Tourist village program is one development priority program for rural development. Despite numerous opportunities to develop tourist villages such as the availability of natural resources and high demand for tourist villages recently, some challenges are still faced to develop tourist villages, especially in a developing country such as Indonesia. Governance problems, infrastructure, and effective partnership are among other factors that remain challenging in developing tourist villages. This study attempts to identify factors that determine the state of tourist villages in Indonesia and determine the appropriate strategies for better tourist village development. Using the case of tourist villages in Kedung Ombo, Central Java, a water based attractive tourist village, this study uses both machine learning and multicriteria approaches by means of Promethee in order to address the objective of the study. This study shows that government support, application of information technology, infrastructure, local participation, partnership, and attractive variations, are among the determinant factors that affect tourist village development. The study also reveals that the appropriate strategies for tourist village development include, improving infrastructure, institutional strengthening, and capacity building. This study could be used to assist local national as well as sub-national governments to effectively manage tourist villages in Indonesia.

Tourism represents a complex multi-actor system. The successful sustainable development of tourism areas requires all stakeholders’ support and a map of the strengths, the relations, and the interests of stakeholder actors to determine appropriate institutional policies. This study aims to map stakeholders’ character at the Kedung Ombo tourism area development as a favorite potential destination in Central Java, Indonesia. Data collection used the focused group discussions method. The data analysis used was the Mactor method. This research shows that the Pemalijuana River Flow Management Office, the Indonesian State Forest Company, and the Regional Development Planning Agency were the dominant actors. The Department of Youth, Sports and Tourism, College, village government, the youth organization, and business people are relay actors. College is an autonomous actor; meanwhile, the youth organization, local government, and community are actor-dependent. The Regional Development Planning Agency Department of Youth, Sports and Tourism, college, village government, youth organizations, and business people are convergent actors who can build strong alliances. The support of BBWS Pemali Juana and Perhutani to collaborate is needed to succeed. The research findings are the basis for making a participative institutional design for the Kedung Ombo tourist area’s success and sustainability.

Keberhasilan pengembangan destinasi wisata membutuhkan analisis tentang karakteristik aktor terkait dengan hubungan antar aktor, sikap aktor terhadap tujuan pengembangan dan kemungkinan aliansi maupun konflik yang muncul. Penelitian ini bertujuan untuk mengidentifikasi tipologi aktor berdasarkan kekuatan dan hubungan antar aktor serta sikap aktor terhadap tujuan pada pengembangan destinasi wisata Kedung Ombo. Penelitian ini menggunakan paradigma penelitian kualitatif-kuantitatif. Metode pengumpulan data menggunakan metode wawancara mendalam, diskusi kelompok fokus dan lokakarya. Analisis data menggunakan metode Mactor (Matrix of Alliances and Conflicts Tactics, Objectives and Recommendations) untuk mengidentifikasi kekuatan, hubungan dan pola aliansi aktor pemangku kepentingan. Hasil penelitian menunjukkan bahwa Balai Besar Wilayah Sungai Pemalijuana, Perum Perhutani dan Badan Perencanaan Pembangunan Daerah, adalah aktor-aktor dominan. Dinas Pemuda, Olahraga dan Pariwisata, Perguruan Tinggi, Pemerintah Desa, Masyarakat, Pelaku Bisnis adalah aktor relay  dan Karang Taruna adalah aktor didominasi. Sebagian besar pemangku kepentingan konvergen dalam mendukung tujuan strategis yang yang akan dicapai. Temuan ini menjadi dasar untuk mengembangkan pola kolaborasi antar seluruh pemangku kepentingan yang diperlukan untuk pengembangan potensi pariwisata Kedung Ombo secara berkelanjutan.

Gempa bumi Cianjur pada tanggal 22 November 2022 mengakibatkan korban jiwa, serta kerusakan dan kerugian material yang cukup besar. Gempa dengan magnitude 5,6 SR tersebut tidak hanya telah mengakibatkan kerusakan yang cukup parah pada infrastruktur umum dan rumah penduduk,  tetapi juga telah mengakibatkan trauma psikologis bagi masyarakat. Oleh karena itu diperlukan penanganan secara menyeluruh berupa rehabilitasi dan rekonstruksi yang bersifat fisik, maupun psikis untuk membantu mengatasi bencana ini. Kegiatan pengabdian kepada masayarakat ini bertujuan untuk membantu para pengungsi korban gempa, khususnya dalam menghadapi trauma psikologis, dengan memberikan penyeluhan dan pelatihan tentang kesiapsiagaan bencana. Kegiatan dilakukan di dusun Mangun, Desa Mangunkarta RT02 RW03, Kecamatan Cugenang, Kabupaten Cianjur. Bentuk kegiatan berupa penguatan mental korban melalui ceramah rohani, sosialisasi tentang wilayah Cianjur sebagai wilayah rawan gempa, dan pelatihan penyiapan tas siaga bencana, serta hiburan untuk anak-anak. Kegiatan ini melibatkan mitra sebagai penerima manafaat adalah relawan korban di lokasi kegiatan dan mitra pelatih yaitu Badan Penaggulangan Bencana Pusat (BNBP). Jumlah peserta pelatihan sebanyak seratus orang terdiri dari orang dewasa dan anak-anak. Hasil kegiatan menunjukkan adanya peningkatan pengetahuan peserta  sebelum dan setelah dilaksanakan sosialisasi dan pelatihan, dan mitra merasa lebih tenang. Kegiatan ini menjadi model yang dapat diterapkan pada wilayah lain, dalam upaya mengurangi korban maupun kerusakan fasilitas saat terjadi bencana, khususnya gempa melalui pemahaman dan kepemilikan pengetahuan tentang kesiapsiagaan bencana

This study aims to predict the progress status of tourism villages in the Kedung Ombo area, Java, Indonesia, and find the antecedent factors of the progress of tourism villages in Indonesia. This study uses a modern approach, namely data mining. Data sources for tourist villages use the data available on the Google link and the observation method. The prediction technique uses the Naïve Bayes machine learning algorithm and Tree Decision on Orange 3.3.0 software. The number of tourist villages analyzed was 126. The results showed that all tourist villages in the Kedung Ombo area were at the development level of the four tourist village classifications of the Ministry of Tourism and Creative Economy. The antecedent factors for the progress of tourism villages are the completeness of ICT facilities, multi-stakeholder partnerships, strong government support, community involvement, and various attractions. Another finding is that the Tree Decision algorithm provides better predictions than the Naïve Bayes method. The results of this study can be used to design policies for developing tourist villages throughout Indonesia.