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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Teknika Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) EXPERT: Jurnal Manajemen Sistem Informasi dan Teknologi Jurnal Informatika Jurnal Informatika Proceeding International Conference on Information Technology and Business Jurnal Teknologi Informasi dan Ilmu Komputer Proceedings Konferensi Nasional Sistem dan Informatika (KNS&I) International conference on Information Technology and Business (ICITB) jurnal Teknologi Informasi Magister Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data) JMM (Jurnal Masyarakat Mandiri) Prosiding Seminar Nasional Darmajaya JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Mathvision : Jurnal Matematika Jurnal Sistem Komputer & Kecerdasan Buatan Jurnal Komunitas: Jurnal Pengabidian Kepada Masyarakat Dinasti International Journal of Economics, Finance & Accounting (DIJEFA) Jurnal Pengabdian UNDIKMA Yumary: Jurnal Pengabdian kepada Masyarakat Journal of Applied Data Sciences International Journal of Business, Technology, and Organizational Behavior (IJBTOB) Jurnal Abdimas Bina Bangsa JUSTIN (Jurnal Sistem dan Teknologi Informasi) Prosiding Konferensi Nasional PKM-CSR Aptekmas : Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian Masyarakat Bidang Sains dan Teknologi Jurnal Publika Pengabdian Masyarakat Journal of Management and Informatics Jurnal Informatika: Jurnal Pengembangan IT SWAGATI: Journal of Community Service JIMAD : Jurnal Ilmiah Multidisiplin
Hendra Kurniawan
Institute Of Informatics And Business Darmajaya
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Studi Kasus: Edukasi Aspek Preventif pada Pengelolaan Hipertensi Syahrizal, Syahrizal; Kurniawan, Hendra; Wijaya, Nanda; Rifqatunnisak, Rifqatunnisak; Anggreiny, Cut Dini
ABDIKAN: Jurnal Pengabdian Masyarakat Bidang Sains dan Teknologi Vol. 4 No. 1 (2025): Februari 2025
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/abdikan.v4i1.4804

Abstract

Hypertension is defined as an increase in systolic blood pressure exceeding 140 mmHg and/or diastolic blood pressure exceeding 90 mmHg. Hypertension is a highly prevalent disease that requires a preventive approach to avoid complications and improve patients' quality of life. This study aims to establish preventive measures for hypertensive patients through family education and home visits. The study adopts a descriptive qualitative approach using case study methods, including interviews, observations, documentation, and family assessments. Interventions involve education on diet, healthy lifestyle practices, exercise, and medication adherence. After one week of intervention, the patient's blood pressure significantly decreased from 160/97 mmHg to 137/88 mmHg. The patient demonstrated improved compliance, including reduced consumption of high-salt foods, increased light physical activity, and adherence to prescribed medications. This study highlights the importance of a low-salt and low-fat diet, regular exercise, and family support in managing hypertension and improving patients' quality of life. In conclusion, intensive education-based interventions and effective family involvement can reduce the severity of hypertension and prevent further complications.
Pembuatan Media Promosi Online Berupa Website pada Gutera Olah Pangan Kurniawan, Hendra; Fajri, Ika Nur
SWAGATI : Journal of Community Service Vol. 1 No. 2 (2023): July
Publisher : Universitas AMIKOM Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24076/swagati.2023v1i2.1146

Abstract

Pasca pendemi Covid-19 yang terjadi di Indonesia telah banyak merubah gaya promosi para pelaku usaha. Banyak pelaku usaha UMKM (Usaha Mikro, Kecil, dan Menengah) yang terdorong untuk memanfaatkan teknologi sebagai media promosi online agar mampu bersaing. Gutera Olah Pangan sebagai mitra merupakan UMKM yang bergerak di bidang makanan yang telah mempunyai produk berupa sari kacang hijau, olahan kacang, buah beku, katering, dan berbagai minuman buah. Menurut data dari BPS (Badan Pusat Statistik) tahun 2020 bahwa kendala terbesar UMKM adalah pemasaran atau penjualan produk dengan prosentase 48,60%. Kendala ini juga dialami oleh mitra yang sulit melakukan penjualan produk yang disebabkan oleh banyaknya produk makanan dan kencenderungan masyarakat memilih produk murah. Upaya promosi menggunakan marketplace dan media sosial telah dilakukan, tetapi belum berdampak signifikan terhadap penjualan. Oleh karena itu, dibutuhkan upaya lain berupa pemanfaatan website agar dapat mendukung kegiatan promosi yang telah dilakukan oleh mitra dan membangun brand image di masyarakat.
Pengembangan Keterampilan Associate Data Scientist melalui Pelatihan dengan RapidMiner Safitri, Egi; Nurlistiani, Rini; Kurniawan, Hendra
Yumary: Jurnal Pengabdian kepada Masyarakat Vol. 5 No. 4 (2025): Juni
Publisher : Penerbit Goodwood

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35912/yumary.v5i4.3664

Abstract

Purpose: This study aims to evaluate the effectiveness of an online Associate Data Scientist training program that utilizes RapidMiner as the primary platform for teaching data science and machine learning. The goal is to assess participants' improvements in data preprocessing, algorithm application, and model evaluation skills. Methodology/approach: The training program was conducted via Zoom and included interactive lectures, live demonstrations, hands-on exercises, and individual assignments. RapidMiner was used as the main tool throughout the sessions. Participants were evaluated through tasks assigned in each session and a final project that required them to analyze a dataset, apply relevant algorithms, and assess model performance. Results/findings: The results showed significant improvement in participants’ technical understanding and application skills. The average final project score was 87.0, indicating strong competence in data handling, algorithm selection, and model evaluation. Most participants completed the project successfully, demonstrating their readiness to apply data science concepts in real-world scenarios. Conclusions: The online training effectively bridged the gap between theory and practice, proving that remote learning can deliver quality outcomes in technical education. The combination of RapidMiner and a structured training format enabled participants to gain applicable skills in data science. However, improvements in instructional delivery and interaction are still needed to optimize learning experiences. Limitations: Challenges included internet connectivity issues and limited real-time interaction, which sometimes hindered learning flow and instructor support. Contribution: This study provides valuable insights into data science education, proving that online programs with practical tools like RapidMiner can successfully build core competencies in aspiring data professionals.
Prediksi Kekambuhan Kanker Tiroid Menggunakan Algoritma Random Forest Safitri, Egi; Rofianto, Dani; Karnila, Sri; Nurjoko, Nurjoko; Kurniawan, Hendra; Arkhiansyah, Yuni; Rizal, Ruki
Jurnal SISKOM-KB (Sistem Komputer dan Kecerdasan Buatan) Vol. 8 No. 3 (2025): Volume VIII - Nomor 3 - Mei 2025
Publisher : Teknik Informatika, Sistem Informasi dan Teknik Elektro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47970/siskom-kb.v8i3.833

Abstract

Kekambuhan kanker tiroid pasca terapi Radioactive Iodine (RAI) merupakan tantangan penting dalam penatalaksanaan jangka panjang pasien. Penelitian ini bertujuan membangun model prediktif untuk mengidentifikasi potensi kekambuhan dengan memanfaatkan data klinis dan patologis menggunakan algoritma Random Forest. Dataset terdiri atas 383 data pasien dengan 13 atribut, termasuk usia, jenis kelamin, staging kanker, jenis patologi, klasifikasi risiko, dan respons terhadap terapi. Proses pra-pemrosesan meliputi penyandian data kategorik, eksplorasi fitur, dan pembagian data latih dan uji secara stratifikasi. Hasil evaluasi menunjukkan performa tinggi dari model, dengan akurasi 96,5%, presisi 96,7%, recall 90,6%, dan AUC 0,99. Analisis fitur menggunakan SHAP mengungkap bahwa Stage, Response, dan Risk merupakan faktor paling berkontribusi terhadap prediksi kekambuhan. Penelitian ini menunjukkan bahwa model Random Forest tidak hanya efektif dalam klasifikasi biner, tetapi juga dapat diinterpretasikan secara klinis untuk mendukung pengambilan keputusan medis yang lebih personal dan preventif.
PENGENALAN SAINS DATA UNTUK MENINGKATKAN LITERASI DATA DAN KESIAPAN KARIER DIGITAL SISWA SEKOLAH MENENGAH ATAS Karnila, Sri; Kurniawan, Hendra; Irianto, Suhendro Yusuf; Muktiawan, Danang Ade; Septiawan, Yuda; Safitri, Egi; Nurjoko, Nurjoko
JMM (Jurnal Masyarakat Mandiri) Vol 9, No 4 (2025): Agustus
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jmm.v9i4.31940

Abstract

Abstrak: Pengenalan sains data di tingkat sekolah menengah memiliki peran penting dalam membekali siswa menghadapi era digital yang kian berkembang. Kegiatan pengabdian ini dirancang untuk menumbuhkan pemahaman siswa terhadap konsep dasar sains data sekaligus mendorong kesiapan mereka dalam meniti karier di bidang digital. Pelatihan dilangsungkan secara tatap muka di Institut Informatika dan Bisnis Darmajaya dan melibatkan 26 siswa dari empat sekolah di Bandar Lampung. Materi pelatihan meliputi pengantar teori sains data, praktik pengolahan dan visualisasi data serta pengantar bahasa pemrograman Python, hingga pengenalan awal pembelajaran mesin. Sebagai bentuk evaluasi, peserta mengikuti pre-test dan post-test dengan menjawab soal pilihan ganda sebanyak 25 soal. Hasil penilaian menunjukkan bahwa mayoritas siswa mengalami peningkatan kemampuan setelah pelatihan yang diberikan. Persentase peningkatan pengetahuan diperoleh melalui analisis hasil melalui pre-test dan post-test. Peningkatan diperoleh, dimana 18 dari 26 siswa menjawab benar soal atau persentase sebesar 69,23%, meningkat 30,73% dari nilai sebelumnya sebesar 38,5%. Hal ini mencerminkan respon yang sangat positif terhadap isi materi dan fasilitas pendukung yang tersedia. Secara keseluruhan, kegiatan ini memberikan pengalaman belajar yang membekas dan bermanfaat, serta dapat dijadikan model untuk pelatihan serupa di masa mendatang.Abstract: The introduction of data science at the high school level has an important role in equipping students to face the growing digital era. This service activity is designed to foster students' understanding of the basic concepts of data science while encouraging their readiness to pursue careers in the digital field. The training was held face-to-face at Darmajaya Informatics and Business Institute and involved 26 students from four schools in Bandar Lampung. The training materials included an introduction to data science theory, data processing and visualization practices and an introduction to the Python programming language, to an early introduction to machine learning. As a form of evaluation, participants took a pre-test and post-test by answering 25 multiple choice questions. The assessment results showed that the majority of students experienced an increase in ability after the training provided. The percentage of knowledge improvement was obtained through analysis of results through pre-test and post-test. An increase was obtained, where 18 out of 26 students answered the questions correctly or a percentage of 69.23%, an increase of 30.73% from the previous value of 38.5%. This reflects a very positive response to the material content and supporting facilities available. Overall, this activity provided a memorable and useful learning experience, and can be used as a model for similar training in the future.
Progressive Massive Fibrosis Detection Using Generative Adversarial Networks and Long Short-Term Memory Irianto, Suhendro Y.; Karnila, Sri; Hasibuan, M.S.; Dewi, Deshinta Arrova; Kurniawan, Tri Basuki; Kurniawan, Hendra
Journal of Applied Data Sciences Vol 6, No 4: December 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i4.707

Abstract

Contribution: Progressive Massive Fibrosis (PMF) is a severe form of pneumoconiosis, affecting individuals exposed to mineral dust, such as coal miners and workers in the artificial stone industry. This condition causes significant pulmonary impairment and increased mortality. Early and accurate detection is vital for effective management, yet traditional diagnostic methods face challenges in differentiating PMF from other pulmonary diseases due to variability in clinical presentations and limitations in imaging techniques. Idea: The study introduces a novel diagnostic framework that integrates Generative Adversarial Networks (GAN) and Long Short-Term Memory (LSTM) networks to enhance the detection and monitoring of PMF. The GAN generates high-fidelity synthetic imaging data to address the issue of limited datasets, while the LSTM network captures temporal patterns in patient data, enabling real-time monitoring of disease progression. Objective: The primary objective of this research is to develop an AI-driven model that improves the accuracy and efficiency of PMF detection and monitoring, facilitating early diagnosis and better treatment planning. Findings: The integrated GAN-LSTM model significantly outperformed traditional diagnostic methods. It proved high accuracy, a Dice coefficient of 0.85, and an Area Under the Curve (AUC) of 0.92, showing precise differentiation of PMF from other pulmonary conditions, such as lung cancer and tuberculosis. Results: The GAN-LSTM framework achieved an accuracy of 91.3%, suggesting that the fusion of GAN and LSTM technologies can effectively address the challenges of limited datasets and heterogeneous disease progression. The model showed promise in enhancing the non-invasive detection and ongoing monitoring of PMF. Novelty: This research stands for a significant advancement in PMF diagnostics by combining GAN and LSTM technologies in a single framework. This approach improves diagnostic accuracy and eases continuous disease monitoring, offering a non-invasive and highly precise solution for PMF detection.
Pengembangan Zonasi Sempadan Sungai Brantas Di Dermaga Joyoboyo Sebagai Kawasan Wisata Berbasis Sistem Informasi Geografi Setyabudi, Irawan; Pratama, Wanda Andika; Kurniawan, Hendra
JIMAD : Jurnal Ilmiah Multidisiplin Vol. 1 No. 3 (2024): JIMAD : Jurnal Ilmiah Multidisiplin (April)
Publisher : Asosiasi Guru dan Dosen Seluruh Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59585/jimad.v1i3.387

Abstract

Regional zoning planning is the initial stage of restructuring the Joyoboyo Pier area as a tourist area based on conservation principles. The principle of conservation in structuring tourist areas located in natural or natural areas is primarily an effort to protect natural resources and facilitate management. With zoning, it is hoped that tourism activities can run well because there is separation of land uses so that maximum land use can be achieved without interference from other land uses. So that a higher quality and environmentally friendly river border environment can be created. The aim of this research is to determine the zoning of the river border at Joyoboyo pier as a tourist area. This research method is a combined qualitative and quantitative method. Meanwhile, data analysis was carried out descriptively and spatially. The results of this research are the zoning of the Joyoboyo pier area with a core zone of 2.40 Ha (14%), a special zone of 2.69 Ha (15%), a buffer zone of 10.50 Ha (60%) and a utilization zone of 1 .94 Ha (11%). The development of river border zoning is the initial stage of establishing the Joyoboyo Pier Area as a tourist area which aims to create a higher quality and environmentally friendly river border and support community empowerment which can increase regional income.
Prediksi Keberhasilan Akademik Menggunakan Metode Regressi Logistik Dan Support Vector Machine Triyasri, Novita; Safitri, Egi; Kurniawan, Hendra; Saputra, M Hardi; Syidada, Amran Rahman; Pratama, Raynaldo Syah
JUSTIN (Jurnal Sistem dan Teknologi Informasi) Vol 13, No 4 (2025)
Publisher : Jurusan Informatika Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/justin.v13i4.89731

Abstract

Penelitian ini bertujuan untuk memprediksi keberhasilan akademik dengan menggunakan dua metode yaitu regresi logistik dan support vector machine (SVM). Keberhasilan akademik seringkali dipengaruhi oleh banyak faktor, antara lain motivasi siswa, keterampilan belajar, dan kondisi sosial ekonomi. Oleh karena itu penting untuk mengidentifikasi variabel-variabel yang mempengaruhi keberhasilan akademik dan menggunakan teknik analisis yang tepat untuk menghasilkan prediksi yang akurat. Data yang digunakan di Penelitian ini mencakup variabel-variabel seperti nilai ujian, motivasi belajar dan tingkat kehadiran siswa. Metode regresi logistik digunakan untuk menganalisis hubungan antara variabel independen dan variabel dependen (hasil akademik), sedangkan SVM digunakan untuk mengklasifikasikan siswa berdasarkan prestasi akademiknya. Hasil penelitian menunjukkan bahwa kedua metode tersebut memberikan tingkat akurasi yang signifikan dalam memprediksi keberhasilan akademik siswa. Namun Regresi logistik menghasilkan model yang lebih sederhana, SVM menunjukkan keunggulan dalam hal akurasi dan kemampuan mengklasifikasikan siswa dengan prestasi akademik lebih tinggi. Penelitian ini memberikan informasi berharga bagi para pendidik dan manajer pendidikan untuk mengidentifikasi siswa yang memerlukan perhatian lebih dalam pembelajaran dan merancang intervensi yang lebih efektif untuk meningkatkan hasil akademik siswa.
SISTEM INFORMASI E-COMMERCE TOKO HIJAB BERBASIS WEB DENGAN METODE EXTREME PROGRAMMING Nurlistiani, Rini; Kurniawan, Hendra; Yuliawati, Dona; Maria, Okta
Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data) Vol. 7 No. 1 (2024): Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data)
Publisher : LP2M Institut Informatika Dan Bisnis Darmajaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30873/simada.v7i1.393

Abstract

Development of increasingly modern technological devices can provide advantages for entrepreneurs to market services and products with the aim of expanding market share with a wide reach. The scope of product sales in an area becomes ineffective in being able to compete to attract consumer interest. The role of information technology can be carried out using internet media so that consumers can access it online or can be called e-commerce. The object of this research was carried out at a hijab shop in the Natar area, South Lampung. The problems that exist include the sales process which is carried out directly, such as consumers coming to the shop to buy products, which has an impact on operational costs, energy and time, especially consumers who are in areas where they cannot see information on the availability of the product they want to buy. The system development method used is Extreme Programming. The results obtained are that the use of the website is running well, as evidenced by the results of system testing using blackbox testing of 91.66%, which means that this e-commerce information system is running successfully and can be used by consumers, especially in the South Lampung area and its surroundings.
Komparasi Metode Apriori dan FP-Growth Data Mining Untuk Mengetahui Pola Penjualan Purwati, Neni; Pedliyansah, Yogi; Kurniawan, Hendra; Karnila, Sri; Herwanto, Riko
Jurnal Informatika: Jurnal Pengembangan IT Vol 8, No 2 (2023)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v8i2.4876

Abstract

 Sales data is generally still rarely used, as well as the Perfume Corner shop just piling up in the database, even though there are problems experienced by the store regarding sales data for the best-selling products and to increase the number of sales of subsequent perfume products, so that the store can survive and develop even better. The algorithm that can be used to manage sales data to overcome this problem is Apriori. The research method used in this research is the KDD (Knowledge Discovery in Database) process. This research produces a high frequency pattern for itemsets with a minimum support value of 20% resulting in products that become The Most Tree Items namely Jo Malone 82.49%, Zarra 28.25%, and Zwitsal 20.34%. While the association rules formed from the value of Min. Supp 20% and Min. Conf 80%, get a combination of 2 itemsets, namely Jo Malone and Zarra. Whereas for the combination of 3 itemsets, namely Jo Malone, Zarra and Baccarte with valid and strong status, it is proven by a lift value greater than 1, therefore the association rules are very appropriate to be used.
Co-Authors - Nurjoko Abdi Darmawan Abdullah Merjani, Abdullah Ade Moussadecq Adu, Steven Jonathan Adytama, Muhammad Rezky Agung Pradana Agus Rahardi Al-Reza, Dimaz Danang Amrullah, Ahmad Nur Hakim Anggreiny, Cut Dini Anita Dewi Purwati Annisa Anggun P Annisa Latifa Antoni Suseno Ardiansyah, Muhamad Iqbal ashari, ulfira Assatulaini Assatulaini Assyfa, Zahra Putri Astuti, Miguna Azima, Muhammad Fauzan Bagus Prihadi Catootjie L. Nalle, Catootjie L. Damayanti, Irah Dani Rofianto Denny Andreas Desi Ratna Sari, Desi Ratna Desy Tri Anggarini Dewi, Deshinta Arrova Diana Tambunan Dina Warsahanda Dona Yuliawati Dwi Wahyuni Edi Edi Pranyoto Egi Safitri Fajri, Ika Nur Fitria - Gare, Kletus Florianus Sera Halimah Halimah Handoko, Melyani Harijanto Wijaya Hasibuan, M.S. Heni Nastiti Hermanto HERMANTO Herwanto, Riko Herwanto, Riko Hikmah, Nor Irawan Setyabudi Irianto, Suhendro Y. Kurniawan, Tri Basuki Lilik Joko Susanto M Yusendra M. Zaky Fanany Zaky Maensya, Alendra Natuah Marbun, Elsa Agustin Maria, Okta Melda Agarina Mochammad Imron Awalludin Muhamad Ariza Eka Yusendra Muhammad Ariza Eka Yusendra Muhammad Fauzan Azima Muhammad Redintan Justin Muhammad Sahri Muji Lestari Muktiawan, Danang Ade Nababan, Badia Roy Ricardo Nadhir, Ahnaf Ronaldo Neni Purwati Niken Larasati Novi Herawadi Sudibyo Nurdianingsih, Aisyah Nurjoko Nurjoko Nurlistiani, Rini Nursiyanto Oktaviani, Eva Oscar, Gusnanda Pedliyansah, Yogi Pratama, Raynaldo Syah Pratama, Wanda Andika Pratiwi, Gadis Kartika Putra, Rizky Samjaya Raden Abdurrahman Raihan Hasbid Ramadhan, Rizki Aditya Reni Widyastuti Rifqatunnisak, Rifqatunnisak Rini Nurlistiani Rizal, Ruki Rizkiana Karmelia Shaura Rohiman Rohiman Rohiman Rohiman Rohmat Hidayat, Kardilah Romadona, Romadona Rosali, Rosali Rossa Wulandari Ruki Rizal Ruki Rizal Rumini Safitri, Egi Saputra, M Hardi Sasya Nadira Satrio, Rafli Banu Septiawan, Yuda Shofiyurrahman Shofiyurrahman Sipora Petronela Telnoni Siswahyudianto Solly Aryza Sri Karnila Sri Karnila Sri Karnila Sri Karnila Sri Karnila Karnila Sri Lestari Sri Rahayu Stefanus Rumangkit Sumarya, Edi Supriyadi Susanti Susanti Susanti Susanti Susanto, Lilik Joko Sushanty Saleh Sutedi Sutedi Swastika, Rahayu Syahrizal Syahrizal Syidada, Amran Rahman Syifa, Khozanah Theresia, Sumini Tri Erri Astoeti Triyasri, Novita Valensia, Alda Caesar Wicakso Bandung Bondowoso Widijanto Sudhana Wijaya, Nanda Y, M Ariza Eka Y. Suhendro Yama, Tri Melda Yan Aditiya Pratama Yogi Pedliyansah Yuni Arkhiansyah Yusminar Yusminar Yusminar Yusminar Zahra, Amalia Zainal Abidin