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All Journal TEKNIK INFORMATIKA Jurnal Ilmiah Informatika Komputer VOLT : Jurnal Ilmiah Pendidikan Teknik Elektro Network Engineering Research Operation [NERO] JITK (Jurnal Ilmu Pengetahuan dan Komputer) Jurnal Komtika (Komputasi dan Informatika) Jiko (Jurnal Informatika dan komputer) Multitek Indonesia : Jurnal Ilmiah KOMPUTEK bit-Tech Journal of Computer Networks, Architecture and High Performance Computing Pilar Teknologi : Jurnal Penelitian Ilmu-ilmu Teknik Jurnal Ilmiah Edutic : Pendidikan dan Informatika Formosa Journal of Computer and Information Science Community: Jurnal Pengabdian Pada Masyarakat Jurnal Pengabdian Masyarakat Bangsa Kenduri: Jurnal Pengabdian Dan Pemberdayaan Masyarakat SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Jurnal ilmiah teknologi informasi Asia Journal Information System and Computer Application Mathematics, Informatics, Knowledge, And Information Research Proceeding of Informatics Collaborations and Dessimenation Meeting (Infocoding)
Cobantoro, Adi Fajaryanto
Program Studi Teknik Informatika, Fakultas Teknik, Universitas Muhammadiyah Ponorogo
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Otomasi Greenhouse Berbasis Mikrokomputer RASPBERRY PI Adi Fajaryanto Cobantoro; Mohammad Bhanu Setyawan; Miftahudin Agung Budi Wibowo
Jurnal Ilmiah Teknologi Informasi Asia Vol 13 No 2 (2019): Volume 13 Nomor 2 (8)
Publisher : LP2M INSTITUT TEKNOLOGI DAN BISNIS ASIA MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32815/jitika.v13i2.360

Abstract

The entry of the industrial revolution era, many occur anthropogenic. One of the causes of ecological imbalances is the lack of reforestation in urban environments. Environmental conditions are the main thing to achieve production. The main factors that influence plant growth and development are temperature and humidity, in this case to reach the desired temperature and humidity is very difficult and difficult to control as needed. As if the temperature and humidity limit agricultural production. From the existing problems, building a greenhouse prototype can automatically control temperature and humidity according to the actual conditions in the plant. To achieve this condition use a control system that controls temperature and humidity automatically. The system works according to the value that has been determined then the value compared with the DHT22 sensor to measure air humidity and YL-69 as a controller of soil moisture and as a controller for watering plants automatically. The prototype testing was done using a computer and raspberry pi microcontroller by connecting the UTP cable to the raspberry pi to the laptop with an internet sharing connection. The prototype can run and can be controlled by telegram.
HARDENING SERVER MENGGUNAKAN METODE PORT KNOCKING PADA SISTEM PROGRAM STUDI TEKNIK INFORMATIKA UNIVERSITAS MUHAMMADIYAH PONOROGO Muhammad Reza; Adi Fajaryanto Cobantoro; Ismail Abdurrozzaq Zulkarnain
Jurnal Ilmiah Informatika Komputer Vol 29, No 3 (2024)
Publisher : Universitas Gunadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35760/ik.2024.v29i3.12954

Abstract

Pada era digitalisasi, keamanan data menjadi sangat rentan terhadap ancaman kebocoran, khususnya pada server yang menyimpan informasi sensitif. Penelitian ini bertujuan meningkatkan keamanan server Program Studi Teknik Informatika Universitas Muhammadiyah Ponorogo melalui implementasi hardening server. Langkah-langkah yang diterapkan meliputi konfigurasi port knocking untuk otentikasi akses, pengaturan firewall iptables, aktivasi portsentry, pemanfaatan Snort sebagai Intrusion Detection System (IDS), dan pemblokiran permintaan ICMP guna menangkal serangan berbasis ping. Pengujian keamanan menggunakan alat audit Lynis menunjukkan peningkatan signifikan, dengan skor keamanan awal 65, yang menunjukkan kerentanan tinggi, meningkat menjadi 96 setelah implementasi hardening. Penelitian ini menghadirkan pendekatan baru dengan mengintegrasikan berbagai mekanisme keamanan secara simultan, termasuk kombinasi port knocking dengan IDS Snort. Pendekatan ini memberikan perlindungan lebih baik terhadap risiko akses tidak sah, yang jarang diterapkan secara bersamaan dalam penelitian serupa. Langkah-langkah utama mencakup pembaruan sistem berkala, perlindungan port SSH (port 22) melalui pengaturan firewall, serta uji urutan otentikasi port knocking yang terintegrasi dengan IDS. Evaluasi dilakukan secara berulang menggunakan Lynis untuk mengukur efektivitas setiap langkah. Hasil penelitian membuktikan bahwa metode ini mampu meningkatkan ketahanan sistem secara substansial, menjaga kerahasiaan, integritas, dan ketersediaan data. Dengan demikian, server Program Studi Teknik Informatika menjadi lebih kuat dalam menghadapi ancaman siber.
Identifikasi Performa Algoritma Fuzzy Mamdani Sebagai Kendali Proses Koagulasi pada Internet of Thing Pembuatan Tahu Yovi Litanianda; David April Riyanto; Angga Prasetyo; Adi Fajaryanto Cobantoro; Ismail Abdurrozaq Zulkarnain
bit-Tech Vol. 7 No. 2 (2024): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v7i2.1972

Abstract

Proses pembuatan tahu dilakukan dalam berapa tahapan. Tahapan terpenting dalam pembuatan tahu yakni terletak pada proses penggumpalan (koagulasi) sari kedelai yang telah direbus. Pada tahapan ini bayak faktor yang menentukan keberhasilannya, diantaranya suhu sari kedelai, PH cuka sebagai katalis reaksi koagulasi dan kecepatan pengadukan. Jika terjadi ketidak sesuaian salah satunya maka akan berakibat sari kedelai gagal menggumpal dan terbuang. Produksi tahu yang masih tradisional membuat pekerjaan ini masih mengandalkan kepiawaian pekerja senior yang terampil. Ketergantungan pada keterampikan pekerja akan menghambat keberlangsungan industry. Untuk mengatasi masalah tersebut, dicoba dikembangkan perangkat IoT yang mampu mengendalikan proses koagulasi pada pembuatan tahu. Sistem ini bekerja berdasarkan algoritma Fuzzy Mamdani yang akan mengolah input nilai suhu sari kedelai dan nilai PH cuka menjadi nlai PWM yang menjadi penentu kecepatan motor pengaduk larutan sari kedelai. Tingkat keberhasilan algoritma fuzzy menangani kondisi nyata yang bervariasi menjadi ukuran performanya. Pengujian dilakukan dengan sekenario menguji lansung dengan kondisi nyata sari kedelai dan cuka untuk diketahui tingkat keberhasilannya dalam melakukan pengendalian proses koagulasi pembuatan tahu. Sebanyak 30 percobaan hasil pengadukan didapati keseluruhan proses dinyatakan berhasil menggumpalkan sari kedelai pada kecepatan motor bervariasi sesuai kendali algoritma Fuzzy mamdani berdasarkan kondisi pH cuka dan suhu sari kedelai. Oleh karena itu penelitian ini menyimpulkan bahwa performa Algoritma Fuzzy mamdani dalam mengendaikan proses koagulasi pembuatan tahu melalui cara mengatur kecepatan pengadukan sebesar 100%. Temuan ini menjadi bukti penguat yang bisa dijadikan dasar bagi para peneliti bahwa algoritma fuzzy sekali lagi berhasil dijadikan rule pengendalian sebuah proses dengan hasil yang meyakinkan.
Implementasi Algoritma Convolutional Neural Network (CNN) Untuk Identifikasi Jenis Tanaman Rimpang (Zingiberaceae) Rani Dwi Kartikasari; Mohammad Bhanu Setyawan; Fauzan Masykur; Adi Fajaryanto Cobantoro
MIKIR : Mathematics, Informatics, Knowledge And Information Research Vol. 1 No. 1 (2025): OCTOBER
Publisher : PT Mekar Research and Publishing

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

Abstract

Rhizomes (Zingiberaceae) are modified plant stems that grow horizontally beneath the soil surface and can produce shoots and new roots from their nodes. Rhizome plants (Zingiberaceae) are known as ginger or spice plants. This research article discusses the identification of rhizome plant species using Convolutional Neural Network (CNN) algorithm with VGG19 architecture, involving a total of 10 classes of data samples. The rhizome images underwent data preprocessing, resizing them from 500 x 500 to 200 x 200 pixels. During the model design phase, three different scenarios were tested, considering variations in dataset proportions, number of epochs, and batch sizes. The results of the three scenarios showed that the second scenario performed the best, achieving an accuracy of 90%, a loss of 0.285, precision of 93%, recall of 89%, and F1-Score of 91%. The first scenario obtained an accuracy of 88%, and the third scenario achieved an accuracy of 82%. However, when applying the model to test images and achieving the highest accuracy of 90% during training, the accuracy dropped to 40% when evaluated on 100 testing data. This drop in accuracy can be attributed to several factors, including noise in the dataset used and insufficient amount of training data, leading to the model being less effective in learning and recognizing data patterns.
CLASSIFICATION OF DURIAN LEAF IMAGES USING CNN (CONVOLUTIONAL NEURAL NETWORK) ALGORITHM Lely Mustikasari Mahardhika Fitriani; Yovi Litanianda; Adi Fajaryanto Cobantoro
JIKO (Jurnal Informatika dan Komputer) Vol 7 No 2 (2024)
Publisher : Program Studi Teknik Informatika Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v7i2.8576

Abstract

This research investigates the classification of durian leaf images using Convolutional Neural Network (CNN) algorithms, specifically focusing on the architectures AlexNet, InceptionNetV3, and MobileNet. The study begins with the collection of a dataset comprising 1604 images for training, 201 images for validation, and 201 images for testing. The dataset includes five classes of durian leaves: Bawor, Duri Hitam, Malica, Montong, and Musang King, chosen for their varied characteristics such as taste, texture, and aroma. Data preprocessing involved several steps to ensure the images were suitable for model training. These steps included data augmentation to increase variability, pixel normalization to standardize the images, and resizing to 150x150 pixels to match the input requirements of the CNN models. After preprocessing, the CNN models were implemented and trained using deep learning frameworks such as TensorFlow and PyTorch. Model performance was evaluated using a Confusion Matrix, which provided detailed insights into classification accuracy, precision, sensitivity, specificity, and F-score. The results indicated that InceptionNetV3 and AlexNet achieved near-perfect classification accuracy, with no misclassifications, demonstrating their robustness and precision in identifying durian leaf images. The training accuracy for both models rapidly approached 100% within the first few epochs and stabilized, while the loss values decreased sharply, indicating effective learning without overfitting. In contrast, MobileNet, while showing high accuracy and low loss during training, exhibited several misclassifications across all classes. The training accuracy of MobileNet also approached 100%, but the presence of misclassifications suggested that further tuning and improvements were necessary. Specifically, MobileNet's Confusion Matrix revealed errors in correctly identifying samples from each class, indicating potential areas for enhancement in the model's architecture or preprocessing techniques. In conclusion, InceptionNetV3 and AlexNet proved to be highly efficient and accurate architectures for classifying durian leaf images, making them suitable for practical applications. MobileNet, although performing well, requires further refinement to achieve the same level of accuracy and reliability. This study highlights the importance of selecting appropriate CNN architectures and the need for thorough preprocessing to optimize model performance in image classification tasks.
The Road Safety Literacy Strengthening Assistance For The Lentera Community (Orderly And Safe Literacy On The Highway) In Ponorogo Regency Ida Yeni Rahmawati; Mohammad Bhanu Setyawan; Adi Fajaryanto Cobantoro; Susi Darihastining; Tri Wahyono; Siti Khoirul Bariyah
KENDURI : Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol. 6 No. 1 (2026): January-April
Publisher : Yayasan Darussalam Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62159/kenduri.v6i1.2150

Abstract

The high number of traffic accidents, especially among students and novice drivers, indicates a low level of road safety literacy in the community. The LENTERA (Orderly and Safe Literacy on the Road) community in Ponorogo Regency was formed as an effort to build collective awareness of the importance of safe driving. This study aims to assist and strengthen the capacity of this community through structured interactive training. The method used in this activity is a participatory descriptive approach, with stages of socialization, training, and evaluation using pre-test and post-test instruments, as well as observation of participant involvement. The results showed a significant increase in participants' understanding of traffic safety principles, with an average pre-test score of 62.06 increasing to 85.12 in the post-test. Observations also showed an increase in participants' enthusiasm, analytical skills, and reflective awareness. The conclusion of this activity is that strengthening safety literacy through a community approach can encourage constructive and sustainable behavioral changes. It is recommended that this community-based training model be replicated in other regions, with cross-sector collaboration and the development of more contextual modules. Furthermore, the outreach materials presented should be based on factual data on frequent accidents and should provide insights into each incident, with the goal of reducing the number of road accidents, particularly among students. Materials supplemented with simulations of road traffic engineering provide knowledge that will be easier to understand in everyday practice and, of course, be more memorable.
Building an Annotated Corpus of Advice-Giving in Indonesian Thesis Supervision for Educational Text Mining Elok Putri Nimasari; Adi Fajaryanto Cobantoro; Mohammad Bhanu Setyawan; Ismail Abdurrozaq; Ariyanti Ariyanti; Navila Uliya Sahidah
Formosa Journal of Computer and Information Science Vol. 5 No. 1 (2026): March 2026
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/fjcis.v5i1.16529

Abstract

While educational text mining has widely examined student feedback and institutional evaluation, little attention has been paid to advice-giving in thesis supervision as an interactional and power-relational practice. Therefore, this present study aims to analyze and build a domain-sensitive annotated corpus of advice-giving in Indonesian thesis supervision for future educational text mining. Using a qualitative-informed corpus development research design, the study collected and analyzed 155 annotated utterances drawn from authentic thesis supervision transcripts across Indonesian universities. The results identified six advice-giving labels classified into three interactional modes: power-over, power-gaining, and power-maintaining following Zhang and Hyland’s theoretical of power and roles. Cohen’s Kappa reached 1.00, indicating perfect annotation agreement. The corpus contributes a reliable methodological foundation for AI-assisted analysis of supervisory discourse and inclusive academic supervisory.
Pengembangan Sistem Pakar Diagnosis Tingkat Stres Menggunakan Metode Certainty Factor Fairuz Destea Hafsha Permanasari; Adi Fajaryanto Cobantoro; Rifqi Rahmatika Az-Zahra
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 3 No. 3 (2026): July
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.21724197

Abstract

Proses penyusunan skripsi sering menimbulkan stres pada mahasiswa akibat tuntutan akademik, keterbatasan waktu, dan berbagai kendala selama penelitian. Kondisi tersebut dapat memengaruhi motivasi dan konsentrasi sehingga diperlukan sistem untuk mendeteksi kondisi psikologis mahasiswa secara dini. Penelitian ini bertujuan merancang dan membangun sistem pakar diagnosis tingkat stres mahasiswa menggunakan metode Certainty Factor (CF) di Institut Agama Islam Riyadlotul Mujahidin (IAIRM) Ngabar. Sistem dikembangkan berbasis web menggunakan framework Laravel, PHP, dan MySQL dengan basis pengetahuan yang mengacu pada instrumen Depression Anxiety Stress Scales (DASS-42) yang terdiri atas 42 gejala. Pengujian dilakukan menggunakan white box testing untuk memastikan fungsi dan alur logika sistem berjalan sesuai rancangan. Hasil penelitian menunjukkan bahwa sistem mampu menghitung nilai Certainty Factor berdasarkan nilai CF User dan CF Pakar serta menghasilkan diagnosis secara otomatis. Pada pengujian, kategori P01 (Stres Ringan) memperoleh nilai CF tertinggi sebesar 82,4%, sedangkan P02 (Kecemasan) sebesar 28% dan P03 (Depresi) sebesar 0%, sehingga sistem menetapkan diagnosis Stres Ringan dengan tingkat keyakinan 82,4%. Sistem yang dikembangkan dapat dimanfaatkan sebagai alat bantu deteksi dini tingkat stres mahasiswa selama proses penyusunan skripsi.
ANALISIS OPTIMASI QUEUE TYPE DALAM MIKROTIK ROUTER OS V7.15 PADA JARINGAN INTERNET DI SMP NEGERI 6 SUDIMORO Daras Fadila; Adi Fajaryanto Cobantoro
MEKAR : Journal Information System and Computer Application Vol. 1 No. 1 (2025): AGUSTUS
Publisher : PT Mekar Research and Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65475/6srksk04

Abstract

Dalam era digital, akses internet yang cepat dan stabil menjadi kebutuhan utama, khususnya di lingkungan pendidikan. SMP Negeri 6 Sudimoro menghadapi kendala dalam pengelolaan trafik jaringan internet, yang berdampak pada performa pembelajaran daring. Penelitian ini bertujuan untuk menganalisis pengaruh penerapan algoritma antrian queue type CoDel, FQ-CoDel, dan CAKE pada Mikrotik RouterOS v7.15 terhadap kualitas layanan jaringan (Quality of Service/QoS), serta menentukan algoritma yang paling optimal. Metode yang digunakan adalah pendekatan kuantitatif dengan pengujian parameter QoS seperti throughput, delay, jitter, dan packet loss berdasarkan standar TIPHON. Data dikumpulkan menggunakan aplikasi Wireshark dan dikonfigurasi melalui Winbox. Hasil pengujian menunjukkan bahwa algoritma FQ-CoDel memberikan performa terbaik dengan nilai throughput tertinggi tanpa peningkatan jitter maupun delay. Berdasarkan hasil tersebut, FQ-CoDel direkomendasikan sebagai queue type yang paling efektif untuk diterapkan pada jaringan internet sekolah. Implementasi algoritma ini diharapkan dapat meningkatkan efisiensi jaringan serta mendukung kelancaran kegiatan belajar mengajar berbasis digital.
OPTIMASI JARINGAN RT/RW NET MENGGUNAKAN SOFTWARE DEFINED NETWORK DAN LOAD BALANCING Fikri Muhamad; Fauzan Masykur; Adi Fajaryanto Cobantoro
MEKAR : Journal Information System and Computer Application Vol. 1 No. 1 (2025): AGUSTUS
Publisher : PT Mekar Research and Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65475/nsghad86

Abstract

Meningkatnya kebutuhan akan akses internet yang stabil dan cepat, terutama di lingkungan RT/RW Net yang melayani pelanggan rumah tangga dengan berbagai kebutuhan seperti streaming dan pengunduhan, memunculkan tantangan dalam pengelolaan lalu lintas jaringan, terutama ketika menggunakan lebih dari satu penyedia layanan internet (ISP). Penelitian ini mengusulkan penerapan arsitektur Software Defined Networking (SDN) sebagai solusi untuk mengatasi masalah distribusi trafik yang tidak merata melalui mekanisme loadbalancing. SDN memberikan kontrol PDF dan fleksibel dalam pengelolaan jaringan, memungkinkan pengaturan lalu lintas secara dinamis dan efisien. Implementasi dilakukan dengan menggunakan pengontrol OpenDaylight dan perangkat MikroTik sebagai router yang dikonfigurasi mendukung protokol OpenFlow untuk loadbalancing dua ISP. Hasil pengujian menunjukkan adanya peningkatan pada parameter Quality of Service (QoS) seperti throughput, delay, jitter, dan packet loss. Dengan penerapan SDN dan loadbalancing setelah dilakukan pengujian dengan QoS didapat hasil rata-rata dari masing-masing parameter yaitu, untuk throughput dengan rata-rata 8,36 mbps , untuk parameter packet loss didapat hasil rata-rata 0.09% , untuk delaynya dengan rata-rata 39 ms dan parameter jitter dengan rata-rata 12,67 ms. Dari semua hasil pengujian parameter diatas membuktikan adanya peningkatan kualitas jaringan dibandingkan dengan sebelum penerapan SDN dan loadbalancing.
Co-Authors ., Sugianti Aidha Putri, Evi Zulfa Aliyadi Aliyadi Angga Prasetyo Anugra, Fery Grahanda Aprilia Cahyanti Arifin, Rizal Arifin, Rizal Ariyanti Astuti, Arin Yuli Charisma Wahyu Aditya Daras Fadila David April Riyanto Dwiyono Ariyadi Efi Mukaromah Elok Putri Nimasari Evi Zulfa Aidha Putri Fairuz Destea Hafsha Permanasari Fauzan Masykur Fauzan Masykur Fery Grahanda Anugra Fikri Muhamad Hardiyan Oktavianto Ida Yeni Rahmawati Indah Puji Astuti Indah Puji Astuti Indah Puji Astuti Ismail Abdurrozaq Ismail Abdurrozaq Zulkarnain Jamilah Karaman Karisma Nanda Arditya Kelik Sussolaikah Khoiru Nur Fitri Khoiru Nurfitri Lely Mustikasari Mahardhika Fitriani M.Bhanu Setyawan Miftahudin Agung Budi Wibowo Moh Bhanu Setyawan Moh. Bhanu Setyawan Mohammad Bhanu Setyawan Mohammad Bhanu Setyawan Mohammad Rizqi Rosyadi Muhammad Reza Navila Uliya Sahidah Novia Anggraini Prasetyo, Angga Rani Dwi Kartikasari Rifqi Rahmatika Az-Zahra Rifqi Rahmatika Azzahra Siti Khoirul Bariyah Sony Dwiki Andika Susi Darihastining Tri Wahyono Viky Friandika Utamandani Wakit Kurniadani Yovi Litanianda Zulkarnain, Ismail Abdurrozzaq