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All Journal Jurnal Ilmiah KOMPUTASI SemanTIK : Teknik Informasi Prosiding Seminar Nasional Riset Kuantitatif Terapan 2017 Simtek : Jurnal Sistem Informasi dan Teknik Komputer Indonesian Journal of Electrical Engineering and Computer Science JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat) Just TI (Jurnal Sains Terapan Teknologi Informasi) Jurnal Pengabdian Masyarakat Ilmu Terapan (JPMIT) Jurnal Matematika, Komputasi dan Statistika Jurnal Fokus Elektroda (Energi Listrik, Telekomunikasi, Komputer, Elektronika dan Kendali) JURNAL PENGABDIAN MASYARAKAT AKADEMISI AnoaTIK: Jurnal Teknologi Informasi dan Komputer ANIMATOR SISFOTENIKA Jurnal Pengabdian Kepada Masyarakat (JAPIMAS)
Natalis Ransi, Natalis
Department Of Computer Science, Halu Oleo University
Religion Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Environmental Science Materials Science & Nanotechnology Mathematics Social Sciences

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Sistem Rekomendasi dan Peminjaman Buku Menggunakan Algoritma Hybrid Based Filtering Lily Aprilyani; Ransi, Natalis; Saputra, Rizal Adi; Isnawaty, Isnawaty
SISFOTENIKA Vol. 14 No. 2 (2024): SISFOTENIKA
Publisher : STMIK PONTIANAK

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Abstract

SMAN 1 Ladongi in East Kolaka has gained a reputation as an educational institution that is highly committed in providing quality education for the younger generation. SMA Negeri 1 Ladongi in East Kolaka Regency has a diverse collection of books, but the library service is still done manually. This process is not only time-consuming, but also less efficient, especially considering the large number of book collections. Implementing an online book recommendation and lending system can be a solution to improve the effectiveness and efficiency of library services. With a mobile web-based system, students and library staff can easily access book recommendations and perform the loan process online. This research uses a Hybrid Recommendation System that combines Item-Based Collaborative Filtering and User-Based Collaborative Filtering methods. The combination of these two methods aims to obtain better recommendation results. Based on the results of testing the accuracy of the recommendations that have been carried out, it is obtained for the MAE value of 4.52, then the MSE value is 0.02 and for the MAPE value obtained is 0.76%.
Sistem Rekomendasi Produk UMKM Menggunakan Algoritma User-Based Collaborative Filtering Berbasis Website Esy Anugerah Rahayu Kasim; Statiswaty, Statiswaty; Ransi, Natalis; Isnawaty, Isnawaty
SISFOTENIKA Vol. 14 No. 2 (2024): SISFOTENIKA
Publisher : STMIK PONTIANAK

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Abstract

Kolaka Regency is one of the regions in Southeast Sulawesi Province that is rich in quality MSME products, but faces obstacles in promoting these products to a wider market. This research aims to adapt and optimise the UBCF method for the Kolaka MSME context and improve the algorithm to overcome the challenges faced, especially data limitations and variations in customer preferences that change quickly. This research method uses a recommendation engine approach with the UBCF method, which is applied through the stages of data preparation, UBCF implementation on a web-based system, and recommendation accuracy testing. The data used is product rating data from users, which is then processed using UBCF. The test results show that this recommendation system is able to provide fairly accurate rating predictions. Based on the results of testing the accuracy of the recommendations that have been carried out, it is obtained for the MAE value of 1.11, then the MSE value of 0.0649 and for the MAPE value obtained of 1.65%. This research contributes to improving the competitiveness of MSME products in Kolaka through UBCF technology, and provides a model that can be applied in other areas with similar characteristics.
ANALISIS SENTIMEN PENGGEMAR SEPAK BOLA TERHADAP PROSES NATURALISASI PEMAIN TIMNAS INDONESIA PADA MEDIA SOSIAL X MENGGUNAKAN SUPPORT VECTOR MACHINE Amal Anugra; Natalis Ransi; Gusti Arviana Rahman
AnoaTIK: Jurnal Teknologi Informasi dan Komputer Vol 3 No 1 (2025): Juni 2025
Publisher : Program Studi Ilmu Komputer FMIPA-UHO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33772/anoatik.v3i1.70

Abstract

Abstract The naturalization process for players for the Indonesian national team has become a hot topic of discussion among football fans. Social media, especially platform X, has become one of the main places for fans to express their opinions and sentiments regarding this matter. This research aims to analyze football fans' sentiments towards the naturalization process of Indonesian national team players using the Support Vector Machine (SVM) method. Sentiment analysis can be used to analyze supporters' opinions and group them into three categories, namely positive, neutral and negative. This research uses the Support Vector Machine method to carry out classification which is carried out with a dividing line (hyperplane) that separates the classes in the data collection of supporters' tweets on social media X (twitter) who have opinions about naturalization. The research results show that the sentiment of Indonesian football fans towards the naturalization process for national team players mostly tends to be positive, with the proportion of positive sentiment reaching 38%, negative sentiment of 37%, and neutral sentiment of 25%. This analysis also reveals several factors that influence fan sentiment, including the performance of naturalized players on the field, football federation policies, and the influence of the media and public opinion.
SISTEM PENDUKUNG KEPUTUSAN PENENTUAN KARYAWAN TERBAIK MENGGUNAKAN METODE SIMPLE ADDITIVE WEIGHTING STUDI KASUS RUMAH SAKIT HATI MULIA KENDARI Achirul Slamet Sugiarto; La Ode Saidi; Natalis Ransi; Andi Tenriawaru; Ferdinand Murni Hamundu; La Surimi
AnoaTIK: Jurnal Teknologi Informasi dan Komputer Vol 4 No 1 (2026): Juni 2026
Publisher : Program Studi Ilmu Komputer FMIPA-UHO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33772/anoatik.v4i1.122

Abstract

The Hati Mulia Kendari Hospital experiences difficulties in analyzing appropriate decision making. The process of determining the best employees still uses the method of adding up each criterion so that the data tends to be unstructured and inaccurate. This research aims to produce a decision support system for determining the best employees using a simple additive weighting method. Simple additive weighting is very important because it can increase efficiency, minimize errors, optimize resources, support evidence-based decisions, overcome complexity, increase decision certainty, increase competitiveness, facilitate innovation, and encourage transparency. This decision support system uses the waterfall development method to build the system, testing the system and data using the black box testing and confusion matrix method. The results of system testing using black box testing obtained results that were in accordance with user needs and the results of data testing with 36 test data using a confusion matrix with 3 outputs produced an accuracy of 94%, precision of 80% and recall of 100%. These results show that this decision support system can be implemented.
IMPLEMENTASI K-MEANS DAN DAVIES BOULDIN INDEX UNTUK PENGELOMPOKAN DAERAH DI SULAWESI TENGGARA BERDASARKAN INDIKATOR PENDIDIKAN DENGAN VISUALISASI SISTEM INFORMASI GEOGRAFIS Sahrul; Natalis Ransi; Muhammad Arfan
AnoaTIK: Jurnal Teknologi Informasi dan Komputer Vol 4 No 1 (2026): Juni 2026
Publisher : Program Studi Ilmu Komputer FMIPA-UHO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33772/anoatik.v4i1.133

Abstract

Penelitian ini menerapkan algoritma K-Means yang diintegrasikan dengan Davies-Bouldin Index (DBI) untuk mengelompokkan wilayah berdasarkan indikator pendidikan. Metode DBI berfungsi menentukan jumlah klaster optimal secara objektif sebelum proses klasterisasi dengan K-Means dilakukan. Hasil penelitian memperoleh jumlah klaster terbaik k=2 (nilai DBI 0,6035) yang mengelompokkan 17 wilayah menjadi dua klaster yang kohesif. Hasil klastering divalidasi secara visual menggunakan Principal Component Analysis (PCA) dan berhasil divisualisasikan dalam peta tematik berbasis Sistem Informasi Geografis (SIG) melalui sistem web yang dibangun dengan framework Streamlit. Simpulan penelitian ini adalah kombinasi K-Means dan DBI menghasilkan klasterisasi wilayah yang objektif dan terukur, serta sistem web memudahkan visualisasi hasilnya secara interaktif
Co-Authors Achirul Slamet Sugiarto Adha Mashur Sajiah Adha Mashur Sajiah Adha Sajiah Aksara, L. M. Fid Amal Anugra Amalia Nurani Basyarah Ambo Wonua Nusantara Ambo Wonua Nusantara, Ambo Wonua Andi Muhammad Fathoni Andi Tenriawaru Andi Tenriawaru Andi Tenriawaru Andi Tenriawaru Andi Tenriawaru Anugrah Septia Ningsih Apriliana Apriliana Ardiyanti Putri Arman Arman Arman Arman ARMAN FASLIH, ARMAN Asa Hari Wibowo Asgari, Hasrul Dimas Aswani Aswani Ayu Pratiwi Bahtiar Aksara, La Ode Muhammad Bambang Pramono Bambang Pramono Bolu, WD. Rizqanun Karyima Budiman, Herdi Chintya Mawadhah Sumitro Dewi Angrawati Edi Cahyono Edi Cahyono Edi Cahyono Ega Agustina Eliyanti Agus Mokodompit Ermalianti, Wa Ode Esy Anugerah Rahayu Kasim Fajriani, Nurul Fathoni, Muhammad Andi Ferdinand Murni Hamundu Feri Fadlin Fitria Rihin Uyun Gafar, Agum Agidtama Golok Jaya, La Ode Muhammad Gusti Arviana Rahman Halim Halim, Halim Hardina, Suci Haryati Haryati Ika Maya Sari Ika Purwanti Ningrum Ika Purwanti Ningrum, Ika Purwanti Indri Anatasya Alam Ipa Rezky Cahyani Pata Islah Audziah Putri Beang Ismiranty Hamsar Isnawaty Isnawaty Isnawaty Isnawaty, Isnawaty Jaya, St. Nawal Jufra, Jufra Jumadil Nangi L.M. Bahtiar Aksara La Gubu La Ode Saidi La Ode Saidi La Pimpi La Sufu La Surimi La Surimi La Surimi La Surimi, La Laila Wahda Basalamah Laode Muhamad Tajidun Lily Aprilyani LM Bahtiar Aksara LM Tajidun LM. Fid Aksara Muh Saiful Muh. Yamin Muhamad Amsyar Muhammad Arfan Muhammad Sadam Husain Mulatifa Laliha Nasser, Gamal Abdel Nur Fitriani Purnama, Ika Purwanti Ningrum Purnamasari P, Yuwanda Putriani, Ananda Rahmat C.T.I, Brilian Rahmat Ramadhan Rahmat Ramadhan Ramdani, Umar Reina Rahmona Rizal Adi Saputra Rosliana Eso Rosliana Eso Rusnia Rusnia Sahrul Sajiah, Adha Mashur Sajiah, Adha Mashur sandy suseno Sanrilla Sanrilla Setiyorini, Asih Statiswaty Suci Hardianti Sudayasa, Putu Sulastrianah Sulastrianah, Sulastrianah Sumitro, Dewi Sari Suparjo Sutardi Sutardi Sutardi Syair, Ayu Sabrina Umar Ramdani Umar Reky Uun Amalia Ramadhani Uyun, Fitria Rihin Vina Ismail Wa Ode Siti Nur Alam Yayi Suryo Prabandari Yuwanda Purnamasari Yuwanda Purnamasari Pasrun Yuwanda Purnamasari, Yuwanda