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All Journal Indonesian Journal of Artificial Intelligence and Data Mining JOURNAL OF APPLIED INFORMATICS AND COMPUTING JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Journal of Engineering, Technology, and Applied Science (JETAS)
Sumendap, Andreas Leonardo
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Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Education Industrial & Manufacturing Engineering Materials Science & Nanotechnology Physics

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ANALISIS QUALITY OF SERVICE JARINGAN WIRELESS LOCAL AREA NETWORK DI KANTOR BUPATI MANOKWARI Matiin, Nur Fatimah; Marini, Lion Ferdinand; Sumendap, Andreas Leonardo
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 9, No 3 (2024)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v9i3.5731

Abstract

Kantor Bupati Manokwari merupakan lembaga pemerintah yang bertanggung jawab atas berbagai aspek administrasi pemerintahan daerah di tingkat kabupaten. Meningkatnya jumlah pengguna internet di Kantor Bupati Manokwari mengakibatkan banyak pengguna mengalami kesulitan untuk memanfaatkan jaringan secara optimal, seperti ketidakstabilan dan kecepatan internet yang rendah saat banyak pengguna mengakses titik akses yang sama secara bersamaan, serta kesulitan dalam terhubung ke jaringan. Studi ini ditujukan guna mengukur mutu layanan jaringan internet pada Kantor Bupati Manokwari agar layanan jaringan internet berada pada tingkat yang optimal dan dapat beroperasi dengan baik. Sehingga, dilakukan penelitian dengan metode kuantitatif dan melakukan pengukuran mutu dari layanan jaringan internet dengan memanfaatkan indikator Quality of Service (QoS) yakni, throughput, packet loss, delay, dan jitter dengan standarisasi jaringan internet versi Telecommunications and Internet Protocol Harmonization Over Networks (TIPHON). Hasil dari studi ini, diperoleh nilai rata-rata throughput 1730,7 kbps, packet loss 0,775%, delay 3,833 ms, dan jitter 3,8345 ms, sehingga dapat disimpulkan uji pengukuran Quality of Service (QoS) di Kantor Bupati Manokwari memperoleh nilai indeks rata-rata 3,5 dan persentase 87,5% yang termasuk ke dalam kategori “Bagus”.
ANALISIS PERBANDINGAN KUALITAS KINERJA JARINGAN ISP TELKOMSEL BAKTI KAMPUNG TANAH RUBUH DAN KAMPUNG YOOM 2 Herdianzah, Aldy; Sumendap, Andreas Leonardo; Kweldju, Alex De
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 1 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i1.5857

Abstract

Pada penelitian ini bertujuan untuk mengukur kualitas kinerja jaringan internet (QoS) pada jaringan seluler BTS Provider Telkosmel bakti di dua lokasi berbebeda yaitu Kampung Tanah Rubuh dan Kampung Yoom 2, distrik manokwari utara ,Provinsi papua barat. Pengukuran QoS dilakukan dengan menggunakan standar TIPHON yang mencakup metrik throughput, delay, jitter, dan packet loss. Untuk mengukur kualitas kinerja jaringan dilakukan pengambilan data dengan menggunakan bantuan software Wireshark ( network analyzer) di kedua loaksi tersebut, data yang dikumpulkan (capture) pada Wireshark kemudian dilakukan pengukuran dan anlaisis sesuai standar yang di tetapkan TIPHON yang dikeluarkan oleh ETSI.  Hasil penelitian menunjukkan bahwa throughput di Kampung Yoom 2 hanya mencapai 3,049 kbps, dengan packet loss sebesar 0,5%, delay 522,940 ms, dan jitter 522,935 ms, yang mengindikasikan kualitas jaringan yang rendah. Sebagai perbandingan, Kampung Tanah Rubuh menunjukkan hasil yang lebih baik karena memiliki nilai Throughput 17.728 Mbps, Packet Loss 1.4%, Delay 181,213 ms, Jitter 181,179 ms. Implikasi dari hasil ini menunjukkan bahwa infrastruktur jaringan di Kampung Tanah Rubuh dan Kampung Yoom 2 memerlukan peningkatan dan perbaikan untuk mencapai kinerja yang lebih baik. Penelitian ini memberikan kontribusi terhadap literatur yang ada dengan menyediakan data kinerja jaringan seluler di daerah terpencil di indonesia dan memberikan rekomendasi bagi peningkatan infrastruktur jaringan terlebih khusus kampung Tanah Rubuh dan kampung Yoom 2.
Web GIS-Based Birdwatching Ecotourism Planning in Kwau Village Reski, Dian; Sumendap, Andreas Leonardo; Dimara, Petrus Abraham
Journal of Engineering, Technology, and Applied Science (JETAS) Vol 7 No 3: December 2025
Publisher : Lamintang Education and Training Centre, in collaboration with the International Association of Educators, Scientists, Technologists, and Engineers (IA-ESTE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36079/lamintang.jetas-0703.954

Abstract

Ecotourism development in Kwau Tourism Village remains limited due to the absence of systematic spatial mapping and insufficient accessible information regarding bird distribution, despite the area’s rich diversity of endemic species and strong potential for bird-watching activities. The main problem lies in the lack of integrated ecological data that can support informed planning and sustainable ecotourism management. This study offers a solution by combining spatial and non-spatial ecological information to produce a comprehensive decision-support system. The research applies field-based GPS mapping of bird observation points, hotspot analysis, and documentation of temporal behavioral patterns such as feeding and lekking activity. All datasets were processed in ArcGIS and incorporated into an interactive WebGIS platform designed to assist tourism managers, local communities, and visitors in understanding spatial patterns and planning ecotourism activities more effectively. The findings show that bird distribution is concentrated in forest zones with low human disturbance and stable canopy structure, with peak activity occurring in the morning and late afternoon, providing optimal viewing opportunities. Accessibility assessments also indicate that trekking routes vary in difficulty depending on terrain and elevation. Overall, this study contributes a replicable model for GIS-supported bird-based ecotourism that strengthens destination management and enhances visitor preparedness through integrated ecological information.
Analysis of the Determinants of Pelni Mobile Adoption Failure in Manokwari: A Hybrid Diffusion of Innovation and Theory of Planned Behaviour Approach Bonai, Yubelina Meilia; Sumendap, Andreas Leonardo; Sanglise, Marlinda
Journal of Applied Informatics and Computing Vol. 10 No. 1 (2026): February 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i1.11959

Abstract

The adoption of digital services like Pelni Mobile in developing regions faces complex challenges. Despite offering ease of access, its adoption rate in Manokwari Regency remains low. Previous studies have not extensively explored typical barriers such as resistance to change, perceived financial costs, inconvenience, and ease of access. This study analyzes the factors behind Pelni Mobile's adoption failure by integrating the DOI and TPB approaches. Data were collected via online questionnaires from 435 participants and analyzed using SEM-PLS. Findings show that Perceived Financial Cost (P=0.000), Resistance to Change (P=0.000), and Inconvenience (P=0.000) have a significant negative influence on Behavioral Intention to Use. This means perceived costs, resistance to change, and inconvenience can reduce usage interest. Conversely, Perceived Ubiquity (P=0.000) has a significant positive influence on usage intention, and Behavioral Intention to Use positively influences Use Behavior, indicating that ease of access can encourage adoption.The implications highlight the need for strategies to reduce financial barriers, improve accessibility, employ educational approaches to address resistance, and enhance user experience. For developers and policymakers, these results serve as a guide for designing more inclusive digital services tailored to the characteristics of developing communities, particularly in contexts similar to Manokwari. Generalizing the findings to other regions must consider local social, economic, and cultural differences.
Analysis of Students’ Perceptions of the Free Nutritious Food Program (MBG) Based on K-Means Clustering Rahmi, Nur; Baisa, Lorna Yertas; Sumendap, Andreas Leonardo
Indonesian Journal of Artificial Intelligence and Data Mining Vol 9, No 1 (2026): March 2026
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v9i1.39240

Abstract

The Free Nutritious Food Program is a strategic policy to support students’ nutritional resilience and readiness to learn. This study examined students’ perceptions of the program and identified respondent profiles using the K-Means clustering algorithm. Data from 501 students were collected through a Likert-scale questionnaire and analyzed to determine distinct perception patterns. The results revealed five clusters with strong validity, indicated by a silhouette value of 0.917. Overall, 74.6% of respondents expressed positive perceptions, suggesting that the program has been well received and supports school nutrition. However, some groups reported concerns regarding menu variety and cleanliness at distribution points. These findings underscore the need for routine quality monitoring, standardized implementation procedures, and greater attention to service consistency. Future studies should also include objective indicators such as body mass index and school attendance to provide a more comprehensive evaluation of program impact
Comparative Study of Machine Learning Methods for Sentiment Analysis of TikTok Comments Related to Cyberbullying Mariwy, Celestina Florecita; Baisa, Lorna Yertas; Sumendap, Andreas Leonardo
Indonesian Journal of Artificial Intelligence and Data Mining Vol 9, No 1 (2026): March 2026
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v9i1.39183

Abstract

The rapid growth of internet use in Indonesia has contributed to the rise of cyberbullying on TikTok, increasing the importance of automated sentiment analysis for digital safety. This study compares the performance of Support Vector Machine, K-Nearest Neighbors, and Naive Bayes in classifying sentiments in TikTok comments related to cyberbullying. The dataset was collected via web scraping and processed through several preprocessing stages, yielding 7,900 unique comments. Sentiment labeling used a lexicon-based approach, and the data were split into training and testing sets with an 80:20 ratio. Results show that 34.18% of comments were negative, indicating a notable level of harmful content. Among the three models, Support Vector Machine performed best with an accuracy of 91.5%, followed by Naive Bayes at 82.8% and K-Nearest Neighbors at 80.8%. These findings suggest Support Vector Machine is the most effective method for sentiment classification in this context and offer a useful reference for developing more accurate content moderation systems on social media.
Public Sentiment Analysis of the Affan Kurniawan Social Issue: A Comparison of Naïve Bayes and SVM Algorithms Mamusung, Marsella Iriana; Baisa, Lorna Yertas; Sumendap, Andreas Leonardo
Indonesian Journal of Artificial Intelligence and Data Mining Vol 9, No 1 (2026): March 2026
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v9i1.39258

Abstract

Social media X is a dynamic public space where opinions on social issues, including the Affan Kurniawan case, spread rapidly. This study aims to analyze sentiment distribution, compare the performance of Multinomial Naïve Bayes and Linear Support Vector Machine (LinearSVC), and evaluate classification consistency under a unified evaluation framework. Indonesian-language posts were collected using keyword-based crawling and cleaned from 10,624 to 7,431 valid records (28 August–2 September 2025). The data were preprocessed through normalization, tokenization, stopword removal, and stemming, and labeled into negative, neutral, and positive sentiments using a lexicon-based approach. The results show a dominance of negative sentiment (50.26%), followed by neutral (30.96%) and positive (18.77%). Using Bag-of-Words features and an 80:20 train–test split, LinearSVC outperformed Naïve Bayes with higher accuracy (0.826 vs 0.745) and macro F1-score (0.759 vs 0.579). This study highlights the effectiveness of SVM as a stronger baseline model for Indonesian sentiment classification on social media data.
Co-Authors Baisa, Lorna Yertas Bonai, Yubelina Meilia Dimara, Petrus Abraham Herdianzah, Aldy Kweldju, Alex De Mamusung, Marsella Iriana Marini, Lion Ferdinand Mariwy, Celestina Florecita Matiin, Nur Fatimah Nur Rahmi Reski, Dian Sanglise, Marlinda