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Rancang Bangun Sistem Smart Parking Berbasis Mobile Menggunakan Mikrokontroler Esp32 Saputra, Ardi; Zahfira, Dayanah; Sidabutar, Honey Christine; Irviantina, Syanti; Halim, Apriyanto
Majalah Ilmiah METHODA Vol. 14 No. 3 (2024): Majalah Ilmiah METHODA
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/methoda.Vol14No3.pp306-317

Abstract

Most universities manage parking for students and lecturers such as motorcycles and cars. But currently, there are many universities that still use manual methods, Mikroskil University is one of the private universities in Medan City which also still uses manual methods by checking the Vehicle Number Certificate by Mikroskil security officers. This inspection can result in a long queue at the exit of the parking area. In addition, students also have difficulty finding available parking spots in the parking area because there is no system that provides directions to see the availability of parking spots. Therefore, in this study a Smart Parking system was built using the application of the Internet of Things (IoT) system by creating a portal with a QR code scanner and adding a light sensor in each parking spot. The sensor testing results show that the light sensor is able to display the results according to the condition of the vehicle and then send the parking spot data to the application server, then based on the black box software testing, it is concluded that the software functionally runs well and produces results as expected. User testing conducted by students also shows the results as expected.
Analisis Dan Perancangan Sistem Informasi Penilaian Kinerja Dosen Universitas Mikroskil Berbasis Web Jordan, Alvito; Jeslim, Jeslim; Manurung, Stieven B.L.; Irviantina, Syanti; Pipin, Sio Jurnalis
Jurnal Sifo Mikroskil Vol. 25 No. 2 (2024): JSM VOLUME 25 NOMOR 2 TAHUN 2024
Publisher : Fakultas Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55601/jsm.v25i2.1351

Abstract

Sistem Penilaian Kinerja Dosen digunakan untuk mengevaluasi kinerja dosen dalam melaksanakan Tridharma Perguruan Tinggi guna meningkatkan kualitas dosen, dan mutu perguruan tinggi. Saat ini, proses penilaian kinerja dosen di Universitas Mikroskil masih menggunakan Microsoft Excel, sehingga rentan terhadap kesalahan perhitungan dan risiko kehilangan data yang dapat mengakibatkan keterlambatan pelaporan hasil kinerja dosen. Oleh karena itu diperlukan analisis dan perancangan sistem informasi penilaian kinerja dosen berbasis web yang dapat mencegah terjadinya kesalahan dalam perhitungan angka kredit berdasarkan pedoman PAK tahun 2019. Penelitian ini menggunakan metode Waterfall sebagai pengembangan sistem. Analisis kebutuhan dilakukan dengan mengidentifikasi masalah dan kebutuhan pengguna melalui wawancara dan studi literatur. Perancangan sistem dibuat menggunakan Unified Modeling Language (UML), dan perancangan prototipe dengan menggunakan figma. Penelitian ini menghasilkan rancangan sistem informasi penilaian kinerja dosen berbasis web dengan fitur perhitungan angka kredit otomatis, pemantauan status laporan, riwayat, berita, serta kustomisasi penilaian angka kredit yang dapat membantu proses penilaian kinerja dosen. Rancangan ini diharapkan dapat menjadi referensi untuk dikembangkan menjadi aplikasi yang dapat diimplementasikan
Deteksi Bahasa Isyarat Berdasarkan Abjad Menggunakan Metode LSTM (Long Short Term Memory) Irviantina, Syanti; Wijaya, Dela Agustri; Situmorang, Desiana R.; Nasution, Nazhiifah Mawaddah Juliyanda
Majalah Ilmiah METHODA Vol. 14 No. 3 (2024): Majalah Ilmiah METHODA
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/methoda.Vol14No3.pp371-376

Abstract

The LSTM based sign language detection system combined with the use of mediapipe can recognize hand gestures in real time with high accuracy. Alphabet based sign language can use this model to collect temporal patterns of hand gestures. The data used in this study are 30 sample for each alphabet based on American Sign Language (ASL). The data is processed through landmark detection on the hand using mediapipe and opencv, keypoints extraction, folder creation and pre – processing with 80% data divisior for training data and 20 % data for testing data. Using Adam optimization, categorical crossentropy loss function and evaluation metric. The model was trained with 100 epochs and evaluated using confusion matrix. The evaluation results showed that the LSTM model performed well with an accuracy of 98%.
Identifikasi Potensi Penipuan pada Transaksi Bank Menggunakan K-Means Clustering Hutagalung, Jessica Uly Sari; Sihombing, Kristin Trivena; Hutabarat, Michael Owen; Irviantina, Syanti
Majalah Ilmiah METHODA Vol. 14 No. 3 (2024): Majalah Ilmiah METHODA
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/methoda.Vol14No3.pp392-395

Abstract

Increasing cases of fraud in bank transactions are a serious concern for financial institutions, resulting in significant economic losses and undermining customer trust. This calls for identifying suspicious transaction patterns through machine-learning approaches to mitigate the risk of fraud. The methods used include problem identification, transaction data collection, and preprocessing to clean and prepare the data and after that, applying the K-Means Clustering algorithm to group transactions based on similar characteristics. The evaluation result obtained in this study using the Silhouette Score is 0.42, indicating a fairly good separation between normal and suspicious transactions. This research is expected to contribute to the development of a more accurate and efficient machine learning-based fraud detection system in banking institutions.
Implementasi Sistem Augmented Reality untuk Organ Dalam dengan Integrasi Berbasis Suara Br Ginting, Geby Laurent; Lubis, Rangga Aprilla; Parapat, Yehezkiel Fernandes; Irviantina, Syanti; Adriansyah, R. A. Fattah
Jurnal Sifo Mikroskil Vol. 26 No. 1 (2025): JSM VOLUME 26 NOMOR 1 TAHUN 2025
Publisher : Fakultas Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55601/jsm.v26i1.1709

Abstract

Pemahaman mengenai organ dalam manusia merupakan komponen penting dalam pembelajaran biologi di tingkat SMA, karena memberikan wawasan mendalam tentang anatomi dan fisiologi organ dalam manusia. Namun, pembelajaran tradisional yang bersifat teoritis menyebabkan siswa kehilangan minat dan mengalami kesulitan memahami konsep-konsep kompleks. Untuk mengatasi hal ini, perlu diperkenalkan metode pembelajaran berbasis teknologi yang dapat meningkatkan pemahaman siswa dalam pembelajaran organ dalam manusia. Oleh karena itu, diperlukan pengembangan aplikasi pembelajaran yang dirancang untuk memperkenalkan organ dalam manusia secara interaktif. Hasil akhir dari pengembangan ini adalah berupa aplikasi pembelajaran bernama "scleARn" yang dikembangkan dengan metode AGILE untuk memberikan solusi pembelajaran interaktif yang menarik. Dengan memanfaatkan teknologi Augmented Reality, aplikasi ini memungkinkan siswa memvisualisasikan organ dalam manusia dalam bentuk objek 3D secara real-time. Fitur Chat Assist berbasis Artificial Intelligence dan suara memungkinkan siswa untuk berinteraksi langsung dan memperoleh informasi lebih lanjut. Hasil pengujian aplikasi, mulai dari blackbox testing hingga pengujian mendalam pada setiap fitur, menunjukkan bahwa scleARn berfungsi sesuai dengan tujuan yang ditetapkan. Tanggapan positif dari siswa SMA mencapai 92,17%, yang mengindikasikan bahwa aplikasi ini memiliki fungsionalitas tinggi serta mudah digunakan, menjadikannya solusi inovatif untuk pembelajaran berbasis teknologi.
Rancang Bangun Sistem Smart Parking Berbasis Mobile Menggunakan Mikrokontroler Esp32 Saputra, Ardi; Zahfira, Dayanah; Sidabutar, Honey Christine; Irviantina, Syanti; Halim, Apriyanto
Majalah Ilmiah METHODA Vol. 14 No. 3 (2024): Majalah Ilmiah METHODA
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/methoda.Vol14No3.pp306-317

Abstract

Most universities manage parking for students and lecturers such as motorcycles and cars. But currently, there are many universities that still use manual methods, Mikroskil University is one of the private universities in Medan City which also still uses manual methods by checking the Vehicle Number Certificate by Mikroskil security officers. This inspection can result in a long queue at the exit of the parking area. In addition, students also have difficulty finding available parking spots in the parking area because there is no system that provides directions to see the availability of parking spots. Therefore, in this study a Smart Parking system was built using the application of the Internet of Things (IoT) system by creating a portal with a QR code scanner and adding a light sensor in each parking spot. The sensor testing results show that the light sensor is able to display the results according to the condition of the vehicle and then send the parking spot data to the application server, then based on the black box software testing, it is concluded that the software functionally runs well and produces results as expected. User testing conducted by students also shows the results as expected.
JURNAL ANALISIS DAN PERANCANGAN MARKETPLACE PASAR TRADISIONAL KOTA MEDAN Satria, Krismulia Wignya; Sitompul, Indra Maruba; Edmund, Edmund; Irviantina, Syanti; Sinaga, Frans Mikael
Jurnal Sifo Mikroskil Vol. 25 No. 1 (2024): JSM VOLUME 25 NOMOR 1 TAHUN 2024
Publisher : Fakultas Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55601/jsm.v25i1.893

Abstract

Pasar tradisional memiliki peran sentral dalam kehidupan masyarakat, menjadi tempat utama bagi proses jual beli untuk memenuhi kebutuhan bahan pokok sehari-hari. Meskipun begitu, kegiatan pasar tradisional yang masih menggunakan metode konvensional mulai tergeser oleh sistem modern, khususnya dengan munculnya aplikasi e-marketplace untuk mempermudah proses transaksi jual beli barang. Penelitian ini bertujuan untuk melakukan analisis dan perancangan aplikasi e-marketplace khususnya di Kota Medan. Dalam perancangan ini, dilakukan proses mengintegrasikan fitur tracking untuk memudahkan pemantauan pengiriman barang, serta menambahkan fitur verifikasi identitas pengguna guna memastikan kejelasan identitas dalam setiap transaksi di aplikasi e-marketplace. Proses analisis dan perancangan dimulai dengan pengumpulan data melalui observasi terhadap aplikasi serupa, perancangan proses menggunakan Diagram Activity, pembuatan tampilan mobile dengan bantuan aplikasi Figma, dan perancangan basis data menggunakan Entity Relationship Diagram (ERD). Dengan adanya rancangan aplikasi e-marketplace untuk pasar tradisional di Kota Medan yang telah dilengkapi dengan sistem tracking, sistem verifikasi identitas, serta seluruh proses transaksi yang dijalankan secara digital, diharapkan dapat memberikan kemudahan kepada pengguna dalam melakukan aktivitas jual-beli. Keberadaan fitur-fitur ini diharapkan juga dapat mempermudah pengembang sistem dalam melaksanakan proses implementasi
Evaluasi Teknik Resampling untuk Class Balancing dalam Analisis Sentimen Kesehatan Mental Berbasis Bi-LSTM Sintiya, Cindy; Hutagaol, Grace Helena; Bate`e, David; Irviantina, Syanti
Jurnal Sifo Mikroskil Vol. 26 No. 2 (2025): JSM VOLUME 26 NOMOR 2 TAHUN 2025
Publisher : Fakultas Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55601/jsm.v26i2.1799

Abstract

Ketidakseimbangan data (imbalanced data) sering menjadi tantangan utama dalam analisis sentimen, terutama ketika model pembelajaran mesin cenderung mengabaikan kelas minoritas yang justru memuat informasi kritis. Penelitian ini mengevaluasi efektivitas teknik class balancing dengan metode resampling, yaitu Random Under-Sampling (RUS) dan Synthetic Minority Over-sampling Technique (SMOTE), dalam meningkatkan performa model LSTM (Long Short-Term Memory) untuk analisis sentimen kesehatan mental. Hasil penelitian menunjukkan bahwa metode SMOTE dapat meningkatkan F1-score pada kelas “Suicidal” dari 64,4% menjadi 72,6%, meskipun terjadi penurunan pada kelas “Depression” dari 73,4% menjadi 59,9%. Sementara itu, metode RUS cenderung menurunkan performa secara keseluruhan, dengan akurasi model turun dari 80,5% menjadi 77,8% akibat penghapusan data secara acak yang mengurangi kualitas representasi data. Penelitian ini menyimpulkan bahwa meskipun teknik resampling dapat membantu menyeimbangkan data, namun penerapannya pada data teks memerlukan kehati-hatian untuk menghindari efek negatif pada performa model.
Pelatihan Pembuatan Konten Pembelajaran Berbasis Video pada SMA Methodist 6 Sinaga, Frans Mikael; Irviantina, Syanti; Pipin, Sio Jurnalis
Journal of Social Responsibility Projects by Higher Education Forum Vol 4 No 3 (2024): Maret 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jrespro.v4i3.4588

Abstract

The use of information technology to support the teaching and learning process is considered important and necessary. It is not only the educators or teachers who are demanded to have the ability to use and utilize information technology, but students as well, in order to meet digital literacy competencies and be able to compete globally. At Swasta Methodist 6 High School, community service activities are carried out with the aim of improving students understanding in creating learning content using Canva and Wondershare Filmora tools. The availability of good facilities and infrastructure at school greatly assists students in utilizing technology to support the learning process. This activity was carried out for 2 days in the school's laboratory, and was attended by 43 students. The evaluation conducted with a pre-test and post-test showed an increase of 80% in the post-test for questions related to the use of Canva tools, and an increase of 60% in the post-test for questions related to the use of Wondershare Filmora tools.
Implementation of BiLSTM-SVM Algorithm to Detect Fake News on Text-Based Media Liman, Felix; Carsten, Carsten; Sufinata, Sufiandy; Irviantina, Syanti; Winardi, Sunaryo
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 9, No 2 (2023): December 2023
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/coreit.v9i2.18982

Abstract

Online media is one of the places where news can spread quickly and everyone can access it easily and freely. Not only real or valid news is spread on online media, but fake news can also be easily spread on online media, and readers sometimes do not realize that the news they read is fake. As a result, wrong opinions arise that can lead to disputes, as well as divisions between individuals or groups. This study implements the BiLSTM-SVM algorithm to detect fake news that is spread on one of the online media, namely Twitter. The steps taken are tidying up the news text (text preprocessing), converting every word from the news text into numbers in vector form (word embedding), processing the numbers, and then classifying the results of the processing with the BiLSTM-SVM model formed with TensorFlow 2.0 help, and see the performance generated by the BiLSTM-SVM algorithm. The results obtained include an accuracy rate of 86% and an F1 Score value of 87.5% in detecting news from data validation with the same news topic.
Co-Authors Adriansyah, R. A. Fattah Apriyanto Halim Bate`e, David Br Ginting, Geby Laurent Carsten, Carsten Edmund, Edmund Hutabarat, Michael Owen Hutagalung, Jessica Uly Sari Hutagaol, Grace Helena Jeslim, Jeslim Jordan, Alvito Liman, Felix Lubis, Rangga Aprilla Manurung, Stieven B.L. Nasution, Nazhiifah Mawaddah Juliyanda Parapat, Yehezkiel Fernandes Pipin, Sio Jurnalis Saputra, Ardi Satria, Krismulia Wignya Sembiring, Rinawati Sidabutar, Honey Christine Sihombing, Kristin Trivena Sinaga, Frans Mikael Sintiya, Cindy Sitompul, Indra Maruba Situmorang, Desiana R. Sufinata, Sufiandy Wijaya, Dela Agustri Winardi, Sunaryo Zahfira, Dayanah