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All Journal Jurnal Pendidikan Matematika Techno.Com: Jurnal Teknologi Informasi Semesta Teknika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Insect (Informatics and Security) : Jurnal Teknik Informatika Metode : Jurnal Teknik Industri Antivirus : Jurnal Ilmiah Teknik Informatika Jurnal Pengabdian Dharma Laksana JURNAL MAHAJANA INFORMASI bit-Tech Mobile and Forensics Jurnal Tekinkom (Teknik Informasi dan Komputer) JIKA (Jurnal Informatika) Abdimas: Papua Journal Of Community Service TRANSFORMASI : JURNAL PENGABDIAN PADA MASYARAKAT Jurnal Pengabdian Masyarakat Jurnal Pustaka Data : Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitektur Komputer Jurnal Informatika Progres FRAMEWORK Jurnal Ilmu Komputer dan Informatika Mathematics Education Journal
Soekarta, Rendra
Teknik Informatika, Universitas Muhammadiyah Sorong
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Neuroscience Public Health Social Sciences Other

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Social Media-Based E-learning and Online Assignments on Algebraic Materials Rahmawati, Miftah Sigit; Soekarta, Rendra
Mathematics Education Journal Vol. 15 No. 2 (2021): Jurnal Pendidikan Matematika
Publisher : Universitas Sriwijaya in collaboration with Indonesian Mathematical Society (IndoMS)

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

Abstract

This study aims at evaluating the application of social media-based e-learning and online assignments during Covid-19 pandemic based on: (1) the availability of facilities and infrastructure in implementing social media-based e-learning and online assignments during the Covid-19 pandemic, (2) comprehension and management of e-learning and online assignments by lecturers and students, (3) social media-based e-learning and online assignments. This study is a qualitative descriptive study using the CIPP evaluation by evaluating each component, including context, input, process and product/outcome. The sources of study data involved lecturers and students of Informatics Engineering at Muhammadiyah University Sorong in Matrix Algebra course. The instruments of primary data collection was online assignments and Google Form questionnaires, while secondary data was obtained through observation, literature study, documentation and interviews. The results show that students obtained an overall average score (mean) of 76.4 from the maximum score of 100, and a percentage of assignment collection of 65.78%. This results were categorized as adequate, in meaning it is rather effective for theory comprehension, and was categorized as moderate in terms of boosting students’ motivation in doing social media-based online assignments, depending on the type of assignment. This signifies that the evaluation of CIPP in social media-based e-learning and online assignments in algebra has positive outcome in terms of infrastructure, management, and use. DOI: https://doi.org/10.22342/jpm.15.2.13714.175-190
Sosialisasi AI di SMP Negeri 1 Raja Ampat Untuk Membangun Pemahaman Siswa Ermin; Dewi Astri Faroeq; Rendra Soekarta; Bita Malissa; Sri Wulandari; La Muhammad Faishal Nurullah; Ilham S; Alfiyyah Faridah
Abdimas: Papua Journal of Community Service Vol. 7 No. 2 (2025): Juli
Publisher : Lembaga Pengembangan dan Pengabdian Masyarakat Universitas Muhammadiyah Sorong

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33506/pjcs.v7i2.4691

Abstract

The Artificial Intelligence (AI) Socialization Program at SMPN 1 Raja Ampat was implemented as an effort to enhance digital literacy in remote areas. This activity aimed to provide students with a basic understanding of AI concepts and their applications in daily life. The methods used included visual presentations, educational video screenings, simple AI application simulations, and group discussions. Evaluation results showed a significant improvement in students’ understanding of AI, with 90% of participants able to explain basic AI concepts after the program. Moreover, students' interest in learning more about AI technology increased, as reflected by their high enthusiasm and active participation throughout the session. Despite challenges such as limited technological infrastructure and varying levels of student comprehension, the program was successfully adapted to local conditions. This initiative is expected to inspire other schools in remote regions to recognize the importance of digital literacy within their curricula, thereby promoting equitable access to knowledge and preparing students for future technological advancements.
IMPLEMENTASI ALGORITMA YOLO UNTUK MENDETEKSI JENIS TANAMAN HIAS BERBASIS ANDROID Soekarta, Rendra; Aras, Suhardi; Rahman, Muh Fadhil
PROGRESS Vol 17 No 1 (2025): April
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v17i1.456

Abstract

Ornamental plants possess high aesthetic value and environmental benefits, yet identifying their species often poses a challenge, especially for beginners. This study aims to develop an Android-based application employing the You Only Look Once version 8 (YOLOv8) algorithm to detect ornamental plant species through leaf images in real-time. The dataset comprises 1,096 images of ornamental plant leaves, including snake plant (Sansevieria), aloe vera (Aloe vera), and coral cactus (Cereus peruvianus). The data were annotated using bounding box techniques, and the model was trained on Google Colab with an 80:20 split between training and testing datasets. The training resulted in an accuracy rate of 96% based on the mean Average Precision (mAP) metric. The application was developed using Android Studio with a user-friendly interface, enabling real-time detection on Android devices with a minimum RAM specification of 3 GB. Application testing involved black-box testing to ensure functionality and usability testing with 31 respondents, revealing a user satisfaction rate of 87%. Some challenges encountered included the impact of lighting on detection accuracy and result variability across different devices. This study contributes to the utilization of artificial intelligence technology for biodiversity education and supports environmental conservation efforts
Implementasi LLM Pada Chatbot PMB Universitas Muhammadiyah Sorong Menggunakan Metode RAG Berbasis Website Talaohu, Syamsudin Aliphadji; Soekarta, Rendra; Surahmanto, Muhammad
Framework : Jurnal Ilmu Komputer dan Informatika Vol 3 No 02 (2025): Framework : Jurnal Teknik Informatika
Publisher : Universitas Muhammadiyah Sorong

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33506/framework.v3i02.4790

Abstract

Dalam beberapa tahun terakhir, pemanfaatan kecerdasan buatan (AI) dalam sektor pendidikan mengalami pertumbuhan yang pesat. Salah satu teknologi AI yang mulai banyak diterapkan adalah chatbot berbasis Large Language Model (LLM), yang dirancang untuk menyajikan informasi secara interaktif dan responsif. Dalam konteks Penerimaan Mahasiswa Baru (PMB), Universitas Muhammadiyah Sorong masih menghadapi tantangan dalam menyediakan layanan informasi yang cepat dan akurat, karena sistem yang digunakan masih berbasis manual melalui media sosial. Hal ini menyebabkan proses tanya jawab menjadi lambat dan kurang efisien, terutama pada saat puncak pendaftaran. Penelitian ini bertujuan untuk mengimplementasikan chatbot berbasis LLM dengan metode Retrieval-Augmented Generation (RAG) untuk mendukung layanan PMB di Universitas Muhammadiyah Sorong. Metode RAG memungkinkan chatbot untuk memahami bahasa alami dan mengakses informasi eksternal secara real-time. Hasil penelitian menunjukkan bahwa chatbot dapat merespons pertanyaan calon mahasiswa dengan akurat dan memperoleh skor usability testing 88,5%, yang menandakan sistem ini mudah digunakan dan bermanfaat. Selain itu, hasil pengujian menggunakan BERTScore menunjukkan bahwa chatbot yang dikembangkan memiliki performa yang tinggi dengan tingkat akurasi sebesar 93%, dengan rata-rata precision 90%, recall 95%, dan f1-score 92%. Hasil ini menunjukkan bahwa chatbot mampu memberikan jawaban dengan tingkat keakuratan yang tinggi, sehingga dapat meningkatkan efisiensi dan kualitas layanan PMB di Universitas Muhammadiyah Sorong.
Deep Learning-Based Approach for Identifying and Counting Wooden Blocks with YOLO Aras, Suhardi; Soekarta, Rendra; Umasugi, Edwin
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.2627

Abstract

The wood processing industry in Indonesia, especially in the Southwest Papua region, faces ongoing challenges in accurately counting wooden logs, a task traditionally performed manually. Manual methods are time-intensive and prone to error, leading to inefficiencies in operations and weaknesses in resource management. This study addresses these challenges by applying a deep learning-based object detection approach, specifically the You Only Look Once version 8 (YOLOv8) algorithm, to automate the detection and counting of wooden beams in real time. YOLOv8 was chosen for its ability to perform high-speed and accurate detection even under varying environmental conditions, such as different lighting levels and camera angles. The model was trained on a custom dataset consisting of 265 annotated images of wooden beams, with a split of 70% for training, 20% for validation, and 10% for testing. Performance evaluation using a confusion matrix revealed a detection accuracy of 94%. These findings suggest that YOLOv8 is highly effective in supporting automation within wood processing workflows. By reducing dependency on manual labor and minimizing counting errors, the system contributes to more accurate inventory tracking and enhanced productivity. This research demonstrates the potential of integrating AI-driven models into mobile and industrial applications for improved efficiency in forestry-related sectors.
Implementation of Deep Learning for Personal Protective Equipment (PPE) Detection on Workers Using the YOLO Algorithm Soekarta, Rendra; Yusuf, Muhammad; Visman, Javan; Hasa, Muh. Fadli; Firdaus, Asno Azzawagama
Mobile and Forensics Vol. 7 No. 2 (2025)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/mf.v7i2.13884

Abstract

Occupational accidents represent a major challenge in the construction and manufacturing industries. This study aims to develop a deep learning model for real-time detection of personal protective equipment (PPE) usage using the YOLOv5 algorithm. Utilizing a dataset that includes four classes (hardhat, no hardhat, coverall, and no coverall), the model was trained and evaluated based on precision, recall, and mean Average Precision (mAP) metrics. The results demonstrated that the model achieved a high accuracy level with an mAP of 0.91 and stable performance. The model can also rapidly and effectively detect safety attributes even in complex work environments, such as varied lighting conditions and numerous background objects. Based on usability testing results of 85.35% and satisfactory black box testing, this study produced a prototype web-based application enabling efficient and effective PPE monitoring. The application is designed to support the improvement of workplace safety across various industrial sectors in a more practical and adaptive manner. It is expected to increase PPE compliance, reduce accident risks, and contribute significantly to workplace safety in the industry. The conclusion indicates that the YOLOv5 algorithm holds great potential for implementation in technology-based safety monitoring systems and supports the development of a safer and more modern industry.
Sistem Pendukung Keputusan Dalam Memilih Dosen Pembimbing Skripsi Berdasarkan Minat Mahasiswa Berbasis Android Web View SIMON, RESKI; Rendra Soekarta; Miftah Sigit Rahmawati
Framework : Jurnal Ilmu Komputer dan Informatika Vol 2 No 01 (2023): Framework : Jurnal ilmu komputer dan Informatika
Publisher : Universitas Muhammadiyah Sorong

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33506/jiki.v2i01.3041

Abstract

Tugas akhir adalah salah satu mata kuliah yang harus ditempuh oleh seorang mahasiswa untuk memperoleh gelar sarjananya. Untuk penentuan dosen pembimbing, mahasiswa tidak dapat memilih dosen pembimbing dan hanya bagian akademik atau fakultas yang dapat menentukan dosen pembimbing sesuai dengan judul yang di ajukan oleh mahasiswa. Namun saat ini karena kekurangan tenaga pengajar maka tidak semua judul tugas yang diajukan oleh bagian akademik. Dengan menerapkan metode perhitungan AHP dengan 5 kriteria yang ditetapkan pada pembahasan yaitu jabatan fungsional, latar belakang, bidang ilmu dan pengalaman membimbing, mahasiswa yang pernah dibimbing. maka perengking yang didapat yaitu Ahmad Fahrizal dengan skor 0,35, Ilham Marasabessy skor 0,25, Ratna skor 0,19, M. Iksan B skor 0,12 dan Christy Radjawane skor 0,10. Jadi pembimbing 1 adalah Ahmad Fahrizal dan pembimbing 2 Ilham Marasabessy. Sistem yang dihasilkan Berbasis web dan mobile yang dimana memiliki data dosen, mahasiswa, kriteria pada dosen yang tertera pada data, aplikasi dapat membantu mahasiswa dalam memudahkan pemilihan dosen pembimbing agar sesuai dengan minat mahasiswa, tampilan yang dihasilkan sudah cukup baik dan dapat digunakan, semoga bermanfaat bagia fakultas prikanan unamin.
Sistem Informasi Pencarian Rumah Sakit, Puskesmas Dan Dokter Praktek Berbasis Android Wattimena, Mikhael; Rendra Soekarta; Muhammad Rizki Setyawan
Framework : Jurnal Ilmu Komputer dan Informatika Vol 2 No 01 (2023): Framework : Jurnal ilmu komputer dan Informatika
Publisher : Universitas Muhammadiyah Sorong

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33506/jiki.v2i01.3042

Abstract

Penggunaan teknologi informasi dan komunikasi, khususnya aplikasi mobile, dapat menjadi solusi dalam memberikan akses informasi kesehatan yang mudah dan cepat bagi masyarakat. Dalam hal ini, pengembangan sistem informasi pencarian rumah sakit, puskesmas, dan dokter praktek berbasis android merupakan salah satu bentuk solusi yang dapat dilakukan. Tujuan dari penelitian ini adalah untuk membangun sistem pencarian rumah sakit, puskesmas dan dokter praktek. Sistem yang dibangun berisi detail alamat rumah sakit, puskesmas dan dokter praktek yang ada di seluruh Kota Sorong juga dapat mendeteksi jarang terdekat sesuai lokasi tempat pengguna. Oleh karena itu aplikasi ini dapat mempermudah pengguna yang baru berkunjung ke Kota Sorong. Aplikasi ini dibangun menggunakan bahasa pemograman android ditambah dengan metode SAW (Simple Additive Weighting) yang merupakan salah satu metode yang digunakan dalam proses pengambilan suatu keputusan. Metode SAW ini merupakan metode yang mencari penjumlahan terbobot dari rating kinerja pada setiap alternatif pada semua atribut. Selain itu aplikasi didukung tampilan yang mudah dipahami. Hal ini didukung juga dengan usability testing sebesar 80% dan didukung dengan pengujian black box yang dapat menguji kebutuhan fungsional aplikasi.
Rancang Bangun Alat Monitoring Suhu Dan Kelembaban Berbasis Internet Of Things (IOT) Pada Gudang Obat Rumah Sakit Aryoko Sorong: Rancang Bangun Alat Monitoring Suhu Dan Kelembaban Berbasis Internet Of Things (IOT) Pada Gudang Obat Rumah Sakit Aryoko Sorong Pandu Diaz Nugraha; Rendra Soekarta; Irman Amri
Framework : Jurnal Ilmu Komputer dan Informatika Vol 2 No 01 (2023): Framework : Jurnal ilmu komputer dan Informatika
Publisher : Universitas Muhammadiyah Sorong

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33506/jiki.v2i01.3044

Abstract

Proper temperature control and monitoring in hospital drug storage plays an important role in maintaining the quality and safety of stored drugs. In this research, we propose an Internet of Things (IoT) based temperature monitoring system using NodeMCU ESP8266 with DHT22 sensor. The purpose of this research is to monitor the temperature of the pharmacy in real time and provide access to temperature data through mobile devices with the Blynk platform. Testing is done by designing and implementing hardware including ESP8266 NodeMCU as a microcontroller and DHT22 temperature sensor as a thermometer. The ESP8266 Node MCU was programmed to periodically collect temperature data from the DHT22 sensor and send it to the Thingspeak cloud platform for storage. The Thingspeak platform was chosen due to its ability to provide data storage and graphing services for visual data observation. Therefore, this research presents a practical solution for temperature monitoring in the pharmacy of Aryoko Korem Hospital. The use of ESP8266 NodeMCU with DHT22 sensor and the integration of Thingspeak and Blynk improve monitoring efficiency and maintain the quality of stored drugs in a critical pharmacy environment.
Rancang Bangun Sistem Alat Pemilah Telur Ayam Siap Jual Menggunakan Microkontroller Arduino dan Firebase Berbasis Android Muhidin, Sakti Maulana; Rendra Soekarta; Teguh Hidayat Iskandar Alam; Nirwana Nurdjan
Framework : Jurnal Ilmu Komputer dan Informatika Vol 2 No 01 (2023): Framework : Jurnal ilmu komputer dan Informatika
Publisher : Universitas Muhammadiyah Sorong

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33506/jiki.v2i01.3046

Abstract

Pada saat ini pemilihan telur ayam yang dilakukan oleh penjual, untuk memilah telur ayam berdasarkan kualitasnya masih menggunakan metode manual. Pemilihan yang sering dilakukan oleh peternak dan penjual adalah dengan cara menerawang telur ayam dengan menggunakan sinar matahari atau lampu senter. Alat pendeteksi kualitas telur ayam dengan memanfaatkan mikrokontroller Arduino UNO sebagai pengolah data yang terbaca dari sensor LDR (Light Dependent Resistor) sejenis resistor yang resistensinya akan berubah seiring denagan perubahan intensitas cahaya yang mengenai telur ayam dimana sensor tersebut akan mengetahui kondisi telur ayam dari intensitas cahaya. telur ayam tersebut akan di hitung jumlahnya oleh sensor ir, servo sebagai penggerak pemilah antara telur ayam yang masuk ke dalam kategori telur dalam kondisi baik atau telur dalam kondisi buruk, jumlah dari telur ayam tersebut akan ditampilkan pada LCD (Liquid Crystal Display) dan aplikasi
Co-Authors Abdillah, Muhammad Insan Achmad Saiku Wadianto Achmad Saiku Wardianto Ackswan, M. Aditya Tri Yudha Pratama Ahmad Nur Aswad Ainun K.D.P, Nofryanti Akbar Akbar Akbar Fahroji Paus Paus Akbar ALFIANI PUTRI FITRIYAH RACHMAN Alfiyyah Faridah Aminuyati Amri, Irman Anak Agung Istri Sri Wiadnyani Anita Rahayu Anita Rahayu Aras, Suhardi Ardian Syah Arfan Amran Sulaiman Arief Firmansyah ARNOLDUS JANSSEN POKENIKA Arpandi, Arpandi Asno Azzawagama Firdaus Asran Parkor Basri, Nurul Annisa Bita Malissa Dewi Astri Faroeq Dewi Astria Faroek Elrico Eri Fridayanti Ermin Ermin Fakhri , La Jupriadi Fitrah Pasaribu, Andi Muhammad Fitriyani Tella Fitriyani Tella Fridayanti, Eri Habibi Habibi Habibi Habibi Hasanuddinn Hasanuddinn Hasanuddinn, Hasanuddinn Hasri Putri Wattiheluw Hasryana Suci Dwi Purwanto Rahasia sakka Hidayatulah, Muhamad Luqman Histiarini, Aprisa Rian Ilham S Jamaluddin kadaton, Muhammad sahid s Katmas, Maskia Kayatun, Siti Nur La Jupriadi Fakhri La Muhammad Faishal Nurullah Latuconsina, Siti Rahma M. Ackswan Malik, Nunung Manurung, Yolanda Iriana Mardiana Muh.Said Melin Manipi, - Mersi Modok Miftah Sigit Rahmawati Modok, Mersi Moh. Fatkur Riski Nur Yahya Riski Mohammad Arief Nur Wahyudien Muh. Fadli Hasa Muhamad Luqman Hidayatulah Muhammad Asrul Muhammad ismail Zulkaedi Muhammad Jundullah Muhammad Rezki Muhammad Rizki Setyawan Muhammad sahid s kadaton Muhammad Taufik Aziz Muhammad Yusuf Muhammad Yusuf MUHAMMAD YUSUF Muhidin, Sakti Maulana Mulyaddin Mulyaddin Mulyaddin, Mulyaddin Musdalipah . Nabila NABILLA RIZQI AMALIA NUR ASRI Ningtias, Arya Ayu Nirwana Nurdjan Novita Sari Nunung Malik Nurbaya Nurdjan, Nirwana Nurhalizah Lizah Nurul Widya Har Ode, Endang Stahputri Pandu Diaz Nugraha Putra, Fajar Rahardika Bahari Rafif Fauzan Ridwan Rahardika Bahari Putra, Fajar Rahman, Muh Fadhil Rahmawati, Miftah Sigit Rawi, Rais Dera Pua Retno Irianto, Dwi Reza Mochammad Said REZKI, REZKI Rinanda Tri Setiawan Rizki Setyawan, Muhammad Romdhana Dwi Fitriyani RoniHardika Roni SADRAK IMMANUEL SERARAWANI Said, Reza Mochammad Setiawan, Rinanda Tri Setyawan, Muhammad SIMON, RESKI Simori, Pascalina Magrice Sinon, Hermon Siti Mutmainah Siti Soleha Rahayu Muklis Hayu SRI WULANDARI Suhardi Aras Suharsono Suharsono Suharsono Suharsono Sulaiman, Arfan Amran Surahmanto Syahputra, Abdi Iman Talaohu, Syamsudin Aliphadji Teguh Hidayat Iskandar Alam Tella, Fitriyani tivani nurizqi Umasugi, Edwin Visman, Javan Wahyu Ramadhan Wardianto, Achmad Saiku Wattimena, Mikhael Yapari, Denny Zulkaedi, Muhammad ismail