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Implementasi Algoritma K-Nearest Neighbor untuk Optimasi Pemberian Reward Siswa SMA Riyanto, Agus; Nurchim; Oktaviani, Intan
Jurnal Sistem Informasi Vol. 12 No. 2 (2025)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsii.v12i2.11017

Abstract

Giving rewards to school students is one strategy to increase learning motivation and participation in school. However, the system used to give rewards is usually still conventional, so it often faces challenges in terms of objectivity and comprehensiveness of assessment criteria. This study aims to apply the K-Nearest Neighbor (KNN) algorithm as an optimization tool in determining student reward recipients in High Schools. The data used include the average report card value, moral values, parents' income, number of siblings and scores in non-academic activities. The KNN method was chosen because of its ability to classify based on the similarity of neighbor data. The research process begins with collecting historical student data, data normalization, determining the KNN model, and evaluating the model. The results of the study show that the KNN model is able to classify students with a certain level of accuracy in recommending the right reward category. The conclusion of this study is that the application of the KNN algorithm can provide a more structured and objective approach to the reward giving process, so that it can help schools make transparent decisions and in accordance with the principles of justice. This system is expected to increase the effectiveness of the reward program and encourage development for students. Keyword : K-Nearest Neighbor, Reward, Classification, Objectivity, Optimization
EVALUASI SISTEM INFORMASI BAGIAN FILING MENGGUNAKAN METODE PIECES DI RUMAH SAKIT PANTI WALUYO YAKKUM SURAKARTA Arif, Yunita Wisda Tumarta; Nurchim, Nurchim; Aulia, Sherina Revita; Nurhayati, Nurhayati
Prosiding Seminar Informasi Kesehatan Nasional 2023 : SIKesNas 2023
Publisher : Fakultas Ilmu Kesehatan Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47701/sikenas.vi.2963

Abstract

Rumah Sakit Panti Waluyo YAKKUM Surakarta memiliki sistem informasi bagian filing yang terintegrasi menjadi salah satu bagian dengan Sistem Informasi Manajamen Rumah Sakit (SIMRS) yang bernama e-filing. Sistem informasi ini diimplementasikan dari bulan April tahun 2021, berdasarkan survei pendahuluan, pengoperasian SIMRS bagian filing masih terjadi kendala dibutuhkannya waktu proses loading untuk menampilkan informasi pada modul menu sehingga menyulitkan petugas menggunakan sistem. Metode yang digunakan untuk mengevaluasi sistem informasi bagian filing adalah metode PIECES. Tujuan dilakukan evaluasi adalah untuk menilai kinerja sistem yang berjalan dengan metode PIECES berdasarkan aspek performance, information, economic, control, dan service. Hasil penelitian ini adalah berdasarkan penilaian responden adalah sistem informasi bagian filing di Rumah Sakit Panti Waluyo YAKKUM Surakarta secara keseluruhan dikategorikan sangat baik dengan rerata presentase 77,40%. Evaluasi sistem informasi bagian filing dari Aspek performance sangat baik presentase 79,13%, sistem mampu menghasilkan troughput, audibilitas, kelaziman komunikasi dan kelengkapan yang sangat baik. Aspek information sangat baik presentase 81,62%, dimana sistem mampu menyajikan informasi, akurasi informasi, aksesbilitas dan relevansi informasi yang sangat baik. Aspek economic Sudah baik presentase 67,74%, dimana reusabilitas sistem dapat dikembangkan sesuai dengan perkembangan perangkat lunak. Aspek control sangat baik presentase 79,4%, dimana keamanan mekanisme dalam mengontrol dan melindungi sistem sangat baik namun tingkat integritas akses data perlu untuk ditingkatkan. Aspek efficiency sangat baik presentase 76,62%, dimana usabilitas usaha untuk mempelajari sistem sangat baik. Aspek service sangat baik presentase 79,94%, dimana sistem memiliki akurasi serta reliabilitas yang sangat baik.
Design And Development of An Automated Watering System For Curly Red Chili Plants Based on Internet Of Things Saputra, Muchammad Yoga; Nurchim, Nurchim; Maulindar, Joni
Journal of Artificial Intelligence and Software Engineering Vol 5, No 3 (2025): September
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i3.7263

Abstract

An ideal soil moisture level between 60% and 80% is crucial for the optimal growth of curly chili plants. However, manual watering methods by farmers are often inefficient and fail to maintain consistent soil moisture. This issue forms the basis of the current research, which aims to develop an automated Internet of Things (IoT)-based watering system for curly chili plants, integrated with a monitoring website. The research method involves using an ESP32 microcontroller connected to a soil moisture sensor and a DHT22 temperature sensor. The data collected by the sensors is sent in real-time to the Firebase Realtime Database as a cloud platform and then visually displayed on a monitoring website. System testing confirmed that the setup successfully monitored soil conditions and air temperature while also controlling a DC mini water pump via a relay for automated watering based on the received data. In conclusion, the implementation of this IoT technology is expected to assist farmers in Kadokan Village in conserving water usage, improving time efficiency, and enhancing the quality and quantity of curly chili production.
Sentiment Analysis of Fans Toward Brand Merchandise Releases Using Support Vector Machine (SVM) Munaiseche, Christian Imanuel; Nurchim, Nurchim; Cipto Utomo, Bangun Prajadi
Journal of Artificial Intelligence and Software Engineering Vol 5, No 3 (2025): September
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i3.7264

Abstract

The release of merchandise by idol groups often sparks various emotional reactions among fans, particularly on social media platforms. This study investigates fan sentiment regarding the birthday merchandise release by JKT48 members on the X (Twitter) platform using the Support Vector Machine (SVM) algorithm. A total of 1,062 comments were collected using the Tweet Harvest tool and manually categorized into three sentiment classes: positive, neutral, and negative. The collected data underwent several pre-processing stages, including case folding, data cleansing, tokenization, and stopword removal. The text data were then transformed into numerical features using the Term Frequency-Inverse Document Frequency (TF-IDF) method. To address the class imbalance issue, the Synthetic Minority Over-sampling Technique (SMOTE) was applied. Experimental results show that the SVM model without SMOTE achieved an accuracy of 84.62% and an F1-score of 76.79%. After applying SMOTE, model performance improved significantly, with accuracy reaching 90.09% and F1-score increasing to 90.15%. Furthermore, the results of 5-fold cross-validation confirmed the positive impact of SMOTE in enhancing the model's ability to classify sentiment, particularly for underrepresented classes.
Co-Authors Abdullah Abdullah Syaifudin Afu Ichsan Pradana Agung Suryadi Agus Riyanto Agustina Srirahayu Ahmad Qashid Husaini Ahmad Setiawan Al Mustofa, Muhammad Hafizh Andrean, Fauzi Andy Ariyanto Ardi Lestari, Sofiana Ardianto Pambudi Arif Wicahyanto Assidiq, Abdul Hafid Atina, Vihi Atmojo, Fattah Satrio Atmojo, Fernando Winantya Aulia, Sherina Revita Awang Long, Zalizah Bagus Muhammad Latif Bondan Wahyu Pamekas Bondan Wahyu Pamekas Carolina Wibowo, Anita Cipto Utomo, Bangun Prajadi Dwi Hartanti Dwi Hartanti Dwi Kurniawan Saputro Edy Kurniawan Eko Purwanto Faiq Muhammad, Nibras Feri Setiyono Gabriel Ardana Hasanah, Herliyani Herliyani Hasanah Ibnu Bagus Setiawan Ichsan Pradana, Afu Ilham Sholeh immaculata yolia dewi Widayanti Indah Nofikasari Indriyas Kukuh Wijayanti Irawan, Etwin Hendri Joni Maulindar Kurniawan, Daniel Ade Mahendra Abdul Rahman, Rizqy Maskhul Ryan Ibrahim Maulindar, Joni Muhammad Rais Ramadhani Mumu, Raul Galvin Rudolf Munaiseche, Christian Imanuel Muttaqi, Bagas Ningsih, Pipin Widya Novianto, Novianto Nugroho, Mohammad Yusuf Nurhayati Nurhayati Nurlita, Catarina Ivanda Nurmalitasari Nurmalitasari Nurmalitasari Nurmalitasari Nurmalitasari Oktaviani, Intan Pamekas, Bondan Wahyu Permatasari, Hanifah Pipit Vidianti Pradana, Afu Ichsan Pramono Pramono Pramono Prasetya, Ian Putra Prastyo, Okik Dwi Pratama, Wahyu Adi Purwanto, Eko Putra Prasetya, Ian Putra Prasetya Putra Pratama, Dita Putra, Wihan Perkasa Nugraha Ragil Saputro, Abdullah Rahadian, Dwiki Rasya Rudi Susanto Rukmini, Siti Santoso, Tri Djoko Saputra, Muchammad Yoga Sari, Nur Avia Adenta Setrayana, Abiyyu Singgih Purnomo Sopingi Sulistyo Wahyu S Sumarlinda, Sri Suryani, Fajar Suryani, Fajar Suryani Taufik Hidayat Tejo Arum, Dinenda Tri Djoko Santosa Untoro, Fendi Uvi Firgianingsih Uvi Firgianingsih Widayanti, immaculata yolia dewi Wijayanti, Indriyas Kukuh Wijiyanto Wijiyanto Wijiyanto Wijiyanto, Wijiyanto Yommy Adhiwira Yudha Yunita Wisda Tumarta Arif Zalizah Awang Long Zalizah Awang Long