of the river. The structure of the bridge itself is planned for a composite bridge type with steel girders (Fy = 355 MPa) and a concrete plate (F'c = 250 MPa), with a structure under a steel pile foundation. and Pier head work 2. The main material used in the construction of cikeruh bridge pillars is f'c = 250 quality concrete, the reinforcement used is screw D-25 iron, threaded D-16 and threaded D-13.
Co-Authors Abdul Kholiq Adrianison, Adrianison Chintara Wanda, Aulia Esha, Indi Fauzi Fauzi Indra Richardo, Kelvin Inonu, Onassis Yusuf Inzaghi, M. Rana Magda, Kardita Neneng Neneng Putra, Rulyansyah Permata Rahardiantini, Ikha Simatupang, Elvando Tunggul Mauliate Susanto, Erliyan Redy Wijaya, Dewi Yanti, Masyitah Novia