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All Journal Jurnal Algoritma Proceedings Konferensi Nasional Sistem dan Informatika (KNS&I) Sinkron : Jurnal dan Penelitian Teknik Informatika Seminar Nasional Teknologi Informasi Komunikasi dan Industri Jurnal Ilmiah Matrik Jurnal Eksplora Informatika JITK (Jurnal Ilmu Pengetahuan dan Komputer) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Voice Of Informatics Jurnal Sistem Cerdas CSRID (Computer Science Research and Its Development Journal) SENSITEK E-JURNAL JUSITI : Jurnal Sistem Informasi dan Teknologi Informasi IT (INFORMATIC TECHNIQUE) JOURNAL Aiti: Jurnal Teknologi Informasi Jurnal Scientia Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Informatics and Digital Expert (INDEX) Jurnal Kewarganegaraan Jurnal PkM MIFTEK Jurnal Algoritma Jurnal Teknologi Informasi
Yoga Handoko Agustin
Institut Teknologi Garut
Religion Aerospace Engineering Arts Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Sentiment Analysis Using Grok AI as an Auto-Labeling Tool in The Text Processing Stage Agustin, Yoga Handoko; Kurniadi, Dede; Julianto, Indri Tri; B. Balilo Jr , Benedicto
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 2 (2025): Research Articles April 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i2.14632

Abstract

A critical aspect of Natural Language Processing (NLP) is text processing, where text labeling represents the most significant challenge due to its resource-intensive nature when conducted manually. At this stage, automatic labeling emerges as a more practical solution, particularly with the advent of Artificial Intelligence (AI), which offers tools to address this obstacle. Grok AI, equipped with a new feature operable on Platform X, provides a promising approach. This study aims to leverage the Grok AI feature on Platform X for automatic text labeling. The research methodology involves labeling text data obtained from a public dataset. To assess the quality of the labeling results, an evaluation method employing Naive Bayes classification modeling is applied. The findings reveal that Grok AI's performance closely approximates that of human labeling. The highest accuracy achieved by Grok AI is 51.71% using the k-Nearest Neighbors (k-NN) algorithm, approaching the human labeling accuracy of 60.52% with k-NN. Furthermore, Grok AI surpasses the performance of VADER labeling, which achieves an accuracy of only 49.49% with Naive Bayes. Consequently, the Grok AI feature on Platform X presents a viable alternative for the automatic labeling of text data.
Implementasi Metode Certainty Faktor Pada Sistem Diagnosa Penyakit Ayam Pedaging (Broiler) Agustin, Yoga Handoko; Mulyani, Asri; Sopandi, Pendi
Jurnal Algoritma Vol 21 No 2 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-2.1526

Abstract

Ayam Pedaging (broiler) merupakan ayam pedaging dengan ukuran tubuh besar yang dapat mencapai berat 1,8-2,5 kg dalam 5-7 minggu. Keunggulan terletak pada efisiensi konversi pakan dengan rasio 1:1,8-2,2, menjadikannya pilihan ekonomis untuk produksi daging. Permintaan terhadap daging ayam pedaging terus meningkat, terutama sebagai sumber  protein hewani, untuk memenuhin kebutuhan pangan masyarakat. Penelitian menerapkan metode ADDIE Analysis pencarian sumber data yang akurat pada seorang pakar, Desain hasil dari Elisitasi oleh seorang pakar, Development mengimplementasikan sistem yang telah direncanakan pada tahap sebelumnya tahap analisis dan desain, Implementasi pengujian sistemmengunakan  black box, Evaluasi meminimalisir kesalahan sistem. Metode "Certainty factor" dari kecerdasan buatan digunakan untuk menghitung tingkat keyakinan diagnosa berdasarkan gejala. Sistem pakar sangat penting bagi industri ayam pedaging dalam memanfaatkan sistem untuk pencegahan penyakit ayam pedaging serta mengatahui ayam sakit dan ayam sehat dan dapat mengurangi jumlah kematian industri ayam. Hasil dari  Penelitan di penghitungan manual yang diberikan nilai oleh seorang pakar  agar dapat dibadingan dengan sistem terdiri dari 10 sempel untuk melakukan nilai akurasi perhitungan pakar dan sistem hasil yang di dapat pada 10 sempel pengujian dengan pakar, 8 diantaranya sesui yang di berikan nilai CF oleh pakar sementara 2 tidak sesui dengan nilai CF oleh pakar menghasilkan nilai akurasi 80 % yang dianggap memadai oleh pakar.
Algoritma Regresi Linier Dalam Prediksi Jumlah Pendaftar Program Pendidikan Di Lingkungan Pesantren : Studi Kasus : Yayasan Al-Mustofa Tambakbaya Agustin, Yoga Handoko; Satria, Eri; Nasrulloh, Anas
Jurnal Algoritma Vol 22 No 1 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-1.1802

Abstract

Al-Mustofa Tambakbaya Foundation manages an Islamic boarding school as well as a Madrasah Aliyah (MA) and Madrasah Tsanawiyah (MTS). Over the past five years, the foundation has experienced fluctuations in the number of new students. This study aims to predict the number of applicants using a linear regression algorithm. The challenge of fluctuating enrollment affects resource planning and curriculum development. The data used includes the number of MA and MTS students from the 2019 to 2023 academic years. This research follows the CRISP-DM stages, starting from business understanding, data collection and preparation, to modeling using linear regression. Model evaluation is done with MAPE, MAE, RMSE, and R-squared. The results show that the model for Regional Domicile and Outside the Region has a MAPE of 8.44% and 12.76%, respectively. The model for MTS students has a MAPE of 6.26% and an R-squared of 91.27%, while the MA student model shows the lowest performance with a MAPE of 20.56% and an R-squared of 21.20%. Predictions for the 2024 academic year show significant growth, especially in regional domicile and MA students. This research offers a practical solution to address fluctuations in enrollment and educational planning at Al-Mustofa Tambakbaya Foundation, as well as highlighting the need for model improvements to increase accuracy in the future.
Prediksi Jumlah Pengunjung Pariwisata di Kabupaten Garut Menggunakan Algoritma Regresi Linear Agustin, Yoga Handoko; Satria, Eri; Siti Nursifa, Fadia
Jurnal Algoritma Vol 22 No 1 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-1.1807

Abstract

Tourism has great potential in driving economic growth through job creation, income enhancement, and positive impacts on various related sectors such as handicrafts, accommodation, and transportation. Garut Regency, located in the southern part of West Java Province, is increasingly recognized for its natural tourist destinations that remain unspoiled and attract many visitors. However, the surge in visitor numbers at these destinations has posed several challenges, including overcrowding that reduces comfort and safety, as well as a decline in service quality due to high demand. Inadequate infrastructure, such as transportation and parking facilities, is also an issue that needs to be addressed. To assist the local government in preparing for future increases in visitor numbers, this study utilizes the Linear Regression algorithm to predict the number of tourist visits to Garut Regency. This algorithm is chosen for its ability to measure the relationship between the dependent variable (number of visitors) and independent variables (factors influencing visits). Data collection is carried out by grouping the number of visitors based on tourist categories, resulting in more accurate and relevant prediction models. The research findings show that the linear regression model can generate predictions with a Mean Absolute Error (MAE) of 11,406.37, Mean Absolute Percentage Error (MAPE) of 6.449, Mean Squared Error (MSE) of 282,815,506.30, and Root Mean Squared Error (RMSE) of 16,817.12. The R-squared (R²) value of 0.9346 indicates that the model can explain approximately 93.46% of the data variance, demonstrating good predictive performance. However, the relatively high MAPE value indicates inconsistencies in the dataset, likely caused by very small or zero actual values. This prediction is expected to assist the Garut Regency Tourism Office in strategic planning and decision-making, such as infrastructure preparation, service quality improvement, and tourism promotion planning. This study also opens up opportunities for further development using other prediction algorithms to achieve more optimal results.
Pemenuhan Kebutuhan Komunitas Maya Dan Pandu Digital Kepada Perangkat Desa di Desa Sindangpalay Hidayat, Miftahul; Multajam, Sri Intan; Adha, Sherly Nabila; Andyarini, Ervina Dwi; Farhan, Muhammad; Aulia, Husni; Sidiq, Repi Fahmi; Nisa, Ziadatun Khoirun; Firmanto, Alam; Afifah, Via Nur; Agustin, Yoga Handoko
Jurnal PkM MIFTEK Vol 3 No 1 (2022): Jurnal PkM MIFTEK
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/miftek/v.3-1.1293

Abstract

Real Work Lecture (KKN) is a form of community service activity by students with an cross-scientific and sectoral approach at a certain time and area. The implementation of KKN activities usually lasts between one to two months and takes place in village-level areas. And the purpose of KKN is so that students can develop ideas based on technology and in an effort to grow, accelerate and prepare development cadres, students gain valuable learning experience through involvement in the community which directly discovers, formulates, solves and tackles development problems in a practical and interdisciplinary, to add insight. Students motivate the community in building villages, to provide experience to students about ways of being in society. The existence of Real Work Lectures has a target so that students can become a ready-to-use generation and at the same time potential successors to development, especially in rural areas, both in the present and in the future. And this report aims to show the results of the KKN activities during the Covid-19 pandemic which we carried out in about a month. Webinars for Virtual Communities. This report also contains information about Sindangpalay Village, where we carried out KKN activities.
Co-Authors Ade Sutedi Adha, Sherly Nabila Afifah, Via Nur Andi Fikri Nugraha Andi Sanjaya Andyarini, Ervina Dwi Anggi Rihadisha Arbi Yuan Aspahany Asep Sugiharto Asgara, Zidan Asri Mulyani Aulia, Husni Ayu Latifah B. Balilo Jr , Benedicto Baswardono, Wiyoga Bayu Muhammad Fauzi Dani Rohpandi Dede Kurniadi Dendi Ramdani Deni Heryanto Ditdit Putuwenda Egi Badar Sambani, Egi Badar Eni Suryeni, Eni Eri Satria Evi Dewi Sri Mulyani Fahmi Fadlillah Falah Insan Pratama Fauzi, Bayu Muhammad Firmanto, Alam Fitri Nuraeni Hari Ilham Nur Akbar HELFY SUSLAWATI Ida Farida Imas Dewi Ariyanti Indri Tri Julianto Intan Hartanti Rahman Ningsih Iwan Setiawan Jungjunan, Aditya Rahma Kusrini, Kusrini Leni Fitriani Leni Fitriani Leni Fitriani, Leni Luthfi, Emha Taufiq Marlina, Rina Miftahul Hidayat, Miftahul Mohamad Fikri Haekal Muhammad Farhan Muhammad Ramdan Rahmatillah Muhammad Rikza Nashrulloh Multajam, Sri Intan Nasrulloh, Anas Nensi Mardhiani Surgawi Nisa, Ziadatun Khoirun Nugraha, Insan Satia Nur'aeni, Irma Oktapiani, Vini Pratama, Fajri Rahayu, Raden Erwin Gunadi Raisman Raisman Ridwan Setiawan Ridwan Setiawan Ridwan Setiawan Rika Lestari Shinta Siti Sundari Sidiq, Repi Fahmi Siti Nursifa, Fadia Sopandi, Pendi Sri Fitrya Kamellia Sri Rahayu Sri Sulastri Srihermaning, Nova _ Susanto Susanto Wahyu Sindu Prasetya Wildan Nugraha Wiyoga Baswardono Yosep Septiana Yuli Nurfitria, Yuli Yusuf Abdul Fatah