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All Journal CogITo Smart Journal JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Servitium Smart Journal
Semmy Wellem Taju
Fakultas Ilmu Komputer, Universitas Klabat
Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering

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Bioinformatics Tools for Data Processing and Prediction of Protein Function Green Arther Sandag; Semmy Wellem Taju
CogITo Smart Journal Vol 4, No 2 (2018): CogITo Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (698.713 KB) | DOI: 10.31154/cogito.v4i2.137.305-315

Abstract

Bioinformatika semakin populer karena kemampuannya untuk menganalisis dan memproses data biologis dengan cepat dan efektif. Bagian penting dari bioinformatika adalah untuk mengidentifikasi fungsi dan karakteristik protein dengan membangun metode prediksi menggunakan algoritma pembelajaran mesin. Ini termasuk bagaimana pembelajaran mesin dapat digunakan untuk menganalisis dan mengklasifikasikan fungsi protein yang cocok untuk digunakan sebagai deteksi penyakit, merancang perawatan medis yang tepat untuk pasien, dan mengembangkan obat untuk beberapa penyakit. Permintaan untuk pembuatan predictive tools dalam menentukan model protein-ligand dan fungsi protein meningkat untuk mempromosikan penelitian biologi dalam lingkungan desain obat yang inovatif. Namun, dibutuhkan banyak waktu dan upaya untuk mengembangkan alat prediksi yang dapat diterapkan pada protein. Dalam penelitian ini kami mengembangkan tools bioinformatika yang dapat secara otomatis mengembalikan data protein dalam bentuk komposisi asam amino (AAC), komposisi pasangan dipeptida (DPC), dan matriks penentuan spesifikasi posisi (PSSM). Data protein, telah kita ambil dari database uniprot yang berisi file fasta. Penelitian ini, kami membuat alat untuk memfasilitasi ilmuwan dalam memproses atau menganalisis data protein dan juga dapat memprediksi fungsi protein menggunakan algoritma pembelajaran mesin seperti Neural Network dan Random Forest. Kata Kunci—Bionformatika, AAC, DPC, PSSM
Bahasa Indonesia Bahasa Inggris Elshadai Gracia Carolina Rampengan Rampengan; Semmy Wellem Taju; Venisa Tewu
CogITo Smart Journal Vol. 9 No. 1 (2023): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v9i1.469.181-192

Abstract

Klabat University provides residential facilities for students, better known as a dormitory. Information services regarding dormitories and reservation rooms at Klabat University are still managed manually between the dormitory and students. Some problems occur when students want to find information and/or reserve a room at the same time. From the problems that have been observed, researchers have designed a Chatbot to facilitate the students to find for information as well as reserve dormitory rooms. The development method used in this research is the prototyping model. To design a chatbot by implementing two-way communication, researchers implemented Natural Language Processing technique with a Machine Learning approach. The result of this research is a new Chatbot widget as a virtual assistant for information services and reservation rooms in the dormitory at Klabat University
Sistem Analisis Sentimen Ulasan Aplikasi Belanja Online Menggunakan Metode Ensemble Learning Debby Erce Sondakh, S.Kom, M.T, Ph.D; Semmy W. Taju; Michelle G. Tene; Arwin E. T. Pangaila
CogITo Smart Journal Vol. 9 No. 2 (2023): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v9i2.525.280-291

Abstract

Terdapat pertumbuhan jumlah dan prevalensi belanja online. Teknologi belanja online memungkinkan pembeli memberikan umpan balik pasca pembelian (komentar dan ulasan) mengenai aplikasi itu sendiri dan aspek-aspek lain dari produk. Umpan balik ini dapat bermanfaat bagi pelanggan dan bisnis. Namun demikian, menyortir, mengkategorikan, dan membaca begitu banyak ulasan secara manual membutuhkan waktu. Analisis sentimen dapat menyelidiki perilaku, pendapat, dan emosi pelanggan melalui komentar/ulasan teks. Pada penelitian ini, Sistem Analisis Sentimen dikembangkan untuk membantu menentukan sentimen dari setiap ulasan dengan menampilkan visualisasi yang menarik dari hasil analisis melalui diagram lingkaran, frekuensi kemunculan kata, dan persentase probabilitas setiap kelas sentimen-positif, netral, dan negatif. Sistem Analisis Sentimen menggunakan model pengklasifikasi ensemble learning dengan algoritma SVM, KNN, dan Random Forest. Ensemble learning menghasilkan hasil yang lebih tepat daripada algoritma tunggal. Ensemble learning menghasilkan model classifier dengan performa yang lebih baik, dengan indikator akurasi 81.8% precision 83%, recall 82%, F1-score 82%.
Sistem Pencarian dan Rekomendasi Tukang Bangunan Menggunakan Mobile-Based dan GPS Marchel Thimoty Tombeng; Semmy Taju; Ferrell Sanger; Reynaldo Daingah
CogITo Smart Journal Vol. 9 No. 2 (2023): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v9i2.566.304-316

Abstract

In the current digital era, information technology-based applications are rapidly evolving and becoming increasingly essential in everyday life. One type of application that is gaining popularity among the public is recommendation applications, especially those for finding handyworkers. Airmadidi is one of the cities in Indonesia with many boarding houses offering various facilities and prices. However, for newcomers seeking handyworkers in the city, finding the right one for their needs can be a challenging and exhausting task. Therefore, there is a need for a recommendation and handyworker search application system that can assist seekers in addressing issues in their boarding houses or homes according to their specific requirements. This application system will gather information about available handyworkers in Airmadidi and provide recommendations based on users' preferences and needs.The aim of this research is to design a recommendation and handyworker search application in Airmadidi using an appropriate software development method supported by the latest technology. This application system is expected to help users easily and efficiently find handyworkers that match their needs. The research methodology employed in this writing includes interviews, literature reviews, and system design using the SDLC (Software Development Life Cycle) method with a spiral model. The stages of the spiral model With the existence of this recommendation and handyworker search application system, searching for handyworkers in Airmadidi is expected to become easier, more efficient, and effective for seekers. Additionally, this research can serve as a reference for similar studies in other areas.
Implementing QR code and Geolocation Technologies for the Student Attendance System Semmy Wellem Taju; Yonatan Putra Mamahit; Jeremy Andrew Pongantung
CogITo Smart Journal Vol. 10 No. 1 (2024): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v10i1.636.642-653

Abstract

Attendance is one of the important factors in supporting lecture activities that can be used to see how well the performance of student attendance in class. Traditional attendance systems used in various educational institutions often cause problems. This research aims to develop an innovative and efficient student attendance system to help the process of taking attendance by utilizing QR-Code and geo-location technologies at Klabat University. The research method employed for this development is the Prototyping Model, which involves iterative development and refinement processes. The system is designed as a web-based application and a mobile application, developed using PHP as the programming language, MySQL as the database management system, Bootstrap 5 as the CSS and JavaScript framework for creating responsive websites, Apache as the web server and Ubuntu 22.04 as the operating system for the server. QR-Code technology is proposed as a medium for recording and verifying student attendance, while Geo-Location technology is used to verify the presence of students in the right lecture venue. The results of this research are expected to make a positive contribution to Klabat University in terms of recording student attendance.
Research Project Topic Recommender System Using Generative Language Model Debby Erce Sondakh, S.Kom, M.T, Ph.D; Semmy Wellem Taju; Jian Kezia Tesalonica Yuune; Anjelita Ferensca Kaminang; Syalom Gabriela Wagey
CogITo Smart Journal Vol. 10 No. 1 (2024): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v10i1.678.654-666

Abstract

Education has become a driver of a person's continuous innovation to improve their quality. Currently, the use of artificial intelligence determines progress in education. In this research, artificial intelligence technology was applied to develop a web-based recommendation system to help students at the Faculty of Computer Science, Klabat University, choose appropriate research topics for their final assignments. To provide personalized and contextually relevant suggestions, the recommendation system leverages deep learning and generative language models, specifically GPT-3. The Rapid Application Development process model is employed to develop the system. Its key components include semantic search, rapid engineering, and an advanced vector database for effective data management and retrieval. The functions provided by the system include user account registration, login, input of major subject grades and research preferences, and personalized recommendation results. Some additional features such as profile management, previous recommendation history, and password reset options are also provided. All these functions have been tested using the black box method.
PENGENALAN ARTIFICIAL INTELLIGENCE (AI) KEPADA SISWA/I SMK NEGERI 1 SORONG Lontaan, Rolly Junius; Taju, Semmy Wellem; Rotikan, Reymon
Servitium Smart Journal Vol 1 No 2 (2023): Servitium Smart Journal
Publisher : Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/servitium.v1i2.11

Abstract

 Artificial Intelligence (AI) adalah cabang ilmu komputer yang perkembangan sangat pesat dan sangat membantu kita dalam memecahkan berbagai macam permasalahan dari yang sederhana hingga yang kompleks oleh sebab itu pengenalan AI sangat penting bagi siswa di SMK Karena teknologi ini semakin banyak digunakan di berbagai bidang termasuk pada bidang pendidikan. Sebagai siswa yang memasuki dunia profesional masa depan, pemahaman tentang AI akan sangat berharga dalam mempersiapkan Anda menghadapi perubahan dan tantangan era digital. Dalam pengenalan AI, siswa akan mempelajari tentang aplikasi AI dalam kehidupan sehari-hari, seperti chatbot, dan machine learning. Melalui kegiatan magang siswa di Universitas Klabat Siswa SMK Negeri 1 Sorong diperkenalkan tentang AI untuk mempersiapkan diri dengan pengetahuan dan keterampilan yang berkaitan dengan pengembangan keterampilan siswa. Kegiatan ini telah menjadikan siswa/i SMK Negeri 1 Sorong mengenal, mengetahui dan bahkan membuat aplikasi sederhana mengenal obyek dan Chatbot with AIML.
Mengakselerasi Keterampilan Rekayasa Perangkat Lunak: Peranan DevOps, SDLC, dan CI/CD dalam Meningkatkan Kompetensi Siswa SMK N 1 Pusomaen Taju, Semmy Wellem; Pungus, Stenly Richard; Lontaan, Rolly Junius; Rotikan, Reymon; Tombeng, Marchel Thimoty
Servitium Smart Journal Vol 2 No 1 (2023): Servitium Smart Journal
Publisher : Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/servitium.v2i1.24

Abstract

Rekayasa Perangkat Lunak (software engineering) merupakan proses komprehensif yang melibatkan pengembangan program aplikasi. Pemahaman mendalam mengenai DevOps (Development Operation), Siklus Hidup Pengembangan Perangkat Lunak (Software Development Life Cycle atau SDLC), serta Integrasi Berkelanjutan/Pengiriman Berkelanjutan (Continuous Integration/Continuous Deployment atau CI/CD) adalah esensial dalam pengembangan aplikasi yang modern. DevOps diarahkan untuk meningkatkan kemudahan akses terhadap software. Model SDLC yang tradisional seringkali dipilih karena kesesuaiannya dalam mengembangkan aplikasi yang mudah dievaluasi. Namun, keterbatasan model ini mengakibatkan pola kerja yang monoton bagi pengembang, sehingga menghambat perubahan dan adaptasi yang cepat. Sebagai solusi, model CI/CD telah dikembangkan menjadi pendekatan inovatif yang mengubah proses pengembangan perangkat lunak dari manual menjadi otomatis. CI/CD tidak hanya memudahkan dan mempercepat proses pengembangan tetapi juga meningkatkan kualitas dari software yang dirilis. Survei yang dilakukan melalui pre-test di SMK N 1 Posumaen menunjukkan adanya kekurangan dalam pengetahuan siswa mengenai prinsip rekayasa perangkat lunak yang canggih ini. Setelah penyampaian materi yang dirancang khusus, terdapat peningkatan yang signifikan dalam pemahaman siswa, sebagaimana dibuktikan oleh hasil post-test.
Aplikasi Identifikasi Gaya Bahasa Sarkasme Dalam Lirik Lagu Berbasis Mobile Menggunakan Support Vector Machine Algoritma Masengi, Julio Joseph Victor; Frans, Rycko Giovann Leon; Taju, Semmy Wellem
Journal of Information System Research (JOSH) Vol 6 No 3 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i3.6103

Abstract

In the digital era, with the widespread use of social media, the use of sarcasm in song lyrics often presents a unique challenge in the interpretation process. One issue is the difficulty in detecting sarcastic language due to its implicit nature and dependence on context. Conventional methods often fail to capture this complex language pattern, which may lead to misunderstandings. This research aims to develop a mobile-based application capable of identifying sarcasm in song lyrics using the Support Vector Machine (SVM) algorithm. The application is designed to detect sarcasm in song lyrics, which is often hard to identify accurately through traditional methods. The development process includes several stages, such as data collection, pre-processing song lyrics data, applying the Term Frequency-Inverse Document Frequency (TF-IDF) method, and feature extraction. A sarcasm keyword dataset containing 600 data points with sarcasm elements and a general song lyrics dataset without sarcasm elements were collected and used for machine learning model training. The processed data is then classified using Support Vector Machine (SVM), which categorizes the analysis results into two main categories: sarcasm and non-sarcasm. The proposed classification model demonstrates performance with an Accuracy of 98.14%, Sensitivity of 96.13%, Specificity of 100%, and MCC of 0.9645, indicating a strong ability to distinguish between sarcastic and non-sarcastic language. This research aims to enhance users' understanding of song lyrics, especially on social media, to reduce misunderstandings related to sarcasm. It is hoped that this research can contribute to the development of technology for understanding sarcastic language in song lyrics.
Menumbuhkan Literasi Teknologi dan Pengembangan Potensi Akademik dan Nonakademik Siswa melalui Pengenalan AI di SMA Negeri 2 Bitung Taju, Semmy Wellem; Moedjahedy, Jimmy; Adam, Stenly Ibrahim; Rotikan, Reymon
Servitium Smart Journal Vol 3 No 2 (2025): Servitium Smart Journal
Publisher : Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/servitium.v3i2.40

Abstract

Artificial Intelligence (AI) has rapidly emerged as a central pillar in the transformation of education in the digital age. This program Pengabdian kepada Masyarakat (PKM) aims to introduce AI technology as an innovative tool in developing the academic and non-academic potential of students at SMA Negeri 2 Bitung. This activity is carried out in the form of an interactive introduction, demonstration of the latest AI applications (examples such as ChatGPT, Copilot and Gemini), as well as assistance in the use of AI in personalized learning, development of critical thinking skills, communication, collaboration and even adaptability. The methods used include participatory and problem-based approaches to encourage active involvement of SMA Negeri 2 Bitung students. As a result, students showed improved understanding of AI concepts and their practical applications, along with a growing interest in exploring digital technologies more deeply. With this activity, it is hoped that it can be a starting point for building an AI technology-based learning environment in schools, as well as creating a young generation that is more adaptive and ready to face the challenges of technological change.
Co-Authors Anjelita Ferensca Kaminang Arwin E. T. Pangaila Djamal, Eleonora Elshadai Gracia Carolina Rampengan Rampengan Ferrell Sanger Frans, Rycko Giovann Leon George Morris William Tangka Green Arther Sandag Jeremy Andrew Pongantung Jian Kezia Tesalonica Yuune Jimmy H Moedjahedy Marchel Thimoty Tombeng Masengi, Julio Joseph Victor Michelle G. Tene Reymon Rotikan Reynaldo Daingah Rolly Junius Lontaan Sondakh, Debby Erce Stenly Ibrahim Adam Stenly Richard Pungus Syalom Gabriela Wagey Venisa Tewu Yonatan Putra Mamahit