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All Journal Dinamik (JELIKU) Jurnal Elektronik Ilmu Komputer Udayana Jurnal Sarjana Teknik Informatika Indonesian Journal of Artificial Intelligence and Data Mining JurTI (JURNAL TEKNOLOGI INFORMASI) Jurnal ULTIMATICS METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Multitek Indonesia : Jurnal Ilmiah Jurnal Teknologi Terpadu Journal of Information System, Applied, Management, Accounting and Research Jurnal Sistem Informasi dan Informatika (SIMIKA) Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Journal of Business and Audit Information System (JBASE) Jurnal Sosial dan Teknologi Jurnal Manajemen Informatika Jayakarta HOAQ (High Education of Organization Archive Quality) : Jurnal Teknologi Informasi Jurnal Vokasi Informatika (JAVIT) Journal Software, Hardware and Information Technology Journal of Technology and Informatics (JoTI) Simpatik: Jurnal sistem Informasi dan Informatika Indonesian Community Journal Blend Sains Jurnal Teknik Populer: Jurnal Penelitian Mahasiswa Jurnal Manajemen Informatika & Teknologi Jurnal Manajemen Informatika dan Bisnis Digital Jurnal Informatika dan Komputer (JIK) Jurnal Sistem Informasi dan Ilmu Komputer Jurnal Komputer Antartika Indonesian Journal of Education And Computer Science Saber: Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi Journal Innovations Computer Science Repeater: Publikasi Teknik Informatika dan Jaringan Mars: Jurnal Teknik Mesin, Industri, Elektro dan Ilmu Komputer KETIK : Jurnal Informatika Sistematis Jurnal Sistem Informasi dan Aplikasi Nusantara Journal of Artificial Intelligence and Information Systems
Kaesmetan, Yampi R
STIKOM Uyelindo Kupang
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Sistem Pendukung Keputusan Pemilihan Sufor Untuk Balita Menggunakan Metode VIKOR dan ELECTRE Saputri, Nur Azizah Indah; Kaesmetan, Yampi R
Jurnal Manajamen Informatika Jayakarta Vol 5 No 1 (2025): JMI Jayakarta (Februari 2025)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jmijayakarta.v5i1.1796

Abstract

Proper nutrition is crucial for supporting the growth and development of toddlers, especially during the golden age, a critical period for building their fundamental abilities. One alternative source of nutrition besides breast milk is formula milk (SUFOR), which plays a significant role in meeting toddlers' nutritional needs. However, the wide variety of formula milk products with different nutritional contents, prices, and characteristics often makes it difficult for consumers, especially mothers, to choose the best option.This study aims to develop a Decision Support System (DSS) using the VIKOR and ELECTRE methods to assist consumers in selecting the best formula milk. The VIKOR method is applied to determine a compromise ranking by considering both the maximum and minimum utility values of each alternative. Meanwhile, the ELECTRE method compares alternatives pairwise based on predefined criteria to identify the most suitable choice. The selection criteria include nutrition, price, product availability, consumer reviews, packaging, and flavor variations.Data collection involves observations in several milk stores in Kupang City and relevant literature studies. The system is designed using PHP, MySQL, and Visual Studio Code to develop a web-based application with two user roles: admin and user. This system not only helps consumers make informed decisions but also raises awareness about the importance of formula milk nutrition. Ultimately, it is expected to contribute to improving toddlers' nutritional status and reducing stunting and wasting rates in Indonesia.
IMPLEMENTASI METODE BERT DAN SVM PADA ANALISIS SENTIMEN GAME GENSHIN IMPACT Anindya, Fazha Safha; Kaesmetan, Yampi R
Jurnal Manajamen Informatika Jayakarta Vol 5 No 1 (2025): JMI Jayakarta (Februari 2025)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jmijayakarta.v5i1.1781

Abstract

The Genshin Impact game has become a global phenomenon with a large player base, especially in Indonesia, which is the 4th largest user country in the world. This study aims to analyze user sentiment towards the game by utilizing data from the social media platform X. The analysis was carried out by comparing two sentiment classification methods, namely Support Vector Machine (SVM) and Bidirectional Encoder Representations from Transformers (BERT). Data was collected through a crawling process using API X and processed through preprocessing stages, such as cleansing, tokenization, and stemming. The SVM method was chosen because of its simplicity in implementation, while the BERT method was used to explore the ability of deep learning to understand complex linguistic contexts. This study shows that BERT provides higher classification accuracy than SVM, especially in handling the diversity of language styles on social media. It is hoped that the results of this research can provide input for game developers to improve user experience through events that are more in line with community preferences.
Pengenalan Wajah Berdasarkan Emosi Manusia Menggunakan SOM (Self Organizing Map) Selan, Frederikus Wanforsan Reynaldy; Owa, Frederikus Mantolda Dede; Kaesmetan, Yampi R
Jurnal Sarjana Teknik Informatika Vol. 12 No. 3 (2024): Oktober
Publisher : Program Studi Informatika, Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/jstie.v12i3.28620

Abstract

Identifikasi melalui password atau kartu rentan terhadap lupa dan pencurian, menyebabkan keamanan yang kurang efektif. Sistem identifikasi biometrik, terutama berbasis ekspresi wajah, menjanjikan solusi lebih baik. Namun, tantangan seperti variabilitas ekspresi dan kondisi pencahayaan membatasi efisiensi. Penelitian ini mengusulkan penggunaan Self Organising Map (SOM) untuk mengatasi kendala tersebut. Meskipun telah ada penelitian sebelumnya, penggabungan pengenalan wajah dan emosi dengan SOM masih terbatas. Tujuan penelitian ini adalah mengembangkan sistem pengenalan wajah berdasarkan emosi manusia menggunakan pendekatan SOM. Pendekatan ini tidak hanya meningkatkan keamanan dan kenyamanan tetapi juga membuka peluang baru dalam interaksi manusia dan mesin, pengawasan keamanan, dan pengembangan teknologi sehari-hari. Dengan mengatasi keterbatasan identifikasi konvensional, penelitian ini memperluas potensi teknologi biometrik
ANALISIS PERBANDINGAN CONVOLUTIONAL NEURAL NETWORK DAN SUPPORT VECTOR MACHINE PADA ANALISIS SENTIMEN RUU PILKADA DI APLIKASI X Ladopurab, Yohana Uba; Kaesmetan, Yampi R.
Journal of Information System, Applied, Management, Accounting and Research Vol 9 No 2 (2025): JISAMAR (March-May 2025)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jisamar.v9i2.1887

Abstract

Regulasi terkait Pemilihan Kepala Daerah (RUU Pilkada) sering menjadi perbincangan publik dan memunculkan beragam opini di media sosial, termasuk di Aplikasi X. Analisis sentimen terhadap opini publik dapat memberikan wawasan berharga bagi pembuat kebijakan dan masyarakat dalam memahami persepsi terhadap RUU Pilkada. Dalam penelitian ini, dilakukan perbandingan antara metode Convolutional Neural Network (CNN) dan Support Vector Machine (SVM) untuk analisis sentimen terhadap data yang dikumpulkan dari Aplikasi X. Berdasarkan hasil evaluasi, SVM menunjukan kinerja yang lebih dibandingkan CNN pada hampir semua matriks, dengan akurasi SVM mencapai 92,38% dan F1-score 27,27%. Sebaliknya, CNN mencatatkan akurasi 62,86 dan F1-score 7,14%. Meskipun CNN unggul dalam pemrsesan data sekuensial, SVM terbukti lebih stabil dan akurat dalam konteks dataset ini.
Sistem Pendukung Keputusan Pemilihan Siswa Berprestasi dengan Metode PROMETHEE Nono, Mariana Selvia; Vladimir Juino Jago Uko, Christianus; Kolihar, Reflon Paskah; Rafael, Simpati Gamalio; Henakin, Yohanes Bala; Kaesmetan, Yampi
Jurnal Vokasi Teknik Informatika Vol 3 No 3 (2023)
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/javit.v3i3.162

Abstract

Penelitian ini membahas implementasi Sistem Pendukung Keputusan (SPK) menggunakan metode PROMETHEE dalam pemilihan siswa berprestasi di SD Muhammadiyah Kupang. SPK dikembangkan dengan mempertimbangkan kriteria-kriteria seperti prestasi akademik, partisipasi dalam kegiatan ekstrakurikuler, keterlibatan dalam kegiatan sosial, dan rekomendasi guru. Melibatkan preferensi dari berbagai pihak, termasuk guru, orang tua, dan administrasi sekolah, SPK menggunakan metode PROMETHEE untuk perbandingan profil siswa dan penentuan peringkat relatif. Hasil penelitian menunjukkan bahwa SPK efektif mengidentifikasi siswa-siswa berprestasi, memberikan kontribusi pada promosi keunggulan akademik, dan mengurangi potensi bias dalam pengambilan keputusan subjektif. Studi kasus di SD Muhammadiyah Kupang menegaskan bahwa SPK ini dapat meningkatkan efisiensi dan keadilan dalam proses pemilihan siswa, memberikan kontribusi signifikan dalam konteks pengambilan keputusan pendidikan dengan pendekatan sistematis dan transparan. SPK yang diusulkan diharapkan menjadi alat berharga bagi SD Muhammadiyah Kupang dalam mendukung perkembangan siswa berprestasi.
Penerapan Sistem Informasi Geografis untuk Optimalisasi Lahan Pertanian Berkelanjutan di Kabupaten Kupang Vito Daniel Boboy; Yampi R Kaesmetan
JUMINTAL: Jurnal Manajemen Informatika dan Bisnis Digital Vol. 4 No. 1 (2025): Mei 2025
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jumintal.v4i1.5004

Abstract

Kupang Regency in East Nusa Tenggara Province has great potential in the agricultural sector, but faces various challenges that can hinder sustainable productivity, such as declining soil quality, land degradation, and changes in rainfall patterns due to the impact of climate change. Therefore, sustainable agricultural land management is very important in maintaining regional food security and increasing agricultural production. This study aims to develop a web-based Geographic Information System (WebGis) that is capable of mapping agricultural land conditions in Kupang Regency. This system is designed to present spatial information on soil fertility levels, the existence of critical land, and the impact of climate variability on agricultural areas. In the process of land analysis and classification, the Self-Organizing Map(SOM) method is used, an unsupervised learning approach that is effective in grouping data based on certain characteristics. The mapping results are then integrated into the WebGis platform so that they can be accessed interactively and easily used by the Department of Agriculture or related policy makers. With this system, it is expected to assist in making more precise, efficient, and sustainable data-based decisions, especially in agricultural land planning and management. Overall, this research is expected to provide a real contribution in efforts to increase the efficiency of land use and encourage environmentally friendly agricultural practices in Kupang Regency.
Pemetaan Penyakit Hewan Ternak di Timor Tengah Selatan Menggunakan GIS dengan Metode K-Means Clustering Rasti Lani; Yampi R Kaesmetan
JUMINTAL: Jurnal Manajemen Informatika dan Bisnis Digital Vol. 4 No. 1 (2025): Mei 2025
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jumintal.v4i1.5005

Abstract

South Central Timor Regency in East Nusa Tenggara Province faces serious challenges in controlling livestock diseases that impact livestock farmers' welfare and food security. rainfall patterns due to climate change impacts. This study aims to develop a WebGis-based Geographic Information System (GIS) to map the distribution of livestock diseases in the region. This system is expected to assist the Animal Husbandry Service in planning efforts to control and prevent diseases more effectively and on target. The method used is K-Means Clustering to group areas based on disease prevalence, disease type, and environmental factors that influence its spread. Accurate spatial data is collected from various sources and integrated into the WebGis platform, resulting in a livestock disease distribution map that can be easily accessed by related parties. The expected results of this study are the availability of fast, accurate, and efficient disease distribution information to support planning for animal disease control and prevention actions. The developed WebGis allows access to real-time and data-based information, thus supporting more strategic decision-making in improving livestock resilience in South Central Timor Regency
Analisis Pola Pembelian Mobil di Indonesia Menggunakan Metode ID3 Maria Yohana Gabriela Sasi; Yampi R Kaesmetan
JUMINTAL: Jurnal Manajemen Informatika dan Bisnis Digital Vol. 4 No. 1 (2025): Mei 2025
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jumintal.v4i1.5352

Abstract

Indonesia's geographical conditions consisting of islands encourage the need to develop efficient transportation, especially automotive, to improve the country's economy. Cars are seen as safer vehicles than motorbikes, and with the increasing number of automotive companies, competition in the market is getting tighter. Car sales, especially from brands such as Toyota, Honda, and Mitsubishi, have shown rapid growth, with Toyota recording sales growth of 6.5% and Honda increasing by 56% in 2023. This condition requires companies to understand consumer needs and implement the right business strategies. The comfort and quality of the car are the main priorities in choosing a vehicle, although price is also an important consideration. With the growth of marketing through social media, the expected data can be used for further analysis, so that manufacturers can improve the quality of their products. The purpose of using the ID3 Method (Iterative Dichotomiser 3) as an algorithm to explore patterns in car purchasing decisions in Indonesia, given its ability to form decision trees that can reflect alternative choices and decision results. This study aims to analyze car purchase data and provide more insight into consumer preferences in the context of the Indonesian automotive market
Klasifikasi Motif Kain Tenun di Pulau Flores Menggunakan Metode CNN dan RNN Kembo, Emanuel Kristiano; Kaesmetan, Yampi R.
Blend Sains Jurnal Teknik Vol. 4 No. 1 (2025): Edisi Juli
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/blendsains.v4i1.816

Abstract

Pulau Flores memiliki kekayaan budaya yang tercermin dalam berbagai motif kain tenun yang dihasilkan oleh masyarakat lokal. Keberagaman motif ini sangat penting untuk dilestarikan, namun proses identifikasi dan klasifikasi motif kain tenun secara manual memiliki tantangan tersendiri. Penelitian ini bertujuan untuk mengembangkan sistem klasifikasi motif kain tenun di Pulau Flores menggunakan metode deep learning, khususnya Convolutional Neural Network (CNN) dan Recurrent Neural Network (RNN). CNN digunakan untuk ekstraksi fitur visual dari gambar motif kain, sementara RNN diterapkan untuk mengenali pola urutan motif yang ada pada kain tenun. Metode ini diharapkan dapat meningkatkan akurasi dalam mengklasifikasikan berbagai motif kain tenun secara otomatis, serta mendukung pelestarian dan digitalisasi warisan budaya daerah. Hasil penelitian menunjukkan bahwa penerapan metode CNN dan RNN dapat memberikan akurasi yang tinggi dalam klasifikasi motif kain tenun, sehingga bermanfaat untuk mempromosikan dan melestarikan kain tenun Flores dalam skala yang lebih luas.
Implementasi Metode SAW (Simple Additive Weighting) Dalam Sistem Pendukung Keputusan Seleksi Penerima Beasiswa KIP Menggunakan Algoritma Profile Matching Frans, Harry Wolter; Kaesmetan, Yampi R
Jurnal Manajemen Informatika & Teknologi Vol. 5 No. 2 (2025): Oktober : Jurnal Manajemen Informatika & Teknologi
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi - Studi Ekonomi Modern

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/1ev5md93

Abstract

Pemberian beasiswa merupakan salah satu upaya strategis untuk meningkatkan akses pendidikan dan mendorong pemerataan kesempatan belajar bagi mahasiswa berprestasi maupun yang berasal dari keluarga kurang mampu. Salah satu program beasiswa yang mendukung hal ini adalah Kartu Indonesia Pintar (KIP) Kuliah. Namun, proses seleksi penerima beasiswa seringkali menghadapi tantangan dalam hal objektivitas dan efisiensi penilaian. Penelitian ini bertujuan untuk mengembangkan sistem pendukung keputusan (SPK) dalam seleksi penerima beasiswa KIP di STIKOM Uyelindo Kupang dengan mengimplementasikan metode Simple Additive Weighting (SAW) dan algoritma Profile Matching. Metode SAW digunakan untuk menghitung nilai akhir berdasarkan pembobotan tiap kriteria, sedangkan metode Profile Matching berfungsi untuk mencocokkan profil ideal dengan data kandidat berdasarkan selisih nilai (GAP) dari setiap kriteria. Penggabungan kedua metode ini diharapkan mampu menghasilkan sistem seleksi yang lebih akurat, transparan, dan efisien dalam menentukan mahasiswa yang paling layak menerima beasiswa. Hasil akhir dari penelitian ini adalah prototipe sistem berbasis komputer yang dapat dijadikan sebagai alat bantu pengambilan keputusan oleh pihak kampus dalam proses seleksi beasiswa KIP.
Co-Authors Abraham Do Hina Abubakar, Muhammad A. Alfayet, Teofano E.D Andrew Delfistian Dethan Anindya, Fazha Safha Atfandianus Ewal Azahra Imran, Fatimah Azis, Mayang Fitrylia Babis, Arjen Yohanes Bajuri, Miftahul K Bastian Jumilton Lenggu Beda, Helena Bendi, Muhammad Indra Boboy, Vito Daniel Boling, Angel Agustina Delfince Toleu Desty A. Bekuliu Dinda Ayusma Tonael Djawas, Julaica F. Dominggus Mangngi Edwin Ariesto Umbu Malahina Elisabeth Kolastriwan Romanda Endang Oekolos Fahik, Ferdinandus Febianus Asa Frans, Harry Wolter Fryonanda, Harfebi Fua, Andreas Curtis Hopper Fuzy Yustika Manik, Fuzy Yustika Ginting, Rudolf F.A. Handul, Yohanes Janssen Helena dorothea Mbura Henakin, Yohanes Bala Jamung, Maria Susanti Jekonia Nelchika Titing Jusrianto A Johannis Kamirsa, Yota Putra Katihara, Gustaf Karel Kehi, Balthasar Kembo, Emanuel Kristiano Kolihar, Reflon Paskah Komba, Clarisa La Beu, Dian Nurcahyani Ladopurab, Yohana Uba Lae, Archangela Cornelia Laoe, Desly sabatini Latuan, Franklyn Priscian Leosae, Sepriono Linus Evrianus Ama Kean Maria Claris Salzano Nurak Maria Yohana Gabriela Sasi Marlinda Vasty Overbeek Marlinda Vasty Overbeek Martin Ch. Liufeto Matulessy, Junus Yosia Eran Saktriawan Melania Zemil Meliana O Meo Mone, Bintang Vieshe Mone, Gerry Moruk, Fransiskus Xaverius Mutty, Nanda Gracenda Christina naikteas, maria rosalinda Nawa, Yesaya Laga Ndun, Alfrend Nelci Non nenometa, elike adielwin Nesi, Maria Yunita Nimrot Doke Para Nindy Aulia Safirah Nono, Mariana Selvia Owa, Frederikus Mantolda Dede Penlaana, Vania Serafin Pua geno, Muhamad Nazhif Zuhri Putra Prawira Yohanes Puka Rafael, Simpati Gamalio Rasti Lani Rexion Alondeo Boimau Reynaldo Behar Rihi, Ivana Ristiana Betris Tosi Rosid, Achmat Saban, Aryandi Sanrina Natalia Evelin Tolan Saputri, Nur Azizah Indah Sayyid Ahmad Wisak Selan, Frederikus Wanforsan Reynaldy Sten Dofanky Mooy Tahuk, Wilhelmina Johana Tefa, Sepri Vito Daniel Boboy Vladimir Juino Jago Uko, Christianus Wole, Jernianti Susanti Wulansari Masan Yafet Balan Yesaya Laga Nawa Yoman Berchmans Yunita Luruk Ulu Yustina Bete Dos Santos Yusuf Elpontus Tanaem