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All Journal Jurnal Sains dan Teknologi Jurnal Sinergitas PkM & CSR FaST : Jurnal Sains dan Teknologi Journal of Computer, Electronic, and Telecommunication (COMPLETE) Prosiding Konferensi Nasional PKM-CSR
Junita Junita
Program Studi Teknik Elektro, Universitas Pelita Harapan
Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Nursing Public Health Social Sciences

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LOKAKARYA FUN LEARNING DENGAN FLOW, GRIT & GROWTH MINDSET [FUN LEARNING WORKSHOP WITH FLOW, GRIT & GROWTH MINDSET] Ihan Martoyo; Marincan Pardede; Julinda Pangaribuan; Mario Gracio A. Rhizma; Henri Putra Uranus; Junita Junita; Herman Kanalebe; Rocky T. Putra; Heri Yulian; Rianto Mangunsong; Rosmaya Nainggolan
Jurnal Sinergitas PKM & CSR Vol 3, No 1 (2018): October
Publisher : Universitas Pelita Harapan

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

Abstract

Three theories in educational psychology: (1) Flow (Mihaly Csikszentmihalyi), (2) Grit (Angela Duckworth), dan (3) Growth mindset (Carol Dweck) open the possibility for fun learning. Flow according to Csikszentmihalyi happens when the challenge in an activity is balanced with the necessary skill, so that one can experience flow during the activity. This feeling of flow is actually what makes learning fun. The concept of grit consists of two components: (1) perseverance and (2) passion for long term goals. Duckworth discovered that grit can predict success better than mere intellect (IQ). Growth mindset is a psychological state where one is not afraid to look stupid and therefore is more open to challenges because he/she focuses more on the learning process rather than momentary results. In the workshop in one private school in Tangerang, the three concepts were explained with concrete examples from movies and other illustrations. Furthermore, we did a demonstration in optical physics with simple equipments to simulate natural phenomena: A rainbow, the red evening sky, and laser deflection due to refractive index difference. Pre-test and post-test results after the fun learning workshop show that the concept of flow and grit is easier to comprehend by the teachers than growth mindset. After the workshop, there is an increase in the opinion that math and physic lessons can also be fun.
Lokakarya Fun Learning Bersama Sma Favorit Di Jakarta: Teori Grit Dan Growth Mindset Lebih Sulit Dari Flow Ihan Martoyo; Mario Gracio A. Rhizma; Rocky T. Putra; Rianto Mangunsong; Heri Yulian; Marincan Pardede; Junita Junita; Julinda Pangaribuan; Henri P. Uranus; Herman Kanalebe
Prosiding Konferensi Nasional Pengabdian Kepada Masyarakat dan Corporate Social Responsibility (PKM-CSR) Vol 2 (2019): Peran Perguruan Tinggi dan Dunia Usaha dalam Mempersiapkan Masyarakat Menghadapi Era I
Publisher : Asosiasi Sinergi Pengabdi dan Pemberdaya Indonesia (ASPPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (241.691 KB) | DOI: 10.37695/pkmcsr.v2i0.494

Abstract

Program Studi Teknik Elektro Universitas Pelita Harapan secara berkala melakukan lokakarya bersama berbagai sekolah untuk membagikan konsep fun learning, yang bertumpu pada 3 teori psikologi: teori flow, teori grit dan teori growth mindset. Walaupun proses pembelajaran modern sudah melibatkan banyak teknologi digital, kualitas pembelajaran itu sendiri diyakini lebih ditentukan oleh teori psikologi yang diterapkan daripada teknologi yang dipakai. Lokakarya kali ini dilakukan bersama guru-guru dari sebuah SMA favorit di Jakarta. Konsep fun learning yang dipresentasikan dilanjutkan dengan diskusi tentang kesulitan menerapkan konsep-konsep tersebut dalam aktivitas belajar yang sesungguhnya. Selain itu, dalam lokakarya juga dilakukan demonstrasi konsep-konsep fisika optik dengan laser dan kotak cahaya sederhana. Demonstrasi dengan peralatan sederhana ini diharapkan dapat dimanfaatkan untuk pembelajaran yang menyenangkan. Diskusi dengan para guru menunjukkan bahwa konsep grit dan growth mindset lebih sulit dipraktikkan dibandingkan konsep flow. Hasil pre-test dan post-test juga menunjukkan bahwa konsep flow lebih mudah ditangkap daripada teori grit dan growth mindset.
ANALISIS SISTEM PENDETEKSI TAHAPAN TIDUR [SLEEP STAGE DETECTION SYSTEM ANALYSIS] Junita Junita
FaST - Jurnal Sains dan Teknologi (Journal of Science and Technology) Vol 7, No 1 (2023): May
Publisher : Universitas Pelita Harapan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19166/jstfast.v7i1.6702

Abstract

 The COVID-19 pandemic has forced some parents to work at home while taking care of their children and taking care of household chores without the help of relatives, housemaids, or nurses. The demands of doing many jobs at once can result in parents, especially parents with babies, being careless in supervising their babies. One of the moments that make parents careless in supervising their babies is when parents suspect the baby is sleeping, because at that moment parents are usually busy doing other chores. With a system that can detect baby's sleep activity, especially detecting stage one, also called NREM (non-rapid eye movement) stage 1, where a person is almost awake, this risk can be minimized because parents can know when the baby is about to wake up and supervise before the baby is fully awake. This study analyzes the ability of two devices, namely, EEG (electroencephalogram) and a smart watch with a sleep tracker feature, as tools for detecting sleep activity of the research subject, specifically detecting stage 1 of the subject’s sleep cycle. In this study, CCTV was also used to find out when the subject was awake. The results of this study indicate that both tools can detect when the subject is awake. Between the two tools used, there was a higher match between CCTV (Closed Circuit Television) footage and the smart watch sleep cycle diagram. For the analysis of the transfer of stages before the subject awakens, the stage that most often becomes the stage before awakening is Light, which is 69.2% for detection with EEG and 76.1% for detection with smart watch. And what rarely happens is moving the sleep stages from Deep to waking up, which is 0% for detection with EEG and 2.3% for detection with smart watch.Bahasa Indonesia Abstract:Pandemi COVID-19 mengharuskan beberapa orang tua bekerja di rumah sambil menjaga anak dan mengurus pekerjaan rumah tangga tanpa bantuan sanak saudara, pembantu rumah tangga, ataupun suster. Tuntutan mengerjakan banyak pekerjaan sekaligus dapat mengakibatkan orang tua, khususnya orang tua dengan bayi, lengah dalam mengawasi bayinya. Salah satu momen yang membuat orang tua lengah dalam mengawasi bayinya adalah ketika orang tua menduga bayinya sedang tidur, karena di momen itu biasanya orang tua paling leluasa untuk mengerjakan pekerjaan yang lain. Dengan sistem yang dapat mendeteksi aktivitas tidur bayi, terutama mendeteksi tahap satu, yang disebut juga dengan NREM (non-rapid eye movement) stage 1, dimana seseorang sudah hampir bangun, risiko tersebut dapat diminimalkan karena orang tua dapat mengetahui ketika bayinya sudah akan terbangun dan mengawasi sebelum bayinya sepenuhnya bangun. Penelitian ini menganalisa kemampuan dua buah alat yaitu, EEG (electroencephalogram) dan smart watch dengan fitur sleep tracker, sebagai alat pendeteksi aktivitas tidur dari subjek penelitian, khususnya mendeteksi tahap 1 dari siklus tidur pada subjek penelitian. Pada penelitian ini digunakan juga CCTV (Closed Circuit Television) untuk mengetahui kapan subjek penelitian sepenuhnya bangun. Hasil dari penelitian ini menunjukkan kedua alat dapat mendeteksi saat subjek terbangun. Di antara kedua alat yang dipakai, didapatkan kesesuaian yang lebih tinggi antara rekaman CCTV dan diagram siklus tidur smart watch. Untuk analisa perpindahan tahapan sebelum subjek penelitian terbangun, tahapan yang paling sering menjadi tahapan sebelum terbangun adalah Light yaitu sebanyak 69,2% untuk pendeteksian dengan EEG dan 76,1% untuk pendeteksian dengan smart watch. Dan yang paling jarang terjadi adalah perindahan tahapan tidur dari Deep kemudian terbangun, yaitu 0% untuk pendeteksian dengan EEG dan 2,3% untuk pendeteksian dengan smart watch.
ANALISIS SISTEM PENDETEKSI TAHAPAN TIDUR [SLEEP STAGE DETECTION SYSTEM ANALYSIS] Junita Junita
FaST : Jurnal Sains dan Teknologi Vol. 7 No. 1 (2023): MAY
Publisher : Universitas Pelita Harapan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19166/jstfast.v7i1.6702

Abstract

 The COVID-19 pandemic has forced some parents to work at home while taking care of their children and taking care of household chores without the help of relatives, housemaids, or nurses. The demands of doing many jobs at once can result in parents, especially parents with babies, being careless in supervising their babies. One of the moments that make parents careless in supervising their babies is when parents suspect the baby is sleeping, because at that moment parents are usually busy doing other chores. With a system that can detect baby's sleep activity, especially detecting stage one, also called NREM (non-rapid eye movement) stage 1, where a person is almost awake, this risk can be minimized because parents can know when the baby is about to wake up and supervise before the baby is fully awake. This study analyzes the ability of two devices, namely, EEG (electroencephalogram) and a smart watch with a sleep tracker feature, as tools for detecting sleep activity of the research subject, specifically detecting stage 1 of the subject’s sleep cycle. In this study, CCTV was also used to find out when the subject was awake. The results of this study indicate that both tools can detect when the subject is awake. Between the two tools used, there was a higher match between CCTV (Closed Circuit Television) footage and the smart watch sleep cycle diagram. For the analysis of the transfer of stages before the subject awakens, the stage that most often becomes the stage before awakening is Light, which is 69.2% for detection with EEG and 76.1% for detection with smart watch. And what rarely happens is moving the sleep stages from Deep to waking up, which is 0% for detection with EEG and 2.3% for detection with smart watch.Bahasa Indonesia Abstract:Pandemi COVID-19 mengharuskan beberapa orang tua bekerja di rumah sambil menjaga anak dan mengurus pekerjaan rumah tangga tanpa bantuan sanak saudara, pembantu rumah tangga, ataupun suster. Tuntutan mengerjakan banyak pekerjaan sekaligus dapat mengakibatkan orang tua, khususnya orang tua dengan bayi, lengah dalam mengawasi bayinya. Salah satu momen yang membuat orang tua lengah dalam mengawasi bayinya adalah ketika orang tua menduga bayinya sedang tidur, karena di momen itu biasanya orang tua paling leluasa untuk mengerjakan pekerjaan yang lain. Dengan sistem yang dapat mendeteksi aktivitas tidur bayi, terutama mendeteksi tahap satu, yang disebut juga dengan NREM (non-rapid eye movement) stage 1, dimana seseorang sudah hampir bangun, risiko tersebut dapat diminimalkan karena orang tua dapat mengetahui ketika bayinya sudah akan terbangun dan mengawasi sebelum bayinya sepenuhnya bangun. Penelitian ini menganalisa kemampuan dua buah alat yaitu, EEG (electroencephalogram) dan smart watch dengan fitur sleep tracker, sebagai alat pendeteksi aktivitas tidur dari subjek penelitian, khususnya mendeteksi tahap 1 dari siklus tidur pada subjek penelitian. Pada penelitian ini digunakan juga CCTV (Closed Circuit Television) untuk mengetahui kapan subjek penelitian sepenuhnya bangun. Hasil dari penelitian ini menunjukkan kedua alat dapat mendeteksi saat subjek terbangun. Di antara kedua alat yang dipakai, didapatkan kesesuaian yang lebih tinggi antara rekaman CCTV dan diagram siklus tidur smart watch. Untuk analisa perpindahan tahapan sebelum subjek penelitian terbangun, tahapan yang paling sering menjadi tahapan sebelum terbangun adalah Light yaitu sebanyak 69,2% untuk pendeteksian dengan EEG dan 76,1% untuk pendeteksian dengan smart watch. Dan yang paling jarang terjadi adalah perindahan tahapan tidur dari Deep kemudian terbangun, yaitu 0% untuk pendeteksian dengan EEG dan 2,3% untuk pendeteksian dengan smart watch.
SISTEM INFORMASI DASHBOARD MONITORING C/N PADA PRODUK SCPC DI PT. PI [DASHBOARD INFORMATION SYSTEM FOR C/N MONITORING ON SCPC PRODUCTS AT PT. PI] Chuan Pratama; Junita Junita
FaST : Jurnal Sains dan Teknologi Vol. 8 No. 2 (2024): NOVEMBER
Publisher : Universitas Pelita Harapan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19166/jstfast.v8i2.9006

Abstract

SCPC (Signal Carrier Per Carrier) is a priority VSAT service that requires continuous frequency signal monitoring to ensure network stability. Currently, this monitoring is performed using a web-based decimator device. However, the monitoring data still requires manual processing to create reports and analyses, which is inefficient and time-consuming. This study developed a web-based dashboard monitoring system that automates the processing of C/N (Carrier to Noise) data for SCPC products at PT. PI. The system was tested using a task scheduler for 14 hours with 30-minute intervals, recording a longest processing time of 16.665 seconds with 11,812 data points, 60.6% RAM usage, and 36.9% CPU usage, and a shortest processing time of 4.026 seconds with 3,546 data points, 53.9% RAM usage, and 39.7% CPU usage. The proposed web application successfully displays historical graphs, total remote counts, databases, top 10 under C/N, tables, and reports, as initially designed. The average dashboard loading time to complete data display is approximately 9.894 seconds. This system is expected to improve the efficiency of SCPC monitoring and provide faster, more accurate reporting.Bahasa Indonesia Abstract:SCPC (Signal Carrier Per Carrier) adalah layanan VSAT prioritas yang memerlukan monitoring sinyal frekuensi secara terus-menerus untuk memastikan kestabilan jaringan. Saat ini, monitoring dilakukan melalui perangkat decimator berbasis web; namun, pengolahan data monitoring menjadi laporan dan analisis masih harus dilakukan secara manual, yang tidak efisien dan memakan waktu. Penelitian ini mengembangkan sistem dashboard monitoring berbasis web yang mampu mengotomatisasi pengolahan data C/N (Carrier to Noise) pada produk SCPC di PT. PI. Sistem ini diuji menggunakan task scheduler selama 14 jam dengan interval 30 menit, di mana waktu proses terlama tercatat 16,665 detik dengan 11.812 data, penggunaan RAM 60,6%, dan CPU 36,9%; sementara waktu tercepat adalah 4,026 detik dengan 3.546 data, penggunaan RAM 53,9%, dan CPU 39,7%. Aplikasi web berhasil menampilkan grafik historis, total remote, basis data, top 10 di bawah C/N, tabel, dan laporan sesuai desain awal. Waktu rata-rata yang dibutuhkan dashboard untuk memuat data hingga selesai adalah sekitar 9,894 detik. Pengembangan sistem ini diharapkan dapat meningkatkan efisiensi monitoring SCPC dan memberikan laporan yang lebih cepat dan akurat.
Rancang Bangun Aplikasi Urun Dana Berbasis Website Untuk Membeli Dan Membagikan Hasil Panen Petani Kepada Masyarakat Pra-Sejahtera M. Rikza As-subhy; Junita Junita; Marincan Pardede
FaST - Jurnal Sains dan Teknologi (Journal of Science and Technology) Vol. 10 No. 1 (2026): MAY
Publisher : Universitas Pelita Harapan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19166/fastjst.v10i1.11083

Abstract

The Indonesian agricultural sector faces structural problems such as low selling prices, instability in the income of small-scale farmers, waste of harvests, and food insecurity among underprivileged communities. This study developed Bagipanen, a web- and Android-based crowdfunding application that integrates a socialfunding model with a mechanism for selling harvests on consignment. The system is designed to connect farmers as commodity providers, donors as funding supporters, and underprivileged communities as beneficiaries. Technically, the application is built using Laravel for the web platform and Flutter for the mobile platform, and is integrated with the Midtrans payment gateway. The research methodology focuses on software engineering with the application of testing through 25 test scenarios covering unit, integration, end-to-end (E2E) testing using Laravel Dusk, performance, and security, with a success rate of 100%. E2E testing results showed an average execution time of 5.35 seconds per scenario, while payment integration testing showed a failure rate of 0%, an average response time of 320 ms, and successful handling of idempotent callbacks. Performance testing recorded a throughput of 33.96 requests/second with a maximum response time of 850 ms at peak load. Software quality analysis showed 87.8% test coverage, 2.3% code duplication, and no critical security vulnerabilities were found.
Wi-Fi Enabled Remote Control Surveillance Vehicle: Design, Implementation, and Performance Analysis Junita Junita; Nicholas Kevin Setiadi
Journal of Computer Electronic and Telecommunication Vol. 6 No. 1 (2025): July
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52435/complete.v6i1.690

Abstract

The rapid advancement of wireless technology has expanded the possibilities for remote-controlled systems, particularly in surveillance and safety applications. This study aims to develop a 4G-enabled remote surveillance vehicle using a Raspberry Pi 4 Model B microprocessor to achieve long-range control and real-time visual feedback. The vehicle integrates a Raspberry Pi 4 with two Electronic Speed Controllers (ESCs) connected to three gearbox motors for movement, along with an OV5647 camera module mounted on a 2-axis gimbal controlled by MG90S servos. The system is programmed in JavaScript using Node.js and Visual Studio Code, enabling a webserver for bidirectional communication between the vehicle and the controller. Key tests demonstrated a maximum operational range of 1.11 km, with the potential for further distance as connectivity permits. The vehicle exhibited an average battery life of 46 minutes and a latency of approximately 49 ms under stable 4G conditions. Additionally, it successfully traversed diverse terrains, including gravel and sand. The findings highlight the vehicle's capability for remote surveillance in hazardous or inaccessible environments, reducing human risk. Future enhancements could include integrating additional sensors for broader applications. This research underscores the feasibility of using cost-effective, off-the-shelf components to build a robust, long-range surveillance system
Optimalisasi Pengendalian Pompa Air Sisa Produksi Berbasis PLC dengan Sensor Floatless Level Switch dan Sensor Redundansi untuk Pencegahan Luapan Air Tangki Industri Abdul Rohman Hakim; Junita; Herman Kanabele
JST (Jurnal Sains dan Teknologi) Vol. 14 No. 3 (2025): October
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jst-undiksha.v14i3.99283

Abstract

Kinerja sistem kontrol pompa otomatis pada tangki penampungan air sisa produksi di area mesin pembuatan dinding ban mengalami penurunan efisiensi akibat kerusakan komponen dan keterbatasan mekanisme berbasis timer. Sistem lama tidak mampu merespons fluktuasi aliran air secara real-time, sehingga sering terjadi luapan tangki dan gangguan operasional. Penelitian ini bertujuan untuk menganalisis panel kontrol berbasis Programmable Logic Controller (PLC) yang terintegrasi dengan sensor floatless level switch dan sensor redundansi untuk mendeteksi level air secara presisi. Sistem dirancang dengan konfigurasi dual pump untuk memastikan keandalan operasi, penataan panel yang lebih rapi, serta fault alarm yang terhubung ke HMI utama. Penelitian menggunakan metode research and development dengan implementasi langsung pada tangki industri, disertai pengujian kinerja melalui simulasi dan pengukuran waktu siklus kerja pompa. Hasil implementasi menunjukkan penurunan signifikan insiden luapan tangki, efisiensi operasional meningkat dengan rata-rata waktu aktif pompa 2,52 menit dan waktu jeda 8,43 menit dan tidak adanya problem terkait air melebihi kapasitas tangki ataupun kerusakan pada sistem pompa yang tidak terdeteksi. Sistem baru terbukti lebih andal, efisien, dan mudah dipelihara dibanding sistem lama. Temuan ini berimplikasi pada peningkatan manajemen air industri sekaligus memperpanjang umur pakai pompa dan mengurangi risiko kerusakan lingkungan.
Co-Authors Abdul Rohman Hakim Chuan Pratama Henri P. Uranus Heri Yulian Heri Yulian Herman Kanabele Herman Kanalebe Herman Kanalebe Julinda Pangaribuan M. Rikza As-subhy Marincan Pardede Mario Gracio A. Rhizma Mario Gracio A. Rhizma Martoyo, Ihan Nicholas Kevin Setiadi Rianto Mangunsong Rianto Mangunsong Rocky T. Putra Rocky T. Putra Rosmaya Nainggolan