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All Journal Jurnal Ilmiah Flash JurTI (JURNAL TEKNOLOGI INFORMASI) The IJICS (International Journal of Informatics and Computer Science) JATI (Jurnal Mahasiswa Teknik Informatika) Journal of Applied Data Sciences Jurnal Manajemen Informatika Jayakarta HOAQ (High Education of Organization Archive Quality) : Jurnal Teknologi Informasi Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal Manajemen Informatika & Teknologi Journal of Novel Engineering Science and Technology Infact: Jurnal Sains dan Komputer JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Edwin Ariesto Umbu Malahina
STIKOM Uyelindo Kupang
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Environmental Science Materials Science & Nanotechnology Mechanical Engineering

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KONSEP DAN RANCANGAN LAYANAN ALTERNATIF BERBAGI MODUL PENGAJARAN DAN PEMBELAJARAN DIGITAL KAMPUS Edwin Ariesto Umbu Malahina; S Sumarlin
Jurnal Ilmiah Flash Vol 6 No 2 (2020)
Publisher : P3M- Politeknik Negeri Kupang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32511/flash.v6i2.713

Abstract

Penelitian ini merupakan penalaran konsep dalam bentuk rancanga design system untuk berbagi modul pengajaran, dimana konsep ini, akan membutuhkan kerjasama dan persetujuan Mitra Kampus dalam berkolaborasi dan berpartisipasi dalam menyusun serta melampirkan cetakan digital file modul digital kedalam system yang akan dikembangkan nantinya. Model system ini menerapkan model waterfall, karena model ini memiliki tahap yang jelas dan sesuai dengan keinginan system yang dikembangkan kedepannya, proses yang dimiliki model ini adalah; analysis, design, implementation, testing, deployment dan maintenance. Pengembangan system berbagi modul ini dapat dijalankan pada aplikasi mobile Android dan web browser baik untuk admin dan client (Mitra Kampus). Konsep ini, diharapkan agar mendorong dan memberikan dampak baik bagi dunia kampus dalam menerapkan system sharing dan update knowledge, sehingga keilmuan, pembelajaran dan kompetensi keahlian setiap tenaga pengajar dapat selalu beradaptasi dengan terapan ilmu dari berbagai kampus-kampus lainnya sehingga tidak ketertinggalan dalam belajar hal-hal baru, serta ilmu yang didapatkan dari kampus-kampus yang bereputasi baik dengan tenaga pengajar yang berkopetansi serta ahli dibidangnya, akan menambah wawasan lebih luas dengan penerapan haring dan update knowledge
Analisa Kebutuhan Pengembangan Model System Barter Di Era Pandemik Covid-19 Berbasis Website Edwin Ariesto Umbu Malahina; Agustina Clarissa Huko Langoday
(JurTI) Jurnal Teknologi Informasi Vol 5, No 1 (2021): JUNI 2021
Publisher : Universitas Asahan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36294/jurti.v5i1.2043

Abstract

Abstract - Barter is an exchange of needs in the form of goods to meet the necessities of life without relying on the financial side first. During the Covid-19 pandemic, many people experienced economic pressure from various problem factors, where people still have to make ends meet during the pendemic period. The purpose of this study is to be able to collect information data whether this system can help meet the needs of the community or not by using the Systems Development Life Cycle (SDLC) system development model as well as quantitative and qualitative approaches by collecting information and distributing questionnaires using the Likert scale method. The barter system that will be developed is website-based, where previously going through the process of analysis and system design first. From the results of the questionnaire calculations obtained, it was found that about an average of 85.93% of the public strongly agreed that this barter system could be developed.Keywords  - barter system, covid-19, Likert scale, Systems Development Life Cycle (SDLC), website. Abstrak – Barter merupakan pertukaran kebutuhan dalam dalam bentuk barang untuk memenuhi kebutuhan hidup tanpa mengandalkan sisi keuangan terlebih dahulu. Dimasa pandemic covid-19 banyak masyarakat mengalami himpitan ekonomi dari berbagai faktor masalah, dimana masyarakat tetap harus memenuhi kebutuhan hidup selama masa pendemik berlangsung.  Tujuan penelitian ini adalah dapat mengumpulkan data informasi apakah system ini dapat membantu dalam memenuhi kebutuhan masyarakat atau tidak dengan menggunakan model pengembangan sistem Systems Development Life Cycle (SDLC) serta pendekatan kuantitatif dan kualitatif yang melalui pengumpulan informasi dan penyebaran kuesioner dengan menggunakan metode skala likert. System barter yang akan dikembangkan adalah berbasis website, dimana sebelumnya akan melalui proses Analisa dan perancangan system terlebih dahulu. Dari hasil kalkulasi kuesioner yang didapatkan, diperoleh bahwa sekitar rata-rata 85,93% masyarakat sangat setuju system barter ini dapat dikembangkan.Kata Kunci - system barter, covid-19, skala likert, Systems Development Life Cycle (SDLC), website.
Aplikasi Monitoring Orang Tua Terhadap Siswa Berbasis Web Pada SMA Negeri 10 Kupang Ayub Djara Lulu; Edwin Ariesto Umbu Malahina; Semlinda Juszandri Bulan
(JurTI) Jurnal Teknologi Informasi Vol 6, No 1 (2022): JUNI 2022
Publisher : Universitas Asahan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36294/jurti.v6i1.2591

Abstract

At this time the development of technology is increasingly advanced, which through the web one can get useful information easily. Therefore, the web can be used by the world of education as a means of information for the community. This is never separated from the name of technological developments that are able to design a system, so that the world of education has increased information technology in the world of education to help improve student learning achievement by using web monitoring. Where it makes it easier to monitor students in various school activities and activities. The large number of students takes a long time in data processing because they still use a manual system so that the information process provided cannot run properly because the assessment of learning outcomes at the school can only be known by parents at the time of receiving report cards. The purpose of this study is to implement a web-based parental monitoring application for students so that the school can use the application to record student activities in the learning process and other activities as well as send information to parents so that they can monitor any information on student attendance history, student grade history, student behavior, report cards, tuition and extracurricular payments. The method used is the Waterfall method or the waterfall method is often called the classical life cycle, where it describes a systematic and sequential approach to software development, in sequence starting from analysis, design, testing coding, and testing. support stage. The expected result of this study is to make it easier for parents to get information and monitor student attendance history, student grade history, student behavior, report cards, tuition and extracurricular payments, with this monitoring the student's learning process can be monitored by parents so that it is more directed. Pada saat ini perkembangan teknologi semakin maju, yang mana melalui web seseorang bisa mendapatkan informasi yang berguna dengan mudah. Oleh karena itu web dapat dimanfaatkan oleh dunia pendidikan sebagai sarana informasi bagi masyarakat. Hal ini tidak pernah lepas dari dengan namanya perkembangan teknologi yang mampu mendesain suatu sistem, sehingga dunia Pendidikan mengalami peningkatan teknologi informasi di dunia pendidikan untuk membantu meningkatkan prestasi belajar siswa dengan menggunakan web monitoring. Dimana memudahkan memonitoring peserta didik dalam berbagai aktivitas dan kegiatan sekolah. Banyaknya jumlah siswa membutuhkan waktu yang cukup lama dalam pengolahan data karena masih menggunakan sistem manual sehingga proses informasi yang diberikan tridak dapat berjalan dengan baik karena penilaian hasil belajar di sekolah tersebut hanya dapat diketahui oleh orang tua pada saat penerimaaan raport. Tujuan penelitian ini adalah aplikasi monitoring orang tua terhadap siswa besbasis web agar pihak sekolah dapat menggunakan aplikasi tersebut untuk mendata kegiatan siswa dalam proses belajar dan kegiatan lainnya sekaligus mengirimkan informasi kepada orang tua agar dapat memonitoring dari setiap informasi riwayat kehadiran siswa, riwayat nilai siswa, perilaku siswa, nilai raport, pembayaran uang sekolah dan ekstrakurikuler. Metode   yang digunakan adalah metode Waterfall metode atau metode air terjun sering dinamakan siklus hidup klasik (classic life cycle), dimana hal ini menggambarkan pendekatan yang sistematis dan juga berurutan pada pengembangan perangkat lunak, secara urutan dimulai dari analisis, desain, pengkodean pengujian, dan tahap pendukung. Hasil yang diharapkan dari penelitian ini adalah mempermudah orang tua siswa mendapatkan informasi dan memonitoring riwayat kehadiran siswa, riwayat nilai siswa, perilaku siswa, nilai raport, pembayaran uang sekolah dan ekstrakurikuler, dengan ada monitoring tersebut proses belajarnya siswa dapat dipantau oleh orang tua siswa  sehingga  lebih terarah.
Simulasi Pengukuran Kadar Air, Ph Tanah, Kelembaban Dan Suhu Udara Menggunakan Mikrokontroler (Arduino-Uno R3) Melania Zemil; Yampi R. Kaesmetan; Edwin A. U. Malahina
(JurTI) Jurnal Teknologi Informasi Vol 6, No 2 (2022): DESEMBER 2022
Publisher : Universitas Asahan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36294/jurti.v6i2.2618

Abstract

Pada kantor Instalasi Penelitian dan Pengembangan Teknologi Pertanian (IPPTP)  Naibonat memiliki sebuah masalah yaitu sulit dalam mengetahui kesuburan tanah ini dikarenakan hanya memiliki 12 orang petugas lapangan yang mengontrol lahan tanam yang luas. Berdasarkan masalah yang ada maka dibuatlah sebuah alat dimana alat ini dapat membantu petugas lapangan dalam mengetahui apakah lahan yang akan ditanami subur atau tidak dengan memperhatikan faktor-faktor yang mempengaruhi kesuburn tanah yaitu kelembaban tanah, suhu dan kelembaban udara, serta pH tanah. Rangcangan alat yang akan dibuat ini menggunakan capacitive soil moisture sensor v1.2 sebagai sensor yang berfungsi mengukur kelembaban tanah, sensor pH tanah yang digunakan untuk mengukur tingkat acid (keasaman) dan alkali (kebasaan) tanah,sensor DHT11 untuk mengukur suhu dan kelembaban udara. Dengan di buatnya alat ini diharapkan dapat membantu petugas lapangan di Instalasi Penelitian dan Pengkajian Teknologi Pertanian (IPPTP) Naibonat dalam menngontrol kesuburan tanah pada lahan tanam.
Teachable Machine: Real-Time Attendance of Students Based on Open Source System Edwin Ariesto Umbu Malahina; Ryan Peterzon Hadjon; Franki Yusuf Bisilisin
The IJICS (International Journal of Informatics and Computer Science) Vol 6, No 3 (2022): November 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/ijics.v6i3.4928

Abstract

The utilization of open source-based services will be very useful, simplifying and accelerating the process of object recognition and complex computational processes, one of them uses the Teachable Machine service. Identification of student faces in real-time attendance is a case study that will be applied to students to recognize and identify accurately and clearly the presence of students during online / offline lectures, by applying Teachable Machine services that have good algorithms with a machine learning approach that utilizes the Tensorflow.js library where the training data testing uses Convolutional Neural Network (CNN). Of the objects identified, the average accuracy of all classes ranged from 91-100%, with the number of samples for each object class being 23 objects or more. Number of sample images in one class. Clothing, object background and lighting intensity around the image object are also very influential in determining the accuracy value of student face recognition later, so that the use of the tensorflow.js library that implements Convolutional Neural Network (CNN) will be very helpful in facial recognition and influencing factors so that the data entered later needs to be further corrected and improved again, so that the results obtained in implementing the online attendance system have been very helpful in detecting student faces with an average accuracy rate of 91.8%
Teachable Machine: Deteksi Dialek Sumba Timur (Kambera) Menggunakan Layanan Open Source Edwin Ariesto Umbu Malahina
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 4: November 2023
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v12i4.8174

Abstract

This research seeks to develop a phonetic detection system for the Kambera dialect, the East Sumba local language, based on the TensorFlow framework that will be implemented in mobile applications. As part of this initiative, this research compiled a representative dataset of Kambera dialect phonetic samples. The main objective is to improve precision in phonetic recognition. Using the Kambera dialect as a case study, the data were extracted and trained using the open-source Teachable Machine service. This research adopted a convolutional neural network (CNN)-based approach combined with the Mel-frequency cepstral coefficients (MFCC) method for more accurate feature extraction. After data collection, model training, testing, and implementation, the model was integrated into the Android platform to benefit the public who wished to understand the Kambera dialect of East Sumba. The development and testing of this system were designed to detect and interpret the phonetics of the local language of East Sumba with the Kambera dialect, making a significant contribution to optimizing phonetic recognition and providing a dataset for ongoing research interests. It also serves as an accessible linguistics educational tool and supports linguistic inclusion and diversification in digital technology. Empirical evaluation showed that the overall average dialect detection precision rate reached 98.3% to 99.6%, with the user satisfaction rate reaching 99.33%. These results confirm that the developed system has a very efficient and good detection capability.
Teachable Machine: Optimization of Herbal Plant Image Classification Based on Epoch Value, Batch Size and Learning Rate Malahina, Edwin Ariesto Umbu; Saitakela, Mardhalia; Bulan, Semlinda Juszandri; Lamabelawa, Marinus Ignasius Jawawuan; Belutowe, Yohanes Suban
Journal of Applied Data Sciences Vol 5, No 2: MAY 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i2.206

Abstract

Herbal plants are a source of natural materials used in alternative medicine and traditional therapies to maintain health. The purpose of this research is to develop an intelligent system application that is able to assist people in independently detecting herbal plants around them, provide education, and most importantly, find the optimal value based on certain parameters. This research uses several values for the parameters studied, namely the epoch value which varies between 10, 50, 100, 250, 750, and 1000; the batch size value which varies between 16, 32, 64, 128, 256, and 512; and the learning rate value which varies between 0.00001, 0.0001, 0.001, 0.01, 0.1, and 1. A total of 10,000 training data samples (1,000 samples in 10 classes) were used in Teachable Machine. The method used is to utilize the TensorFlow framework in the Teachable Machine service to train image data. This framework provides Convolutional Neural Networks (CNN) algorithms that can perform image classification with a high degree of accuracy. The test results for more than three months showed that the highest optimal value was achieved at the 50th epoch value, with a learning rate of 0.00001, and a batch size of 32, which resulted in an accuracy rate between 98% and 100%. Based on these results, a mobile web-based intelligent system application service was developed using the TensorFlow framework in Teachable Machine. This application is expected to be widely implemented for the benefit of the community. However, the challenges and limitations in training this test data are the large number of data classes that will be very good so that machine learning can learn to recognize objects but will take hours to train, then the training image object data has a clean background from other objects so that when tested it is not detected and influenced as another object or can result in a decrease in the percentage value.
A Grid-search Method Approach for Hyperparameter Evaluation and Optimization on Teachable Machine Accuracy: A Case Study of Sample Size Variation Malahina, Edwin Ariesto Umbu; Iriane, Gregorius Rinduh; Belutowe, Yohanes Suban; Katemba, Petrus; Asmara, Jimi
Journal of Applied Data Sciences Vol 5, No 3: SEPTEMBER 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i3.290

Abstract

This study aims to evaluate the effectiveness of the grid-search method in hyperparameter optimization on Teachable Machine (TM) using a varying number of image samples. The hyperparameters studied include epoch (e), batch size (b), and learning rate (l). A structured grid-search method approach will be applied to test 216 hyperparameter combinations across 6 categories of sample size per class, namely 10, 25, 50, 100, 250, and 500. The results showed that the optimal combination findings were obtained based on variations in the number of samples as follows: 10 samples using e:100, b:256, l:0.001 get an accuracy range of ≥ 90%; for 25 samples using e:500, b:16, l:0.001 get an accuracy range ≥ 97%; for 50 samples using e:100, b:512, l:0.001 get an accuracy range ≥ 88%; for 100 samples using e:500, b:32, l:0.001 get an accuracy range ≥ 88%; for 250 samples using e:50, b:16, l:0.001 get an accuracy range ≥ 92%, and finally 500 samples using e:500, b:256, l:0.001 get an accuracy range ≥ 96% and on average are able to achieve 100% accuracy from the detection test results of the best value performed for each sample variation of the image object. This research provides significant contributions or benefits in finding the optimal hyperparameter configuration, minimizing overfitting, and shortening the search time for TM accuracy in image classification, particularly in human face recognition. The findings support the development of more efficient and accurate TMs and provide practical guidance for finding better hyperparameter optimization using the grid-search method approach. The results of this study have implications for improving the effectiveness and accuracy of TM models and their development in mobile web applications
Media Pembelajaran Kampung Raja Prailiu Kabupaten Sumba Timur Berbasis Augmented Reality Duka, Alsha Day; Malahina, Edwin Ariesto Umbu
Jurnal Manajamen Informatika Jayakarta Vol 5 No 1 (2025): JMI Jayakarta (Februari 2025)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jmijayakarta.v5i1.1783

Abstract

The rapid development of digital technology has a significant impact in various fields, including cultural preservation. Augmented Reality (AR) is a technology that combines two-dimensional or three-dimensional virtual objects into the real world and then projects them in real time, making learning about culture more interactive and interesting. Effect House is a platform that allows the development of interactive AR effects, including Head tracking features, which can be integrated with social media such as TikTok. Therefore, the purpose of this research is to develop AR-based interactive learning media with Head tracking quiz features as a solution in learning and preserving the culture of Kampung Raja Prailiu in East Sumba Regency. This village has cultural wealth such as traditions, traditional houses, ikat weaving, and typical traditional rituals that must be introduced, preserved and passed on to the younger generation. Through the Head tracking quiz features, users can learn about the culture of Raja Prailiu Village by moving their head to select answers in an interactive quiz. At the end of the quiz, users will get a total score as an evaluation of their understanding of the culture of Kampung Raja Prailiu. With this research, the learning proces become more interesting and interactive.
AUGMENTED REALITY BERBASIS PELACAKAN OBJEK PEMBELAJARAN MOTIF DAN MAKNA KAIN TENUN ATAMBUA Pereira, Yubita Dasilva; Malahina, Edwin Ariesto Umbu
Jurnal Manajamen Informatika Jayakarta Vol 5 No 1 (2025): JMI Jayakarta (Februari 2025)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jmijayakarta.v5i1.1789

Abstract

This study, titled "Object Tracking Based on Augmented Reality in Interactive Learning for the Recognition of Motifs and Philosophy of Atambua Woven Fabrics," aims to develop an Augmented Reality (AR)-based application capable of tracking objects on woven fabrics and providing interactive information about the motifs and their underlying philosophy. By leveraging AR technology, this application is expected to enhance public understanding, particularly among younger generations, of the cultural values embedded in the woven fabrics of East Nusa Tenggara, specifically in Belu Regency. The research was conducted at the Atambua Weaving Gallery using the Waterfall software development method. The expected outcome of this study is the creation of an interactive tool that can support cultural heritage preservation while increasing the gallery’s appeal to visitors. Thus, this research has the potential to make a significant contribution to cultural preservation efforts and the development of interactive education in Indonesia.
Co-Authors Abdul Syawal Laan, Muhammad Adi Jufriansah Agustina Clarissa Huko Langoday Aulia Safirah, Nindy Ayub Djara Lulu Azmi Khusnani Duka, Alsha Day Franki Yusuf Bisilisin Jimi, Asmara Kaesmetan, Yampi R Mardhalia Saitakela Melania Zemil Menhya Snae Muhammad Agus Muljanto Muhammad Syahrul Ramadhan A.S. Dapubeang Natzir, Sadam Muhammad Pereira, Yubita Dasilva Petrus Katemba Rudi Hariyanto Ryan Peterzon Hadjon S Sumarlin S Sumarlin Sadam Muhammad Natzir Salsa Sukma Semlinda Juszandri Bulan Yohanes Suban Belutowe Yudhiakto Pramudya Zampi, Aprilia Ch