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All Journal Tekno - Pedagogi : Jurnal Teknologi Pendidikan Teknika TELKOMNIKA (Telecommunication Computing Electronics and Control) Primary: Jurnal Pendidikan Guru Sekolah Dasar Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Jurnal CoreIT Journal of Natural Science and Integration Seminar Nasional Teknologi Informasi Komunikasi dan Industri J I M P - Jurnal Informatika Merdeka Pasuruan Applied Information System and Management Jurnal Nasional Komputasi dan Teknologi Informasi JURIKOM (Jurnal Riset Komputer) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal IDAMAN (Induk Pemberdayaan Masyarakat Pedesaan) Building of Informatics, Technology and Science Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Zonasi: Jurnal Sistem Informasi INFORMASI (Jurnal Informatika dan Sistem Informasi) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Jurnal Sistem Komputer dan Informatika (JSON) TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Teknik Informatika (JUTIF) Jurnal Computer Science and Information Technology (CoSciTech) Jurnal Pendidikan dan Teknologi Indonesia Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer Knowbase : International Journal of Knowledge in Database Malcom: Indonesian Journal of Machine Learning and Computer Science SATIN - Sains dan Teknologi Informasi
Pizaini Pizaini
Universitas Islam Negeri Sultan Syarif Kasim Riau
Aerospace Engineering Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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Klasifikasi Sentimen Masyarakat Terhadap Kaesang Pangarep pada Media Sosial Twitter/X Menggunakan MLP Classifier dengan Fitur FastText Tarmizi, Veci Cahyono; Agustian, Surya; Okfalisa, Okfalisa; Pizaini, Pizaini
TIN: Terapan Informatika Nusantara Vol 6 No 7 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i7.8815

Abstract

Social media has become a primary channel for the public to express their opinions and reactions toward various political developments in Indonesia. One of the prominent discussions revolves around Kaesang Pangarep’s appointment as the Chairman of the Indonesian Solidarity Party (PSI). This study aims to analyze and classify public sentiment regarding this issue by employing the Multi-Layer Perceptron (MLP) algorithm integrated with FastText-based text representation. The dataset was collected from Twitter using keywords such as “Kaesang PSI”, and was further expanded with additional data from general topics including Covid-19 and Open Topic, ensuring a balanced distribution across positive, neutral, and negative sentiment categories for a more comprehensive representation of public opinion. The model’s performance was evaluated through four metrics: accuracy, precision, recall, and F1 Score. The experimental results demonstrate that the MLP–FastText model achieved consecutive scores of 0. 5129 for F1 Score, 0. 6035 for accuracy, 0. 5319 for precision, and 0. 5996 for recall. These findings indicate that the combination of MLP and FastText effectively captures sentiment patterns within textual data, particularly in the context of unstructured and dynamic social media content, and performs well when enhanced with relevant external data augmentation strategies.
Penerapan Algoritma C4.5 Mengklarifikasi Penerimaan Bantuan Sosial Menggunakan Feature Selection M Wandi Dwi Wirawan; Siska Kurnia Gusti; Jasril Jasril; Pizaini Pizaini
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 1 (2023): September 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i1.6653

Abstract

The Indonesian government's efforts to overcome poverty in Indonesia are through the Smart Indonesia Card (KIP) program which is carried out by the government in the form of providing assistance to underprivileged families. The main aim of distributing KIP assistance is to help send underprivileged children to continue their education, the difficulties found in receiving KIP are due to the large number of residents registering, as well as the data having several conditions, the limited time available in providing KIP by sub-district parties, the completion base is relatively low, therefore the provision of assistance must be right on target. Therefore, the aim of this research is to look for the most influential attributes in receiving KIP assistance in order to improve the results of the data verification process. After carrying out Feature Selection using Information Gain, the most influential attributes can be obtained. The influences are Number of Art, Number of Rooms, Cooking Room, Refrigerator, Motorbike. Therefore, we need to know some of the attributes that most influence the selection of KIP assistance so that we can get accuracy values from decision tree modeling using the C4.5 algorithm or decision tree. Test This experiment can produce a decision tree in which the Number of Art attribute is the most influential attribute with the success rate of KIP acceptance. This evaluation uses a confusion matrix to obtain an accuracy value of 98.21%, precision of 98.21%, recall of 99.48%.
Penerapan Seleksi Fitur Untuk Klasifikasi Penerima Bantuan Sosial Pangkalan Sesai Menggunakan Metode K-Nearest Neighbor Muhammad Fauzan; Siska Kurnia Gusti; Jasril Jasril; Pizaini Pizaini
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 1 (2023): September 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i1.6654

Abstract

The inability to fulfill basic human needs is how poverty is defined. To address this issue, the indonesian goverment implements various social assistance programs, one of which is Kartu Indonesia Pintar (KIP), aimed at providing free education to children aged 7-18 who are economically disadvantaged. However, in the distribution of aid in the Pangkalan sesai sub-district, distributing officers often face challenges due to the high number of eligible recipients applying, complex data requierements, and limited time for the officers. Distributing this social assistance accurately is crusial. Therefore, this research aims to determine the accuracy value for the data of potential recipients of the Kartu Indonesia Pintar (KIP to enhance the data verification process’s outcomes. To tackle this issue, the research employs the K-Nearest Neighbor (K-NN) algoritm and also employs feature selection using Information Gain to reduce less influential attributes. The data used consists of 1998 records of KIP beneficiaries from the 2023 in excel format, with 33 attributes. After performing data cleaning an Information Gain-based feature selection, the dataset is reduced to 1675 records, with 5 selected attributes. The best classification result in this study is achieved with ratios of 7:3 and 8:2, and a value of k = 5, yielding the highest accuracy of 98,21%. The lowest accuracy is obtained using a ratio of 9:1 with the same k value when not using Information Gain, resulting in an accuracy of 89,82%.
Klasifikasi Sentimen Komentar Youtube Tentang Pembatalan Indonesia Sebagai Tuan Rumah Piala Dunia U-20 Menggunakan Algoritma Naïve Bayes Classifer Ilham Habibi Hasibuan; Elvia Budianita; Surya Agustian; Pizaini Pizaini
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 2 (2023): Desember 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i2.7096

Abstract

Text mining is a method used to perform tasks such as document classification, clustering, information extraction, sentiment analysis, and information retrieval. The Federation Internationale Football Association (FIFA), the international football governing body, has designated Indonesia as the host country for the U-20 World Cup starting in 2019. Indonesia is expected to be the choice venue for the U-20 World Cup in 2021. However, due to the Covid outbreak -19, the World Cup was rescheduled and is now scheduled to take place in 2023. Indonesia officially relinquished its position as host on March 31 2023. One of the reasons is the many factions that oppose the presence of the Israeli national team in Indonesia. As a result, various public reactions responded to Indonesia's decision to cancel holding the U-20 World Cup, especially on the Narasi tv YouTube channel video entitled "The U-20 World Cup Failed to Be Held in Indonesia, Let's Look at it from Two Perspectives | Discussion". Since the video was uploaded until August 16 2023, the total comments generated were 4,629 comments. This research uses a Naïve Bayes classifier approach. Naïve Bayes Classifier (NBC) is a direct probabilistic classifier that exploits Bayes' Theorem under strong independence conditions. The tests carried out show that the model performance when using stopword removal and stemming techniques is superior in classifying classes in the dataset. The F1-Score is 59.70% and the Accuracy value is 63.43%. Furthermore, after identifying the most efficient model for applying naïve Bayes classification, evaluation was carried out on validation data resulting in an F1-Score of 58.72% and an accuracy rate of 61.65%. Classification analysis shows that Indonesian people have a negative view or are disappointed with the cancellation
Expert Validation: Development of an Ethnoscience-Based E-Module to Improve Students' Critical Thinking Skills and Environmental Awareness Yovita, Yovita; Pizaini, Pizaini; Berlian, Mery; Tahir, Musa; Vebrianto, Rian
Tekno - Pedagogi : Jurnal Teknologi Pendidikan Vol. 16 No. 2 (2026): Tekno-Pedagogi
Publisher : Program Magister Teknologi Pendidikan Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aims to develop an ethnoscience-based e-module on the subject of Living Things and Their Environment to improve critical thinking skills and environmental awareness of junior high school students. The background of this study is based on the weaknesses of conventional learning which is still teacher-centered, abstract, and does not integrate local cultural values thus hampering active student involvement and their understanding of environmental issues. The study used the Research and Development (R&D) method with the ADDIE (Analysis, Design, Development, Implementation, Evaluation) development model. The subjects were junior high school students in Pekanbaru City. The instruments used included a validity questionnaire from media & technology experts, material & pedagogical experts, linguists, and ethnoscience experts; as well as a questionnaire on teacher practicality and student practicality. The results of validation by media, language, material, and ethnoscience experts showed that the e-module had a very good validity level with an average of 88.25%, as well as a very good practicality value with an average of 85%. Thus, this ethnoscience- based e-module is declared feasible, practical, and effective as a contextual learning medium that integrates scientific concepts with local wisdom and supports 21st-century learning
Co-Authors Abdillah, Rahmad Adha, Martin Aditya Dyan Ramadhan Afdhalel Vickro Agung Teguh Wibowo Almais Ahmad Fauzan Akhyar, Amany Albis Ya Albi Alwis Nazir Alwis Nazir Andrian Wahyu Arvansyah, M Afdhol Aslis Wirda Hayati Ayu Fransiska Bebi Oktaviani Che Hussin, Ab Razak citra ainul mardhia putri Deny Dewana Hastanto Dhymas Julyan Riyanto Eka Pandu Cynthia Elin Haerani Elvia Budianita Fadhilah Syafria Fahmi Kasri Fajar Febriyadi Fakhrezi, Muhammad Dzaki Faris Apriliano Eka Fardianto Faris Fauzan Ray T Febi Yanto Fitra Kurnia Fitri Insani Fitri Insani Fitri Insani Fitri, Dina Deswara Gusti, Siska Kurnia Haikal Zikri Heru Sukoco Husnan Husnan Ibrahim Armadian Pujakesuma Ilham Habibi Hasibuan Iwan Iskandar Iwan Iskandar Iwan Iskandar Iwan Iskandar Iwan Jasril Jasril Jesi Alexander Alim Jesi Alexander Alim Kana Saputra S Khonofi, Khoidir Lestari Handayani Lola Oktavia m azwan M Wandi Dwi Wirawan M. Saski Mandiro, Mulia Anton Mery Berlian Muhammad Affandes Muhammad Affandes Muhammad Fauzan Muhammad Fikry Muhammad Irsyad Muhammad Irsyad Muhammad Ridha Mulia Anton Mandiro Musa Thahir Muslimin, Al’hadiid Najmi, Risna Lailatun Nanda Sepriadi Nazir, Alwis Nazruddin Safaat H Neni Hermita Novi Yanti Novialdi T Novri Rahman Novriyanto Novriyanto Nur Iza Nuradha Liza Utami Okfalisa Okfalisa Okfalisa Okfalisa Putri, Adilah Atikah Rahmad Abdillah Rahmad Kurniawan Reski Mai Candra Reski Mai Chandra Rometdo Muzawi, Rometdo Roziana Roziana, Roziana Saktioto Saktioto Suci Rahayu Sugi Guritman Sukma Evadini Surya Agustian Suwanto Sanjaya Syarifuddin Syarifuddin Tahir, Musa Tarmizi, Veci Cahyono Teddie Darmizal Thahir, Musa Tommy Tanu Wijaya Umar Syarif Vebrianto, Rian Wenny Tarisa Oktaviany Wirdiani, Putri Syakira Yelfi Vitriani Yovita Yovita Yusra Yusra, Yusra Zuriati Ardila Safitri