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All Journal EXPERT: Jurnal Manajemen Sistem Informasi dan Teknologi International Journal of Artificial Intelligence Research RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Journal of Information Technology and Computer Science (JOINTECS) INTECOMS: Journal of Information Technology and Computer Science Jurnal Riset Informatika Jurnal Informatika Kaputama (JIK) Buana Ilmu Jurnal Informasi dan Teknologi Buana Information Technology and Computer Sciences (BIT and CS) JURNAL PENDIDIKAN, SAINS DAN TEKNOLOGI Infotek : Jurnal Informatika dan Teknologi Djtechno: Jurnal Teknologi Informasi Jurnal Tika Dirgamaya: Jurnal Manajemen dan Sistem Informasi Abdimas Jurnal Komtekinfo Jurnal Buana Pengabdian Innovative: Journal Of Social Science Research JIM: Jurnal Ilmiah Mahasiswa Pendidikan Sejarah INTERNAL (Information System Journal) CSRID
Tukino
Universitas Buana Perjuangan Karawang
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Evaluation of Critical Thinking Disposition in Learning using E-Learning Tukino Paryono; Gunawan Gunawan; Sutarto Sutarto; Danny Manongga
INTERNAL (Information System Journal) Vol. 5 No. 2 (2022)
Publisher : Masoem University

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Abstract

Critical thinking disposition includes seven habits as a motivation in analyzing problems to make decisions in the online learning system applied at the University. E-Learning application as online learning media which is equipped with various facilities to support Lecturer activities.  The purpose of this study was to determine the differences in critical thinking disposition based on the gender of the lecturer and the level of the Lecturer's Academic Position.  The results of the analysis of the calculation of the average score on the evaluation of critical thinking dispositions based on the gender of women (M=3.02) and men (M=3.23) means that there are differences in critical thinking although relatively little. The difference is found in statements related to reading habits, digging and uploading material, easy to receive input, studying material, reviewing assignments and being open.  Meanwhile, the f-count value is 0.903 which is smaller than the f-table is 3.24 at p <0.50, this indicates that there is no significant difference in the Lecturer's Academic Position level in applying critical thinking dispositions in using E-Learning applications for the learning process. Two indicators, gender and Lecturer's Academic Position evaluated with 14 statements for 7 aspects have not shown significant differences, this provides an opportunity to be studied more deeply in compiling statement indicators and can be related to the development of Lecturer's critical thinking disposition with taxono bloom.
Seleksi Penerimaan Bantuan Internet Gratis dengan Menggunakan Metode AHP Tukino Paryono; Muhamad Rizky Arfani; Agustia Hananto; Baenil Huda
INTERNAL (Information System Journal) Vol. 6 No. 1 (2023)
Publisher : Masoem University

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Abstract

The internet is an information technology that is able to provide benefits for life and is a major requirement as a means of communication, entertainment or business. Covid 19 spreads throughout the City or Regency to villages in all regions in Indonesia which has a broad impact on the world of Education, especially Elementary and Middle School Education. Seeing the change in learning patterns from face-to-face to online learning, there are obstacles that are felt by students, especially in learning that requires the teaching and learning process between teachers and students to be carried out remotely (online). To support online learning, adequate internet facilities are needed. Provision of internet packages can be provided free of charge with due observance of predetermined requirements. To support the provision of free internet packages, a decision support system is needed to determine the selection of receiving free internet assistance so that it is right on target by using the Analytical Hierarchy Process (AHP) solving procedure. This method is used to make rankings for selecting free internet recipients, where the highest score is generated based on the best criteria. The results of calculations with this method. Where to make a decision support system in order to prevent errors in determining the criteria that deserve free internet assistance.
Penerapan Software Testing Life Cycle Pada Pengujian Otomatisasi Platform Dzikra Ruliansyah Ruliansyah; Tukino; Baenil Huda; April Lia Hananto
Computer Science Research and Its Development Journal Vol. 15 No. 1: February 2023
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid.15.1.2023.01-11

Abstract

PT Bejana Investidata Globalindo (BIGIO), as an IT consultant and software development company, develops an in-house product called Dzikra which is a platform to help users build good habits in worship. In order to develop this system, the company requires a daily worship content management system known as the Dzikra web admin. The Software Development Life Cycle (SDLC) has several stages, one of the important stages is the testing stage which has the goal of evaluating whether the software has been created in accordance with the specifications and detects bugs or errors. Black box testing automation with Robot Framework can provide good testing documentation and can reduce human errors during the testing process. The implementation of the Software Testing Life Cycle (STLC) in the testing process can also make the testing flow more structured and provide a better focus on each testing stage. The results of the testing show that of the six features tested, they have run as expected. It is hoped that this research will provide support to PT Bejana Investidata Globalindo (BIGIO) in automating software testing process.
Classification Of Kredivo Application Reviews Based On User Satisfaction Aspects With The SVM Method Haprilianh Hasanah; Tukino; Shofa Shofia Hilabi
Jurnal Riset Informatika Vol. 7 No. 4 (2025): September 2025
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v7i4.390

Abstract

The development of the fintech sector in Indonesia has encouraged the creation of various digital payment applications, one of which is Kredivo which provides instant credit and installments without a credit card. In this study, we analyzed and classified Kredivo application user reviews based on satisfaction attributes using the Support Vector Machine (SVM) method. Review data was collected from the Google Play Store and pre-processed using text preprocessing, InSet dictionary-based sentiment tagging, TF-IDF feature extraction, and training-test data splitting in an 80:20 ratio. Based on the analysis, most Kredivo user reviews were observed to have positive sentiment of 38.70%, negative sentiment of 26.90%, and neutral of 34.40%. The SVM model developed for Kredivo review sentiment labeling works with positive, negative, and neutral. Word cloud visualization recognizes the most important words with positive tones such as "mantap", "baik", "cepat", "mudah", and "transaksi", as well as the most important words with negative tones such as "hapus", "bayar", "bulan", "meminjam", and "tidak". The results of this study can be feedback for Kredivo developers and other fintech platforms to improve services based on user needs and demands, as well as strengthen business strategies according to customer satisfaction levels.
MODELING THE DISTRIBUTION OF HIV CASES WITH K-MEANS CLUSTERING CASE STUDY OF WEST JAVA PROVINCE Muhammad Difa Prakoso Fuadi; Tukino; Agustia Hananto; Fitria Nurafriani
Jurnal Riset Informatika Vol. 7 No. 3 (2025): Juni 2025
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2107.927 KB) | DOI: 10.34288/jri.v7i3.374

Abstract

In Indonesia, the problem of HIV/AIDS is a serious concern because the trend of cases tends to increase in several regions, including in West Java Province, 2018 data from the Health Office shows a significant variation in the number of HIV cases among districts and cities in the province, in this journal, a visualization process is carried out using Google Colaboratory (Google Colab) to provide an overview of the distribution pattern of cases based on the results of the K-Means Clustering algorithm. The results showed the existence of three main clusters, namely areas with low, medium, and high numbers of cases. Large cities such as Bandung and Bekasi were in the group with the highest number of cases, while peripheral and rural areas showed lower numbers of cases. This finding is expected to be the basis for formulating more effective health policies, especially in education programs, early detection, and community-based interventions to support the goal of eliminating HIV by 2030, then what can be done is to carry out intervention strategies or steps to prevent the spread of HIV tailored to the risk level of each cluster resulting from clustering analysis. Local governments are expected to utilize the results of this mapping to develop more detailed prevention strategies according to the characteristics of each region.
Text Data Classification Using the SVM Model on the LMDB Minecraft Dataset Bayu Yoga Astario; Tukino; Agustia Hananto; Fitria Nurapriani; Elfina Novalia
Jurnal Informasi dan Teknologi 2025, Vol. 7, No. 2
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.vi0.620

Abstract

Text classification is a fundamental task in Natural Language Processing (NLP) aimed at categorizing text data into predefined classes. This study implements a Support Vector Machine (SVM) model to classify text data from the LMDB Minecraft Dataset, which contains user reviews of the Minecraft movie. The research involves text preprocessing, TF-IDF feature extraction, and SVM model training. The classification results are evaluated using accuracy, precision, recall, f1-score, and confusion matrix metrics. The comment data is also analyzed based on the timing of their appearance in the movie. All processes are visualized in diagrams; the final results are saved in Excel format. The SVM model performs adequately on informal and domain-specific language data, providing a foundation for future research in similar text classification contexts.
SISTEM INFORMASI MANAJEMEN STOK OBAT BERBASIS WEB PADA APOTEK BIMA FARMA Irsyadul I&#039;bad; Tukino Tukino; April Lia Hananto; Baenil Huda; Fitria Nurapriani
EXPERT: Jurnal Manajemen Sistem Informasi dan Teknologi Vol 16, No 1 (2026): Juni
Publisher : Universitas Bandar Lampung (UBL)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36448/expert.v16i1.4801

Abstract

Manajemen stok obat di Apotek Bima Farma masih dilakukan secara manual, sehingga menyebabkan selisih data stok mencapai 8%–12% dan memperlambat proses pencarian serta pelaporan hingga sekitar 3 jam. Penelitian ini bertujuan membuat sistem informasi manajemen stok obat yang berbasis web agar bisa mempercepat dan membuat lebih tepat dalam mengolah data, serta mengurangi perbedaan stok hingga di bawah 2%. Sistem tersebut dibuat dengan menggunakan metode Waterfall, dan dalam pembuatan nya dilakukan perancangan menggunakan UML serta ERD. Sistem ini kemudian diimplementasikan dengan menggunakan framework CodeIgniter 3 yang berbasis PHP dan MySQL, serta menerapkan arsitektur MVC. Uji coba dilakukan dengan metode Black Box terhadap 12 skenario dan berhasil mencapai tingkat keberhasilan 100%. Selain itu, juga dilakukan pengujian dengan metode White Box dan diperoleh nilai kompleksitas siklomatis V(G) = 2. Hasil menunjukkan bahwa sistem berhasil mengotomatisasi proses pencatatan transaksi, memberikan informasi stok secara langsung dan segera, serta menghemat waktu dalam pembuatan laporan dari sekitar 3 jam menjadi kurang dari 30 menit. Selain itu, perbedaan antara stok yang ada dan yang diperlukan berhasil dikurangi hingga di bawah 2%. Dengan demikian, sistem yang dikembangkan efektif dalam meningkatkan efisiensi dan akurasi pengelolaan stok obat serta layak diterapkan pada apotek skala kecil hingga menengah
ANALISIS USER SENTIMENT APLIKASI GOOGLE MAPS, MAPS.ME DAN WAZE MENGGUNAKAN METODE SUPPORT VECTOR MACHINE Ilham Fariz Asya Mubarok; Baenil Huda; Agustia Hananto; Tukino Tukino; Huban Kabir
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 8 No 1 (2023): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v8i1.3020

Abstract

Nowadays, the routing app is often used by many people, this app is very useful for users to find the best route by just entering the address code, this app can provide travel routes which can be taken by different kinds of vehicles. In Indonesia itself, there are several widely used route guidance apps with various positive and negative reviews. In this study, different types of apps namely Google Maps, Maps.me and Waze were used and the data is from user feedback through an online survey. The purpose of this study is to find out the users' ratings for each application which was used as the material for the study. Support Vector Machine method was used to process the data. For each app, 750 comments were received and the final result of maps.me was the app with the highest score based on 86.40% accuracy, 86.55% precision and 99.69% recall. The maps.me app received 68% positive reviews, followed by Waze with 29% and Google Maps with 3%. This makes maps.me the app with the highest score based on positive reviews.
Assessment Decision Support System Best Teacher By Using Analytical Hierarchy Process (AHP) Method April Lia Hananto; Bayu Priyatna; Fitria Nurapriani; Ahmad Fauzi; Tukino Tukino; Naufal Zubdi Ahnaf
International Journal of Artificial Intelligence Research Vol 6, No 1.1 (2022)
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v6i1.1.572

Abstract

Assessment of teachers by the Principal of SMA Negeri 1 Kedungwaringin certainly needs to be done to determine the best teacher, so that teacher performance is in accordance with the specified competencies because the teacher is the most important and influential role in the world of education in the process of teaching and learning activities. The assessment was carried out not only for civil servants (PNS), including honorary teachers who also participated in the assessment process so that there were no limitations in evaluating teachers at SMA Negeri 1 Kedungwaringin. This assessment process uses the Analytical Hierarchy Process (AHP) Algorithm. The method used aims to determine the best teacher at SMA Negeri 1 Kedungwaringin who is in accordance with the assessment criteria prepared. The results of the ranking show that Dian Purwanti, S.Pd obtained the highest score of 0.342 out of 5 other teachers. This application is expected to assist school principals in determining the best teacher based on the criteria and weight of each existing value.
KLASIFIKASI ULASAN APLIKASI KOPI KENANGAN PADA GOOGLE PLAYSTORE MENGGUNAKAN ALGORITMA NAIVE BAYES Muhammad Abil Fadli; Tukino tukino; Elfina Novalia; April Lia Hananto
Djtechno: Jurnal Teknologi Informasi Vol 6, No 2 (2025): Agustus
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/djtechno.v6i2.7037

Abstract

Aplikasi Kopi Kenangan merupakan aplikasi yang digunakan untuk pemesanan minuman secara online milik perusahaan PT Bumi Berkah Boga. Selain hal tersebut aplikasi ini juga membantu perusahaan menerima ulasan terkait pengalaman pelanggan dalam menggunakan layanan aplikasi kopi kenangan. Namun ulasan pelanggan di Google Playstore memiliki jumlah data yang banyak sehingga sulit dianalisis secara manual. Tujuan penelitian ini melakukan klasifikasi ulasan pelanggan pada aplikasi Kopi Kenangan mempergunakan algoritma Naïve bayes. Metode penelitian ini meliputi pengumpulan data, preprocessing, pemodelan dan evaluasi. Data yang dipergunakan dalam penelitian ini yaitu sebesar 1000 data dengan lima kategori yaitu promo, pelayanan, performa aplikasi, transaksi dan kualitas produk. Hasil penelitian menunjukkan bahwa kategori ulasan terbanyak adalah tentang performa aplikasi dengan persentase 45% dari total 1000 data ulasan. Hasil akurasi penelitian yaitu sebesar 85% yang menunjukkan bahwa model dapat melakukan klasifikasi data kategori sentimen dengan cukup baik.
Co-Authors ., Widiyawati Aditia Agustian Adittia Agustian Agneresa Agneresa Ahmad Fauzi Ammar Sufyan April Lia Hananto Aprilia Putri Nardilasari Aurel Adhitya Anwar Awaljan Situmorang Baenil Huda Bayu Yoga Astario Danny Manongga Daryanto Herdiana Dyno Syaiful Annam Faqih Pratama Muthi Fitria Nurafriani Fitria Nurapriani Fitria Nurapriani Fitria Ratna Sari Fizra Firdaus Nillan Gunawan Gunawan Hananto, Agustia Haprilianh Hasanah Huban Kabir Ilham Fariz Asya Mubarok Insan Kamaludin Arifin Irpan Hilmi Irsyadul I&#039;bad Kamila Berkah* Muhamad Djaka Permana Muhamad Rizky Arfani Muhammad Abil Fadli Muhammad Difa Prakoso Fuadi Muhammad Hatami Muhammad Khaerudin Naufal Zubdi Ahnaf Novalia, Elfina Novia Cahya Utami Priyatna, Bayu Riandi Nandaputra Ruliansyah Ruliansyah Saepul Aripiyanto Saepul Aripiyanto Sandi Ahmad Seia Piantara Shofa Shofia Hilabi Shofa Shofiah Hilabi Siti Masruroh Sutarto Sutarto Tatuhey, Emy Lenora Tita Puspita Sari Witulas Ambang Cahyati Wresti Andriani