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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer Indonesian Journal of Business Intelligence (IJUBI) PENGABDI: Jurnal Hasil Pengabdian Masyarakat Emerging Information Science and Technology Jurnal Mandiri IT Jurnal Jarlit
Haryanto, Eri
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Library & Information Science Mathematics Social Sciences Other

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RANCANG BANGUN SISTEM PENYIRAM TANAMAN OTOMATIS BERBASIS INTERNET OF THINGS (IOT) DENGAN MEMANFAATKAN SOLAR CELLS (STUDI KASUS TAMAN SISWA CODE KOTA YOGYAKARTA) Haryanto, Eri; Lukmanfiandy, Sofyan; Fitriastuti, Fatsyahrina; Setyorini, Agustin; Nurharyanto, Erry Maricha Oki
Jurnal Jarlit Vol. 16 No. 1 (2020): PENINGKATAN KUALITAS SUMBER DAYA MANUSIA YANG MENDORONG PEMERATAAN PEMBANGUNAN
Publisher : Badan Perencanaan Pembangunan Daerah Kota Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70154/jid.v16i1.21

Abstract

Penelitian ini akan melakukan rancang bangun sistem penyiram tanaman otomatis berbasis Internet of Things (IoT) dengan memanfaatkan solar cells sebagai energi listriknya. Implementasi sistem ini dilaksanakan di Taman Wisata Code di Kelurahan Cokrodiningratan Kecamatan Jetis Kota Yogyakarta. Penelitian ini dilakukan dengan metode waterfall dengan tahapan-tahapan yang sistematis. Solar panel telah berhasil menghasilkan listrik AC dengan tegangan 220V sehingga dapat digunakan untuk mensuplay listrik ke pengendali perangkat IoT. Mode penyiraman terdiri dari mode otomatis dengan jadwal yang dapat diatur dari platform IoT berbasis web dan mode penyiraman dengan remote jarak jauh lewat jaringan internet. Kedua mode penyiraman dapat berjalan dengan baik dan berhasil menyiram tanaman di lokasi penelitian.
Implementation of role-based access control, multi tenancy and audit logging in a single sign-on system Aswintama, Putranta; Haryanto, Eri; Setyawan, Ryan Ari
Jurnal Mandiri IT Vol. 14 No. 1 (2025): July: Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v14i1.441

Abstract

As enterprises increasingly require centralized, secure, and efficient authentication mechanisms, Single Sign-On (SSO) has emerged as a strategic approach to managing user access. This study discusses the implementation of an SSO system based on Laravel Livewire with support from JSON Web Token (JWT) and OAuth, developed for PT Radiator Springs Indonesia. The system integrates three main components: Role-Based Access Control (RBAC) for access rights management, a Multi-Tenancy architecture for separating users across organizational units, and Audit Logging to track user activities. The analysis shows significant improvements in security, with 87.5% fewer unauthorized access attempts and enhanced user management efficiency, evidenced by a 71.43% reduction in time to onboard new users. Additionally, the system generates over 300+ audit log entries per day, improving monitoring and compliance capabilities.
Forensik Internet Of Things pada Device Level berbasis Embedded System Haryanto, Eri; Riadi, Imam
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 6 No 6: Desember 2019
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (4014.539 KB) | DOI: 10.25126/jtiik.2019661828

Abstract

Perangkat Internet of Things (IoT) merupakan perangkat cerdas yang memiliki interkoneksi dengan jaringan internet global. Investigasi kasus yang menyangkut perangkat IoT akan menjadi tantangan tersendiri bagi investigator forensik. Keberagaman jenis perangkat dan teknologi akan memunculkan tantangan baru bagi investigator forensik. Dalam penelitian ini dititikberatkan forensik di level internal device perangkat IoT. Belum banyak bahkan belum penulis temukan penelitian sejenis yang fokus dalam analisis forensik perangkat IoT pada level device. Penelitian yang sudah dilakukan sebelumnya lebih banyak pada level jaringan dan level cloud server perangkat IoT. Pada penelitian ini dibangun environment perangkat IoT berupa prototype smart home sebagai media penelitian dan kajian tentang forensik level device. Pada penelitian ini digunakan analisis model forensik yang meliputi collection, examination, analysis, dan reporting dalam investigasi forensik untuk menemukan bukti digital. Penelitian ini berhasil mengungkap benar-benar ada serangan berupa injeksi malware terhadap perangkat IoT yang memiliki sistem operasi Raspbian, Fedberry dan Ubuntu Mate. Pengungkapan fakta kasus mengalami kesulitan pada perangkat IoT yang memiliki sistem operasi Kali Linux. Ditemukan 1 IP Address komputer penyerang yang diduga kuat menanamkan malware dan mengganggu sistem kerja perangkat IoT.AbstractThe Internet of Things (IoT) is an smart device that has interconnection with global internet networks. Investigating cases involving IoT devices will be a challenge for forensic investigators. The diversity of types of equipment and technology will create new challenges for forensic investigators. In this study focused on forensics at the IoT device's internal device level, there have not been many similar research that focuses on forensic analysis of IoT devices at the device level. Previous research has been done more at the network level and cloud level of IoT device's. In this study an IoT environment was built  a smart home prototype as a object for research and studies on forensic level devices. This study, using forensic model analysis which includes collection, examination, analysis, and reporting in finding digital evidence. This study successfully revealed that there was really an attack in the form of malware injection against IoT devices that have Raspbian, Fedberry and Ubuntu Mate operating systems. Disclosure of the fact that the case has difficulties with IoT devices that have the Kali Linux operating system. Found 1 IP Address of an attacker's computer that is allegedly strongly infusing malware and interfering with the work system of IoT devices.
Workshop Desain Pembelajaran Menarik dan Interaktif Berbasis AI untuk Meningkatkan Keterampilan Dosen dalam Mendesain Pembelajaran Daring Mawarni, Sella; Fitriastuti, Fatsyahrina; Haryanto, Eri; Ibrahim, Nurwahyuningsih; Syah, Maenuddin Bustanil
PENGABDI PENGABDI: VOL. 6, NO.2 (2025)
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26858/pengabdi.v6i2.81330

Abstract

Abstrak. Pembelajaran daring menjadi salah satu pola pembelajaran yang banyak diadaptasi, khususnya dalam lingkungan perguruan tinggi. Mendesain sebuah pembelajaran daring memiliki komponen yang berbeda dibandingkan pembelajaran tatap muka. Salah satu perbedaannya yakni pola interaksi antara dosen dan mahasiswa yang menyebabkan rendahnya keterlibatan mahasiswa dalam pembelajaran daring. Mitra pada kegiatan workshop ini adalah Universitas Janabadra Yogyakarta. Kegiatan workshop ini bertujuan untuk meningkatkan pemahaman dan keterampilan dosen-dosen Universitas Janabadra dalam mendesain pembelajaran daring di platform LMS Janalearning. Materi workshop juga dikaitkan dengan pemanfaatan AI untuk mendesain pembelajaran daring yang menarik dan interaktif. Metode yang digunakan dalam workshop ini mencakup presentasi materi, tutorial & praktik terbimbing, dan diskusi. Paparan materi disajikan sebagai fondasi terkait konsep desain pembelajaran daring dan beberapa aplikasi AI yang dapat digunakan dosen untuk melengkapi kebutuhan konten pembelajaran daring. Pada sesi tutorial & praktik terbimbing dosen dipandu secara step-by-step untuk dapat menghasilkan sebuah konten menggunakan aplikasi AI serta strategi mengintegrasikannya kedalam pembelajaran daring. Hasil diskusi, evaluasi dan refleksi yang dilaksanakan pada akhir workshop menunjukkan antusiasme yang tinggi dari peserta serta peningkatan kompetensi pedagogik khususnya dalam memanfaatkan AI kedalam pembelajaran daring. Kata Kunci: Workshop, Pembelajaran Daring, AI, Kecerdasan Buatan, Learning Management System.
Convolutional Neural Network-Based Model for Indonesian Offensive Text Classification Mayndeta, Daniel; Setyawan, Ryan Ari; Haryanto, Eri
Emerging Information Science and Technology Vol. 6 No. 2 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.v6i2.29704

Abstract

This study presents a Convolutional Neural Network (CNN)-based model for classifying offensive and non-offensive Indonesian text using a dataset of 10,054 tweets collected from Twitter/X. The dataset was manually annotated into two classes and processed through a series of text-cleaning, tokenization, and padding steps before being used to train the model. Several training durations were tested to evaluate the effect of epoch variation on model performance. The results show that the model trained for 70 epochs achieved the best overall performance, with a testing accuracy of 86.73%, precision of 0.8793, recall of 0.8834, F1-score of 0.8814, and a ROC-AUC value of 92.08%. The confusion matrix analysis indicates strong classification capability for both classes, with the model performing slightly better in identifying offensive text due to distinctive lexical patterns. These findings demonstrate that the CNN architecture, supported by trainable word embeddings, is effective for Indonesian offensive-text classification. Future improvements may include integrating pretrained language models or expanding the dataset to enhance contextual understanding and robustness.
SENTIMENT ANALYSIS UNTUK REVIEW DESTINASI WISATA UNGGULAN GUNUNG KIDUL MENGGUNAKAN METODE LEXICON DAN PIVOT Larasati, Larasati; Nabilla, Shalsa; Haryanto, Eri
Indonesian Journal of Business Intelligence (IJUBI) Vol 5 No 2 (2022): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21927/ijubi.v5i2.2604

Abstract

Sentiment analysis is the process of using text analytics to get various data sources from the internet and various social media platforms. Comment data is obtained through Twitter social media. This classification is used to determine how comments interpret tourist attractions in Gunungkidul. Lexicon-based and Pivoting are used to group people's opinions into three classes: positive, negative, and neutral sentiments. This method is used to classify the results of community comment data written as community satisfaction with tourism in Gunungkidul. This study aims to discover people's opinions about tourism in Gunungkidul during the Covid-19 pandemic. The results of this study are used to determine the classification of community comment data so that services can be easily developed through comments provided by the community. The sentiment analysis results contained the categories of positive emotions 51%, negative 1%, and neutral 48%.
Co-Authors Aswintama, Putranta Fatsyahrina Fitriastuti Imam Riadi Larasati Larasati Lukmanfiandy, Sofyan Mayndeta, Daniel Nabilla, Shalsa Nurharyanto, Erry Maricha Oki Nurwahyuni Ryan Ari Setyawan Sella Mawarni Setyorini, Agustin Syah, Maenuddin Bustanil