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FROM TRADITION TO TOURISM: SUSTAINABLE MANAGEMENT STRATEGY FOR RUTONG DIGITAL HERITAGE VILLAGE COMPETITIVENESS Aunalal, Zany Irayati; Tangnga, Meiske Helena; Luturmas, Join Rachel; Hahury, Jessy Juniu; Titioka, Stenly Ronaldo; Siahaya, Joice
Jurnal Maneksi (Management Ekonomi Dan Akuntansi) Vol. 14 No. 3 (2025)
Publisher : Politeknik Negeri Ambon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31959/jm.v14i3.3288

Abstract

Introduction: This research develops sustainable management strategies to enhance the competitiveness of Rutong Village as Indonesia's first digital tourism destination in the South Leitimur District, Ambon CityMethods: Employing a qualitative approach with SWOT-AHP analysis, the study engaged 15 key informants through in-depth interviews, participatory observation, and focus group discussions.Results: The analysis reveals critical internal factors, including natural beauty (68% coral coverage), rich cultural heritage (12 oral traditions, 6 traditional dances), and national recognition as a Digital Heritage Village (ADWI 2023), alongside challenges of limited accessibility, inadequate promotion, and seasonal dependence. External factors encompass government support opportunities, eco-tourism trends, and digitalization potential, while facing threats from destination competition, environmental degradation, and climate vulnerabilities. The research yields eight prioritized strategies, with SO1 (Integrated Tourism Attraction Enhancement) ranking highest, followed by SO2 (Strategic Partnerships), and WO1 (Sustainable Eco-Tourism Development). Implementation prioritizes strengthening unique cultural-natural synergies, developing strategic collaborations, and establishing sustainable tourism infrastructure. This framework provides a replicable model for traditional villages balancing economic growth with cultural preservation and environmental sustainability. Keywords: Sustainable tourism, digital heritage village, competitiveness strategy, SWOT-AHP analysis, community-based tourism.
Peningkatan Literasi Digital dan Keamanan Siber Bagi Siswa SMAS BPD Tobelo Selatan Pattiasina, Tiska; Luturmas, Join Rachel; Fredriksz, Grace; Salhuteru, Andrie CH; Matuankotta, Febiola; Nunumete, Laura S
Jurnal Pengabdian Masyarakat (ABDIRA) Vol 5, No 4 (2025): Abdira, Oktober
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/abdira.v5i4.1093

Abstract

The development of digital technology has had a significant impact on high school students, particularly in their use of the internet and social media. However, the lack of digital literacy and cybersecurity awareness remains a problem that needs to be addressed. This community service activity aims to improve digital literacy and cybersecurity understanding among students at SMAS BPD Tobelo Selatan. The methods used included lectures, discussions, and QA sessions, with material covering digital literacy, social media ethics, cyberbullying, hoaxes, and personal data protection. The activity was held offline on September 7, 2025, with 15 students participating. Evaluation was conducted using a Guttman Scale questionnaire to assess participant responses to the activity. Results showed that all students (100%) expressed satisfaction, indicating that the activity successfully improved students' understanding of digital literacy and cybersecurity. Therefore, this community service activity makes a positive contribution in equipping students with wise, safe, and responsible digital skills to face the challenges of the digital era.
PERBANDINGAN KINERJA ALGORITMA SVM DAN NAIVE BAYES PADA KLASIFIKASI PRESTASI AKADEMIK SISWA: STUDI KASUS SMAS BPD TOBELO SELATAN Pattiasina, Tiska; Fredriksz, Grace; Luturmas, Join Rachel; Salhuteru, Andrie CH; Matuankotta, Febiola; Nunumete, Laura S; Jupriyanto, Jupriyanto
Jurnal Teknologi Informasi Mura Vol 18 No 1 (2026): Jurnal Teknologi Informasi Mura
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jti.v18i1.2915

Abstract

Students’ academic achievement is an important indicator of the success of the educational process; however, its assessment is often subjective and not yet fully data-driven. Therefore, a systematic analytical approach is required to classify students’ academic achievement objectively and accurately. This study aims to compare the performance of Support Vector Machine (SVM) and Naive Bayes algorithms in classifying the academic achievement of grade III students at SMAS BPD Tobelo Selatan. A data mining approach using classification techniques was applied, involving 17 attributes as predictor variables and two target classes of academic achievement, namely Very Good and Good. Data processing and model evaluation were conducted using the WEKA software, with performance measured through accuracy, precision, recall, and the Area Under the Receiver Operating Characteristic Curve (AUC-ROC). The results indicate that the SVM algorithm achieves the best performance in terms of accuracy, precision, and recall, each reaching 97.78%, while the Naive Bayes algorithm obtains the highest AUC-ROC value of 98.08%. These findings demonstrate that SVM is superior in prediction accuracy, whereas Naive Bayes shows excellent capability in class discrimination. This study is expected to support data-driven academic decision-making in school environments.
PERBANDINGAN KINERJA ALGORITMA SVM DAN NAIVE BAYES PADA KLASIFIKASI PRESTASI AKADEMIK SISWA: STUDI KASUS SMAS BPD TOBELO SELATAN Pattiasina, Tiska; Fredriksz, Grace; Luturmas, Join Rachel; Salhuteru, Andrie CH; Matuankotta, Febiola; Nunumete, Laura S; Jupriyanto, Jupriyanto
Jurnal Teknologi Informasi Mura Vol 18 No 1 (2026): Jurnal Teknologi Informasi Mura
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jti.v18i1.2915

Abstract

Students’ academic achievement is an important indicator of the success of the educational process; however, its assessment is often subjective and not yet fully data-driven. Therefore, a systematic analytical approach is required to classify students’ academic achievement objectively and accurately. This study aims to compare the performance of Support Vector Machine (SVM) and Naive Bayes algorithms in classifying the academic achievement of grade III students at SMAS BPD Tobelo Selatan. A data mining approach using classification techniques was applied, involving 17 attributes as predictor variables and two target classes of academic achievement, namely Very Good and Good. Data processing and model evaluation were conducted using the WEKA software, with performance measured through accuracy, precision, recall, and the Area Under the Receiver Operating Characteristic Curve (AUC-ROC). The results indicate that the SVM algorithm achieves the best performance in terms of accuracy, precision, and recall, each reaching 97.78%, while the Naive Bayes algorithm obtains the highest AUC-ROC value of 98.08%. These findings demonstrate that SVM is superior in prediction accuracy, whereas Naive Bayes shows excellent capability in class discrimination. This study is expected to support data-driven academic decision-making in school environments.
PENGARUH DISIPLIN KERJA TERHADAP KINERJA PEGAWAI PADA KANTOR SATUAN POLISI PAMONG PRAJA (SATPOL PP) PROVINSI MALUKU Gea, Visi Wantri; Sahertian, Olivia Laura; Luturmas, Join Rachel
Jurnal Administrasi Terapan Vol. 5 No. 1 (2026): Maret
Publisher : P3M Politeknik Negeri Ambon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31959/jat.v5i1.3767

Abstract

This study aims to determine how work discipline affects employee performance at Satpol PP of Maluku Province. This research is based on the importance of discipline as a key factor in improving work effectiveness, since good discipline creates order, responsibility, and compliance with regulations, which in turn impacts employee performance. The research method used is a quantitative method with an associative approach. The population of this study consists of all employees of the Satpol PP of Maluku Province, with the sampling technique carried out using purposive sampling. The research instrument is a questionnaire, while the data analysis technique applies simple linear regression analysis with the help of SPSS software.The results of this study indicate that work discipline has a positive and significant effect on employee performance atSatpol PP of Maluku Province. The higher the level of discipline possessed by employees, the better their performance will be. Work discipline contributes 69.5% to the improvement of employee performance, thus it can be concluded that discipline is an important factor in enhancing work effectiveness. Keywords: Work Discipline, Performance.