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All Journal Sistemasi: Jurnal Sistem Informasi Informatika JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Djtechno: Jurnal Teknologi Informasi KERNEL: Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika Jurnal Ilmiah Edutic : Pendidikan dan Informatika DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY J-ENSITEC (Journal of Engineering and Sustainable Technology) Jurnal Manajemen Sistem Informasi SISFOTENIKA Akademika
Oki Dahwanu
Universitas Jambi
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Library & Information Science Mechanical Engineering Other

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Analisis dan Perancangan Jaringan Saraf Tiruan untuk Mengidentifikasi Tingkat Kematangan Buah Belimbing Manis (Averrhoa carambola L.) Dahwanu, Oki; Sarjono, Sarjono
Jurnal Manajemen Sistem Informasi Vol 4 No 1 (2019): JURNAL MANAJEMEN SISTEM INFORMASI
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Starfruit is one of the fruits that are widely cultivated in Indonesia. But at this time sorting of starfruit is stilldone manually by humans, consequently resulting in a uniform level of maturity that is not good. For thisreason, a system is needed that can identify the level of maturity of starfruit with artificial neural networks.The main problem of designing artificial neural networks is how to analyze and design an artificial neuralnetwork architecture in order to determine the maturity level of sweet starfruit properly. This study aims todesign artificial neural networks with backpropagation method to identify the maturity level of starfruit.From the results of the study, the best configuring of backpropagation artificial neural network model is amodel of artificial neural networks with 3 inputs, 11 hidden layer neurons and 3 outputs (3-11-3). With thisconfiguration, artificial neural networks are able to identify the level of maturity with a success rate of 95.8%of 48 starfruit test data.
Klasifikasi Risiko Gempa Bumi menggunakan metode Decision Tree Akbar, Niko; Alghifari, Hamzah; Abdillah, Nurul; Dahwanu, Oki
DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY Vol 6, No 2: DESEMBER 2025
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/device.v6i2.7843

Abstract

Gempa bumi merupakan salah satu bencana alam yang sulit diprediksi namun memiliki dampak besar terhadap kehidupan manusia. Oleh karena itu, diperlukan suatu pendekatan analitis yang mampu mengidentifikasi pola dan hubungan antarparameter gempa untuk mendukung sistem peringatan dini. Penelitian ini bertujuan untuk melakukan Klasifikasi Dampak akan kejadian gempa bumi menggunakan metode Data Mining berbasis Decision Tree. Data yang digunakan berasal dari katalog gempa yang memuat atribut seperti Tanggal Kejadian (timestamp), magnitudo, kedalaman, serta koordinat lokasi (latitude dan longitude). Proses analisis meliputi tahap pembersihan data (data cleaning), transformasi, dan pembuatan model klasifikasi Decision Tree untuk menentukan tingkat potensi dan dampak gempa serta mengetahui keakuratan gempa bumi berdasarkan data dari tahun ketahun. Hasil penelitian menunjukkan bahwa atribut magnitudo memiliki pengaruh signifikan terhadap tingkat risiko gempa. Model Decision Tree yang dibangun mampu menghasilkan aturan klasifikasi seperti “Jika magnitudo <5 maka berpotensi Risiko gempa bumi rendah, sedangkan magnitudo antara 5-7 berisiko gempa bumi sedang, dan magnitudo ≥ 7 maka berpotensi Risiko Gempa Bumi Tinggi”, yang dapat digunakan untuk mendukung pengambilan keputusan dalam mitigasi bencana. Dengan demikian, metode Decision Tree terbukti efektif dalam mengungkap pola tersembunyi dari data gempa bumi dan dapat menjadi dasar bagi sistem prediksi serta peringatan dini gempa di masa mendatang. Disimpulkan bahwa akurasi masing – masing sebesar 100 %, sedangkan recall sebesar 100 % tapi hasil precision menunjukkan statistik yang berbeda yakni Prediksi Tidak Berpotensi Gempa Bumi  Besar sebesar 100%, sedangkan Prediksi Tidak berpotensi Gempa Bumi sedang sebesar 99,67%, dan terakhir prediksi Tidak berpotensi Gempa Bumi Kecil sebesar 96 %. Hasil pengujian ternyata menghasilkan magnitude rendah dengan ukuran >5,350 tergolong rendah, sedangkan magnitude rendah dengan ukuran <5,350 mempunyai frekuensi yang banyak. Dan Beberapa data berdasarkan statistik Magnitudo >5.350 ukuran sedang dari data sebanyak 16 data. Sedangkan magnitudo ≤ 5.350 Ukuran Rendah sebanyak 6716 Data yang ditemukan dan sudah dianalisis.
ANALISIS DAN PERANCANGAN SISTEM INFORMASI PEMASARAN PERUMAHAN BERBASIS WEB MENGGUNAKAN METODE PROTOTYPE PADA PT LESTARI INTI PROPERTI JAMBI: Marketing Information System, Web-Based Application, Prototype Method, Unified Modeling Language, Subsidized Housing Alghifari, Hamzah; Akbar, Niko; Abdillah, Nurul; Dahwanu, Oki
JURNAL AKADEMIKA Vol 18 No 1 (2025): Jurnal Akademika
Publisher : LP2M Universitas Nurdin Hamzah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53564/6psph742

Abstract

Due to its manual reliance on conventional promotional techniques such as distributing flyers and posters, PT Lestari Inti Properti faces challenges in selling subsidized housing products. In the digital era, this situation limits promotional reach and reduces marketing effectiveness. The goal of this project is to create a web-based marketing information system that can manage the company's sales and administration data in an integrated manner and function as a digital promotional tool. Using the Unified Modeling Language (UML) methodology, prototyping techniques are applied through the phases of rapid design, testing and feedback, prototyping, and requirements communication. The result of this study is the design of a prototype housing marketing information system that includes a login module, housing data management, ordering procedures, and transaction reports. Use case structures, activity diagrams, and class diagrams are used in the design of this system to fully explain how users interact with business operations. This system can increase marketing reach, speed up administrative procedures, and reduce data input errors, according to the design results. Therefore, PT Lestari Inti Properti can improve operational effectiveness and competitiveness in the digital market by using a web-based marketing information system.
Development of a Web-Based Application for Predicting Stroke Patient Emergency Levels Using the Naïve Bayes Algorithm Nurul Abdillah; Oki Dahwanu; Hamzah Alghifari; Niko Akbar
EDUTIC Vol 13, No 1: 2026
Publisher : Universitas Trunodjoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/edutic.v13i1.34303

Abstract

Stroke is a serious disease that requires prompt and appropriate treatment; therefore, determining the level of patient Emenrgency Levels is critically important. This study aims to develop a web-based application for predicting the Emenrgency Levels level of stroke patients using the Naïve Bayes algorithm as a classification method. The research data were obtained from the medical records of stroke patients at RSUP Dr. M. Djamil Padang during March and April 2025, with a total of 222 data samples. The attributes used in this study include age, gender, address, length of stay, ward class, BPJS insurance membership status, and comorbidities, with Emenrgency Levels status as the class attribute classified into Emenrgency and non-Emenrgency. The application was developed as a web-based system to facilitate easy access for medical personnel in utilizing the prediction system. The experimental results indicate that the Naïve Bayes algorithm achieved an accuracy of 77.48% with an error rate of 22.52%. The findings of this study are expected to assist medical personnel in supporting faster and more objective decision-making regarding the Emenrgency Levels level of stroke patients.
Comparison of Machine Learning Algorithms (SVM, Random Forest, and Naïve Bayes) for Predicting Rice Production Oki Dahwanu; Nurul Abdillah; Niko Akbar; Hamzah Alghifari
J-ENSITEC (Journal of Engineering and Sustainable Technology) Vol. 12 No. 02 (2026): June 2026
Publisher : Universitas Majalengka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31949/j-ensitec.v12i02.18386

Abstract

Global rice production faces mounting pressure from population growth and climate change, yet traditional statistical models fail to capture the complex nonlinear dynamics between environmental factors and crop yields. To address this gap, this study systematically compares the accuracy of three machine learning algorithms, Support Vector Machine (SVM), Random Forest (RF), and Naïve Bayes (NB) for predicting rice production fluctuations due to climate change using the latest local climate data from Indonesia. A dataset of 96 monthly observations (2018–2025) comprising climate features (temperature, humidity, wind speed, precipitation, cloud cover, sunshine duration) and rice production categories (Low, Medium, High) was analyzed. Algorithm performance was evaluated using accuracy, precision, recall, and F1-score. The results demonstrate that Random Forest significantly outperforms the other methods, achieving an accuracy of 95%, precision of 0.9571, recall of 0.95, and F1-score of 0.95, compared to SVM (75% accuracy) and Naïve Bayes (70% accuracy). This study provides the first head-to-head comparison of these three algorithms for rice yield prediction in Indonesia using current climate data. The key benefit over pre-existing approaches is the empirical confirmation that ensemble learning, particularly Random Forest, offers superior predictive reliability for crop yield forecasting under high feature complexity, thereby enabling more accurate, data-driven agricultural policy and food security planning.
KLASIFIKASI DAN PREDIKSI KELUARGA BERISIKO STUNTING DI PROVINSI JAMBI MENGGUNAKAN METODE KNN DAN NAIVE BAYES Niko Akbar; Hamzah Alghifari; Nurul Abdillah; Oki Dahwanu
DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY Vol 7, No 1: JUNI 2026
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/device.v7i1.8522

Abstract

Di Indonesia Prevalensi stunting sebesar 37,2%, naik dari 35,6% pada tahun 2019 dan 36,8%, dengan mayoritas dipengaruhi oleh penduduk setempat. Kementerian Kesehatan Indonesia memperkirakan bahwa prevalensi stunting akan mencapai 38,9% pada tahun 2020. Permasalahannya Beberapa Data yang diambil dan dipakai berupa data sekunder yang di ada diwebsite opendata provinsi jambi yang berjudul Faktor Penapisan Keluarga Berisiko Stunting di Provinsi Jambi. Dengan menggunakan algoritma KNN dan Naïve Bayes, maka didapatkan hasilnya berupa kedua algoritma cocok untuk pengklasteran dan Scoring dari algoritma menunjukkan hasil yang berbeda. Karena keakurasiannya sesuai dengan perhitungan manual yang telah dijabarkan pada bagian pengolahan data. Beberapa hasil dari cross-validasi menyatakan bahwa nilai accuracy 85,29%, nilai precision berupa 83,33%, nilai recall 85,29%.
Komparasi Efektivitas Augmented Reality dan Virtual Reality sebagai Media Pembelajaran: Tinjauan Sistematis: Comparative Effectiveness of Augmented and Virtual Reality Learning: Systematic Review Hamzah Alghifari; Niko Akbar; Nurul Abdillah; Oki Dahwanu
SISFOTENIKA Vol. 16 No. 2 (2026): SISFOTENIKA
Publisher : STMIK PONTIANAK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30700/sisfotenika.v16i2.643

Abstract

Teknologi imersif seperti Augmented Reality (AR) dan Virtual Reality (VR) telah menciptakan peluang baru dalam bidang pendidikan. Namun, masih ada perdebatan tentang teknologi mana yang dapat meningkatkan hasil pembelajaran. Tujuan dari penelitian ini adalah untuk membandingkan efektivitas realitas maya (AR) dan realitas virtual (VR) sebagai media pembelajaran dengan menggunakan pendekatan Systematic Literature Review (SLR) yang didasarkan pada PRISMA 2020. Tiga basis data utama (Scopus, IEEE Xplore, dan ScienceDirect) digunakan untuk melakukan pencarian literatur dari tahun 2019 hingga tahun 2020. Dari 562 artikel yang ditemukan, 42 memenuhi persyaratan inklusi dan dianalisis secara naratif-komparatif. Hasil penelitian menunjukkan bahwa dibandingkan dengan metode konvensional, kedua teknologi meningkatkan motivasi, keterlibatan, dan hasil belajar. Sementara realitas virtual memiliki keunggulan dalam simulasi skenario berbahaya, retensi materi kompleks, dan imersi mendalam, AR unggul dalam aksesibilitas, kemudahan adopsi, dan integrasi konteks dunia nyata. Bahasa, STEM, dan kedokteran adalah bidang yang paling banyak memanfaatkan keduanya. Biaya perangkat, kesiapan guru, dan infrastruktur adalah masalah utama, terutama di negara berkembang. Studi ini membantu memilih teknologi berdasarkan tujuan pembelajaran dan konteks institusi. Kata kunci—Augmented reality, Virtual reality, Efektivitas Pembelajaran, Media Pembelajaran, Systematic Literature Review.
Optimasi Keuntungan Produksi Gorong-Gorong Menggunakan Metode Simpleks pada Usaha Konblock Bangun Lestari Fauzi Nurhamdi; Syarif Hidayat; Pradita Eko Prasetyo Utomo; Oki Dahwanu
KERNEL: Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika Vol 7, No 1 (2026)
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.kernel.2026.v7i1.8556

Abstract

This study aims to optimize the production profit of concrete culvert products at Konblock Bangun Lestari using the simplex method. The observed business produces three types of culverts with different dimensions, material requirements, and processing times. Data were collected through direct field observation and interviews to obtain information on resource availability, including cement, sand, and working hours. A linear programming model was formulated with the objective of maximizing profit under material and time constraints. The simplex method was applied to determine the optimal production combination. The results show that producing 30 units of type B culverts yields the maximum profit of Rp12,300,000 while fully utilizing available resources. This finding demonstrates that the simplex method can effectively support production decision-making in small-scale manufacturing businesses.
Efektivitas dan Keandalan Protokol MQTT pada Internet of Things: Tinjauan Literatur Sistematis Berbasis PRISMA 2020 Pariyadi Pariyadi; Fattachul Huda Aminuddin; Ahmad Husna Ahadi; Oki Dahwanu; Muhammad Damas Fatih
Journal of Information System Research (JOSH) Vol 7 No 4 (2026): July 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i4.10049

Abstract

This study aims to present a systematic literature review (SLR) of the performance, security, and Quality of Service (QoS) of the Message Queuing Telemetry Transport (MQTT) protocol in Internet of Things (IoT) environments based on articles published between 2020 and 2026. The SLR follows the PRISMA 2020 guidelines and the Kitchenham and Charters guidelines for software engineering studies. A total of 30 core articles, comprising 7 reputable international journals and 23 nationally accredited SINTA journals, were purposively selected based on thematic relevance and methodological quality. The search was conducted using IEEE Xplore, ScienceDirect, SpringerLink, MDPI, Garuda, and SINTA with the keywords “MQTT,” “IoT,” “performance,” “security,” and “QoS.” The selection process followed the PRISMA flow, consisting of identification (n=487), screening (n=86), eligibility assessment (n=43), and included studies (n=30). The data were extracted and thematically synthesized to address four research questions (RQ1–RQ4), with Scopus-indexed international studies included as contextual comparators. The findings indicate that MQTT outperforms HTTP in terms of bandwidth efficiency and low latency, particularly on resource-constrained devices, with reported latency ranging from 45 to 210 ms depending on the QoS level and testing scenario. The dominant performance parameters include latency, throughput, and packet loss. Security approaches encompass TLS/RSA encryption, domestic cryptography, and Random Forest-based attack detection, achieving an accuracy of 97.2%, although TLS encryption may reduce throughput by up to 30%. QoS 1 represents a balanced option for non-critical applications, whereas QoS 2 is appropriate for vital data. The main research gap is the absence of integrated performance, security, and QoS testing within a single experimental framework. Therefore, future research should focus on lightweight security, context-aware adaptive QoS, and real-world-scale validation through integrative studies that examine the interaction among these three aspects.
Perancangan Sistem Informasi Promosi dan Penjualan Berbasis Web Pada Unit Produksi SMKN 1 Ampek Angkek Menggunakan Framework CodeIgniter Nurul Abdillah; Oki Dahwanu; Hamzah Alghifari; Niko Akbar
Jurnal Informatika Vol 12, No 3 (2024): INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v12i3.8165

Abstract

The Production Unit (PU) plays an important role in fostering students’ entrepreneurial skills through the creation of economically valuable products and services. However, product promotion at the Production Unit of SMK N 1 Ampek Angkek has so far only been carried out through exhibitions held once every semester. The school’s less strategic location results in many products remaining unsold, and those stored for too long often become damaged. To address this issue, a web-based promotional and sales information system was designed using the CodeIgniter framework. The system was developed using UML (Unified Modeling Language) modeling with an object-oriented approach. The programming languages used were PHP with the CodeIgniter framework and JavaScript, while MySQL served as the database and Sublime Text 3 as the code editor. The result of this design is a web-based information system that can present craft product information more widely and efficiently. This system helps the Production Unit promote its products without time and location limitations and provides convenience for consumers to view and purchase products online.
Co-Authors Ahmad Husna Ahadi Alghifari, Hamzah Aminuddin, Fattachul Huda Ari Andrianti Elsi Alfionita Syawal Fatih, Muhammad Damas Fauzi Nurhamdi Hamzah Alghifari M. Yonggi Puriza Nata, Rudi Niko Akbar Niko Akbar Niko Akbar Niko Akbar Nurul Abdillah Pariyadi Pradita Eko Prasetyo Utomo Rahmad Ashar Renaldi Yulvianda Sarjono Sarjono, Sarjono Syarif Hidayat Yandi Anzari Yandi Anzhari Yudistira, Miranty