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All Journal JSM (Jurnal SIFO Mikroskil) Jurnal Teknologi Informasi dan Ilmu Komputer Dinamisia: Jurnal Pengabdian Kepada Masyarakat JMM (Jurnal Masyarakat Mandiri) Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Jurnal Sistem Informasi Kaputama (JSIK)
Roni Yunis
STMIK Mikroskil
Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering Social Sciences Other

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ANALISIS DAN PERANCANGAN APLIKASI MOBILE LET’SING Silaen, Dika Jur Aeini; Yunis, Roni; Sembiring, Salsalina Br
Jurnal Sistem Informasi Kaputama (JSIK) Vol. 6 No. 2 (2022): Volume 6, Nomor 2, Juli 2022
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jsik.v6i2.196

Abstract

Let’sing merupakan perancangan antarmuka aplikasi mobile yang bergerak dibidang tarik suara. Kegiatan pencarian guru vokal masih memakan waktu cukup lama, sulitnya menentukan kesesuaian tempat dan waktu antara guru vokal dan murid, kurangnya informasi tentang kemampuan seorang guru vokal tersebut sehingga kriterianya tidak sesuai dengan yangdiiginkan. Metodologi yang digunakan untuk menganalisis masalah dan mencari solusi permasalahan adalah metodologi design sprint yang memiliki 5 tahapan yaitu understand, diverge, decide, prototype, validate. Oleh karena itu, untuk membantu permasalahan tersebut penulis membuat rancangan baru yang membantu memudahkan pencarian guru vokal. Hasil dari analisis dan perancangan aplikasi mobile let’sing diharapkan dapat membantu murid mendapatkan informasi kriteria dan kemampuan berupa biodata, pengalaman, prestasi dan cara mengajar dari guru vokal dan dapat mempersingkat waktu pencarian dan pemesanan.
Enhancing Rice Production Prediction: A Comparative Machine Learning Analysis of Climate Variables Yunis, Roni; Sudarto; Adiputra Pardosi, Irpan
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 13 No. 1 (2024)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v13i1.71527

Abstract

This study aims to enhance rice production prediction through a comparative analysis of machine learning models utilizing climate variables. Eight models were assessed on a predetermined dataset, with Support Vector Regression (SVR) emerging as the top performer. Following the identification of significant climate variables influencing rice production, the models underwent evaluation using two hyperparameter approaches: random search and manual tuning. SVR outperformed other models, achieving impressive metrics with MAE 0.180, MSE 0.186, RMSE 0.431, and an exceptionally low MAPE of 0.020. Key factors influencing rice production included productivity and area, along with humidity, rainfall, temperature, wind velocity, and sunshine duration. Favorable conditions for rice output encompassed low humidity, moderate rainfall, increased wind speed, and prolonged sunshine, while rainfall and temperature exhibited minimal impact. The success of random search emphasizes the importance of effective hyperparameter tuning. This research provides valuable insights for enhancing rice production prediction.
Peran Interaktivitas dalam Penggunaan E-learning: Perluasan Model UTAUT Saragih, Yuni Marlina; Panjaitan, Erwin Setiawan; Yunis, Roni
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 10 No 1: Februari 2023
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2023105877

Abstract

Perubahan proses belajar mengajar menjadi daring dilaksanakan oleh STMIK Mikroskil untuk mematuhi kebijakan yang dibuat Menteri Pendidikan dan Kebudayaan dalam masa darurat penyebaran covid-19 di Indonesia. Sebelum covid-19 terjadi, STMIK Mikroskil telah menerapkan E-learning yaitu moodle. Namun selama pandemi covid-19 penggunaan E-learning meningkat pesat dan tidak dapat mendukung besarnya transaksi yang dilakukan dalam kegiatan pembelajaran online, sehingga STMIK Mikroskil memutuskan untuk menggunakan Microsoft Teams sebagai media pembelajaran online. Dengan menggunakan Microsoft Teams, diharapkan interaksi antara dosen dan mahasiswa berlangsung secara rutin dan tepat waktu, mendukung serta bersifat membangun. Sehingga perlu dilakukan pengujian untuk memahami sejauh mana faktor penerimaan dan pemanfaatan teknologi Microsoft Teams di STMIK Mikroskil. Penelitian ini bertujuan untuk menguji pengaruh interaktivitas pada penerimaan sistem Microsoft Teams dengan menggunakan Model UTAUT. Secara khusus, survei dilakukan pada mahasiswa aktif STMIK Mikroskil jurusan Teknik Informatika dan Sistem Informasi, yang mencakup 348 responden. Dengan menggunakan model persamaan struktural (SEM) dan perangkat lunak SmartPLS. Kontribusi utama penelitian ini adalah pengenalan variable interaktivitas pada model UTAUT yang memiliki pengaruh signifikan terhadap minat pemanfaatan sistem. Dari hasil penelitian dapat disimpulkan bahwa ekspektasi kinerja, pengaruh sosial, ekspektasi usaha, interaktivitas berpengaruh positif terhadap minat pemanfaatan, dan minat pemanfaatan berpengaruh positif terhadap minat penggunaan sistem Microsoft Teams. Sedangkan kondisi fasilitas tidak berpengaruh terhadap minat penggunaan Microsoft Teams.AbstractSTMIK Mikroskil changed the teaching and learning process to online in order to comply with laws established by the Minister of Education and Culture during the COVID-19 outbreak in Indonesia. STMIK Mikroskil had introduced E-learning, specifically Moodle, prior to covid-19. However, during the COVID-19 epidemic, the usage of E-learning exploded, and because the enormous number of transactions carried out in online learning activities could not be supported, STMIK Mikroskil chose Microsoft Teams as an online learning medium. It is intended that by adopting Microsoft Teams, interactions between instructors and students would be more frequent, on time, supportive, and productive. As a result, testing is required to determine the extent to which Microsoft Teams technology adoption and use at STMIK Mikroskil is required. Using the UTAUT Model, this study will investigate the impact of interaction on Microsoft Teams system acceptability. The poll was performed on active STMIK Mikroskil students majoring in Informatics and Information Systems Engineering, with a total of 348 responses. The structural equation model (SEM) and the SmartPLS software were used. The most notable addition of this study is the inclusion of the interactivity variable in the UTAUT model, which has a considerable impact on system utilization interest. The study's findings suggest that performance expectations, social pressures, corporate expectations, and interaction all play a role.
Analisis Time Series dan Perancangan Dashboard untuk Memprediksi Penjualan dengan Metode Prophet dan SARIMAX Khaw, Brian; Irwanto, Ricky; Yunis, Roni; Elly, Elly
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.v26i2.1797

Abstract

Penelitian ini membahas analisis data deret waktu untuk memprediksi penjualan menggunakan metode Prophet dan SARIMAX. Metode ini dipilih karena mampu menangani pola musiman, tren, dan faktor eksternal yang penting dalam memaksimalkan akurasi prediksi penjualan. Dataset Walmart dari periode 2012-2015 digunakan sebagai data utama, sementara data eksternal diambil dari Google Trends. Penelitian ini menggunakan kerangka kerja OSEMN yang meliputi pengumpulan, pembersihan, eksplorasi, pemodelan, dan interpretasi data. Hasil evaluasi menunjukkan model SARIMAX lebih unggul pada skenario mingguan dan bulanan dengan MAPE sebesar 2,589% dan 0,930% dibandingkan model Prophet dengan MAPE sebesar 2,753% dan 1,045%. Hasil penelitian ini juga menunjukkan penambahan faktor eksogen pada kedua model ini tidak memberikan dampak yang signifikan dalam meningkatkan performa model. Hasil prediksi data penjualan divisualisasi melalui dashboard interaktif yang membantu pengguna memahami hasil prediksi secara intuitif.
Strengthening Digital Literacy and Organizational Management System Based on ISO 21001 to Support Kurikulum Merdeka: Penguatan Literasi Digital dan Sistem Manajemen Organisasi Berbasiskan ISO 21001 untuk Mendukung Kurikulum Merdeka Yunis, Roni; Sudarto, Sudarto; Ginting, Sugianta Ovinus; Jeni, Mutiara; Riri, Riri; Wijaya, Viona Guanita
Dinamisia : Jurnal Pengabdian Kepada Masyarakat Vol. 9 No. 2 (2025): Dinamisia: Jurnal Pengabdian Kepada Masyarakat
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/dinamisia.v9i2.23398

Abstract

The community service (PkM) aims to improve digital literacy and ISO 21001 implementation at SMAN 2 Lubuk Pakam to support the Kurikulum Merdeka. The methods used include socialization, training, technology application, mentoring, and evaluation. The results showed an increase in digital literacy understanding by 2.20% and ISO 21001 implementation by 5.70%, with participant participation in activities reaching 94.60%. In addition, the program also produced a community of digital creators and an internal quality assurance unit that is expected to play an active role in improving the quality of education. The application of technology and ISO 21001 has proven to play an important role in supporting information technology-based learning, especially through the Learning Management System (LMS). The sustainability of this program is expected to strengthen the capacity of SMAN 2 Lubuk Pakam in facing the challenges of education in the digital era, as well as improving the quality of learning
SISTEM PEMANTAUAN LINGKUNGAN KANDANG KAMBING BERBASIS IOT DALAM MENDUKUNG SMART FARMING PADA ARJUNA FARM Wong, Ng Poi; Andri, Andri; Darwin, Darwin; Pardosi, Irpan Adiputra; Yunis, Roni; Sihombing, Poltak; Pratama, Yudhistira Adhitya
JMM (Jurnal Masyarakat Mandiri) Vol 9, No 5 (2025): Oktober
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jmm.v9i5.33646

Abstract

Abstrak: Kondisi lingkungan kandang dapat mempengaruhi produktivitas ternak dan dapat menjadi dasar dalam pengembangan infrastruktur peternakan dalam konsep Smart Farm. Permasalahan pada Arjuna Farm adalah kesulitan dalam memperoleh data lingkungan kandang kambing untuk keperluan memprediksi produksi susu hingga pengembangan infrastruktur kandang berbasis Smart Farm. Kegiatan ini bertujuan menerapkan sistem pemantauan lingkungan berbasis IoT untuk memantau suhu, kelembaban, cahaya, suara, gas metana, kualitas udara, dan aktivitas pergerakan kambing. Metode yang digunakan meliputi wawancara, perancangan, pengembangan, penerapan, dan evaluasi sistem dalam bentuk observasi dengan indikator pembacaan manual terhadap visualisasi data secara real-time, dengan melibatkan 7 (tujuh) dosen dari 3 (tiga) institusi dan mitra Arjuna Farm. Kegiatan ini berhasil mengembangkan sistem yang mampu mendeteksi dan memvisualisasikan data sensor kondisi lingkungan kandang kambing, dimana hasil evaluasi menunjukkan sistem berhasil mendeteksi suhu kandang berkisar 25-50°C, kelembaban hingga 99%, intensitas cahaya hingga 175 lux, intensitas suara di kisaran 550 unit sensor, serta gas metana dan kualitas udara secara stabil.Abstract: The environmental conditions of the barn can affect livestock productivity and can form the basis for the development of livestock infrastructure in the Smart Farm concept. The problem at Arjuna Farm is the difficulty in obtaining environmental data from the goat barn for the purpose of predicting milk production and developing Smart Farm-based barn infrastructure. This activity aims to implement an IoT-based environmental monitoring system to monitor temperature, humidity, light, sound, methane gas, air quality, and goat movement activity. The methods used include interviews, design, development, implementation, and evaluation of the system through observation with manual readings of real-time data visualisation, involving 7 (seven) lecturers from 3 (three) institutions and Arjuna Farm partners. This activity successfully developed a system capable of detecting and visualising sensor data on the environmental conditions of goat pens, with evaluation results showing that the system successfully detected pen temperatures ranging from 25-50°C, humidity up to 99%, light intensity up to 175 lux, sound intensity within 550 sensor units, as well as stable methane gas and air quality levels.
Comparison of Machine Learning Methods with Optimization for Paddy Production Prediction Yunis, Roni; Adiputra Pardosi, Irpan
Jurnal Sifo Mikroskil Vol. 27 No. 1 (2026): JSM VOLUME 27 NOMOR 1 TAHUN 2026
Publisher : Fakultas Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55601/jsm.v27i1.2017

Abstract

Food security remains a critical challenge in Indonesia, where rice serves as the primary staple and demand continues to rise with population growth. Fluctuations in paddy production pose significant risks to supply stability, highlighting the need for accurate and reliable forecasting models. This study presents a comparative evaluation of Random Forest and Support Vector Regression (SVR) for paddy production prediction using national-level production data aggregated from provincial statistics in Indonesia, incorporating Grid Search and Random Search to optimize model performance. Experimental results demonstrate that SVR optimized with Random Search achieves superior predictive accuracy, yielding an RMSE of 27,478.58 and a MAPE of 0.05%, indicating both low absolute and relative errors. This performance suggests that SVR is more effective in modeling the non-linear and continuous dynamics inherent in paddy production data. Furthermore, Random Search consistently outperforms Grid Search, reflecting its ability to efficiently explore complex hyperparameter spaces. These findings underscore the critical role of both model selection and optimization strategy in improving forecasting reliability. The proposed approach provides a robust framework for data-driven agricultural planning and offers practical value for policymakers in managing food supply, reducing uncertainty, and enhancing national food security.
Co-Authors Andri Andri Darwin Darwin Elly Elly Irpan Pardosi Irwanto, Ricky Jeni, Mutiara Khaw, Brian Kristian Telaumbanua Ng Poi Wong Panjaitan, Erwin Setiawan Poltak Sihombing Riri Riri Saragih, Yuni Marlina Sembiring, Salsalina Br Silaen, Dika Jur Aeini Sudarto Sugianta Ovinus Ginting Wijaya, Viona Guanita Yudhistira Adhitya Pratama