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All Journal International Journal of Electrical and Computer Engineering Jurnal Edukasi Elektro Jurnal Teknologi Informasi dan Ilmu Komputer KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) JOIN (Jurnal Online Informatika) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal CoreIT BAREKENG: Jurnal Ilmu Matematika dan Terapan PRODUCTUM : Jurnal Desain Produk (Pengetahuan dan Perancangan Produk) International Journal of Computing Science and Applied Mathematics J-Dinamika: Jurnal Pengabdian Kepada Masyarakat Jurnal Teknologi Informasi dan Pendidikan Indonesian Journal of Electrical Engineering and Computer Science Community Development Journal: Jurnal Pengabdian Masyarakat Economics and Digital Business Review NUCLEUS: Jurnal Sains dan Teknologi Jurnal ComunitA Servizio Jurnal Pengabdian Masyarakat Akademisi Economic Reviews Journal JatiRenov: Jurnal Aplikasi Teknologi Rekayasa dan Inovasi JSSIT: Jurnal Sains dan Sains Terapan
Prasetyo, Tegar
Information Technology, Faculty Of Vocational Studies, Institut Teknologi Del
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Development of DelTalk (an English learning application) using Agile Method Tegar Arifin Prasetyo; Monalisa Pasaribu; Tiurma Lumban Gaol; Togu Novriansyah Turnip; Juli Yanti Damanik; Andree Panjaitan; Mei Pane; Nathan Fernando Lumban Tobing; Lilis Marito Pardosi; Timothy Timothy; Yohana Sihombing
Jurnal Teknologi Informasi dan Pendidikan Vol 16 No 1 (2023): Jurnal Teknologi Informasi dan Pendidikan
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jtip.v16i1.662

Abstract

English has become a world language that must be mastered by many people because English has dominated the era of communication to connect and transfer knowledge to the entire world. When it comes to the development of mobile applications for language learning, previous research has tended to emphasize testing on various technologies such as multimedia, virtual and augmented reality, conversational agents and artificial intelligence-based systems. This research, therefore, aimed to develop a mobile-based English learning application that provided English learning in the form of stories called the Deltalk. This mobile-based English learning application provides features in which the users can practice their speaking in English. This app was developed by integrating ASR (Automatic Speech Recognition) technology provided by NOVO Learning. The ASR was integrated with Deltalk through the API (Application Programming Interface) and Websocket. Deltalk development adapted two agile frameworks, including Scrum and Lean Software Development by performing MVP process one time.
Evaluating the efficacy of univariate LSTM approach for COVID-19 data prediction in Indonesia Tegar Arifin Prasetyo; Joshua Pratama Silitonga; Matthew Alfredo; Risky Saputra Siahaan; Roberd Saragih; Dewi Handayani; Rudy Chandra
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 2: May 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i2.pp1353-1366

Abstract

The coronavirus disease 2019 (COVID-19) pandemic, originating in 2020, has emerged as a critical global issue due to its rapid and widespread transmission. Indonesia, among the affected nations, has taken measures to address the situation, including the development of a deep learning model for predicting future COVID-19 infection and spread. This predictive tool serves as a valuable reference for the government and stakeholders, aiding them in making informed decisions and implementing appropriate measures to contain the virus. The deep learning model employs the long short-term memory (LSTM) algorithm, chosen for its ability to recognize temporal patterns in the country’s COVID-19 data. The model creation process involves data collection, preprocessing, model architecture planning, modeling, training, and evaluation. Two LSTM models were developed: a univariate and a multivariate model. Following thorough training and evaluation, the univariate model emerged as the superior choice, boasting evaluation metrics of 16.72 for mean absolute percentage error (MAPE) and 66.36 for root mean squared error (RMSE). This model was then deployed on a publicly accessible website, presenting visualizations of past COVID-19 data and predictions of future cases through line graphs. This user-friendly platform enables the public to access and analyze the data easily.
Refining tomato disease recognition: hyperparameter tuning on ResNet-101 architecture for precise leaf-based classification Tegar Arifin Prasetyo; Tiurma Lumban Gaol; Nico Felix Sipahutar; Tessalonika Siahaan; Trito Exaudi Manik; Rudy Chandra
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 2: May 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i2.pp1204-1213

Abstract

Tomatoes plants are widely recognized as versatile vegetables globally. This study aims to develop a high-precision web interface for classifying various leaf diseases in tomatoes. Utilizing a convolutional neural network (CNN) algorithm using the residual network-101 (ResNet-101) architecture, this tool aids farmers in accurately identifying leaf diseases in tomatoes, thereby reducing the risk of crop failure. The dataset comprises 6,800 images, categorized into four classes: early blight, spider mites two spotted, tomato yellow leaf curl virus, and healthy tomatoes, each containing 1,700 images. Hyperparameter tuning was conducted as part of an experiment aimed at enhancing the performance of the model. Experiments involved varying epoch values (10, 25, 30, 50, 60, 75, 100, and 110), a fixed batch size of 4, different learning rates (0.1, 0.01, 0.001, 0.0001), and num workers (4, 8, 16). The results demonstrated an accuracy of 99% with 100 epochs, a batch size of 4, a learning rate of 0.001, and 16 num workers. Consequently, this research contributes to a deeper understanding of disease management in tomato plants, ensuring optimal quality and quantity of the harvest.
Penerapan Website untuk Digitalisasi dan Pengembangan Bisnis di Usaha Pemandian Air Panas Karunia Sipoholon Rudy Chandra; Tegar Arifin Prasetyo; Tahan HJ Sihombing; Juan Carlos Munthe; Christian Benedict Lumbantoruan; Dame Sisri Haryati Katarina Rumapea; Herbeth Augustinus Napitupulu
JURNAL Comunità Servizio : Jurnal Terkait Kegiatan Pengabdian kepada Masyarakat, terkhusus bidang Teknologi, Kewirausahaan dan Sosial Kemasyarakatan Vol. 6 No. 1 (2024): APRIL
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat (LPPM), Univesitas Kristen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33541/cs.v6i1.5297

Abstract

Traveling is an activity that people do to unwind from their daily routines. There are many types of travel destinations, and one of them is a natural hot spring located in Situmeang Habinsaran Village, Sipoholon District, North Tapanuli. Besides being a tourist destination, natural hot springs are believed to have the ability to cure various skin diseases and promote healthier skin. The owner of the Karunia hot spring business is one of the entrepreneurs who provide hot spring baths, accommodations/homestays, and a restaurant. This business opportunity has become more competitive with many similar ventures opening up. Marketing and promoting this natural attraction continues. As time goes by, the promotion and business systems need to be enhanced by using information technology to improve. A website is one of the means for promotion and branding, enabling the digitization of the established business. Building a website is applied for promotional purposes and to enhance credibility with the public, making them more familiar with the hot spring tourism in Sipoholon, especially Karunia hot spring. The website also serves as a centralized platform for financial management, cash flow, and business operations, which have previously been done manually. The goal of creating this website is for partners to increase income and improve business branding
Uji Sensoris Es Krim Susu Kambing dan Sari Kedelai Hitam Eka Putri Manurung, Nancy; Hermialingga, Septi; Prasetyo, Tegar; Amri Yahya, Muhammad; Sari Utami, Aldila
JSSIT: Jurnal Sains dan Sains Terapan Vol 1 No 2 (2023): JSSIT: Jurnal Sains dan Sains Terapan
Publisher : Fakultas Sains dan Teknologi, UIN Sulthan Thaha Saifuddin Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30631/jssit.v1i2.25

Abstract

Salah satu bahan dalam pembuatan es krim yaitu susu kambing. Inovasi terbaru peningkatan kualitas es krim yaitu mengombinasikannya dengan sari kedelai hitam yang juga dapat menurunkan biaya produksi es krim. Penelitian ini bertujuan untuk mengetahui sifat sensoris dari es krim susu kambing dan sari kedelai hitam yang menggunakan ice cream maker portable. Perbandingan bahan baku pembuatan es krim yaitu 100:0; 75:25; 50:50. Es krim kemudian dicampung dengan susu krim, susu skim, kuning telur, stabilizer menggunakan formulasi ICM. Adonan es krim kemudian dipasteurisasi, aging, agitas, dan freezer. Es krim yang telah jadi dilakukan pengujian sensoris dengan menghadirkan 20 panelis tak terlatik menggunakan skor 1 sampai 9. Rata es krim memiliki warna agak purih kehitaman, beraroma langu, berasa manis, memiliki tekstur lembut dan memiliki daya terima yang baik. Kesimpulan penelitian ini yaitu es krim dengan campuran 75:25 memiliki skor sensoris tertinggi.
Pencegahan Perundungan pada Anak-Anak Sekolah Dasar dengan Sosialisasi Anti Bullying Dunia Pendidikan Manurung, Nancy Eka Putri; Dewantara, Billy; Prasetyo, Tegar; Burhan, Abi; Nugraha, Yoga Aji; Yahya, Muhammad Amri; Cahya, Gemala; Hermialingga, Septi
JatiRenov: Jurnal Aplikasi Teknologi Rekayasa dan Inovasi Vol 3 No 2 (2024): Edisi November
Publisher : Unit Penelitian dan Pengabdian Masyarakat Politeknik Pertanian Negeri Pangkajene Kepulauan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51978/jatirenov.v3i2.919

Abstract

Sekolah sebagai lembaga pendidikan formal memiliki tujuan untuk menyelenggarakan proses pembelajaran secara efektif dan berkualitas guna menghasilkan siswa yang unggul serta berperan penting dalam mendukung perkembangan anak. Namun masih banyak siswa yang belum mencapai perkembangan optimal. Salah satu faktor yang menghambat kemajuan mereka adalah adanya kasus perundungan (bullying) di sekolah. Dampak negatif dari kasus bullying pada anak usia sekolah korban dapat mengalami konsekuensi jangka panjang. Bagi anak yang melakukan bullying cenderung akan terus mengulang perilaku tersebut hingga dewasa, sementara korban bullying akan terus menderita efek yang berlangsung lama seperti merasakan stres, depresi, kebencian terhadap pelaku, dendam, keinginan untuk keluar dari sekolah, rasa malu, tertekan, terancam, dan kebencian terhadap lingkungan sosialnya. pencegahan terkait bullying didunia pendidikan salah satu caranya yakni dengan melakukan program sosialisasi ke sekolah-sekolah oleh praktisi dengan keilmuan yang relevan dan kompeten. Sosialisasi dilaksanakan di SD Negeri 52 Kota Prabumulih pada kelas 5 dengan peserta 18 siswa yang terdiri dari 8 siswa laki-laki dan 10 siswa Perempuan. Tingkat pemahaman siswa terhadap tindakan perundungan diukur melalui pre-test dan post-test dimana hasilnya menunjukkan adanya peningkatan persentase nilai post-test tentang pemahaman siswa terhadap materi yang disampaikan mengenai perundungan. Hal ini dapat disimpulkan bahwa sosialisasi berhasil dilakukan dalam upaya pencegahan bullying di lingkungan sekolah, dan dapat dilakukan secara berkelanjutan pada seluruh kelas
Pengaruh Promosi, Lokasi Dan Kualitas Pelayanan Terhadap Keputusan Pembelian Konsumen D’sas Cafe & Resto Kalianda Prasetyo, Tegar; Saodin, Saodin
Economics and Digital Business Review Vol. 6 No. 2 (2025): February - July
Publisher : STIE Amkop Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37531/ecotal.v6i2.2225

Abstract

Industri Restoran dan Cafe adalah salah satu sector bisnis yang terus berkembang dan bertransformasi dengan cepat, dengan persaingan yang semakin ketat. Penelitian ini bertujuan untuk mengetahui pengaruh lokasi, promosi dan kualitas layanan terhadap keputusan pembelian pada D’SAS Cafe & Resto Kalianda dan menganalisis faktor yang paling dominan dalam mempengaruhi keputusan pembelian pada D’SAS Cafe & Resto Kalianda. Populasi dalam penelitian ini adalah para konsumen D’SAS Cafe & Resto Kalianda. Sampel yang diambil sebanyak 96 responden dengan pendekatan Accidental sampling. Berdasarkan analisis data statistik, indikator-indikator pada penelitian ini bersifat valid dan variabelnya bersifat reliabel. Pada pengujian uji t, nilai signifikan variabel Promosi (X1) terhadap Keputusan pembelian (Y) 0,000 < 0,05 dan nilai t hitung 4.032 > t tabel 1.986. Variabel Lokasi (X2) terhadap Keputusan pembelian (Y) 0,037 < 0,05 dan nilai t hitung 2.113 > t tabel 1.986. Variabel Kualitas Pelayanan (X3) terhadap Keputusan pembelian (Y) 0,032 < 0,05 dan nilai t hitung 2.174 > t tabel 1.986. pada pengujian uji F Variabel Promosi, Lokasi, Keputusan Pembelian terhadap Keputusan Pembelian dengan nilai signifikan 0,000 < 0,05 dan nilai F hitung 13.059 > 3,10. Hasil penelitian ini disimpulkan bahwa Promosi, Lokasi dan Kualitas Pelayanan secara parsial berpengaruh positif dan signifikan terhadap Keputusan Pembelian. Promosi, Lokasi dan Kualitas pelayanan secara Bersama-sama berpengaruh positif dan signifikan terhadap Keputusan Pembelian konsumen D’SAS Cafe & Resto Kalianda.
Design and Implementation of the Shortest Path Navigation in Samosir District using Branch and Bound Algorithm Chandra, Rudy; Arifin Prasetyo , Tegar
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 2 (2024): April 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i2.5585

Abstract

Samosir has a large area and several tourist attractions, making it difficult for visitors to explore the island. Unknowing the route can make the journey less fun and waste time. In general, tourists seek to know the fastest way to a tourist location to save time and money while on vacation. As a result, we require an application that will offer directions to the shortest path. This research aims to develop a web-based application that may display a map of the shortest travel to a tourist site. This website will display a map that marks the route from the origin point to the destination point. The Branch and Bound algorithm is used to determine the shortest path. The Python libraries OSMnx, Folium, and NetworkX modify paths and show a route map with OpenStreetMap. The error value of the distance between the branch, the bound algorithm, and Google Maps is used to obtain the RMSE accuracy value. The RMSE value is 3.02 and the MAPE value is 0.0023 indicating that the application produced already has a good implementation prototype. Furthermore, there is no significant distinction between the appearance of maps that implement OpenStreetMap and Google Maps.
Recurrent Neural Network Model for Short-term Electric Load Forecasting Yahya, Muhammad Amri; Prasetyo, Tegar; Fikri, Muhammad
Jurnal Edukasi Elektro Vol. 9 No. 2 (2025): Jurnal Edukasi Elektro Volume 9, No. 2, November 2025
Publisher : DPTE FT UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jee.v9i2.86643

Abstract

Accurate short-term electricity load forecasting is critical for planning power generation and maintaining cost efficiency. Since the amount of electricity generated significantly affects the cost-efficiency of power generation, a forecasting method with high accuracy is required. In response, this study developed a Recurrent Neural Network (RNN) model architecture trained using three different algorithms: Levenberg-Marquardt, Bayesian Regularization, and Scaled Conjugate Gradient. The model's performance was evaluated using the Mean Absolute Percentage Error (MAPE) metric. Historical load data were categorized by day type and divided into training and testing sets. The best-performing RNN model was used to carry out load forecasting, which was then compared to the forecasting results from PT PLN. Among the models tested, the RNN trained with Bayesian Regularization, configured with an 8-16-1 network architecture using a learning rate of 0.01 achieved the highest accuracy. In a two-week forecasting simulation, this model reached a MAPE of 1.4084%, significantly outperforming the 3.3160% error from PLN’s conventional forecasting method. These results underpin the effectiveness of RNNs, particularly when trained with Bayesian Regularization, for enhancing short-term electricity load forecasting within the scope of this dataset.
RADIO LABELING OF BANANA GRAPHS Sarbaini, Sarbaini; Nazaruddin, Nazaruddin; Rizki, Muhammad; Umam, Muhammad Isnaini Hadiyul; Hamzah, Muhammad Luthfi; Prasetyo, Tegar Arifin
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (341.268 KB) | DOI: 10.30598/barekengvol17iss1pp0165-0170

Abstract

Let G=(V, E) be a graph. An L(3,2,1) labeling of G is a function such that for every , , and if . Let , a labeling is a labeling where all labels are not greater than . An ) number of , denoted by , is the smallest non-negative integer such that has a labeling. In this paper, we determine of banana graphs.
Co-Authors Abi Burhan Adha, Ufairi Africano, Fernando Agustin, Ririn Dita Aji Nugraha, Yoga Akbar, M. Jofandio Amri Yahya, Muhammad Anastasia Marsada Uli Simamora Andree Panjaitan Aprianda, Ridho Ardian, Rizki Asido Saragih Aulia Akhmad BillY Dewantara Christian Benedict Lumbantoruan Dame Sisri Haryati Katarina Rumapea Desiana, Lidia Dewi Handayani Ebtaria Nadeak, Ebtaria Edi Kurniawan Eka Putri Manurung, Nancy Elmi Rahmawati, Elmi Emy Sonia Sinambela Ester Saulina Hutabarat Evan Richardo Sianipar Evelina Evelina Fauziah, Putri Khafifah Fernandez, Melanie Frengki Simatupang Fritz Marpaung Gemala Cahya Goklas Henry Agus Panjaitan Hafizah, Nanda Nur Hamzah, Muhammad Luthfi Henny Flora Panjaitan Henry Agus Panjaitan , Goklas Henry Agus Panjaitan, Goklas Herbeth Augustinus Napitupulu Hermialingga, Septi Iammillah, Azmiyatul Ilhami, Ilhami Italiano Wowiling, Gerry Joshua Pratama Silitonga Juan Carlos Munthe Juli Yanti Damanik Juniasari, Juniasari Lawy Xenna Lestari, Leni Ayu Lilis Marito Pardosi Lumban Gaol, Tiurma Lumbangaol, Heni Ernita Manurung, Nancy Eka Putri Matthew Alfredo Mei Pane Muhammad Fikri Muhammad Ilham Maulana Muhammad Rizki Mula Timbul Sigiro, Marojahan N. Nazaruddin Najah, Nabila Safinatun Nathan Fernando Lumban Tobing Nico Felix Sipahutar Nugraha, Yoga Aji Panca Rahmat Siagian, Iqbal Pangaribuan, Maria Partogi Pardede, Immanuel Pasaribu, Monalisa Poibe Leny Naomi Pratami, Viekhen Irza Putri Manurung, Nancy Eka Risky Saputra Siahaan Roberd Saragih Romauli Sianipar Rudy Chandra Rudy Chandra Safitri, Nita Octaria Samuel Sibuea Saodin, Saodin Sarbaini Sarbaini Sarbaini Sarbaini Sari Utami, Aldila SIAGIAN, WESLY MAILANDER Siahaan, Samuel Jefri Saputra Siahaan, Veny Sianipar, Johan Immanuel Silaen, Willy Cristover Silvia Agustin Siregar, Horas Marolop Amsal Suandika Napitupulu Tahan HJ Sihombing Tanjung, Muhammad Al Chapis Abdilla Tessalonika Siahaan Timothy Timothy Tiurma Lumban Gaol Togu Novriansyah Turnip Trito Exaudi Manik Umam, Muhammad Isnaini Hadiyul Victor Lambok Desrony Wardani, Yoshinta Kusuma Wesly Mailander Siagian Yahya, Muhammad Amri Yohana Sihombing Yohanssen Pratama