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All Journal Jurnal technoscientia Jurnal Informatika dan Teknik Elektro Terapan ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika International Journal of Artificial Intelligence Research Informatics for Educators and Professional : Journal of Informatics KOPERTIP: Jurnal Ilmiah Manajemen Informatika dan Komputer JURNAL ILMIAH INFORMATIKA Conference SENATIK STT Adisutjipto Yogyakarta Jurnal ICT : Information Communication & Technology Jurnal Sistem Informasi Kaputama (JSIK) Jurnal Pelayanan dan Pengabdian Masyarakat (Pamas) JISKa (Jurnal Informatika Sunan Kalijaga) Jurnal Informatika dan Rekayasa Perangkat Lunak JURSIMA (Jurnal Sistem Informasi dan Manajemen) JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Teknik Informatika C.I.T. Medicom JURNAL TEKNOLOGI TECHNOSCIENTIA Jurnal Informatika Terpadu Baselang: Jurnal Ilmu Pertanian, Peternakan, Perikanan dan Lingkungan Jurnal Janitra Informatika dan Sistem Informasi Abdimas Altruis: Jurnal Pengabdian Kepada Masyarakat Jurnal Informatika Teknologi dan Sains (Jinteks) International Journal of Hydrological and Environmental for Sustainability Literasi: Jurnal Pengabdian Masyarakat dan Inovasi J-Icon : Jurnal Komputer dan Informatika Jurnal Teknologi Pangan dan Industri Perkebunan JURSIMA AMMA : Jurnal Pengabdian Masyarakat Jurnal Informatika: Jurnal Pengembangan IT Jurnal Sistem Informasi dan Manajemen Jurnal Accounting Information System (AIMS) INTERNAL (Information System Journal)
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Journal : Jurnal Informatika Terpadu

 1 
Prediksi Hasil Panen Padi Tahun 2023 menggunakan Metode Regresi Linier di Kabupaten Indramayu Diyanti yanti; Martanto; Agus Bahtiar
Jurnal Informatika Terpadu Vol 9 No 1 (2023): Maret, 2023
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jit.v9i1.657

Abstract

Indramayu Regency has the West Java region's largest harvested land area and the most rice production. The size of harvested land in the Indramayu Regency area has also increased from year to year. In 2019 Indramayu Regency had a land area of 215,731 Ha; then, land acquisition increased the size of land in Indramayu Regency in 2020 it increased to 226, 626 Ha, and in 2021 it increased again to 227,051 Ha. Certain factors play an essential role in raising standards and increasing productivity. These factors are planting area, harvested area, rainfall, and crop failure, where these factors cannot be predicted. This research will discuss the application of the Linear Regression method, namely the method used to examine the relationship between a tertiary variable and two or more secondary variables. Based on predictions using the python programming language, the rice harvest in 2023 is 1510403 tons/GKP, with MAE, MSE, RMSE, and R2-Score values. The system displays MAE (Mean Absolute Error) values: 5449.45, MSE (Mean Squared Error) values: 72325540.80, RMSE (Roots Mean Squared Error): 8504.44, and R2-Score: 0.93 with predictions that 2023 will experience a decrease from the previous year.
Analisis Algoritma K-Nearest Neighbor terhadap Sentimen Pengguna Aplikasi Shopee Muhammad Saifurridho; Martanto Martanto; Umi Hayati
Jurnal Informatika Terpadu Vol 10 No 1 (2024): Maret, 2024
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jit.v10i1.1054

Abstract

One way to gauge users' thoughts and sentiments towards a particular product, service, or subject is by conducting sentiment analysis on reviews posted on the Google Playstore platform. Among the plethora of apps available on the Google Playstore is Shopee. Due to the vast and unstructured nature of user comments in the review section, it becomes challenging to quickly and accurately grasp the overall information. This research aims to classify sentiments as positive, negative, or neutral, with the hope that the Shopee app can improve. Hence, the K-Nearest Neighbor Algorithm is employed to analyze sentiments to ensure users' opinions regarding their interaction with the Shopee program. Sentiment analysis is utilized to categorize reviews into positive, neutral, and negative groups. A dataset of 2000 entries is used in this analysis, obtained through web scraping, with 70% as training data and 30% as test data. The results indicate that this data split scenario yields the best model, achieving an accuracy of 70%, precision of 50.5%, recall of 44.8%, and an F1-score of 48.3% overall. To optimize results further, the implementation of more optimal data sampling techniques is necessary to attain a more balanced class distribution in both training and test data.
Analisis Algoritma K-Nearest Neighbor terhadap Sentimen Pengguna Aplikasi Shopee Saifurridho, Muhammad; Martanto, Martanto; Hayati, Umi
Jurnal Informatika Terpadu Vol 10 No 1 (2024): Maret, 2024
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jit.v10i1.1054

Abstract

One way to gauge users' thoughts and sentiments towards a particular product, service, or subject is by conducting sentiment analysis on reviews posted on the Google Playstore platform. Among the plethora of apps available on the Google Playstore is Shopee. Due to the vast and unstructured nature of user comments in the review section, it becomes challenging to quickly and accurately grasp the overall information. This research aims to classify sentiments as positive, negative, or neutral, with the hope that the Shopee app can improve. Hence, the K-Nearest Neighbor Algorithm is employed to analyze sentiments to ensure users' opinions regarding their interaction with the Shopee program. Sentiment analysis is utilized to categorize reviews into positive, neutral, and negative groups. A dataset of 2000 entries is used in this analysis, obtained through web scraping, with 70% as training data and 30% as test data. The results indicate that this data split scenario yields the best model, achieving an accuracy of 70%, precision of 50.5%, recall of 44.8%, and an F1-score of 48.3% overall. To optimize results further, the implementation of more optimal data sampling techniques is necessary to attain a more balanced class distribution in both training and test data.
Analisis Sentimen Aplikasi SeaBank dengan Algoritma Naive Bayes untuk Optimalisasi Pelayanan Putri, Niken Zeliana; Martanto, Martanto; Dikananda, Arif Rinaldi; Rifa’i, Ahmad
Jurnal Informatika Terpadu Vol 11 No 1 (2025): Maret, 2025
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jit.v11i1.1721

Abstract

The rapid development of digital banking technology requires improvements in service quality to remain competitive in the financial industry. Seabank Indonesia is one of the widely used digital banking applications, making sentiment analysis of user reviews an essential aspect of understanding their perceptions of the provided services. This study evaluates user sentiment toward the Seabank application by implementing the Naïve Bayes algorithm to optimize service quality. The research data was obtained through a web scraping process from the Google Play Store, totalling 1,000 reviews. The Knowledge Discovery in Databases (KDD) approach was applied in the analysis, encompassing preprocessing stages such as cleaning, casefolding, tokenization, stopword removal, stemming, and Term Frequency-Inverse Document Frequency (TF-IDF) representation. The classification model was built by splitting the dataset into 70% training and 30% test data. The evaluation results indicate that the developed model achieved an accuracy of 88%, with a precision of 95%, recall of 87%, and F1-score of 91%. An analysis of all reviews revealed that 70.5% were positive, while 29.5% were negative. These findings demonstrate that the Naïve Bayes algorithm is effective in analyzing user sentiment and provides valuable insights for developers to enhance the quality of Seabank Indonesia’s services.
Co-Authors A, Ronny Abdillah, Naufal Abdul Rosid, Rizal Ahmad Rifai Aji Dian Permana, Muhamad Aji Saputra, Mohammad AKBAR, MUHAMAD DENI Alfin Maulana Almadina, Muhammad Fitrian Shousyade Alpian Novansyah, Indi Andini, Eva Ardhanur, Ichlas Asmana, Asmana Augustian Pangestiazi, Irvanda Azahra, Amaliyah Putri Aziz Sahidin, Naufal Bernadeta Wuri Harini Cep Lukman Rohmat Chrisna Basila Rahman, Muhammad Damar Widjaja Darmanto Darmanto Dea Eryanti Putri Dewi Yuliyanti, Dewi Dian Ade Kurnia Dias Bayu Saputra Dikananda, Arif Rinaldi Dilita Pramasmawari Lita Dita Rizki Amalia Diyanti yanti Djoko Untoro Suwarno Dwi Hastuti, Ningrum Edy, Benediktus Yudha Fadhil Muhammad Bsysyar Faisal Adam, Faisal Faizal Rizqi, Muhammad Faroman Syarief, Faroman Fathur Rezki Junaedi, Muhammad fatimah, lilis Fauzan Afrizal, Ricky Febriani, Budi Febriyani, Adinda Fihir, Muhammad Fithriyani, Nurul Muna Fuji Astri, Dewanti Gifthera Dwilestari Hamam, Moh Hardika Hardika, Hardika Harini, BW Haryanto, Agustinus Surya Hayati , Umi Hayati, Umi Heliyanti Susana Hepsi Nindiasari Hidayat, Fajar Ignatius Adi Prabowo Ika Anikah Iksan Maulana, Muhammad Irfan Ali Irfan Ali, Irfan irfan cholid Iswanjono Iswanjono Jamaludin, Maulana Jamalul'ain, Abdul Kamil, Firmanilah Khoirunisa, Pitria Kholilullah, Mohammad khusnul khotimah Linggo Sumarno Lukmanul Hakim Lutfi Hakim Ma'arif Syaefullah, Muhammad Mahardika, Fathoni Maulana Jamaludin Maulana Yusuf, Muhammad Meida Nurus Mirna Mirna Moruk, Ewaldus Mu'min Azis, Muhammad Mubarok Mubarok Muhamad Djaelani Muhamad farhan Tholhah hidayat Muhamad Jihad Andiana Muhamad Taufik Sugandi Muhammad Aditya Rabbani Adit Muhammad Fadhilah Muhammad Haikal Muhammad Hasan Fadlun Muhammad Saifurridho Mujibulloh, Mujibulloh Mulyawan Mulyawan, Mulyawan Musyarofah Musyarofah, Musyarofah Muzani, Muhamad Muzilin, Elin Nailil Amani, Najiyah Nana Suarna Nanita, Nanita Nining Rahaningsih Nova Zulfahmi, A Nova Zulfahmi, A. Nur Asih, Nur Nur Hermawan, Ilham Nurhanifah, Indah Odi Nurdiawa Odi Nurdiawan Panca Wardanu, Adha Petrus Setyo Prabowo Prabowo, PS Prahara, Sukma Primawan, A.Bayu Puji Rahayu Putri, Niken Zeliana Raditya Danar Dana Ramdan Adi Surya, Muhamad Rifa'i, Ahmad Rifa’I, Ahmad Rinaldi Dikananda, Arif Rinaldi, Arif Riskandi, Muhammad Rizal Rizal Rizka Amelia Rohman, Dede Ronny Dwi Agusulistyo Saeful Anwar Safrudin, Muhamad Saifurridho, Muhammad Salsabila Ainal Wasilah, Qonita Samsudin, Risma'ruf Setiyani, Th. Prima Ari Setiyani, TPA Siti Paridah, Ninda Sri Suwartini Subur, Muhamad Sulistiyana Sulistiyana Sumarno, L Suryaningsih Suryaningsih Suwarno, DU Syahri, Ibnu Nava Syam Al ghifari, Muhammad Syamsul Aripin, Muhammad Syaripah, Imas Syifa, Nurkhasanah Fadhila Tati Suprapti Thomas Agam Tjendro Tri Anelia Tri Gustiane, Indri Tuti Hartati Umi Hayati Ummiyati Ummiyati W Widyastuti, W Wibowo, Daniel Widjaja, D Wihadi, Dwiseno WIHADI, RB DWISENO Willy Prihartono Wiwien Widyastuti Wujarso, Riyanto Yudhistira Arie Wijaya Zulfahmi, A. Nova