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All Journal Jurnal Psikologi RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Jurnal Ilmiah Teknik (JUIT)
Mochammad Akbar Marwan
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Social Sciences

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ONLINE ADOLESCENT'S SELF-DISCLOSURE AS SOCIAL MEDIA USERS: THE ROLE OF EXTRAVERSION PERSONALITY, PERCEPTION OF PRIVACY RISK, CONVENIENCE OF RELATIONSHIP MAINTENANCE, AND SELF-PRESENTATION Rahardjo, Wahyu; Qomariyah, Nurul; Hermita, Matrissya; Suhatril, Ruddy J.; Marwan, Mochammad Akbar; Andriani, Inge
Jurnal Psikologi Vol 19, No 3 (2020): September 2020
Publisher : Faculty of Psychology, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jp.19.3.219-232

Abstract

Adolescences' excessive online self-disclosure is now a social phenomenon arising in social media use. The adolescences also tend to share their privacy. This study aims to determine whether extraversion personality, perceived privacy risks, the convenience of maintaining relationships, and online self-presentation influence self-disclosure in adolescents. This study involved 619 adolescents (185 male and 434 female) aged 13-22 years (M = 19.39, SD = 1.83). The participants are active social media users collected from several areas in Indonesia. Multiple regression analysis is used to test the hypothesis. The results show that several variables simultaneously affect online self-disclosure in adolescents (R2 = .422; F (4, 614) = 111.944, p < .01). However, in details, online self-presentation does not have a significant effect on online self-disclosure among adolescents. This result shows that personality factors and adolescent perceptions of the low privacy risk on social media, as well as the goal of maintaining social relations with other members of social media, encourage them to be more online disclose on social media.
PENERAPAN METODE RATIONAL UNIFIED PROCESS (RUP) DALAM PEMBUATAN WEB PEMBELAJARAN ELEKTRONIK UNTUK SEKOLAH MENENGAH PERTAMA Mochammad Akbar Marwan; Naeli Umniati; Ricky Agus Tjiptanata; Raihan Budiyarto
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 7 No 2 (2022): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v7i2.2457

Abstract

Metode Rational Unified Process (RUP) merupakan kerangka proses dalam pengembangan perangkat lunak yang dapat disesuaikan dengan tujuan organisasi pengembangan dan tim proyek perangkat lunak. Pembelajaran elektronik merupakan sistem pembelajaran berdasarkan pengajaran formal tetapi dengan bantuan sumber daya elektronik. Komponen utama dari pembelajaran elektronik adalah penggunaan komputer dan internet. Web pembelajaran elektronik untuk Sekolah Menengah Pertama (SMP) ini dibuat dengan menggunakan framework CodeIgniter. Web ini memiliki tiga otoritas pengguna yaitu administrator, pengajar, dan siswa. Pengujian web dengan metode blackbox testing berhasil dengan baik. Pengukuran kegunaan sistem (usability) dilakukan terhadap 24 responden pengguna web menggunakan kuesioner. Kuesioner dibuat berdasarkan kriteria yang terdapat pada USE Questionnaire dan penilaian berdasarkan skala Likert. Pengukuran usability menghasilkan nilai 89,08% yang artinya adalah sangat layak.
Implementation of Machine Learning for Freshwater Fish Detection Ivan Maurits; Priyo Sarjono Wibowo; Marwan, Mochammad Akbar
Jurnal Ilmiah Teknik Vol. 5 No. 1 (2026): Januari: Jurnal Ilmiah Teknik
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/juit.v5i1.1427

Abstract

Recent advancements in mobile technology and machine learning have enabled the development of practical tools, such as Android applications, to assist in real-time fish species identification, particularly in the context of freshwater fisheries in Indonesia. Objective: This research aims to design and implement an Android application that helps anglers accurately identify and categorize freshwater fish species native to Indonesia. The app integrates machine learning-based image recognition to provide a practical tool for fishing enthusiasts while supporting conservation efforts for Indonesia’s freshwater biodiversity. Methodology: A quantitative approach was employed, focusing on mobile application development using Kotlin for Android. The application uses a TensorFlow Lite-based image recognition model for real-time image processing on mobile devices. Data for the model were gathered from publicly available fish species datasets. The system was tested across multiple Android devices to evaluate compatibility and efficiency. Findings: The application successfully identifies and classifies various freshwater fish species in Indonesia, providing users with accurate species profiles, biological characteristics, and appropriate bait recommendations. The system operates efficiently in real-time on mobile devices without relying on cloud computing, ensuring accessibility in remote areas. Testing results across different Android devices confirm the app's robustness and user-friendly interface. Implications: This research demonstrates the integration of mobile technology and machine learning in fisheries, offering a valuable tool for both recreational and professional anglers. The app promotes awareness of freshwater fish species preservation and supports sustainable fishing practices. Additionally, it can serve educational purposes by enhancing knowledge of local biodiversity and fostering fish conservation efforts. Originality: This research introduces an innovative mobile-based solution to freshwater fish identification. Unlike previous studies, which focused on desktop-based methods, this study offers a practical mobile application that operates efficiently in real-time on-site. The originality lies in combining machine learning and mobile technology to address fish identification challenges while contributing to biodiversity conservation.
Co-Authors Inge Andriani Ivan Maurits Matrissya Hermita Naeli Umniati Nurul Qomariyah Priyo Sarjono Wibowo Raihan Budiyarto Ricky Agus Tjiptanata Suhatril, Ruddy J. Wahyu Rahardjo