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All Journal Jurnal Review Pendidikan dan Pengajaran (JRPP) Jurnal Abdi Insani Journal of Intelligent Decision Support System (IDSS) JOINTER : Journal of Informatics Engineering Jurnal Informatika dan Rekayasa Perangkat Lunak Bisnis Net : Jurnal Ekonomi dan Bisnis Djtechno: Jurnal Teknologi Informasi Indonesian Journal of Innovation Studies Jurnal Matematika Dan Ilmu Pengetahuan Alam LLDikti Wilayah 1 (JUMPA) Edutik : Jurnal Pendidikan Teknologi Informasi dan Komunikasi
Medi Hermanto Tinambunan
Universitas Negeri Manado
Aerospace Engineering Agriculture, Biological Sciences & Forestry Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Neuroscience Physics Social Sciences Other

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KLASIFIKASI TINGKAT KEPUASAN MAHASISWA TERHADAP FASILITAS PADA FTIK UNIVERSITAS DHARMAWANGSA MEDAN DENGAN ALGORITMA NAIVE BAYES Medi Hermanto Tinambunan; Alfiansyah Hasibuan; Sri Wahyuni; Arif Sobirin Wibowo
Bisnis-Net Vol 6, No 1 (2023)
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/bn.v6i1.3356

Abstract

ABSTRACT Facilities are a support for the implementation of a process in a business in this case the Dharmawangsa University campus, by increasing the level of student satisfaction with the facilities available, student comfort in learning will be achieved. This study used questionnaire data on 70 respondents who were students of Dharmawangsa University. Previously, the questionnaire consisted of 42 questions. After being tested for validity and reliability, 20 questions were obtained. Then from the results of the questionnaire data, a classification of student satisfaction levels will be carried out using one of the algorithms in data mining, namely Naive Bayes. The results obtained by using the rapid miner application with 50 training data and 19 data testing data, the results obtained are a classification accuracy of 73.68% with a recall value of 83.33% and a precision of 83.33%, then there are 9 attributes that have a value dissatisfaction is higher than the satisfaction score given by respondents, this can be a concern of the leadership to improve these facilities so as to increase the level of satisfaction with the facilities provided by Dharmawangsa University.Keywords: Student Satisfaction, Data Mining, Naive Bayes
Sistem Pendukung Keputusan Penentuan Siswa Berprestasi Menggunakan Metode Weight Product (WP) Demi Mardian; Neneng Neneng; Ajeng Savitri Puspaningrum; Alfiansyah Hasibuan; Medi Hermanto Tinambunan
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol 4, No 2 (2023): Volume 4 Nomor 2 Juni 2023
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jatika.v4i2.2593

Abstract

Penilaian dilakukan oleh sistem dengan tetap mengikuti kriteria-kriteria yang ditentukan. Metode yang di pakai dalam pengambilan keputusan pemilihan siswa berprestasi salah satunya yang dapat digunakan adalah dengan menggunakan weight product (WP). Metode WP merupakan solusi pemilihan Siswa Berprestasi karena merupakan algoritma yang mampu mengkomodasi banyaknya kriteria dan menghasilkan solusi. Algoritma ini menghasilkan alternatif dengan membrikan bobot pada masing-masing kriterianya. Kriteria yang akan di gunakan untuk penelitian ini adalah nilai rata-rata raport, nilai extrakulikuler, nilai kedisiplinan, nilai kehadiran, dan nilai non akademik kegiatan. Implementasi sistem denagn melakukan penerapan secara langsung sistem informasi kepada guru yang mangajar dan bagian operator sekolah, serta melakukan pengujian sistem kepada 2 Dosen dan 8 guru atau operator sekolah, serta denagn metode pengujiannya menggunakan ISO 25010, pengujian dilakukan yaitu pada aspek fungsionality, dan oprability, dengan masing-masing nilai didapat untuk fungsioallity 90,91%, untuk oprability 78% dengan hasil pengujian tersebut maka sistem informasi dinyatakan layak untuk mengatasi penentuan siswa berprestasi.
PERILAKU PENYIMPANGAN SOSIAL REMAJA KECANDUAN SIRUP OBAT BATUK KOMIX SEBAGAI SUMBER BELAJAR PPKn di MTs MA’ARIF NU 3 KEMRANJEN Arif Sobirin Wibowo; Ida Bagus Weda Wigena; Medi Hermanto Tinambunan; I Gede Budi Mahendra
Jurnal Review Pendidikan dan Pengajaran (JRPP) Vol. 6 No. 2 (2023): Volume 6 No. 2 Tahun 2023
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jrpp.v6i2.17919

Abstract

Penelitian ini bertujuan untuk menjadikan fenomena perilaku penyimpangan sosial remaja, penyebab serta alasan mengapa remaja sampai kecanduan sirup obat batuk komix sebagai sumber belajar PPKn di MTs Ma’arif Nu 3 Kemranjen. Subjek penelitian ini adalah remaja terutama usia sekolah yang menggunakan sirup obat batuk komix dalam jumlah yang diluar dosis sehingga menyebabkan kecanduan yang berlokasi di Kecamatan Sumpiuh Kabupaten Banyumas. Penelitian ini menggunakan desain penelitian fenomenologi Edmund Husserl karena meneliti fenomena suatu kelompok yaitu penggunaan sirup obat batuk komix yang berlebihan dikalangan remaja sehingga menyebabkan kecanduan. Teknik dan alat pengumpulan data yang digunakan adalah observasi yaitu pengamatan terhadap objek penelitian, wawancara mendalam terhadap remaja yang kecanduan sirup obat batuk komix dan dokumentasi untuk mengumpulkan data data yang diperlukan. Analisis data dilakukan secara terus menerus sampai tuntas sehingga datanya jenuh. Hasil penelitian ini secara ringkas adalah Penyebab remaja menggunakan sirup obat batuk dalam jumlah yang banyak adalah permasalahan di dalam keluarga sehingga menyebabkan degradasi moral karena kurangnya pengawasan dan bimbingan orang tua sehingga secara langsung ataupun tidak terjadi penyimpangan sosial dikalangan remaja, pergaulan teman dan rasa penasaran sehingga mencoba-coba namun akhirnya kecanduan. Efek kenikmatan yang mereka rasakan setelah minum CMC adalah, pusing, badan terasa ringan, bisa melupakan sejenak masalah yang ada dan mengantuk namun tidak bisa tidur. Tetapi ada efek lain yaitu dapat memunculkan sifat asli peminum.
Optimization of K-Means algorithm in grouping data using the statistical gap method Alfiansyah Hasibuan; Djubir R.E. Kembuan; Christine Takarina Meitty Manoppo; Medi Hermanto Tinambunan
Journal of Intelligent Decision Support System (IDSS) Vol 6 No 3 (2023): September : Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v6i3.149

Abstract

In this study, we study the core concepts of the K-Means algorithm, explore its algorithmic framework, computation steps, and practical applications. Using data that is used as a basic need to perform calculations from the k-means algorithm optimization method. Using data taken from the r studio dataset with the EuStockMarkets dataset. The purpose of this study is to optimize the k-means algorithm and cluster the clustering process from a dataset, minimizing the objective function that has been set in the clustering process. The tools used are R Studio. Based on the results of this study, profiling of each group formed can be carried out. Based on the grouping results that have been carried out, the grouping results are 75.7% the accuracy of the statistical Gap method in optimizing clusters from existing datasets and the results of 92.9% are obtained from the results of minimizing the object functions in the dataset from grouping with k-means. The smaller the percentage in this grouping process the better it is in optimizing the clusters from the dataset. The author applies the k-means clustering algorithm to minimize objects for grouping from the EuStockMarkets dataset which consists of 4 variables. And the author uses the Statistical Gap method to optimize the clusters from the dataset.
ANALISIS PERBANDINGAN HASIL PREDIKSI SISTEM PENDUKUNG KEPUTUSAN METODE SIMPLE ADDITIVE WEIGHTING DENGAN PREFERENCE SELECTION INDEX DALAM MENENTUKAN MAHASISWA PENERIMA BEASISWA Medi Hermanto Tinambunan; Sri Wahyuni
Bisnis-Net Vol 6, No 2 (2023)
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/bn.v6i2.3900

Abstract

Bantuan Pendidikan sangat perlu menjadi perhatian karena saat ini mayoritas mahasiswa yang berpotensi dan memiliki kemampuan akan tetapi terkendala dari segi keuangan sehingga hal ini perlu ditanggapi dengan serius oleh pemerintah, saat ini pemerintah melalui kementerian Pendidikan telah berusaha memberikan bantuan dana berupa beasiswa diantaranya adalah beasiswa peningkatan prestasi akademik. Saat ini untuk mendapatkan beasiswa setiap universitas tentunya mendapatkan kuota yang terbatas hal ini dilakukan guna untuk memberikan pemerataan bantuan Pendidikan, dikarenakan perbedaan yang besar antara kuota yang didapatkan dengan mahasiswa yang membutuhkan bantuan sehingga perlu diberikan seleksi kelayakan mahasiswa yang berhak mendapatkan beasiswa. Penelitian ini mengambil data sampel dari daftar beasiswa semester genap 2023 dilingkungan Universitas Negeri Manado khususnya di Program Studi Teknik Informatika, kemudian dilakukan normalisasi data untuk dapat digunakan pada metode SAW dan PSI, setelah dilakukan normalisasi selanjutnya dilakukan perhitungan menggunakan metode SAW dan PSI, setelah didapatkan hasil prediksi dari kedua metode maka selanjutnya akan diuji tingkat akurasi menggunakan metode confusion matrik maka didapatkan hasilnya bahwa metode SAW memiliki tingkat akurasi sebesar 98,13% dan kemudian tingkat akurasi PSI sebesar 97,24% berdasarkan hasil akurasi prediksi maka SAW memiliki tingkat akurasi lebih tinggi disbanding PSI.
Comparison performance analysis of autoregressive integrated moving average and deep learning long-short term memory forecasting weather data Hasibuan, Alfiansyah; Tinambunan, Medi Hermanto; Putra, Purwa Hasan
Jurnal Matematika Dan Ilmu Pengetahuan Alam LLDikti Wilayah 1 (JUMPA) Vol. 3 No. 1 (2023): March: Mathematics and natural science
Publisher : Lembaga Layanan Pendidikan Tinggi Wilayah I Sumatra Utara (LLDikti I)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54076/jumpa.v3i1.302

Abstract

Information about the weather is crucial in assisting human activities and labor because the weather is a factor that cannot be separated and is closely related to all human activities. The purpose this study to compare performance the Autoregressive Integrated Moving Average (AIMA) and Long-Short Term Memory (LSTM) algorithm models with case studies of weather forecasting. This study uses comparison of two methods, forecasting using AIMA and LSTM methods. LSTM method provides the best forecasting performance for attribute minimum temperature, maximum temperature, and average temperature with the Root mean squared error value below 1.45 and the Mean Absolute Error value below 1.14. For attributes of average humidity and solar radiation with a Root mean squared error value of 2.62 to 3.82 and a Mean Absolute Error value of 2.21 to 3.2. Precipitation forecasting has the highest error value with a root mean squared error value of 9.99 and a mean absolute error of 6.5. The AIMA method provides the best forecasting performance on the attribute minimum temperature, maximum temperature, and average temperature with the Root mean squared error value below 1.47 and the Mean Absolute Error value below 1.16. For the sun exposure attribute with a Root mean squared error value of 2.91 to 3.05. Whereas the average humidity attribute has the highest error with the Root mean squared error value reaching 4.97 and the Mean Absolute Error reaching 3.99. LSTM method is better in terms of forecasting results and in terms of computation time. From every forecast made, the LSTM method produces a smaller error value.
IMPLEMENTASI METODE AGILE DALAM PENGEMBANGAN APLIKASI ABSENSI BERBASIS QRCODE PADA SMP NEGERI 7 PERCUT SEI TUAN Tinambunan, Medi Hermanto; Wahyuni, Sri; Yasir, Amru; Simanjuntak, Marthin Yohannes; Siregar, Amir Hamzah
Djtechno: Jurnal Teknologi Informasi Vol 5, No 2 (2024): Agustus
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/djtechno.v5i2.4812

Abstract

Perkembangan teknologi saat ini sangat cepat, hampir seluruh elemen pekerjaan sudah menggunakan teknologi, hal ini juga yang menjadi perhatian penting oleh kepala sekolah SMP Negeri 7 Percut Sei Tuan, tentunya sangat dibutuhkan sebuah sistem absensi yang dapat memberikan informasi dan rekapitulasi data dengan cepat, saat ini SMP Negeri 7 Percut Sei Tuan hanya menggunakan absensi secara manual, yang dimaksud dengan manual adalah menggunakan cetakan absensi dan melakukan tanda tangan langsung pada cetakan dan guru memanggil nama siswa, hal ini tentunya memakan waktu yang lama serta tidak efisien dalam menjalankan proses belajar mengajar. Berdasarkan informasi yang didapatkan dari wawancara dengan para guru, dibutuhkan waktu sekitar 10 sampai dengan 20 menit hanya untuk melakukan absensi sehingga waktu untuk pembelajaran terpotong cukup banyak. Berdasarkan permasalahan tersebut perlu dilakukan penyelesaian terkait waktu yang lumayan banyak termakan oleh absensi, salah satu cara yang dapat dilakukan adalah dengan membangun sebuah aplikasi dengan menerapkan metode Agile Software Development yang dapat membantu siswa dan guru untuk melakukan absensi dengan cepat, cukup hanya dengan guru mengingatkan kembali siswa untuk melakukan absensi dengan aplikasi absensi berbasis qrcode pada saat pembelajaran berakhir atau sebelum mata pelajaran terakhir selesai. Saat pengujian sistem tentunya sangat membantu para guru dan orangtua dalam melakukan pemantauan kehadiran siswa disekolah, karena fitur aplikasi ini dapat memberikan informasi melalui email ketika siswa melakukan absensi disekolah, sehingga orang tua dapat mengetahui apakah anak mereka sudah hadir disekolah. Berdasarkan hasil pengujian blackbox didapatkan tingkat kepuasan pengguna baik orangtua dan guru sangat terbantu dalam pemantuan absensi serta memberikan penilaian positif.
Buku Tamu Digital Menggunakan Teknologi Optical Character Recognition Dan Framework Laravel Rapar, Pedro Vincensius; Rorimpandey, Gladly Caren; Tinambunan, Medi Hermanto
JOINTER : Journal of Informatics Engineering Vol 6 No 01 (2025): JOINTER : Journal of Informatics Engineering
Publisher : Program Studi Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53682/jointer.v6i01.398

Abstract

The use of information technology has become essential in improving operational efficiency and data accuracy, particularly in visitor registration systems. At PT. Pertamina Geothermal Energy Area Lahendong, visitor data collection was still carried out manually, often resulting in long queues, unreadable handwriting, and data management difficulties. This study proposes the development of a web-based digital guest book system using Optical Character Recognition (OCR) technology and the Laravel framework. OCR is employed to extract visitor data automatically from images of ID cards (KTP), eliminating the need for manual entry. The system was developed using the Rapid Application Development (RAD) methodology, which emphasizes iterative prototyping and user involvement. User Acceptance Testing (UAT) showed a high satisfaction score of 90.2%, categorized as "Very Good." In addition, OCR testing demonstrated 100% accuracy in extracting data from high-quality KTP images. The implementation of this system simplifies the visitor registration process, reduces the reliance on manual input, no need to leave the ID card at the security post, and enhances data security.
PENINGKATAN LITERASI ENERGI TERBARUKAN MELALUI IMPLEMENTASI MICROGRID PANEL SURYA DAN PENGEMBANGAN PLATFORM E-LEARNING DI SMKN 3 TONDANO Mahendra, I Gede Budi; Wigena, Ida Bagus Weda; Tinambunan, Medi Hermanto
Jurnal Abdi Insani Vol 12 No 9 (2025): Jurnal Abdi Insani
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/abdiinsani.v12i9.2848

Abstract

The need for renewable energy literacy in vocational education is becoming increasingly urgent to support energy transition and green education. SMK Negeri 3 Tondano has the potential to develop solar energy through learning activities and electrical engineering practices. However, teachers' and students' understanding of renewable energy concepts, energy efficiency, and solar power generation systems (PLTS) is still limited. This situation has led to low adoption of clean energy technology in teaching and learning processes and the school environment. This community service programme aims to enhance renewable energy literacy and technical capacity among school staff through an educational, participatory, and applied approach. The activities included interactive outreach, technical training, development of a Learning Management System, formation of an Energy Task Force, installation of a 300 Wp microgrid PLTS, and development of technical SOPs. A total of 43 participants, consisting of teachers, students, and technicians, were actively involved. Pre-test–post-test evaluation results showed significant improvements: the average teacher score increased from 58–65 to 84–88, while students improved from 44–52 to 73–79, with an N-Gain of 0.56–0.66. The PLTS system generates 1.2–1.4 kWh per day and can operate practical loads for 3–5 hours. Follow-up activities include integrating renewable energy materials into project-based learning, self-managed LMS management, and the implementation of maintenance SOPs. This activity demonstrates that the school-based energy education model can be replicated to strengthen the energy transition at the national level.
Predictive Classification of Online Gambling Impacts in North Sulawesi Using Naive Bayes: Klasifikasi Prediktif Dampak Judi Online di Sulawesi Utara Menggunakan Naive Bayes Tameo, Vito Ernesto; Tinambunan, Medi Hermanto; Rorimpandey, Gladly C.
Indonesian Journal of Innovation Studies Vol. 26 No. 4 (2025): October
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v26i4.1728

Abstract

General background: Online gambling has become a growing societal issue in Indonesia, affecting various economic and social dimensions. Specific background: North Sulawesi is identified as one of the most vulnerable regions, with a high volume of gambling transactions and significant social consequences. Knowledge gap: Previous studies in Indonesia have focused mainly on behavioral, legal, or health aspects, with limited use of predictive modeling to map community vulnerability. Aims: This study aims to analyze the social, economic, and psychological impacts of online gambling and to develop a predictive model using the Naive Bayes algorithm to classify impact levels. Results: Based on data from 504 respondents, the model achieved an accuracy rate of 94.05% in classifying impacts into light, moderate, and severe categories. Precision and recall were highest for light and severe categories, while moderate categories showed lower performance. Novelty: This research introduces a data-driven predictive approach within a regional Indonesian context, which has been underexplored in prior studies. Implications: The findings provide a practical foundation for regional governments to design targeted interventions, ranging from digital literacy programs to psychological rehabilitation services, based on data-driven risk classification. Highlight: The model achieved 94.05% accuracy in classifying online gambling impacts. Regional data provided structured insights into social, economic, and psychological consequences. Findings support evidence-based policymaking for targeted local interventions. Keyword:Online Gambling, Predictive Classification, Naive Bayes Algorithm, Social and Economic Impacts, North Sulawesi
Co-Authors Alfiansyah Hasibuan Amir Hamzah Siregar, Amir Hamzah Arif Sobirin Wibowo Christine Takarina Meitty Manoppo Demi Mardian Gladly Caren Rorimpandey I Gede Budi Mahendra Ida Bagus Weda Wigena Kawengian, Argentino Michaelovic Kembuan, Djubir Ruslan Edy Lestari, Ira Widarti Setu Neneng Neneng Perangin-angin, Laura Ivo Pither, Claudia Putra, Purwa Hasan Rapar, Pedro Vincensius Simanjuntak, Marthin Yohannes Sri Wahyuni Sumakul, Novia Tesalonika Tameo, Vito Ernesto Yasir, Amru